From 3027c4b5c0641f940af12b764c92de9688b2bb7a Mon Sep 17 00:00:00 2001 From: Mike Deck Date: Sun, 24 Jan 2016 22:39:29 -0600 Subject: [PATCH 001/115] Grammar, usage and formatting updates --- README.md | 46 +++++++++++++++++++++++----------------------- 1 file changed, 23 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index 61f3b57..103a812 100644 --- a/README.md +++ b/README.md @@ -1,17 +1,17 @@ # AWS Lambda Reference Architecture: Real-time File Processing -The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that utilizes [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. This simple architecture is described in this [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) and [blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/). This sample applicaton demonstrates a Markdown conversion application where Lambda is used to convert Markdown files to HTML and plain text. +The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. This simple architecture is described in this [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) and ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) on the AWS Compute Blog. This sample application demonstrates a Markdown conversion application where Lambda is used to convert Markdown files to HTML and plain text. ## Running the Example -The provided [AWS CloudFormation template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) can be used to launch a stack that demonstrates the Lambda file processing reference architecture. Detailed information about the this template can be found in the CloudFormation Template Details section below. +You can use the provided [AWS CloudFormation template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *CloudFormation Template Resources* section of this document. -**Important:** Because the AWS CloudFormation stack name is used in the name of the S3 buckets, that stack name must only contain lowercase letters. Please use lowercase letters when typing the stack name. The provided CloudFormation template retreives its Lambda code from a bucket in the us-east-1 region. To launch this sample in another region, please modify the template and upload the Lambda code to a bucket in that region. +**Important** Because the AWS CloudFormation stack name is used in the name of the Amazon Simple Storage Service (Amazon S3) buckets, that stack name must only contain lowercase letters. Use lowercase letters when typing the stack name. The provided CloudFormation template retrieves its Lambda code from a bucket in the us-east-1 region. To launch this sample in another region, please modify the template and upload the Lambda code to a bucket in that region. -Use the button below to launch the stack via the AWS Console. +Choose **Launch Stack** to launch the template in the us-east-1 region in your account: -[![Launch into Lambda ETL into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) Alternatively, you can use the following command to launch the stack using the AWS CLI. This assumes you have already [installed the AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). @@ -22,9 +22,9 @@ aws cloudformation create-stack \ --capabilities CAPABILITY_IAM ``` -## Testing +## Testing the Example -Once you have created the stack using the provided template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. The README.md file in this repository can be used as an example file. Once the file has been uploaded, you can see the resulting HTML and plain text files in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. +After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use this README.md file in the repository as an example file. After the file has been uploaded, you can see the resulting HTML and plain text files in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. @@ -33,50 +33,50 @@ BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-pro aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md ``` -After the file has been uploaded to the input bucket you can inspect the output bucket to see the rendered HTML and plain text output files created by the Lambda functions. +After the file has been uploaded to the input bucket, you can inspect the output bucket to see the rendered HTML and plain text output files created by the Lambda functions. You can also view the CloudWatch logs generated by the Lambda functions. -## Cleaning Up +## Cleaning Up the Example Resources -To tear down the deployed resources you must complete the following steps: +To remove all resources created by this example, do the following: 1. Delete all objects in the input and output buckets. 1. Delete the CloudFormation stack. -1. Delete the CloudWatch Log groups that contain the execution logs for the two processor functions. +1. Delete the CloudWatch log groups that contain the execution logs for the two processor functions. ## CloudFormation Template Resources ### Parameters -- *CodeBucket*: Name of the S3 bucket in the stack's region that contains the code for the two Lambda functions, ProcessorFunctionOne and ProcessorFunctionTwo. Defaults to the managed bucket 'awslambda-reference-architectures'. +- **CodeBucket** - Name of the S3 bucket in the stack's region that contains the code for the two Lambda functions, ProcessorFunctionOne and ProcessorFunctionTwo. Defaults to the managed bucket `awslambda-reference-architectures`. -- *CodeKeyPrefix*: The key prefix for the Lambda function code relative to `CodeBucket`. Defaults to 'file-processing'. +- **CodeKeyPrefix** - The key prefix for the Lambda function code relative to `CodeBucket`. Defaults to `file-processing`. ### Resources [The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) creates the following resources: -- *InputBucket*: An Amazon Simple Storage Service (Amazon S3) bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger both processing functions. +- **InputBucket** - An S3 bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger both processing functions. -- *OutputBucket*: An Amazon S3 bucket that is populated by the processor functions with the transformed files. +- **OutputBucket** - An S3 bucket that is populated by the processor functions with the transformed files. -- *InputNotificationTopic*: An Amazon Simple Notification Service (Amazon SNS) topic used to invoke multiple Lambda functions in response to each object creation notification. +- **InputNotificationTopic** - An Amazon Simple Notification Service (Amazon SNS) topic used to invoke multiple Lambda functions in response to each object creation notification. -- *NotificationPolicy*: An Amazon SNS topic policy which permits `InputBucket` to call the `Publish` action on the topic. +- **NotificationPolicy** - An Amazon SNS topic policy which permits `InputBucket` to call the `Publish` action on the topic. -- *ProcessorFunctionOne*: An AWS Lambda function that converts Markdown files to HTML. The deployment package for this function must be located at s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip. +- **ProcessorFunctionOne** - An AWS Lambda function that converts Markdown files to HTML. The deployment package for this function must be located at `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`. -- *ProcessorFunctionTwo*: An AWS Lambda function that converts Markdown files to plain text. The deployment package for this function must be located at s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip. +- **ProcessorFunctionTwo** - An AWS Lambda function that converts Markdown files to plain text. The deployment package for this function must be located at `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`. -- *LambdaExecutionRole*: An AWS Identity and Access Management (IAM) role used by the two Lambda functions. +- **LambdaExecutionRole** - An AWS Identity and Access Management (IAM) role used by the two Lambda functions. -- *RolePolicy*: An IAM policy associated with `LambdaExecutionRole` that allows the functions to get objects from `InputBucket`, put object to `OutputBucket` and log to Amazon CloudWatch. +- **RolePolicy** - An IAM policy associated with **LambdaExecutionRole** that allows the functions to get objects from `InputBucket`, put object to `OutputBucket` and log to Amazon CloudWatch. -- *LambdaInvokePermissionOne*: A policy that enables Amazon SNS to invoke ProcessorFunctionOne based on notifications from InputNotificationTopic. +- **LambdaInvokePermissionOne** - A policy that enables Amazon SNS to invoke ProcessorFunctionOne based on notifications from InputNotificationTopic. -- *LambdaInvokePermissionTwo*: A policy that enables Amazon SNS to invoke ProcessorFunctionTwo based on notifications from InputNotificationTopic. +- **LambdaInvokePermissionTwo** - A policy that enables Amazon SNS to invoke ProcessorFunctionTwo based on notifications from InputNotificationTopic. ## License From 0b328b55fdd101a1e33e6dd6cd5d2305602813e5 Mon Sep 17 00:00:00 2001 From: aaronkao Date: Thu, 31 Mar 2016 10:31:48 -0700 Subject: [PATCH 002/115] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 103a812..61526ac 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# AWS Lambda Reference Architecture: Real-time File Processing +# Serverless Reference Architecture: Real-time File Processing The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. This simple architecture is described in this [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) and ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) on the AWS Compute Blog. This sample application demonstrates a Markdown conversion application where Lambda is used to convert Markdown files to HTML and plain text. From 2832ee162d35310624530be84f1ac1a38f027ae5 Mon Sep 17 00:00:00 2001 From: Aaron Kao Date: Thu, 2 Jun 2016 21:58:05 -0700 Subject: [PATCH 003/115] Added translated READMEs --- README.md | 3 ++ README/README-CN.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-DE.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-ES.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-FR.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-IT.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-JP.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-KR.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-PT.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-RU.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ README/README-TW.md | 84 +++++++++++++++++++++++++++++++++++++++++++++ 11 files changed, 843 insertions(+) create mode 100644 README/README-CN.md create mode 100644 README/README-DE.md create mode 100644 README/README-ES.md create mode 100644 README/README-FR.md create mode 100644 README/README-IT.md create mode 100644 README/README-JP.md create mode 100644 README/README-KR.md create mode 100644 README/README-PT.md create mode 100644 README/README-RU.md create mode 100644 README/README-TW.md diff --git a/README.md b/README.md index 61526ac..a2dd6e7 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,7 @@ # Serverless Reference Architecture: Real-time File Processing +README Languages: [DE](README/README-DE.md) | [ES](README/README-ES.md) | [FR](README/README-FR.md) | [IT](README/README-IT.md) | [JP](README/README-JP.md) | [KR](README/README-KR.md) | +[PT](README/README-PT.md) | [RU](README/README-RU.md) | +[CN](README/README-CN.md) | [TW](README/README-TW.md) The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. This simple architecture is described in this [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) and ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) on the AWS Compute Blog. This sample application demonstrates a Markdown conversion application where Lambda is used to convert Markdown files to HTML and plain text. diff --git a/README/README-CN.md b/README/README-CN.md new file mode 100644 index 0000000..23ac454 --- /dev/null +++ b/README/README-CN.md @@ -0,0 +1,84 @@ +# 无服务器参考架构：实时文件处理 + +实时文件处理参考架构是一个受事件驱动的通用并行数据处理架构，使用 [AWS Lambda](https://aws.amazon.com/lambda)。该架构非常适合需要某个对象的多种衍生数据的工作负载。此 [示意图](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) 以及 AWS 计算博客上的 ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) 中介绍了这个简单架构。这个示例应用程序演示了一个 Markdown 转换应用程序，该应用程序使用 Lambda 来将 Markdown 文件转换为 HTML 和纯文本。 + +## 运行示例 + +您可以使用提供的 [AWS CloudFormation 模板](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) 启动一个堆栈，该堆栈演示了 Lambda 文件处理参考架构。在本文档的 *CloudFormation 模板资源* 部分中提供了有关通过该模板创建的资源的详细信息。 + +**重要提示** 由于 AWS CloudFormation 堆栈名称在 Amazon Simple Storage Service (Amazon S3) 存储桶的名称中使用，该堆栈名称只能包含小写字母。在键入堆栈名称时，使用小写字母。提供的 CloudFormation 模板会从 us-east-1 区域的存储桶中检索其 Lambda 代码。要在另一个区域中启动此示例，请修改模板并将 Lambda 代码上传到该区域的存储桶中。 + + +选择 **Launch Stack** 以在您账户的 us-east-1 区域中启动模板： + +[![使用 CloudFormation 在北弗吉尼亚区域中启动 Lambda 文件处理](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +此外，您可以通过 AWS CLI 使用以下命令来启动堆栈。这假设您已 [安装 AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)。 + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## 测试示例 + +在您使用 CloudFormation 模板创建堆栈后，可以通过将 Markdown 文件上传到已在堆栈中创建的 InputBucket 来测试系统。您可以使用存储库中的此 README.md 文件作为示例文件。在上传该文件后，您可以在堆栈的输出存储桶中看到生成的 HTML 和纯文本文件。您还可以在 CloudWatch 日志中查看每个函数，以便了解函数执行的详细信息。 + +您可以使用下面的命令，将示例文件从提供的 S3 存储桶复制到您堆栈的输入存储桶中。 + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +在将该文件上传到输入存储桶后，您可以检查输出存储桶，查看 Lambda 函数创建的 HTML 和纯文本格式的输出文件。 + +您还可以查看 Lambda 函数生成的 CloudWatch 日志。 + +## 清理示例资源 + +要删除此示例创建的所有资源，请执行以下操作： + +1.删除输入和输出存储桶中的所有对象。 +1.删除 CloudFormation 堆栈。 +1.删除包含两个处理程序函数的执行日志的 CloudWatch 日志组。 + + + +## CloudFormation 模板资源 + +### 参数 +- **CodeBucket** - 堆栈区域中的 S3 存储桶的名称，该区域包含两个 Lambda 函数 ProcessorFunctionOne 和 ProcessorFunctionTwo 的代码。默认为托管存储桶 `awslambda-reference-architectures`。 + +- **CodeKeyPrefix** - 与 `CodeBucket` 相关的 Lambda 函数代码的键前缀。默认为 `file-processing`。 + +### 资源 +使用 [提供的模板](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +可创建以下资源： + +- **InputBucket** - 一个保存原始 Markdown 文件的 S3 存储桶。将文件上传到此存储桶时，将同时触发两个处理函数。 + +- **OutputBucket** - 一个 S3 存储桶，该存储桶由处理程序函数使用转换的文件填充。 + +- **InputNotificationTopic** - 一个 Amazon Simple Notification Service (Amazon SNS) 主题，该主题用于调用多个 Lambda 函数来响应各个对象创建通知。 + +- **NotificationPolicy** - 一个 Amazon SNS 主题策略，该策略允许 `InputBucket` 对主题调用 `Publish` 操作。 + +- **ProcessorFunctionOne** - 一个用于将 Markdown 文件转换为 HTML 的 AWS Lambda 函数。此函数的部署程序包必须位于 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip` 中。 + +- **ProcessorFunctionTwo** - 一个用于将 Markdown 文件转换为纯文本的 AWS Lambda 函数。此函数的部署程序包必须位于 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip` 中。 + +- **LambdaExecutionRole** - 一个 AWS Identity and Access Management (IAM) 角色，该角色由这两个 Lambda 函数使用。 + +- **RolePolicy** - 一个与 **LambdaExecutionRole** 关联的 IAM 策略，该策略允许函数从 `InputBucket` 获取对象，将对象置入 `OutputBucket`，并记录到 Amazon CloudWatch。 + +- **LambdaInvokePermissionOne** - 一个策略，该策略允许 Amazon SNS 根据来自 InputNotificationTopic 的通知调用 ProcessorFunctionOne。 + +- **LambdaInvokePermissionTwo** - 一个策略，该策略允许 Amazon SNS 根据来自 InputNotificationTopic 的通知调用 ProcessorFunctionTwo。 + + +## 许可证 + +此示例参考架构已获得 Apache 2.0 许可。 diff --git a/README/README-DE.md b/README/README-DE.md new file mode 100644 index 0000000..cc73f50 --- /dev/null +++ b/README/README-DE.md @@ -0,0 +1,84 @@ +# Serverlose Referenzarchitektur: Dateiverarbeitung in Echtzeit + +Die Referenzarchitektur zur Dateiverarbeitung in Echtzeit ist eine ereignisgesteuerte Architektur zur parallelen Datenverarbeitung für allgemeine Zwecke, die [AWS Lambda](https://aws.amazon.com/lambda) verwendet. Die Architektur eignet sich optimal für Arbeitslasten, die mehr als eine Datenableitung eines Objekts benötigen. Diese einfache Architektur wird in diesem [Diagramm](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) und [im Blogpost "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) auf dem AWS Compute-Blog beschrieben. Diese Beispielanwendung zeigt eine Markdown-Konvertierungsanwendung in Fällen, in denen Lambda zur Markdown-Dateikonvertierung von HTML in Nur-Text verwendet wird. + +## Ausführen der Beispielanwendung + +Mithilfe der bereitgestellten [AWS CloudFormation-Vorlage](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) können Sie einen Stapel starten, der die Referenzarchitektur für die Lambda-Dateiverarbeitung zeigt. Details über die mithilfe dieser Vorlage erstellen Ressourcen finden Sie im Abschnitt *Ressourcen der CloudFormation-Vorlage* in diesem Dokument. + +**Wichtig** Da der AWS CloudFormation-Stapelname im Namen des Amazon Simple Storage Service (Amazon S3)-Buckets verwendet wird, darf dieser Stapelname nur aus Kleinbuchstaben bestehen. Verwenden Sie daher Kleinbuchstaben für den Stapelnamen. Die bereitgestellte CloudFormation-Vorlage ruft den Lambda-Code aus einem Bucket für die Region "us-east-1" ab. Um dieses Beispiel in einer anderen Region zu starten, ändern Sie die Vorlage und laden Sie den Lambda-Code in einen Bucket für diese Region hoch. + + +Wählen Sie **Launch Stack**, um die Vorlage für die Region "us-east-1" in Ihrem Konto zu starten: + +[![Starten der Lambda-Dateiverarbeitung mit CloudFormation in Nord-Virginia](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +Alternativ können Sie den Stapel mit dem folgenden Befehl und mithilfe von AWS CLI starten. Dies setzt jedoch voraus, dass Sie [die AWS CLI bereits installiert haben](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## Testen der Beispielanwendung + +Nachdem Sie den Stapel mithilfe der CloudFormation-Vorlage erstellt haben, können Sie das System testen, indem Sie eine Markdown-Datei in den im Stapel erstellten "InputBucket" hochladen. Sie können die README.md-Datei im Repository als Beispieldatei verwenden. Nachdem die Datei hochgeladen wurde, können Sie die resultierenden HTML- und Nur-Text-Dateien im Ausgabe-Bucket des Stapels sehen. Sie können ebenfalls CloudWatch-Protokolle für die einzelnen Funktionen aufrufen, um Details zu ihrer Ausführung anzuzeigen. + +Mithilfe der folgenden Befehle können Sie eine Beispieldatei vom bereitgestellten S3-Bucket in den Empfangs-Bucket des Stapels kopieren. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +Nachdem die Datei in den Empfangs-Bucket hochgeladen wurde, können Sie den Ausgabe-Bucket überprüfen, um die gerenderten HTML- und Nur-Text-Ausgabedateien zu sehen, die von den Lambda-Funktionen erstellt wurden. + +Ebenfalls können Sie die von den Lamda-Funktionen generierten CloudWatch-Protokolle aufrufen. + +## Bereinigen der Beispielressourcen + +Gehen Sie wie folgt vor, um alle in diesem Beispiel erstellten Ressourcen zu entfernen: + +1. Löschen Sie alle Objekte in den Empfangs- und Ausgabe-Buckets. +1. Löschen Sie den CloudFormation-Stapel. +1. Löschen Sie die CloudWatch-Protokollgruppen, die die Ausführungsprotokolle der zwei Prozessorfunktionen enthalten. + + + +## Ressourcen der CloudFormation-Vorlage + +### Parameter +- **CodeBucket** – Name des S3-Buckets in der Region des Stapels, der den Code für die zwei Lambda-Funktionen, "ProcessorFunctionOne" und "ProcessorFunctionTwo", enthält. Verwendet standardmäßig den verwalteten Bucket "awslambda-reference-architectures". + +- **CodeKeyPrefix** – Schlüsselpräfix für den Lambda-Funktionscode, der sich auf "CodeBucket" bezieht. Verwendet standardmäßig "file-processing". + +### Ressourcen +[Die bereitgestellte Vorlage](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +erstellt die folgenden Ressourcen: + +- **InputBucket** – ein S3-Bucket, der die Markdown-Dateien mit den Rohdaten enthält. Das Hochladen einer Datei in diesen Bucket löst beide Verarbeitungsfunktionen aus. + +- **OutputBucket** – ein S3-Bucket, den die Verarbeitungsfunktionen mit den transformierten Dateien auffüllen. + +- **InputNotificationTopic** – ein Amazon Simple Notification Service (Amazon SNS)-Thema, das verwendet wird, um mehrere Lambda-Funktionen als Reaktion auf die einzelnen Objekterstellungsbenachrichtigungen aufzurufen. + +- **NotificationPolicy** – eine Amazon SNS-Themenrichtlinie, die gestattet, dass "InputBucket" die Aktion "Veröffentlichen" für das Thema aufruft. + +- **ProcessorFunctionOne** – eine AWS Lambda-Funktion, die Markdown-Dateien in HTML umwandelt. Das Bereitstellungspaket für diese Funktion muss sich unter "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip" befinden. + +- **ProcessorFunctionTwo** – eine AWS Lambda-Funktion, die Markdown-Dateien in Nur-Text umwandelt. Das Bereitstellungspaket für diese Funktion muss sich unter "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip" befinden. + +- **LambdaExecutionRole** – eine AWS Identity and Access Management (IAM)-Rolle, die von den zwei Lambda-Funktionen verwendet wird. + +- **RolePolicy** – eine mit **LambdaExecutionRole** verknüpfte IAM-Richtlinie, die ermöglicht, dass Funktionen Objekte aus "InputBucket" abrufen, Objekte in "OutputBucket" platzieren und Protokolle an Amazon CloudWatch ausgeben. + +- **LambdaInvokePermissionOne** – eine Richtlinie, die es Amazon SNS ermöglicht, "ProcessorFunctionOne" basierend auf Benachrichtigungen von "InputNotificationTopic" aufzurufen. + +- **LambdaInvokePermissionTwo** – eine Richtlinie, die es Amazon SNS ermöglicht, "ProcessorFunctionTwo" basierend auf Benachrichtigungen von "InputNotificationTopic" aufzurufen. + + +## Lizensierung + +Dieses Beispiel einer Referenzarchitektur ist unter Apache 2.0 lizensiert. diff --git a/README/README-ES.md b/README/README-ES.md new file mode 100644 index 0000000..80644a5 --- /dev/null +++ b/README/README-ES.md @@ -0,0 +1,84 @@ +# Arquitectura de referencia sin servidor: Procesamiento de archivos en tiempo real + +La arquitectura de referencia Procesamiento de archivos en tiempo real es una arquitectura de procesamiento de datos en paralelo controlada por eventos de propósito general que usa [AWS Lambda](https://aws.amazon.com/lambda). Esta arquitectura es ideal para cargas de trabajo que necesitan obtener más de un dato de un objeto. Esta arquitectura sencilla se describe en este [diagrama](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) y en la [entrada de blog "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) del blog AWS Compute. Esta aplicación de ejemplo muestra una aplicación de conversión de Markdown en la que se utiliza Lambda para convertir archivos Markdown en HTML y texto sin formato. + +## Ejecución del ejemplo + +Puede usar la [plantilla de AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) proporcionada para lanzar una pila que muestre la arquitectura de referencia de procesamiento de archivos con Lambda. En la sección *Recursos de la plantilla de CloudFormation* de este documento encontrará información detallada sobre los recursos creados por esta plantilla. + +**Importante** Como el nombre de la pila de AWS CloudFormation se usa en el nombre de los buckets de Amazon Simple Storage Service (Amazon S3), ese nombre de pila solo debe contener letras en minúscula. Use letras en minúscula cuando escriba el nombre de la pila. La plantilla de CloudFormation proporcionada recupera su código Lambda de un bucket de la región us-east-1. Para ejecutar este ejemplo en otra región, modifique la plantilla y cargue el código Lambda en un bucket de esa región. + + +Elija **Launch Stack** para lanzar la plantilla en la región us-east-1 de su cuenta: + +[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +También puede usar el siguiente comando para lanzar la pila mediante el CLI de AWS. Se presupone que ya ha [instalado AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## Probar el ejemplo + +Una vez creada la pila mediante la plantilla de CloudFormation, puede probar el sistema cargando un archivo Markdown en el InputBucket que se creó en la pila. Puede usar este archivo README.md del repositorio como archivo de ejemplo. Después de cargar el archivo, puede ver los archivos HTML y de texto sin formato resultantes en el bucket de salida de la pila. También puede ver los logs de CloudWatch de cada una de las funciones si desea obtener información detallada de la ejecución. + +Puede usar los siguientes comandos para copiar un archivo de ejemplo del bucket de S3 proporcionado en el bucket de entrada de la pila. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +Después de cargar el archivo en el bucket de entrada, puede examinar el bucket de salida para ver los archivos de salida HTML y de texto sin formato resultantes creados por las funciones Lambda. + +También puede ver los logs de CloudWatch generados por las funciones Lambda. + +## Borrado de los recursos del ejemplo + +Para eliminar todos los recursos creados por este ejemplo, proceda del modo siguiente: + +1. Elimine todos los objetos de los buckets de entrada y salida. +1. Elimine la pila de CloudFormation. +1. Elimine los grupos de logs de CloudWatch que contienen los logs de ejecución de las dos funciones de procesamiento. + + + +## Recursos de la plantilla de CloudFormation + +### Parámetros +- **CodeBucket**: nombre del bucket de S3 de la región de la pila que contiene el código de las dos funciones Lambda, ProcessorFunctionOne y ProcessorFunctionTwo. Está establecido de forma predeterminada en el bucket administrado `awslambda-reference-architectures`. + +- **CodeKeyPrefix**: el prefijo de clave del código de la función Lambda correspondiente a `CodeBucket`. De forma predeterminada es `file-processing`. + +### Recursos +[La plantilla proporcionada](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +crea los recursos siguientes: + +- **InputBucket**: un bucket de S3 que almacena los archivos Markdown sin formato. Al cargar un archivo en este bucket se desencadenarán ambas funciones de procesamiento. + +- **OutputBucket**: un bucket de S3 que rellenan las funciones de procesamiento con los archivos convertidos. + +- **InputNotificationTopic**: un tema de Amazon Simple Notification Service (Amazon SNS) usado para invocar a varias funciones Lambda en respuesta a cada notificación de creación de un objeto. + +- **NotificationPolicy**: una política de tema de Amazon SNS que permite a `InputBucket` llamar a la acción `Publish` en el tema. + +- **ProcessorFunctionOne**: una función de AWS Lambda que convierte archivos Markdown en HTML. El paquete de implementación de esta función debe estar ubicado en `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`. + +- **ProcessorFunctionTwo**: una función de AWS Lambda que convierte archivos Markdown en texto sin formato. El paquete de implementación de esta función debe estar ubicado en `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`. + +- **LambdaExecutionRole**: un rol de AWS Identity and Access Management (IAM) usado por las dos funciones Lambda. + +- **RolePolicy**: una política de IAM asociada a **LambdaExecutionRole** que permite que las funciones obtengan objetos de `InputBucket`, coloquen objetos en `OutputBucket` y creen un log en Amazon CloudWatch. + +- **LambdaInvokePermissionOne**: una política que permite a Amazon SNS invocar a ProcessorFunctionOne a partir de las notificaciones de InputNotificationTopic. + +- **LambdaInvokePermissionTwo**: una política que permite a Amazon SNS invocar a ProcessorFunctionTwo a partir de las notificaciones de InputNotificationTopic. + + +## Licencia + +Este ejemplo de arquitectura de referencia tiene licencia de Apache 2.0. diff --git a/README/README-FR.md b/README/README-FR.md new file mode 100644 index 0000000..fc6ec40 --- /dev/null +++ b/README/README-FR.md @@ -0,0 +1,84 @@ +# Architecture de référence sans serveur : Traitement de fichier en temps réel + +L'architecture de référence de traitement de fichier en temps réel est une architecture à visée générale de traitement de données en parallèle piloté par les événements qui utilise [AWS Lambda](https://aws.amazon.com/lambda). Cette architecture est idéale pour les charges de travail qui ont besoin de plusieurs dérivés de données d'un objet. Cette architecture simple est décrite dans ce [diagramme](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) et le [billet de blog « Fanout S3 Event Notifications to Multiple Endpoints »](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) sur le blog de calcul AWS. Cet exemple d'application illustre une application de conversion Markdown dans laquelle Lambda est utilisé pour convertir des fichiers Markdown en HTML et en texte brut. + +## Exécution de l'exemple + +Vous pouvez utiliser le [template AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) fourni pour lancer une stack qui illustre l'architecture de référence de traitement de fichier Lambda. Vous trouverez des détails sur les ressources créées par ce template dans la section *Ressources de template CloudFormation* de ce document. + +**Important** Comme le nom de stack AWS CloudFormation est utilisé dans le nom des buckets (compartiments) Amazon Simple Storage Service (Amazon S3), le nom de stack ne doit contenir que des lettres minuscules. Utilisez des lettres minuscules lorsque vous tapez le nom de stack. Le template CloudFormation fourni extrait son code Lambda d'un bucket dans la région us-east-1. Pour lancer cet exemple dans une autre région, veuillez modifier le template et charger le code Lambda dans un bucket de cette région. + + +Sélectionnez **Launch Stack** pour lancer le template dans la région us-east-1 dans votre compte : + +[![Lancement de Lambda de traitement de fichier en Virginie du Nord) avec CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +Sinon, vous pouvez utiliser la commande suivante pour lancer la stack à l'aide de l'interface de ligne de commande AWS CLI. Cela présume que vous avez déjà [installé AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## Test de l'exemple + +Une fois que vous avez créé la stack à l'aide du template CloudFormation, vous pouvez tester le système en chargeant un fichier Markdown dans le bucket (compartiment) InputBucket créé dans la stack. Vous pouvez utiliser ce fichier README.md dans le référentiel comme exemple de fichier. Une fois que le fichier a été chargé, vous pouvez afficher les fichiers HTML et en texte brut dans le bucket de sortie de votre stack. Vous pouvez également afficher les journaux CloudWatch pour chacune des fonctions pour voir les détails de leur exécution. + +Vous pouvez utiliser les commandes suivantes pour copier un exemple de fichier depuis le bucket (compartiment) S3 fourni vers le bucket d'entrée de votre stack. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +Une fois que le fichier a été chargé dans le bucket (compartiment) d'entrée, vous pouvez inspecter le bucket de sortie pour afficher les fichiers HTML et en texte brut de sortie créés par les fonctions Lambda. + +Vous pouvez également afficher les journaux CloudWatch générés par les fonctions Lambda. + +## Nettoyage des ressources de l'exemple + +Pour supprimer toutes les ressources créées par cet exemple, procédez comme suit : + +1. Supprimez tous les objets des buckets (compartiments) d'entrée et de sorties. +1. Supprimez la stack CloudFormation. +1. Supprimez les groupes de journaux qui contiennent les journaux d'exécution pour les deux fonctions de traitement. + + + +## Ressources du template CloudFormation + +### Paramètres +- **CodeBucket** - Nom du bucket (compartiment) S3 dans la région de la stack qui contient le code des deux fonctions Lambda, ProcessorFunctionOne et ProcessorFunctionTwo. Par défaut, il s'agit du bucket opéré par `awslambda-reference-architectures`. + +- **CodeKeyPrefix** - Le préfixe de clé pour le code de fonction Lambda relatif à `CodeBucket`. La valeur par défaut est `file-processing`. + +### Ressources +[Le template fourni](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +crée les ressources suivantes : + +- **InputBucket** - Un bucket (compartiment) S3 qui contient les fichiers Markdown bruts. Le chargement d'un fichier dans ce bucket déclenchera les deux fonctions de traitement. + +- **OutputBucket** - Un bucket S3 alimenté par les fonctions de traitement avec les fichiers transformés. + +- **InputNotificationTopic** - Une rubrique Amazon Simple Notification Service (Amazon SNS) utilisée pour appeler plusieurs fonctions Lambda en réponse à chaque notification de création d'objet. + +- **NotificationPolicy** - Une politique de rubrique Amazon SNS qui autorise `InputBucket` à appeler l'action `Publish` sur la rubrique. + +- **ProcessorFunctionOne** - Une fonction AWS Lambda qui convertit des fichiers Markdown en HTML. Le package de déploiement pour cette fonction doit être situé dans `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`. + +- **ProcessorFunctionTwo** - Une fonction AWS Lambda qui convertit des fichiers Markdown en texte brut. Le package de déploiement pour cette fonction doit être situé dans `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`. + +- **LambdaExecutionRole** - Un rôle AWS Identity and Access Management (IAM) utilisé par les deux fonctions Lambda. + +- **RolePolicy** - Une politique IAM associée à **LambdaExecutionRole** qui autorise les fonctions à extraire des objets de `InputBucket`, à les mettre dans `OutputBucket` et à se connecter à Amazon CloudWatch. + +- **LambdaInvokePermissionOne** - Une politique qui permet à Amazon SNS d'appeler ProcessorFunctionOne en fonction de notifications d'InputNotificationTopic. + +- **LambdaInvokePermissionTwo** - Une politique qui permet à Amazon SNS d'appeler ProcessorFunctionTwo en fonction de notifications d'InputNotificationTopic. + + +## Licence + +Cet exemple d'architecture de référence est fourni sous licence sous Apache 2.0. diff --git a/README/README-IT.md b/README/README-IT.md new file mode 100644 index 0000000..b529e19 --- /dev/null +++ b/README/README-IT.md @@ -0,0 +1,84 @@ +# Architettura di riferimento senza server: elaborazione dei file in tempo reale + +L'architettura di riferimento per l'elaborazione dei file in tempo reale è un'architettura di elaborazione dati parallela, basata sugli eventi e destinata a scopi generici che utilizza [AWS Lambda](https://aws.amazon.com/lambda). Tale architettura è ideale per i carichi di lavoro che necessitano di più di un derivato dati di un oggetto. Questa architettura semplice è descritta in questo [diagramma](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) e nel [post "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) del blog AWS Compute. L'architettura esempio mostra un'applicazione di conversione Markdown in cui Lambda viene utilizzato per convertire file Markdown in HTML e testo semplice. + +## Esecuzione dell'esempio + +È possibile utilizzare il [modello AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) fornito, per avviare uno stack che mostra l'architettura di riferimento per l'elaborazione dei file Lambda. I dettagli sulle risorse create da questo modello sono disponibili nella sezione *CloudFormation Template Resources* di questo documento. + +**Important** Poiché il nome dello stack di AWS CloudFormation è utilizzato nel nome dei bucket di Amazon Simple Storage Service (Amazon S3), il nome di tale stack deve contenere solo lettere minuscole. Utilizzare lettere minuscole durante la digitazione del nome dello stack. Il modello di CloudFormation fornito recupera il suo codice Lambda da un bucket nella regione Stati Uniti orientali 1. Per avviare questo esempio in un'altra regione, modificare il modello e caricare il codice Lambda in un bucket di quella regione. + + +Selezionare **Launch Stack** per avviare il modello nella regione Stati Uniti orientali 1 nell'account personale: + +[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +In alternativa, è possibile utilizzare il comando seguente per avviare lo stack tramite AWS CLI. Ciò presuppone l'[installazione di AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## Test dell'esempio + +Dopo aver creato lo stack tramite il modello di CloudFormation, è possibile eseguire il test del sistema caricando un file Markdown nell'InputBucket creato nello stack. È possibile utilizzare il file README.md nel repository come file di esempio. Una volta caricato il file, è possibile visualizzare i risultanti file HTML e di testo semplice nel bucket di output dello stack. È possibile visualizzare anche i registri di CloudWatch di ciascuna funzione per vedere i dettagli della loro esecuzione. + +È possibile utilizzare i comandi seguenti per copiare un file di esempio dal bucket S3 fornito nel bucket di input dello stack. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +Una volta caricato il file nel bucket di input, è possibile ispezionare il bucket di output per vedere la resa dei file di output HTML e di testo semplice creati dalle funzioni di Lambda. + +È possibile visualizzare anche i registri di CloudWatch generati dalle funzioni di Lambda. + +## Eliminazione delle risorse dell'esempio + +Per eliminare tutte le risorse create da questo esempio, effettuare i seguenti passaggi: + +1. Eliminare tutti gli oggetti nei bucket di input e output. +1. Eliminare lo stack di CloudFormation. +1. Eliminare i gruppi di registro di CloudWatch che contengono i registri di esecuzione per le due funzioni del processore. + + + +## Risorse dei modelli di CloudFormation + +### Parametri +- **CodeBucket**: nome del bucket S3 nella regione dello stack che contiene il codice per le due funzioni di Lambda, ProcessorFunctionOne e ProcessorFunctionTwo. Impostazioni predefinite sul bucket gestito "awslambda-reference-architectures". + +- **CodeKeyPrefix**: prefisso della chiave per il codice delle funzioni di Lambda relativo a "CodeBucket". Impostazioni predefinite su "file-processing". + +### Risorse +[Il modello fornito](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +crea le risorse seguenti: + +- **InputBucket**: bucket S3 che contiene i file Markdown non elaborati. Il caricamento di un file in questo bucket attiva entrambe le funzioni di elaborazione. + +- **OutputBucket**: bucket S3 popolato dalle funzioni del processore con i file trasformati. + +- **InputNotificationTopic**: argomento di Amazon Simple Notification Service (Amazon SNS) utilizzato per richiamare più funzioni di Lambda in risposta alla notifica della creazione di ciascun oggetto. + +- **NotificationPolicy**: policy dell'argomento di Amazon SNS che permette a "InputBucket" di richiedere l'azione "Publish" all'argomento. + +- **ProcessorFunctionOne**: funzione di AWS Lambda che converte i file Markdown in HTML. Il pacchetto di distribuzione per questa funzione deve essere collocato in "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip". + +- **ProcessorFunctionTwo**: funzione di AWS Lambda che converte i file Markdown in testo semplice. Il pacchetto di distribuzione per questa funzione deve essere collocato in "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip". + +- **LambdaExecutionRole**: ruolo di AWS Identity and Access Management (IAM) utilizzato dalle due funzioni di Lambda. + +- **RolePolicy**: policy di IAM associata a **LambdaExecutionRole** che consente alle funzioni di prendere oggetti da "InputBucket", posizionare oggetti in "OutputBucket" e accedere ad Amazon CloudWatch. + +- **LambdaInvokePermissionOne**: policy che consente ad Amazon SNS di richiamare ProcessorFunctionOne in base alle notifiche di InputNotificationTopic. + +- **LambdaInvokePermissionTwo**: policy che consente ad Amazon SNS di richiamare ProcessorFunctionTwo in base alle notifiche di InputNotificationTopic. + + +## Licenza + +La licenza di questo esempio di architettura di riferimento è fornita con Apache 2.0. diff --git a/README/README-JP.md b/README/README-JP.md new file mode 100644 index 0000000..90a140c --- /dev/null +++ b/README/README-JP.md @@ -0,0 +1,84 @@ +# サーバーレスリファレンスアーキテクチャ: リアルタイムのファイル処理 + +リアルタイムのファイル処理リファレンスアーキテクチャは、[AWS Lambda](https://aws.amazon.com/lambda) を使用する、汎用でイベント駆動型の並列データ処理アーキテクチャです。このアーキテクチャは、オブジェクトの複数のデータ派生物を必要とするワークロードに最適です。このシンプルなアーキテクチャについては、この [図](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) および AWS コンピューティングブログの ["Fanout S3 Event Notifications to Multiple Endpoints" ブログの投稿](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) で説明しています。このサンプルアプリケーションは、Markdown ファイルを HTML とプレーンテキストに変換するために Lambda を使用する Markdown 変換アプリケーションを示しています。 + +## 例の実行 + +用意された [AWS CloudFormation テンプレート](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) を使用して、Lambda ファイル処理のリファレンスアーキテクチャを示すスタックを起動できます。このテンプレートで作成されるリソースの詳細は、このドキュメントの「*CloudFormation テンプレートのリソース*」セクションで説明しています。 + +**重要** AWS CloudFormation スタック名が Amazon Simple Storage Service (Amazon S3) バケット名で使用されるため、そのスタック名には小文字のみを含める必要があります。スタック名を入力するときは小文字を使用してください。用意された CloudFormation テンプレートは、us-east-1 region リージョンのバケットからその Lambda コードを取得します。別のリージョンでこのサンプルを起動するには、テンプレートを変更し、そのリージョンのバケットに Lambda コードをアップロードします。 + + +[**Launch Stack**] を選択して、アカウントで us-east-1 リージョンにテンプレートを起動します。 + +[![CloudFormation を使用して Lambda ファイル処理を北バージニアに起動する](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +代わりに、次のコマンドで、AWS CLI を使用してスタックを起動できます。この例では、すでに [AWS CLI をインストール済み](http://docs.aws.amazon.com/cli/latest/userguide/installing.html) であることを前提としています。 + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## 例のテスト + +CloudFormation テンプレートを使用してスタックを作成したら、スタックで作成された InputBucket に Markdown ファイルをアップロードしてシステムをテストできます。レポジトリ内のこの README.md ファイルは、サンプルファイルとして使用できます。ファイルがアップロードされたら、生成される HTML とプレーンテキストファイルをスタックの出力バケットで表示できます。各関数の CloudWatch ログを表示して、実行の詳細を確認することもできます。 + +次のコマンドを使用して、用意された S3 バケットからスタックの入力バケットにサンプルファイルをコピーすることができます。 + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +ファイルが入力バケットにアップロードされたら、出力バケットを検査し、Lambda 関数によって作成され、レンダリングされた HTML およびプレーンテキスト出力ファイルを表示できます。 + +Lambda 関数によって生成された CloudWatch ログを表示することもできます。 + +## リソース例のクリーンアップ + +この例で作成されたすべてのリソースを削除するには、次の操作を行います。 + +1.入出力バケットのすべてのオブジェクトを削除します。 +1.CloudFormation スタックを削除します。 +1.2 つのプロセッサ関数の実行ログを含む CloudWatch ロググループを削除します。 + + + +## CloudFormation テンプレートのリソース + +### パラメーター +- **CodeBucket** - 2 つの Lambda 関数 (ProcessorFunctionOne および ProcessorFunctionTwo) のコードを含む、スタックのリージョンの S3 バケットの名前。デフォルトはマネージドバケット `awslambda-reference-architectures` です。 + +- **CodeKeyPrefix** - `CodeBucket` に相対的な Lambda 関数コードのキープレフィックス。デフォルトは `file-processing` です。 + +### リソース +[用意されたテンプレート](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + では以下のリソースが作成されます。 + +- **InputBucket** - Markdown の raw ファイルを保持する S3 バケット。このバケットにファイルをアップロードすると、両方の処理関数がトリガーされます。 + +- **OutputBucket** - プロセッサ関数によって、変換されたファイルが入力される S3 バケット。 + +- **InputNotificationTopic** - 各オブジェクトの作成通知に応答して複数の Lambda 関数を呼び出すために使用される Amazon Simple Notification Service (Amazon SNS) トピック。 + +- **NotificationPolicy** - トピックで `Publish` アクションを呼び出す `InputBucket` を許可する Amazon SNS トピックポリシー。 + +- **ProcessorFunctionOne** - Markdown ファイルを HTML に変換する AWS Lambda 関数。この関数のデプロイパッケージは `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip` にあります。 + +- **ProcessorFunctionTwo** - Markdown ファイルをプレーンテキストに変換する AWS Lambda 関数。この関数のデプロイパッケージは `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip` にあります。 + +- **LambdaExecutionRole** - 2 つの Lambda 関数によって使用される AWS Identity and Access Management (IAM) ロール。 + +- **RolePolicy** - 関数が `InputBucket` からオブジェクトを取得し、オブジェクトを `OutputBucket` に配置して、Amazon CloudWatch に記録できるようにする **LambdaExecutionRole** に関連付けられた IAM ポリシー。 + +- **LambdaInvokePermissionOne** - Amazon SNS が InputNotificationTopic からの通知に基づいて ProcessorFunctionOne を呼び出せるようにするポリシー。 + +- **LambdaInvokePermissionTwo** - Amazon SNS が InputNotificationTopic からの通知に基づいて ProcessorFunctionTwo を呼び出せるようにするポリシー。 + + +## ライセンス + +このリファレンスアーキテクチャサンプルは Apache 2.0 でライセンスされています。 diff --git a/README/README-KR.md b/README/README-KR.md new file mode 100644 index 0000000..c63e05c --- /dev/null +++ b/README/README-KR.md @@ -0,0 +1,84 @@ +# 서버 없는 레퍼런스 아키텍처: 실시간 파일 처리 + +실시간 파일 처리 레퍼런스 아키텍처는 이벤트 중심의 범용 병렬 데이터 처리 아키텍처이며 [AWS Lambda](https://aws.amazon.com/lambda)를 사용합니다. 이 아키텍처는 객체의 데이터 파생이 하나 이상 필요한 워크로드에 적합합니다. 이 간단한 아키텍처는 이 [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) 및 AWS Compute 블로그의 ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/)에 설명되어 있습니다. 이 단순한 애플리케이션은 Lambda를 사용하여 Markdown 파일을 HTML 및 일반 텍스트로 변환하는 Markdown 변환 애플리케이션을 보여줍니다. + +## 예제 실행 + +제공된 [AWS CloudFormation template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template)을 사용하여 Lambda 파일 처리 레퍼런스 아키텍처를 보여주는 스택을 시작할 수 있습니다. 이 템플릿을 통해 생성된 리소스에 대한 세부 정보는 본 문서의 *CloudFormation 템플릿 리소스* 단원에서 제공됩니다. + +**중요** AWS CloudFormation 스택 이름은 Amazon Simple Storage Service(Amazon S3) 버킷에서 사용되므로 이 스택 이름은 소문자만 포함해야 합니다. 스택 이름을 입력할 때는 소문자만 사용하십시오. 제공된 CloudFormation 템플릿은 us-east-1 리전의 버킷에서 Lambda 코드를 가져옵니다. 이 샘플을 다른 리전에서 시작하려면 템플릿을 수정하고 Lambda 코드를 해당 리전의 버킷에 업로드하십시오. + + +**Launch Stack**을 선택하여 계정의 us-east-1 리전에서 템플릿을 시작합니다. + +[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +그 밖에도 다음 명령을 사용하여 AWS CLI를 사용하여 스택을 시작할 수 있습니다. 이 단계를 실행하기 위해 이미 [installed the AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)를 완료했다고 가정합니다. + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## 예제 테스트 + +CloudFormation 템플릿을 사용하여 스택을 만든 후 Markdown 파일을 스택에 만들어진 InputBucket으로 업로드하여 시스템을 테스트할 수 있습니다. 리포지토리의 이 README.md 파일을 예제 파일로 사용할 수 있습니다. 파일을 업로드한 후 스택의 출력 버킷에서 결과 HTML과 일반 텍스트 파일을 확인할 수 있습니다. 각 함수의 CloudWatch 로그를 통해 각각의 실행 세부 정보를 볼 수도 있습니다. + +다음 명령을 사용하여 제공된 S3 버킷에서 샘플 파일을 스택의 입력 버킷으로 복사할 수 있습니다. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +파일을 입력 버킷으로 업로드한 후 출력 버킷을 검사하여 렌더링된 HTML과 Lambda 함수에 의해 생성된 일반 텍스트 출력 파일을 확인할 수 있습니다. + +Lambda 함수에 의해 생성된 CloudWatch 로그도 볼 수 있습니다. + +## 예제 리소스 정리 + +이 예제에서 생성된 모든 리소스를 제거하려면 다음을 수행합니다. + +1. 입력 및 출력 버킷에서 모든 객체를 삭제합니다. +1. CloudFormation 스택을 삭제합니다. +1. 두 프로세서 함수에 대한 실행 정보가 포함된 CloudWatch 로그 그룹을 삭제합니다. + + + +## CloudFormation 템플릿 리소스 + +### 파라미터 +- **CodeBucket** - 스택의 리전에 있는 S3 버킷의 이름이며 두 Lambda 함수(ProcessorFunctionOne 및 ProcessorFunctionTwo)에 대한 코드가 포함되어 있습니다. 관리형 버킷 `awslambda-reference-architectures`의 기본값입니다. + +- **CodeKeyPrefix** - `CodeBucket`과 관련된 Lambda 함수 코드의 키 접두사입니다. `file-processing`의 기본값입니다. + +### 리소스 +[The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template)은 +다음 리소스를 만듭니다. + +- **InputBucket** - 원시 Markdown 파일이 저장된 S3 버킷입니다. 이 버킷에 파일을 업로드하면 두 처리 함수가 트리거됩니다. + +- **OutputBucket** - 변형된 파일이 있는 프로세서 함수에 의해 채워지는 S3 버킷입니다. + +- **InputNotificationTopic** - 각 객체 생성 알림에 대한 응답으로 여러 Lambda 함수를 호출하는 Amazon Simple Notification Service(Amazon SNS) 주제입니다. + +- **NotificationPolicy** - `InputBucket`이 주제에 대한 `Publish` 작업을 호출할 수 있도록 허용하는 Amazon SNS 주제 정책입니다. + +- **ProcessorFunctionOne** - Markdown 파일을 HTML로 변환하는 AWS Lambda 함수입니다. 이 함수의 배포 패키지가 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`에 있어야 합니다. + +- **ProcessorFunctionTwo** - Markdown 파일을 일반 텍스트로 변환하는 AWS Lambda 함수입니다. 이 함수의 배포 패키지가 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`에 있어야 합니다. + +- **LambdaExecutionRole** - 두 Lambda 함수에서 사용하는 AWS Identity and Access Management(IAM) 역할입니다. + +- **RolePolicy** - **LambdaExecutionRole**과 연결된 IAM 정책이며 함수가 `InputBucket`으로부터 객체를 얻고, `OutputBucket`에 객체를 추가하고 Amazon CloudWatch에 로그를 기록할 수 있도록 허용합니다. + +- **LambdaInvokePermissionOne** - Amazon SNS가 InputNotificationTopic의 알림을 기반으로 ProcessorFunctionOne을 호출할 수 있게 하는 정책입니다. + +- **LambdaInvokePermissionTwo** - Amazon SNS가 InputNotificationTopic의 알림을 기반으로 ProcessorFunctionTwo를 호출할 수 있게 하는 정책입니다. + + +## 라이선스 + +이 레퍼런스 아키텍처 샘플은 Apache 2.0에서 라이선스가 부여되었습니다. diff --git a/README/README-PT.md b/README/README-PT.md new file mode 100644 index 0000000..e84ee94 --- /dev/null +++ b/README/README-PT.md @@ -0,0 +1,84 @@ +# Arquitetura de referência sem servidor: processamento de arquivos em tempo real + +A arquitetura de referência de Processamento de arquivos em tempo real é uma arquitetura de processamento de uso geral, com base em evento e com dados paralelos que usa [AWS Lambda](https://aws.amazon.com/lambda). Esta arquitetura é ideal para cargas de trabalho que precisam de mais de um derivado de dados de um objeto. Esta arquitetura simples está descrita neste [diagrama](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) e em [postagem do blog "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) no Blog de computação da AWS. Esta aplicação da amostra demonstra uma aplicação de conversão Markdown em que o Lambda é usado para converter arquivos Markdown para HTML e texto sem formatação. + +## Executando o exemplo + +Você pode usar o [modelo AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) fornecido para iniciar uma pilha que demonstra a arquitetura de referência de processamento de arquivo Lambda. Os detalhes sobre os recursos criados por este modelo são fornecidos na seção *Recursos do modelo do CloudFormation* deste documento. + +**Importante** Como o nome da pilha do AWS CloudFormation é usado no nome dos buckets Amazon Simple Storage Service (Amazon S3), o nome da pilha deve conter apenas letras minúsculas. Use letras minúsculas ao digitar o nome da pilha. O modelo do CloudFormation fornecido recupera seu código do Lambda de um bucket na região us-east-1. Para iniciar esta amostra em outra região, modifique o modelo e faça o upload do código do Lambda em um bucket nessa região. + + +Escolha **Launch Stack** para iniciar o modelo na região us-east-1 em sua conta: + +[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +Alternativamente, você pode usar o seguinte comando para iniciar a pilha usando o AWS CLI. Isso pressupõe que você já [instalou o AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## Testando o exemplo + +Depois de ter criado a pilha usando o modelo CloudFormation, você pode testar o sistema de upload de um arquivo Markdown para o InputBucket que foi criado na pilha. Você pode usar esse arquivo README.md no repositório como um arquivo de exemplo. Depois que o arquivo foi carregado, você pode ver os arquivos HTML e os textos sem formatação resultantes do bucket de saída da pilha. Você também pode visualizar os registros de CloudWatch para cada uma das funções, a fim de ver os detalhes da sua execução. + +Você pode usar os seguintes comandos para copiar um arquivo de amostra do bucket S3 fornecido dentro do bucket de entrada da sua pilha. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +Depois que o arquivo foi carregado para o bucket de entrada, você pode inspecionar o bucket de saída para ver os arquivos de saída HTML e texto sem formatação criados pelas funções lambda. + +Você também pode visualizar os registros do CloudWatch gerados pelas funções lambda. + +## Limpando os recursos de exemplo + +Para remover todos os recursos criados por este exemplo, faça o seguinte: + +1. Exclua todos os objetos nos buckets de entrada e saída. +1. Exclua a pilha do CloudFormation. +1. Exclua os grupos de registro do CloudWatch que contêm os registros de execução para as duas funções de processador. + + + +## Recursos do modelo do CloudFormation + +### Parâmetros +- **CodeBucket** - Nome do bucket S3 na região da pilha que contém o código para as duas funções Lambda, ProcessorFunctionOne e ProcessorFunctionTwo. O padrão para o bucket gerenciado é "awslambda-reference-architectures". + +- **CodeKeyPrefix** - O prefixo de chaves para o código da função Lambda em relação ao "CodeBucket". O padrão é "file-processing". + +### Recursos +[O modelo fornecido](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +cria os seguintes recursos: + +- **InputBucket** - Um bucket S3 que contém os arquivos Markdown não processados. Fazer upload de um arquivo para este bucket irá desencadear ambas as funções de processamento. + +- **OutputBucket** - Um bucket S3 que é preenchido pelas funções do processador com os arquivos transformados. + +- **InputNotificationTopic** - Um tópico Amazon Simple Notification Service (Amazon SNS) usado para chamar múltiplas funções Lambda em resposta a cada notificação de criação do objeto. + +- **NotificationPolicy** - Uma política de tópico Amazon SNS que permite "Input Bucket" para chamar a ação "Publish" sobre o tema. + +- **ProcessorFunctionOne** - Uma função Lambda AWS que converte os arquivos Markdown para HTML. O pacote de implementação para esta função deve estar localizado em "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip". + +- **ProcessorFunctionTwo** - Uma função Lambda da AWS que converte arquivos Markdown para texto sem formatação. O pacote de implementação para esta função deve estar localizado em "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip". + +- **LambdaExecutionRole** - Uma função AWS Identity and Access Management (IAM) usada pelas duas funções Lambda. + +- **RolePolicy** - Uma política de IAM associada ao **LambdaExecutionRole** que permite às funções obter objetos do "InputBucket", colocar objeto para "OutputBucket" e registro para o Amazon CloudWatch. + +- **LambdaInvokePermissionOne** - Uma política que permite ao Amazon SNS invocar ProcessorFunctionOne com base em notificações dos InputNotificationTopic. + +- **LambdaInvokePermissionTwo** - Uma política que permite ao Amazon SNS invocar ProcessorFunctionTwo com base nas notificações do InputNotificationTopic. + + +## Licença + +Este exemplo de arquitetura de referência é licenciado sob a licença do Apache 2.0. diff --git a/README/README-RU.md b/README/README-RU.md new file mode 100644 index 0000000..716621a --- /dev/null +++ b/README/README-RU.md @@ -0,0 +1,84 @@ +# Эталонная бессерверная архитектура: обработка файлов в реальном времени + +Эталонная архитектура для обработки файлов в реальном времени – это универсальная архитектура параллельной обработки данных на основе событий, которая использует [AWS Lambda](https://aws.amazon.com/lambda). Она идеально подходит для рабочих нагрузок, для которых требуется несколько производных данных объекта. Эта простая архитектура описана на этой [схеме](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) и в ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) в блоге AWS Compute. В примере приложения Lambda используется для преобразования файлов Markdown в HTML и текст. + +## Запуск примера + +Вы можете использовать предоставленный [шаблон AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template), чтобы запустить стек, демонстрирующий эталонную архитектуру для обработки файлов с помощью Lambda. Сведения о ресурсах, созданных этим шаблоном, представлены в разделе «Ресурсы шаблона CloudFormation» этого документа. + +**Важно!** Так как имя стека AWS CloudFormation используется в имени корзин Amazon Simple Storage Service (Amazon S3), оно должно содержать только строчные буквы. При вводе имени стека используйте только строчные буквы. Предоставленный шаблон CloudFormation извлекает код Lambda из корзины в регионе us-east-1. Чтобы запустить пример в другом регионе, измените шаблон и загрузите код Lambda в корзину в этом регионе. + + +Выберите **Launch Stack**, чтобы запустить шаблон в регионе us-east-1 в вашем аккаунте: + +[![Запуск обработки файлов Lambda в Северной Вирджинии с помощью CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +Или же выполните следующую команду, чтобы запустить стек с помощью AWS CLI. При этом предполагается, что вы уже [установили AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## Тестирование примера + +После создания стека с помощью шаблона CloudFormation вы можете проверить систему, загрузив файл Markdown в корзину InputBucket, созданную стеком. Для примера можно использовать файл README.md в этом репозитории. После передачи файла вы увидите полученные HTML-файл и текстовый файл в выходной корзине стека. Вы также можете просмотреть сведения о выполнении каждой функции в журналах CloudWatch. + +Выполните следующие команды, чтобы скопировать пример файла из корзины S3 во входную корзину вашего стека. + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +После передачи файла во входную корзину вы можете просмотреть выходную корзину, где расположены полученные HTML-файл и текстовый файл, созданные функциями Lambda. + +Вы также можете просмотреть журналы CloudWatch, созданные функциями Lambda. + +## Очистка ресурсов примера + +Чтобы удалить все ресурсы, созданные этим примером, выполните следующие действия. + +1. Удалите все объекты во входной и выходной корзинах. +1. Удалите стек CloudFormation. +1. Удалите группы журналов CloudWatch, содержащие журналы выполнения двух функций обработки. + + + +## Ресурсы шаблона CloudFormation + +### Параметры +- **CodeBucket** – имя корзины S3 в регионе стека, содержащей код для двух функций Lambda: ProcessorFunctionOne и ProcessorFunctionTwo. По умолчанию используется управляемая корзина awslambda-reference-architectures. + +- **CodeKeyPrefix** – префикс ключа для кода функции Lambda относительно CodeBucket. Значение по умолчанию: file-processing. + +### Ресурсы +[Предоставленный шаблон](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +создает следующие ресурсы. + +- **InputBucket** – это корзина S3, в которой размещены файлы Markdown. При загрузке файла в эту корзину вызываются обе функции обработки. + +- **OutputBucket** – в эту корзину S3 функции обработки добавляют преобразованные файлы. + +- **InputNotificationTopic** – тема Amazon Simple Notification Service (Amazon SNS), используемая для вызова нескольких функций Lambda в ответ на каждое оповещение о создании объекта. + +- **NotificationPolicy** – политика темы Amazon SNS, позволяющая InputBucket вызвать действие Publish для темы. + +- **ProcessorFunctionOne** – эта функция AWS Lambda преобразует файлы Markdown в HTML. Пакет развертывания для нее должен быть расположен по следующему пути: s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip. + +- **ProcessorFunctionTwo** – эта функция AWS Lambda преобразует файлы Markdown в текстовые файлы. Пакет развертывания для нее должен быть расположен по следующему пути: s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip. + +- **LambdaExecutionRole** – эту роль AWS Identity and Access Management (IAM) используют две функции Lambda. + +- **RolePolicy** – политика IAM, связанная с ролью LambdaExecutionRole, которая позволяет функциям извлекать объекты из корзины InputBucket, добавлять объекты в корзину OutputBucket и вести журнал в Amazon CloudWatch. + +- **LambdaInvokePermissionOne** – политика, позволяющая Amazon SNS вызывать функцию ProcessorFunctionOne в ответ на оповещения от InputNotificationTopic. + +- **LambdaInvokePermissionTwo** – политика, позволяющая Amazon SNS вызывать функцию ProcessorFunctionTwo в ответ на оповещения от InputNotificationTopic. + + +## Лицензия + +Данная эталонная архитектура лицензирована в соответствии с лицензией Apache 2.0. diff --git a/README/README-TW.md b/README/README-TW.md new file mode 100644 index 0000000..7627ab4 --- /dev/null +++ b/README/README-TW.md @@ -0,0 +1,84 @@ +# 無伺服器參考架構：即時檔案處理 + +即時檔案處理參考架構是利用 [AWS Lambda](https://aws.amazon.com/lambda) 運作的一般用途、事件驅動的平行資料處理架構。此架構很適合需要一個以上的物件資料衍生物的工作負載。在 [示意圖](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) 與 AWS 運算部落格的 ["Fanout S3 Event Notifications to Multiple Endpoints" 部落格文章](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) 中，有關於此簡易架構的說明。此簡易的應用程式示範 Markdown 轉換應用程式，Lambda 使用此應用程式將 Markdown 檔案轉換為 HTML 與純文字。 + +## 執行範例 + +您可以使用系統提供的 [AWS CloudFormation 範本](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) 啟動示範 Lambda 檔案處理參考架構的堆疊。本文件的 *CloudFormation 範本資源* 章節中有提供關於此範例所建立資源的詳細資訊。 + +**重要** 由於 AWS CloudFormation 堆疊名稱將使用於 Amazon Simple Storage Service (Amazon S3) 儲存貯體的名稱，因此堆疊名稱只能包含小寫字母。輸入堆疊名稱時，請使用小寫字母。系統提供的 CloudFormation 範本會從 us-east-1 區域的儲存貯體取回其 Lambda 程式碼。若要在其他區域啟動此範例，請修改範本並將 Lambda 程式碼上傳至該區域的儲存貯體。 + + +選擇 **Launch Stack** 以啟動您帳戶的 us-east-1 區域中的範本。 + +[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) + +或者，您可以使用以下命令啟動堆疊以使用 AWS CLI。這裡假設您已 [安裝 AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)。 + +```bash +aws cloudformation create-stack \ + --stack-name lambda-file-processing \ + --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ + --capabilities CAPABILITY_IAM +``` + +## 測試範例 + +在您使用 CloudFormation 範本建立堆疊之後，可藉由將 Markdown 檔案上傳至於堆疊中建立的 InputBucket 以測試系統。您可以使用儲存庫中的 README.md 檔案做為範例檔案。在檔案上傳之後，可在您的堆疊的輸出儲存貯體中看到結果的 HTML 與純文字檔案。您亦可檢視各項功能的 CloudWatch 記錄以查看其執行的詳細資訊。 + +您可以使用以下命令，將範例檔案從系統提供的 S3 儲存貯體複製至您的堆疊的輸入儲存貯體。 + +``` +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +``` + +在檔案上傳至輸入儲存貯體之後，您可以檢查輸出儲存貯體以查看經過 Lambda 功能處理的 HTML 與純文字輸出檔案。 + +您亦可檢視由 Lambda 功能產生的 CloudWatch 記錄。 + +## 清除應用範例資源 + +若要移除此範例建立的所有資源，請執行以下動作： + +1.刪除輸入與輸出儲存貯體中的所有物件。 +1.刪除 CloudFormation 堆疊。 +1.刪除包含兩個處理器功能的執行記錄的 CloudWatch 記錄群組。 + + + +## CloudFormation 範本資源 + +### 參數 +- **CodeBucket** - 包含兩個 Lambda 功能 ProcessorFunctionOne 與 ProcessorFunctionTwo 的堆疊區域中的 S3 儲存貯體的名稱。預設為受管儲存貯體「awslambda-reference-architectures」。 + +- **CodeKeyPrefix** - 與「CodeBucket」相關的 Lambda 功能程式碼的金鑰前綴。預設為「file-processing」。 + +### 資源 +[系統提供的範本](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +建立以下資源： + +- **InputBucket** - 存放原始 Markdown 檔案的 S3 儲存貯體。上傳檔案至此儲存貯體將觸發兩個處理功能。 + +- **OutputBucket** - 由處理器功能與轉換後的檔案所填入的 S3 儲存貯體。 + +- **InputNotificationTopic** - 用於呼叫多個 Lambda 功能以回應各個物件建立通知的 Amazon Simple Notification Service (Amazon SNS) 主題。 + +- **NotificationPolicy** - 允許「InputBucket」呼叫主題上的「Publish」動作的 Amazon SNS 主題政策。 + +- **ProcessorFunctionOne** - 可將 Markdown 檔案轉換為 HTML 的 AWS Lambda 功能。此功能的部署套件必須位於「s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip」。 + +- **ProcessorFunctionTwo** - 可將 Markdown 檔案轉換為純文字的 AWS Lambda 功能。此功能的部署套件必須位於「s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip」。 + +- **LambdaExecutionRole** - 由兩個 Lambda 功能使用的 AWS Identity and Access Management (IAM) 角色。 + +- **RolePolicy** - 與 **LambdaExecutionRole** 關聯的 IAM 政策，它允許功能從「InputBucket」取得物件、將物件放入「OutputBucket」，以及記錄至 Amazon CloudWatch。 + +- **LambdaInvokePermissionOne** - 可讓 Amazon SNS 依據來自 InputNotificationTopic 的通知以呼叫 ProcessorFunctionOne 的一個政策。 + +- **LambdaInvokePermissionTwo** - 可讓 Amazon SNS 依據來自 InputNotificationTopic 的通知以呼叫 ProcessorFunctionTwo 的一個政策。 + + +## 授權 + +此參考架構範例依據 Apache 2.0 授權。 From 16175bf5a7eea3b8b732302153d73ae9f3aba51a Mon Sep 17 00:00:00 2001 From: Kyle Somers Date: Fri, 19 May 2017 12:12:06 -0400 Subject: [PATCH 004/115] updated lambda runtime to 6.10 latest node version --- lambda_file_processing.template | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lambda_file_processing.template b/lambda_file_processing.template index 62f07a0..dac389a 100644 --- a/lambda_file_processing.template +++ b/lambda_file_processing.template @@ -115,7 +115,7 @@ "Arn" ] }, - "Runtime": "nodejs", + "Runtime": "nodejs6.10", "MemorySize": 128, "Timeout": 3 } @@ -135,7 +135,7 @@ "Arn" ] }, - "Runtime": "nodejs", + "Runtime": "nodejs6.10", "MemorySize": 128, "Timeout": 3 } From ab27ff941df07812d937e758246df9b2a7e72cfc Mon Sep 17 00:00:00 2001 From: Ghosh Date: Thu, 29 Mar 2018 13:02:31 -0400 Subject: [PATCH 005/115] added SAM template --- .gitignore | 2 + README.md | 29 ++++ lambda_file_processing.yml | 131 ++++++++++++++++++ .../data-processor-1/data-processor-1.js | 0 src/data-processor-1/package-lock.json | 20 +++ .../data-processor-2/data-processor-2.js | 0 src/data-processor-2/package-lock.json | 20 +++ 7 files changed, 202 insertions(+) create mode 100644 .gitignore create mode 100644 lambda_file_processing.yml rename data-processor-1.js => src/data-processor-1/data-processor-1.js (100%) create mode 100644 src/data-processor-1/package-lock.json rename data-processor-2.js => src/data-processor-2/data-processor-2.js (100%) create mode 100644 src/data-processor-2/package-lock.json diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..c424d5b --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +post-sam.yml +**/node_modules diff --git a/README.md b/README.md index a2dd6e7..d1ea6bd 100644 --- a/README.md +++ b/README.md @@ -25,6 +25,35 @@ aws cloudformation create-stack \ --capabilities CAPABILITY_IAM ``` +## Using SAM + +Install the dependencies for lambda + +```cd src/data-processor-1 && npm install async marked +cd src/data-processor-2 && npm install async marked +``` + +Run SAM package (equivalent to aws cloudformation package) + +``` +aws cloudformation package \ + --template-file lambda_file_processing.yml \ + --s3-bucket sam-stuff \ + --output-template-file post-sam.yml + +``` + + +Deploy the SAM template + +``` +aws cloudformation deploy \ + --template-file ./post-sam.yml \ + --stack-name lambda-file-refarch \ + --capabilities CAPABILITY_IAM +``` + + ## Testing the Example After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use this README.md file in the repository as an example file. After the file has been uploaded, you can see the resulting HTML and plain text files in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. diff --git a/lambda_file_processing.yml b/lambda_file_processing.yml new file mode 100644 index 0000000..ca656d7 --- /dev/null +++ b/lambda_file_processing.yml @@ -0,0 +1,131 @@ +AWSTemplateFormatVersion: '2010-09-09' +Transform: 'AWS::Serverless-2016-10-31' +Description: CFN template to create architecture represented at https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/. +Resources: + ProcessorFunctionOne: + Type: 'AWS::Serverless::Function' + Properties: + Handler: data-processor-1.handler + Runtime: nodejs6.10 + CodeUri: ./src/data-processor-1/ + Role: !GetAtt [LambdaExecutionRole, Arn] + + ProcessorFunctionTwo: + Type: 'AWS::Serverless::Function' + Properties: + Handler: data-processor-2.handler + Runtime: nodejs6.10 + CodeUri: ./src/data-processor-2/ + Role: !GetAtt [LambdaExecutionRole, Arn] + + InputBucket: + Type: AWS::S3::Bucket + Properties: + BucketName: !Join ['-', [!Ref 'AWS::StackName', !Ref 'AWS::AccountId', files]] + NotificationConfiguration: + TopicConfigurations: + - Event: s3:ObjectCreated:* + Topic: !Ref 'InputNotificationTopic' + DependsOn: NotificationPolicy + OutputBucket: + Type: AWS::S3::Bucket + Properties: + BucketName: !Join ['-', [!Ref 'InputBucket', out]] + InputNotificationTopic: + Type: AWS::SNS::Topic + Properties: + Subscription: + - Endpoint: !GetAtt [ProcessorFunctionOne, Arn] + Protocol: lambda + - Endpoint: !GetAtt [ProcessorFunctionTwo, Arn] + Protocol: lambda + NotificationPolicy: + Type: AWS::SNS::TopicPolicy + Properties: + PolicyDocument: + Id: PushBucketNotificationPolicy + Version: '2012-10-17' + Statement: + - Sid: AllowBucketToPushNotificationEffect + Effect: Allow + Principal: + Service: s3.amazonaws.com + Action: sns:Publish + Resource: !Ref 'InputNotificationTopic' + Condition: + ArnLike: + aws:SourceArn: !Join ['', ['arn:aws:s3:*:*:', !Join ['-', [!Ref 'AWS::StackName', + !Ref 'AWS::AccountId', files]]]] + Topics: + - !Ref 'InputNotificationTopic' + LambdaExecutionRole: + Type: AWS::IAM::Role + Properties: + AssumeRolePolicyDocument: + Version: '2012-10-17' + Statement: + - Effect: Allow + Principal: + Service: + - lambda.amazonaws.com + Action: + - sts:AssumeRole + Path: / + RolePolicy: + Type: AWS::IAM::Policy + Properties: + PolicyName: root + PolicyDocument: + Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - logs:CreateLogGroup + - logs:CreateLogStream + - logs:PutLogEvents + Resource: arn:aws:logs:*:*:* + - Effect: Allow + Action: + - s3:GetObject + Resource: !Join ['', ['arn:aws:s3:::', !Ref 'InputBucket', /*]] + - Effect: Allow + Action: + - s3:PutObject + Resource: !Join ['', ['arn:aws:s3:::', !Ref 'OutputBucket', /*]] + Roles: + - !Ref 'LambdaExecutionRole' + LambdaInvokePermissionOne: + Type: AWS::Lambda::Permission + Properties: + FunctionName: !GetAtt [ProcessorFunctionOne, Arn] + Action: lambda:InvokeFunction + Principal: sns.amazonaws.com + SourceArn: !Ref 'InputNotificationTopic' + LambdaInvokePermissionTwo: + Type: AWS::Lambda::Permission + Properties: + FunctionName: !GetAtt [ProcessorFunctionTwo, Arn] + Action: lambda:InvokeFunction + Principal: sns.amazonaws.com + SourceArn: !Ref 'InputNotificationTopic' +Outputs: + Bucket: + Description: Storage location for data which is to be processed by Lambda functions + Value: !Ref 'InputBucket' + BucketOut: + Description: Storage location for data which is to be processed by Lambda functions + Value: !Ref 'OutputBucket' + Topic: + Description: SNS topic to fanout S3 Event notifications to Lambda functions + Value: !Ref 'InputNotificationTopic' + ProcessorFnOne: + Description: Lambda function receiving SNS messages of S3 events + Value: !Ref 'ProcessorFunctionOne' + ProcessorFnTwo: + Description: Lambda function receiving SNS messages of S3 events + Value: !Ref 'ProcessorFunctionTwo' + + + + + \ No newline at end of file diff --git a/data-processor-1.js b/src/data-processor-1/data-processor-1.js similarity index 100% rename from data-processor-1.js rename to src/data-processor-1/data-processor-1.js diff --git a/src/data-processor-1/package-lock.json b/src/data-processor-1/package-lock.json new file mode 100644 index 0000000..881b236 --- /dev/null +++ b/src/data-processor-1/package-lock.json @@ -0,0 +1,20 @@ +{ + "lockfileVersion": 1, + "dependencies": { + "async": { + "version": "2.6.0", + "resolved": "https://registry.npmjs.org/async/-/async-2.6.0.tgz", + "integrity": "sha512-xAfGg1/NTLBBKlHFmnd7PlmUW9KhVQIUuSrYem9xzFUZy13ScvtyGGejaae9iAVRiRq9+Cx7DPFaAAhCpyxyPw==" + }, + "lodash": { + "version": "4.17.5", + "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.5.tgz", + "integrity": "sha512-svL3uiZf1RwhH+cWrfZn3A4+U58wbP0tGVTLQPbjplZxZ8ROD9VLuNgsRniTlLe7OlSqR79RUehXgpBW/s0IQw==" + }, + "marked": { + "version": "0.3.19", + "resolved": "https://registry.npmjs.org/marked/-/marked-0.3.19.tgz", + "integrity": "sha512-ea2eGWOqNxPcXv8dyERdSr/6FmzvWwzjMxpfGB/sbMccXoct+xY+YukPD+QTUZwyvK7BZwcr4m21WBOW41pAkg==" + } + } +} diff --git a/data-processor-2.js b/src/data-processor-2/data-processor-2.js similarity index 100% rename from data-processor-2.js rename to src/data-processor-2/data-processor-2.js diff --git a/src/data-processor-2/package-lock.json b/src/data-processor-2/package-lock.json new file mode 100644 index 0000000..881b236 --- /dev/null +++ b/src/data-processor-2/package-lock.json @@ -0,0 +1,20 @@ +{ + "lockfileVersion": 1, + "dependencies": { + "async": { + "version": "2.6.0", + "resolved": "https://registry.npmjs.org/async/-/async-2.6.0.tgz", + "integrity": "sha512-xAfGg1/NTLBBKlHFmnd7PlmUW9KhVQIUuSrYem9xzFUZy13ScvtyGGejaae9iAVRiRq9+Cx7DPFaAAhCpyxyPw==" + }, + "lodash": { + "version": "4.17.5", + "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.5.tgz", + "integrity": "sha512-svL3uiZf1RwhH+cWrfZn3A4+U58wbP0tGVTLQPbjplZxZ8ROD9VLuNgsRniTlLe7OlSqR79RUehXgpBW/s0IQw==" + }, + "marked": { + "version": "0.3.19", + "resolved": "https://registry.npmjs.org/marked/-/marked-0.3.19.tgz", + "integrity": "sha512-ea2eGWOqNxPcXv8dyERdSr/6FmzvWwzjMxpfGB/sbMccXoct+xY+YukPD+QTUZwyvK7BZwcr4m21WBOW41pAkg==" + } + } +} From c7333ba56db55eb9750ffe702380c2559dcf2644 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Thu, 29 Mar 2018 13:04:24 -0400 Subject: [PATCH 006/115] minor change to readme --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index d1ea6bd..9dea670 100644 --- a/README.md +++ b/README.md @@ -29,7 +29,8 @@ aws cloudformation create-stack \ Install the dependencies for lambda -```cd src/data-processor-1 && npm install async marked +``` +cd src/data-processor-1 && npm install async marked cd src/data-processor-2 && npm install async marked ``` From 26b1bfabd6013ebf68bfb69c1210f4cd2b7b4986 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 11:05:54 -0400 Subject: [PATCH 007/115] adding pipeline --- pipeline/main.yaml | 68 ++++++++++++++ pipeline/pipeline-roles.yaml | 136 ++++++++++++++++++++++++++++ pipeline/pipeline.yaml | 170 +++++++++++++++++++++++++++++++++++ 3 files changed, 374 insertions(+) create mode 100644 pipeline/main.yaml create mode 100644 pipeline/pipeline-roles.yaml create mode 100644 pipeline/pipeline.yaml diff --git a/pipeline/main.yaml b/pipeline/main.yaml new file mode 100644 index 0000000..5786400 --- /dev/null +++ b/pipeline/main.yaml @@ -0,0 +1,68 @@ +AWSTemplateFormatVersion: "2010-09-09" +Description: "Main template for a CI/CD Serverless application." +Parameters: + AppName: + Type: String + Description: Name of the application + MinLength: "1" + MaxLength: "80" + AllowedPattern: "[A-Za-z0-9-]+" + ConstraintDescription: Malformed input parameter. AppName must only contain upper and lower case letters, numbers, and -. + SAMInputFile: + Type: String + Description: The filename for the SAM file. + Default: lambda_file_processing.yml + SAMOutputFile: + Type: String + Description: The filename for the output SAM file from the buildspec file. + Default: post-sam.yaml + CodeBuildImage: + Type: String + Default: "aws/codebuild/nodejs:4.3.2" + Description: Image used for CodeBuild project. + CICDS3BucketName: + Type: String + Default: "sam-stuff" + Description: S3 Bucket where the pipeline templates live + GitHubRepoName: + Type: String + Default: "" + Description: The GitHub repo name + GitHubRepoBranch: + Type: String + Description: The GitHub repo branch code pipelines should watch for changes on + Default: master + GitHubUser: + Type: String + Description: GitHub UserName. This username must have access to the GitHubToken. + GitHubToken: + NoEcho: true + Type: String + Description: "Secret. OAuthToken with access to Repo. Long string of characters and digits. Go to https://github.com/settings/tokens" +Resources: + ServerlessRoles: + Type: "AWS::CloudFormation::Stack" + Properties: + Parameters: + AppName: !Ref AppName + TemplateURL: + Fn::Sub: https://${CICDS3BucketName}.s3.amazonaws.com/templates/pipeline-roles.yaml + ServerlessPipeline: + Type: "AWS::CloudFormation::Stack" + DependsOn: [ServerlessRoles] + Properties: + Parameters: + AppName: !Ref AppName + SAMInputFile: !Ref SAMInputFile + SAMOutputFile: !Ref SAMOutputFile + CodeBuildImage: !Ref CodeBuildImage + GitHubRepoName: !Ref GitHubRepoName + GitHubRepoBranch: !Ref GitHubRepoBranch + GitHubUser: !Ref GitHubUser + GitHubToken: !Ref GitHubToken + CICDS3BucketName: !Ref CICDS3BucketName + CodePipelineRole: !GetAtt ServerlessRoles.Outputs.CodePipelineRole + CloudformationRole: !GetAtt ServerlessRoles.Outputs.CloudformationDeployRole + CodeBuildRole: !GetAtt ServerlessRoles.Outputs.CodeBuildRole + TemplateURL: + Fn::Sub: https://${CICDS3BucketName}.s3.amazonaws.com/templates/pipeline.yaml diff --git a/pipeline/pipeline-roles.yaml b/pipeline/pipeline-roles.yaml new file mode 100644 index 0000000..b9906db --- /dev/null +++ b/pipeline/pipeline-roles.yaml @@ -0,0 +1,136 @@ +AWSTemplateFormatVersion: "2010-09-09" +Description: Common resources for application deployed to Lambda +Parameters: + AppName: + Type: String + Description: Name of the application. + MinLength: "1" + MaxLength: "100" +Resources: + CodeBuildTrustRole: + Description: Creating service role in IAM for AWS CodeBuild + Type: AWS::IAM::Role + Properties: + RoleName: !Sub "${AppName}-codebuild-role" + AssumeRolePolicyDocument: + Statement: + - Effect: Allow + Principal: + Service: [codebuild.amazonaws.com] + Action: sts:AssumeRole + Path: / + CodeBuildRolePolicy: + Type: AWS::IAM::Policy + DependsOn: CodeBuildTrustRole + Description: Setting IAM policy for the service role for AWS CodeBuild + Properties: + PolicyName: CodeBuildRolePolicy + PolicyDocument: + Statement: + - Effect: Allow + Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] + Resource: ["*"] + - Effect: Allow + Resource: ["*"] + Action: ["s3:*"] + - Effect: Allow + Resource: ["*"] + Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] + - Effect: Allow + Resource: ["*"] + Action: ["sns:SendMessage"] + Roles: [!Ref CodeBuildTrustRole] + CloudFormationTrustRole: + Description: Creating service role in IAM for AWS CloudFormation + Type: AWS::IAM::Role + Properties: + RoleName: !Sub "${AppName}-cloudformation-role" + AssumeRolePolicyDocument: + Statement: + - Effect: Allow + Principal: + Service: [cloudformation.amazonaws.com] + Action: sts:AssumeRole + Path: / + CloudFormationRolePolicy: + Type: AWS::IAM::Policy + DependsOn: CloudFormationTrustRole + Description: Setting IAM policy for the service role for AWS CloudFormation + Properties: + PolicyName: CloudFormationRolePolicy + PolicyDocument: + Statement: + - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] + Resource: "*" + Effect: Allow + - Action: ["s3:PutObject"] + Resource: ["arn:aws:s3:::codepipeline*"] + Effect: Allow + - Action: ["lambda:*"] + Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" + Effect: Allow + - Action: ["apigateway:*"] + Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Effect: Allow + - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Effect: Allow + - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy"] + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Effect: Allow + - Action: ["iam:PassRole"] + Resource: ["*"] + Effect: Allow + - Action: ["cloudformation:CreateChangeSet"] + Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" + Effect: Allow + - Action: ["cloudformation:CreateChangeSet"] + Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Include" + Effect: Allow + Roles: [!Ref CloudFormationTrustRole] + CodePipelineTrustRole: + Description: Creating service role in IAM for AWS CodePipeline + Type: AWS::IAM::Role + Properties: + RoleName: !Sub "${AppName}-codepipeline-role" + AssumeRolePolicyDocument: + Statement: + - Effect: Allow + Principal: + Service: [codepipeline.amazonaws.com] + Action: sts:AssumeRole + Path: / + CodePipelineRolePolicy: + Type: AWS::IAM::Policy + DependsOn: CodePipelineTrustRole + Description: Setting IAM policy for the service role for AWS CodePipeline + Properties: + PolicyName: CodePipelineRolePolicy + PolicyDocument: + Statement: + - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] + Resource: "*" + Effect: Allow + - Action: ["s3:PutObject"] + Resource: ["arn:aws:s3:::codepipeline*"] + Effect: Allow + - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] + Resource: "*" + Effect: Allow + - Action: ["cloudwatch:*", "s3:*", "sns:*", "cloudformation:*", "rds:*", "sqs:*", "iam:PassRole"] + Resource: "*" + Effect: Allow + - Action: ["lambda:InvokeFunction", "lambda:ListFunctions"] + Resource: "*" + Effect: Allow + Roles: [!Ref CodePipelineTrustRole] +Outputs: + CodePipelineRole: + Description: "Role for code pipeline" + Value: !GetAtt CodePipelineTrustRole.Arn + CloudformationDeployRole: + Description: "Role for cloudformation to deploy with." + Value: !GetAtt CloudFormationTrustRole.Arn + CodeBuildRole: + Description: "Role for code build to build" + Value: !GetAtt CodeBuildTrustRole.Arn diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml new file mode 100644 index 0000000..ea98632 --- /dev/null +++ b/pipeline/pipeline.yaml @@ -0,0 +1,170 @@ +AWSTemplateFormatVersion: "2010-09-09" +Description: "Template for full CI/CD serverless applications." +Parameters: + AppName: + Type: String + Description: Name of the application. + SAMInputFile: + Type: String + Description: The filename for the SAM file. + SAMOutputFile: + Type: String + Description: The filename for the output SAM file from the buildspec file + CodeBuildImage: + Type: String + Default: "aws/codebuild/nodejs:4.3.2" + Description: Image used for CodeBuild project. + GitHubRepoName: + Type: String + Description: The GitHub repo name + GitHubRepoBranch: + Type: String + Description: The GitHub repo branch code pipelines should watch for changes on + Default: master + GitHubUser: + Type: String + Description: GitHub UserName. This username must have access to the GitHubToken. + GitHubToken: + NoEcho: true + Type: String + Description: "Secret. OAuthToken with access to Repo. Long string of characters and digits. Go to https://github.com/settings/tokens" + CodePipelineRole: + Type: String + Description: Role the pipeline will use + CloudformationRole: + Type: String + Description: Role for cloudformation + CodeBuildRole: + Type: String + Description: Role for code build + CICDS3BucketName: + Type: String + Description: S3 Bucket where the pipeline templates live +Resources: + CodeBuildProject: + DependsOn: [S3Bucket] + Description: Creating AWS CodeBuild project + Type: AWS::CodeBuild::Project + Properties: + Artifacts: + Type: CODEPIPELINE + Description: !Sub "Building stage for ${AppName}." + Environment: + ComputeType: BUILD_GENERAL1_SMALL + EnvironmentVariables: + - Name: S3_BUCKET + Value: !Ref S3Bucket + - Name: INPUT_FILE + Value: !Ref SAMInputFile + Image: !Ref CodeBuildImage + Type: LINUX_CONTAINER + Name: !Sub "${AppName}-build" + ServiceRole: !Ref CodeBuildRole + Source: + Type: CODEPIPELINE + Tags: + - Key: app-name + Value: !Ref AppName + TimeoutInMinutes: 5 + S3Bucket: + Description: Creating Amazon S3 bucket for AWS CodePipeline artifacts + Type: AWS::S3::Bucket + DeletionPolicy: Retain + Properties: + BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}" + VersioningConfiguration: + Status: Enabled + S3ArtifactBucketPolicy: + DependsOn: [S3Bucket] + Description: Setting Amazon S3 bucket policy for AWS CodePipeline access + Type: AWS::S3::BucketPolicy + Properties: + Bucket: !Ref S3Bucket + PolicyDocument: + Version: "2012-10-17" + Id: SSEAndSSLPolicy + Statement: + - Sid: DenyInsecureConnections + Effect: Deny + Principal: "*" + Action: s3:* + Resource: !Sub "arn:aws:s3:::${S3Bucket}/*" + Condition: + Bool: + aws:SecureTransport: false + ProjectPipeline: + DependsOn: [S3Bucket, CodeBuildProject] + Description: Creating a deployment pipeline for your project in AWS CodePipeline + Type: AWS::CodePipeline::Pipeline + Properties: + Name: !Sub "${AppName}-pipeline" + RoleArn: !Ref CodePipelineRole + Stages: + - Name: Source + Actions: + - Name: source + InputArtifacts: [] + ActionTypeId: + Version: "1" + Category: Source + Owner: ThirdParty + Provider: GitHub + OutputArtifacts: + - Name: !Sub "${AppName}-SourceArtifact" + Configuration: + Repo: !Ref GitHubRepoName + Branch: !Ref GitHubRepoBranch + OAuthToken: !Ref GitHubToken + Owner: !Ref GitHubUser + RunOrder: 1 + - Name: Build + Actions: + - Name: build-from-source + InputArtifacts: + - Name: !Sub "${AppName}-SourceArtifact" + ActionTypeId: + Category: Build + Owner: AWS + Version: "1" + Provider: CodeBuild + OutputArtifacts: + - Name: !Sub "${AppName}-BuildArtifact" + Configuration: + ProjectName: !Sub "${AppName}-build" + RunOrder: 1 + - Name: Deploy + Actions: + - Name: create-changeset + InputArtifacts: + - Name: !Sub "${AppName}-BuildArtifact" + ActionTypeId: + Category: Deploy + Owner: AWS + Version: "1" + Provider: CloudFormation + OutputArtifacts: [] + Configuration: + StackName: !Sub "${AppName}-serverless-stack" + ActionMode: CHANGE_SET_REPLACE + RoleArn: !Ref CloudformationRole + ChangeSetName: pipeline-changeset + Capabilities: CAPABILITY_NAMED_IAM + TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" + ParameterOverrides: !Sub '"CICDS3BucketName":"${CICDS3BucketName}"}' + RunOrder: 1 + - Name: execute-changeset + InputArtifacts: [] + ActionTypeId: + Category: Deploy + Owner: AWS + Version: "1" + Provider: CloudFormation + OutputArtifacts: [] + Configuration: + StackName: !Sub "${AppName}-serverless-stack" + ActionMode: CHANGE_SET_EXECUTE + ChangeSetName: pipeline-changeset + RunOrder: 2 + ArtifactStore: + Type: S3 + Location: !Ref S3Bucket From 52eb822f21eb95fec054911b9f4961407f4868a4 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 11:35:46 -0400 Subject: [PATCH 008/115] changing buildspec.yml location --- src/buildspec.yml | 12 ++++++++++++ 1 file changed, 12 insertions(+) create mode 100644 src/buildspec.yml diff --git a/src/buildspec.yml b/src/buildspec.yml new file mode 100644 index 0000000..e5d7de7 --- /dev/null +++ b/src/buildspec.yml @@ -0,0 +1,12 @@ +version: 0.0 +containers: + LambdaFunctions: + phases: + during_build: + commands: + - cd data-processor-1 && pwd && npm install + - cd data-processor-2 && pwd && npm install + - aws cloudformation package --template $INPUT_FILE --s3-bucket $S3_BUCKET --output-template post-sam.yaml + artifacts: + files: + - post-sam.yaml From e0ea2bcc1c6a0dfe0c170361de332b3cd54b6697 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 11:49:42 -0400 Subject: [PATCH 009/115] rollback previous change --- src/buildspec.yml => buildspec.yml | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename src/buildspec.yml => buildspec.yml (100%) diff --git a/src/buildspec.yml b/buildspec.yml similarity index 100% rename from src/buildspec.yml rename to buildspec.yml From 5da0a694f51e96fe4c36c136b78e37dd2f3f2fcb Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 11:54:48 -0400 Subject: [PATCH 010/115] fix buildspec --- buildspec.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/buildspec.yml b/buildspec.yml index e5d7de7..49d349b 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -4,8 +4,8 @@ containers: phases: during_build: commands: - - cd data-processor-1 && pwd && npm install - - cd data-processor-2 && pwd && npm install + - cd src/data-processor-1 && pwd && npm install + - cd src/data-processor-2 && pwd && npm install - aws cloudformation package --template $INPUT_FILE --s3-bucket $S3_BUCKET --output-template post-sam.yaml artifacts: files: From 272f2ab9103c9895854084afd82edd8b3ac8925f Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 11:57:52 -0400 Subject: [PATCH 011/115] added package.json --- src/data-processor-2/package-lock.json | 20 ------------------- .../package.json} | 0 2 files changed, 20 deletions(-) delete mode 100644 src/data-processor-2/package-lock.json rename src/{data-processor-1/package-lock.json => data-processor-2/package.json} (100%) diff --git a/src/data-processor-2/package-lock.json b/src/data-processor-2/package-lock.json deleted file mode 100644 index 881b236..0000000 --- a/src/data-processor-2/package-lock.json +++ /dev/null @@ -1,20 +0,0 @@ -{ - "lockfileVersion": 1, - "dependencies": { - "async": { - "version": "2.6.0", - "resolved": "https://registry.npmjs.org/async/-/async-2.6.0.tgz", - "integrity": "sha512-xAfGg1/NTLBBKlHFmnd7PlmUW9KhVQIUuSrYem9xzFUZy13ScvtyGGejaae9iAVRiRq9+Cx7DPFaAAhCpyxyPw==" - }, - "lodash": { - "version": "4.17.5", - "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.5.tgz", - "integrity": "sha512-svL3uiZf1RwhH+cWrfZn3A4+U58wbP0tGVTLQPbjplZxZ8ROD9VLuNgsRniTlLe7OlSqR79RUehXgpBW/s0IQw==" - }, - "marked": { - "version": "0.3.19", - "resolved": "https://registry.npmjs.org/marked/-/marked-0.3.19.tgz", - "integrity": "sha512-ea2eGWOqNxPcXv8dyERdSr/6FmzvWwzjMxpfGB/sbMccXoct+xY+YukPD+QTUZwyvK7BZwcr4m21WBOW41pAkg==" - } - } -} diff --git a/src/data-processor-1/package-lock.json b/src/data-processor-2/package.json similarity index 100% rename from src/data-processor-1/package-lock.json rename to src/data-processor-2/package.json From 4bc7d56c334ce94446d30f2f0b73b4c354335892 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 15:40:04 -0400 Subject: [PATCH 012/115] removed dependency on local package.json --- buildspec.yml | 4 ++-- src/data-processor-2/package.json | 20 -------------------- 2 files changed, 2 insertions(+), 22 deletions(-) delete mode 100644 src/data-processor-2/package.json diff --git a/buildspec.yml b/buildspec.yml index 49d349b..587bc5f 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -4,8 +4,8 @@ containers: phases: during_build: commands: - - cd src/data-processor-1 && pwd && npm install - - cd src/data-processor-2 && pwd && npm install + - cd src/data-processor-1 && pwd && npm install async marked + - cd src/data-processor-2 && pwd && npm install async marked - aws cloudformation package --template $INPUT_FILE --s3-bucket $S3_BUCKET --output-template post-sam.yaml artifacts: files: diff --git a/src/data-processor-2/package.json b/src/data-processor-2/package.json deleted file mode 100644 index 881b236..0000000 --- a/src/data-processor-2/package.json +++ /dev/null @@ -1,20 +0,0 @@ -{ - "lockfileVersion": 1, - "dependencies": { - "async": { - "version": "2.6.0", - "resolved": "https://registry.npmjs.org/async/-/async-2.6.0.tgz", - "integrity": "sha512-xAfGg1/NTLBBKlHFmnd7PlmUW9KhVQIUuSrYem9xzFUZy13ScvtyGGejaae9iAVRiRq9+Cx7DPFaAAhCpyxyPw==" - }, - "lodash": { - "version": "4.17.5", - "resolved": "https://registry.npmjs.org/lodash/-/lodash-4.17.5.tgz", - "integrity": "sha512-svL3uiZf1RwhH+cWrfZn3A4+U58wbP0tGVTLQPbjplZxZ8ROD9VLuNgsRniTlLe7OlSqR79RUehXgpBW/s0IQw==" - }, - "marked": { - "version": "0.3.19", - "resolved": "https://registry.npmjs.org/marked/-/marked-0.3.19.tgz", - "integrity": "sha512-ea2eGWOqNxPcXv8dyERdSr/6FmzvWwzjMxpfGB/sbMccXoct+xY+YukPD+QTUZwyvK7BZwcr4m21WBOW41pAkg==" - } - } -} From bad24535a3b6bce30a20eb0aecc70d84b38a6a90 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 15:53:16 -0400 Subject: [PATCH 013/115] fixed an error in template --- pipeline/pipeline.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index ea98632..3813ba4 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -150,7 +150,7 @@ Resources: ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" - ParameterOverrides: !Sub '"CICDS3BucketName":"${CICDS3BucketName}"}' + ParameterOverrides: !Sub '{"CICDS3BucketName":"${CICDS3BucketName}"}' RunOrder: 1 - Name: execute-changeset InputArtifacts: [] From 5f49d8c535a626999e1714b61b502b6c55880714 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 15:59:35 -0400 Subject: [PATCH 014/115] added a file list to observe if the npm deps are being downloaded in correct dir --- buildspec.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/buildspec.yml b/buildspec.yml index 587bc5f..d30b0d2 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -5,7 +5,7 @@ containers: during_build: commands: - cd src/data-processor-1 && pwd && npm install async marked - - cd src/data-processor-2 && pwd && npm install async marked + - cd src/data-processor-2 && npm install async marked && ls - aws cloudformation package --template $INPUT_FILE --s3-bucket $S3_BUCKET --output-template post-sam.yaml artifacts: files: From dfd274c732782d17fa60bd22f1792d8357f09e5e Mon Sep 17 00:00:00 2001 From: Ghosh Date: Fri, 30 Mar 2018 16:20:15 -0400 Subject: [PATCH 015/115] fixing parameter overrides --- pipeline/pipeline.yaml | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 3813ba4..f9e324a 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -150,7 +150,10 @@ Resources: ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" - ParameterOverrides: !Sub '{"CICDS3BucketName":"${CICDS3BucketName}"}' + ParameterOverrides: !Sub | + { + "CICDS3BucketName": "${CICDS3BucketName}" + } RunOrder: 1 - Name: execute-changeset InputArtifacts: [] From 8a7478ac654cc4e073a8951d1fde5aaf7d5b825b Mon Sep 17 00:00:00 2001 From: Ghosh Date: Tue, 17 Apr 2018 16:26:06 -0400 Subject: [PATCH 016/115] fixing param overrides --- pipeline/pipeline.yaml | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index f9e324a..826e9c0 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -150,10 +150,7 @@ Resources: ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" - ParameterOverrides: !Sub | - { - "CICDS3BucketName": "${CICDS3BucketName}" - } + #ParameterOverrides: !Sub '{"CICDS3BucketName":"${CICDS3BucketName}"}' RunOrder: 1 - Name: execute-changeset InputArtifacts: [] From 2ba2d74ed1eb2fc25de6a782e7a9daea4a294e0b Mon Sep 17 00:00:00 2001 From: Ghosh Date: Tue, 17 Apr 2018 17:01:45 -0400 Subject: [PATCH 017/115] added sns permission to cfn role --- pipeline/pipeline-roles.yaml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/pipeline/pipeline-roles.yaml b/pipeline/pipeline-roles.yaml index b9906db..2451f24 100644 --- a/pipeline/pipeline-roles.yaml +++ b/pipeline/pipeline-roles.yaml @@ -72,6 +72,9 @@ Resources: - Action: ["apigateway:*"] Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" Effect: Allow + - Action: ["sns:*"] + Resource: !Sub "arn:aws:sns:${AWS::Region}::*" + Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow From 56ea763d4061a4f02cbeccd8cc054a4d35e53c66 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Tue, 17 Apr 2018 17:18:06 -0400 Subject: [PATCH 018/115] Yaml error --- pipeline/pipeline-roles.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipeline/pipeline-roles.yaml b/pipeline/pipeline-roles.yaml index 2451f24..45801bb 100644 --- a/pipeline/pipeline-roles.yaml +++ b/pipeline/pipeline-roles.yaml @@ -72,7 +72,7 @@ Resources: - Action: ["apigateway:*"] Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" Effect: Allow - - Action: ["sns:*"] + - Action: ["sns:*"] Resource: !Sub "arn:aws:sns:${AWS::Region}::*" Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] From f20368be9ecb518c4ef460c79f023b77214090e0 Mon Sep 17 00:00:00 2001 From: Ghosh Date: Tue, 24 Apr 2018 19:29:43 -0400 Subject: [PATCH 019/115] fixed sns permissions --- pipeline/pipeline-roles.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pipeline/pipeline-roles.yaml b/pipeline/pipeline-roles.yaml index 45801bb..5d2e759 100644 --- a/pipeline/pipeline-roles.yaml +++ b/pipeline/pipeline-roles.yaml @@ -73,7 +73,7 @@ Resources: Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" Effect: Allow - Action: ["sns:*"] - Resource: !Sub "arn:aws:sns:${AWS::Region}::*" + Resource: !Sub "arn:aws:sns:${AWS::Region}:*:*" Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" From d516463b214e318a0b7aa5ae4733d02cc181271b Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Fri, 27 Sep 2019 17:35:27 -0400 Subject: [PATCH 020/115] Initial version of updated architecture. * Triggering CloudWatch Events from CloudTrail logs --- .gitignore | 1 + file_processing.yml | 175 ++++++++++++++++++++++++++++++++ src/conversion/conversion.py | 7 ++ src/conversion/requirements.txt | 1 + src/sentiment/sentiment.py | 5 + 5 files changed, 189 insertions(+) create mode 100644 file_processing.yml create mode 100644 src/conversion/conversion.py create mode 100644 src/conversion/requirements.txt create mode 100644 src/sentiment/sentiment.py diff --git a/.gitignore b/.gitignore index c424d5b..ee50dd7 100644 --- a/.gitignore +++ b/.gitignore @@ -1,2 +1,3 @@ +packaged-template.yml post-sam.yml **/node_modules diff --git a/file_processing.yml b/file_processing.yml new file mode 100644 index 0000000..f550577 --- /dev/null +++ b/file_processing.yml @@ -0,0 +1,175 @@ +AWSTemplateFormatVersion: '2010-09-09' +Transform: 'AWS::Serverless-2016-10-31' +Description: SAM template to create file processing architecture represented at TBD. + +Resources: + InputBucket: + Type: AWS::S3::Bucket + + CloudTrailBucket: + Type: AWS::S3::Bucket + + InputBucketTrail: + DependsOn: CloudTrailBucketPolicy + Type: AWS::CloudTrail::Trail + Properties: + S3BucketName: !Ref CloudTrailBucket + EventSelectors: + - DataResources: + - Type: 'AWS::S3::Object' + Values: + - !Sub |- + arn:aws:s3:::${InputBucket}/ + IncludeManagementEvents: false + ReadWriteType: WriteOnly + IsLogging: true + + CloudTrailBucketPolicy: + Type: AWS::S3::BucketPolicy + DependsOn: CloudTrailBucket + Properties: + Bucket: !Ref CloudTrailBucket + PolicyDocument: + Version: "2012-10-17" + Statement: + - + Sid: "AWSCloudTrailAclCheck" + Effect: "Allow" + Principal: + Service: "cloudtrail.amazonaws.com" + Action: "s3:GetBucketAcl" + Resource: !Sub |- + arn:aws:s3:::${CloudTrailBucket} + - + Sid: "AWSCloudTrailWrite" + Effect: "Allow" + Principal: + Service: "cloudtrail.amazonaws.com" + Action: "s3:PutObject" + Resource: + !Sub |- + arn:aws:s3:::${CloudTrailBucket}/AWSLogs/${AWS::AccountId}/* + Condition: + StringEquals: + s3:x-amz-acl: "bucket-owner-full-control" + + FileProcessingQueuePolicy: + # https://forums.aws.amazon.com/message.jspa?messageID=743094 + Type: AWS::SQS::QueuePolicy + Properties: + Queues: + - !Ref ConversionQueue + - !Ref SentimentQueue + PolicyDocument: + Version: '2012-10-17' + Statement: + - + Effect: Allow + Principal: + AWS: '*' + Action: + - sqs:SendMessage + Resource: !GetAtt ConversionQueue.Arn + Condition: + ArnEquals: + aws:SourceArn: !GetAtt FileProcessingRule.Arn + - + Effect: Allow + Principal: + AWS: '*' + Action: + - sqs:SendMessage + Resource: !GetAtt SentimentQueue.Arn + Condition: + ArnEquals: + aws:SourceArn: !GetAtt FileProcessingRule.Arn + + FileProcessingRule: + Type: AWS::Events::Rule + DependsOn: + - ConversionQueue + - SentimentQueue + Properties: + Description: Rule to capture S3 PutObject events + EventPattern: + source: + - aws.s3 + detail-type: + - AWS API Call via CloudTrail + detail: + eventSource: + - s3.amazonaws.com + eventName: + - PutObject + requestParameters: + bucketName: + - !Ref InputBucket + State: 'ENABLED' + Targets: + - Arn: !GetAtt ConversionQueue.Arn + Id: Convert + - Arn: !GetAtt SentimentQueue.Arn + Id: Sentiment + + ConversionQueue: + Type: AWS::SQS::Queue + DependsOn: ConversionDlq + Properties: + VisibilityTimeout: 300 + RedrivePolicy: + deadLetterTargetArn: !GetAtt ConversionDlq.Arn + maxReceiveCount: 5 + + ConversionDlq: + Type: AWS::SQS::Queue + Properties: + VisibilityTimeout: 300 + + ConversionFunction: + Type: 'AWS::Serverless::Function' + Properties: + Handler: conversion.handler + Runtime: python3.6 + CodeUri: ./src/conversion/ + Policies: + - SQSPollerPolicy: + QueueName: + !GetAtt ConversionQueue.Arn + Events: + ConversionQueueReaderEvent: + Type: SQS + Properties: + Queue: !GetAtt ConversionQueue.Arn + BatchSize: 10 + + SentimentQueue: + Type: AWS::SQS::Queue + DependsOn: SentimentDlq + Properties: + VisibilityTimeout: 300 + RedrivePolicy: + deadLetterTargetArn: !GetAtt SentimentDlq.Arn + maxReceiveCount: 5 + + SentimentDlq: + Type: AWS::SQS::Queue + Properties: + VisibilityTimeout: 300 + + SentimentFunction: + Type: 'AWS::Serverless::Function' + Properties: + Handler: sentiment.handler + Runtime: python3.6 + CodeUri: ./src/sentiment/ + Policies: + - SQSPollerPolicy: + QueueName: + !GetAtt SentimentQueue.Arn + Events: + SentimentQueueReaderEvent: + Type: SQS + Properties: + Queue: !GetAtt SentimentQueue.Arn + BatchSize: 10 + \ No newline at end of file diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py new file mode 100644 index 0000000..292bbc3 --- /dev/null +++ b/src/conversion/conversion.py @@ -0,0 +1,7 @@ +def handler(event, context): + # records = event['Records'] + # print(records) + print(event) + return('ok') + + diff --git a/src/conversion/requirements.txt b/src/conversion/requirements.txt new file mode 100644 index 0000000..3cda9eb --- /dev/null +++ b/src/conversion/requirements.txt @@ -0,0 +1 @@ +markdown \ No newline at end of file diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py new file mode 100644 index 0000000..07e04ab --- /dev/null +++ b/src/sentiment/sentiment.py @@ -0,0 +1,5 @@ +def handler(event, context): + # records = event['Records'] + # print(records) + print(event) + return('ok') \ No newline at end of file From 3447d7a426a9685920deef705ad864d7ee1fe953 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Sun, 29 Sep 2019 14:58:46 -0400 Subject: [PATCH 021/115] Working version to convert markdown file to html and upload to target bucket --- README.md | 55 +++++----- file_processing.yml | 13 +++ img/lambda-refarch-fileprocessing-simple.png | Bin 0 -> 79859 bytes src/conversion/conversion.py | 105 ++++++++++++++++++- src/conversion/requirements.txt | 1 + 5 files changed, 144 insertions(+), 30 deletions(-) create mode 100644 img/lambda-refarch-fileprocessing-simple.png diff --git a/README.md b/README.md index 9dea670..7bf7496 100644 --- a/README.md +++ b/README.md @@ -5,9 +5,13 @@ README Languages: [DE](README/README-DE.md) | [ES](README/README-ES.md) | [FR]( The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. This simple architecture is described in this [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) and ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) on the AWS Compute Blog. This sample application demonstrates a Markdown conversion application where Lambda is used to convert Markdown files to HTML and plain text. +## Architectural Diagram + +![Reference Architecture - Real-time File Processing](img/lambda-refarch-fileprocessing-simple.png) + ## Running the Example -You can use the provided [AWS CloudFormation template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *CloudFormation Template Resources* section of this document. +You can use the provided [AWS SAM template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *CloudFormation Template Resources* section of this document. **Important** Because the AWS CloudFormation stack name is used in the name of the Amazon Simple Storage Service (Amazon S3) buckets, that stack name must only contain lowercase letters. Use lowercase letters when typing the stack name. The provided CloudFormation template retrieves its Lambda code from a bucket in the us-east-1 region. To launch this sample in another region, please modify the template and upload the Lambda code to a bucket in that region. @@ -29,27 +33,26 @@ aws cloudformation create-stack \ Install the dependencies for lambda -``` -cd src/data-processor-1 && npm install async marked -cd src/data-processor-2 && npm install async marked +```bash +cd src/conversion && pip install -r requirements.txt -t . +cd src/sentiment && pip install -r requirements.txt -t . ``` Run SAM package (equivalent to aws cloudformation package) -``` -aws cloudformation package \ - --template-file lambda_file_processing.yml \ - --s3-bucket sam-stuff \ - --output-template-file post-sam.yml - +```bash +sam package \ + --template-file file_processing.yml \ + --output-template-file packaged-template.yml \ + --s3-bucket ``` Deploy the SAM template ``` -aws cloudformation deploy \ - --template-file ./post-sam.yml \ +sam deploy \ + --template-file packaged-template.yml \ --stack-name lambda-file-refarch \ --capabilities CAPABILITY_IAM ``` @@ -83,33 +86,35 @@ To remove all resources created by this example, do the following: ## CloudFormation Template Resources ### Parameters -- **CodeBucket** - Name of the S3 bucket in the stack's region that contains the code for the two Lambda functions, ProcessorFunctionOne and ProcessorFunctionTwo. Defaults to the managed bucket `awslambda-reference-architectures`. - -- **CodeKeyPrefix** - The key prefix for the Lambda function code relative to `CodeBucket`. Defaults to `file-processing`. +TBD ### Resources [The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) creates the following resources: -- **InputBucket** - An S3 bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger both processing functions. +- **InputBucket** - An S3 bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger processing functions. + +- **CloudTrailBucket** - An S3 bucket that is used to store CloudTrail data. + +- **InputBucketTrail** - An CloudTrail definition that captures events put into the **CloudTrailBucket**. -- **OutputBucket** - An S3 bucket that is populated by the processor functions with the transformed files. +- **CloudTrailBucketPolicy** - A S3 policy which permits the AWS CloudTrail service to write data to the **CloudTrailBucket**. -- **InputNotificationTopic** - An Amazon Simple Notification Service (Amazon SNS) topic used to invoke multiple Lambda functions in response to each object creation notification. +- **FileProcessingQueuePolicy** - A SQS policy that allows the **FileProcessingRule** to publish events to the **ConversionQueue** and **SentimentQueue**. -- **NotificationPolicy** - An Amazon SNS topic policy which permits `InputBucket` to call the `Publish` action on the topic. +- **FileProcessingRule** - A CloudWatch Events Rule that monitors CloudTrail `PubObject` events from the **InputBucket**. -- **ProcessorFunctionOne** - An AWS Lambda function that converts Markdown files to HTML. The deployment package for this function must be located at `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`. +- **ConversionQueue** - TBD. -- **ProcessorFunctionTwo** - An AWS Lambda function that converts Markdown files to plain text. The deployment package for this function must be located at `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`. +- **ConversionDlq** - TBD. -- **LambdaExecutionRole** - An AWS Identity and Access Management (IAM) role used by the two Lambda functions. +- **ConversionFunction** - TBD. -- **RolePolicy** - An IAM policy associated with **LambdaExecutionRole** that allows the functions to get objects from `InputBucket`, put object to `OutputBucket` and log to Amazon CloudWatch. +- **SentimentQueue** - TBD. -- **LambdaInvokePermissionOne** - A policy that enables Amazon SNS to invoke ProcessorFunctionOne based on notifications from InputNotificationTopic. +- **SentimentDlq** - TBD. -- **LambdaInvokePermissionTwo** - A policy that enables Amazon SNS to invoke ProcessorFunctionTwo based on notifications from InputNotificationTopic. +- **SentimentFunction** - TBD. ## License diff --git a/file_processing.yml b/file_processing.yml index f550577..8eac7b1 100644 --- a/file_processing.yml +++ b/file_processing.yml @@ -127,6 +127,7 @@ Resources: ConversionFunction: Type: 'AWS::Serverless::Function' + DependsOn: ConversionTargetBucket Properties: Handler: conversion.handler Runtime: python3.6 @@ -135,6 +136,15 @@ Resources: - SQSPollerPolicy: QueueName: !GetAtt ConversionQueue.Arn + - S3FullAccessPolicy: + BucketName: + !GetAtt InputBucket.Arn + - S3FullAccessPolicy: + BucketName: + !GetAtt ConversionTargetBucket.Arn + Environment: + Variables: + TARGET_BUCKET: !Ref ConversionTargetBucket Events: ConversionQueueReaderEvent: Type: SQS @@ -142,6 +152,9 @@ Resources: Queue: !GetAtt ConversionQueue.Arn BatchSize: 10 + ConversionTargetBucket: + Type: AWS::S3::Bucket + SentimentQueue: Type: AWS::SQS::Queue DependsOn: SentimentDlq diff --git a/img/lambda-refarch-fileprocessing-simple.png b/img/lambda-refarch-fileprocessing-simple.png new file mode 100644 index 0000000000000000000000000000000000000000..8dd2b8f0fd593848d53d74cf99643c596738a777 GIT binary patch literal 79859 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literal 0 HcmV?d00001 diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 292bbc3..d2f1e69 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -1,7 +1,102 @@ -def handler(event, context): - # records = event['Records'] - # print(records) - print(event) - return('ok') +import json +import os + +import boto3 +import botocore +import markdown + +max_object_size = 104857600 # 100MB = 104857600 bytes + +target_bucket = os.getenv('TARGET_BUCKET') + +s3_resource = boto3.resource('s3') + + +def check_s3_object_size(bucket, key_name): + try: + size = s3_resource.Object(bucket, key_name).content_length + except Exception as e: + print('Error: {}'.format(str(e))) + size = 'NaN' + return size + +def get_s3_object(bucket, key_name): + try: + s3_resource.Bucket(bucket).download_file(key_name, '/tmp/{}'.format(key_name)) + return 'ok' + except botocore.exceptions.ClientError as e: + if e.response['Error']['Code'] == '404': + return 'Error: s3://{}/{} does not exist'.format(bucket, key_name) + else: + return 'Error: {}'.format(str(e)) + +def convert_to_html(file): + try: + file_string = open(file).read() + except Exception as e: + print('Error: {}'.format(str(e))) + raise + + return markdown.markdown(file_string) + +def upload_html(target_bucket, target_key, source_file): + try: + s3_resource.Object(target_bucket, target_key).upload_file(source_file) + html_upload = 'ok' + except Exception as e: + print('Error: {}'.format(str(e))) + html_upload = 'fail' + + return html_upload + + +def handler(event, context): + log_event = {} + + try: + json_body = json.loads(event['Records'][0]['body']) + request_params = json_body['detail']['requestParameters'] + bucket_name = request_params['bucketName'] + key_name = request_params['key'] + log_event['source_s3_bucket_name'] = bucket_name + log_event['source_s3_key_name'] = key_name + + size = check_s3_object_size(bucket_name, key_name) + + download_status = get_s3_object(bucket_name, key_name) + + local_file = '/tmp/{}'.format(key_name) + + if download_status == 'ok': + log_event['source_s3_download'] = 'ok' + key_bytes = os.stat(local_file).st_size + log_event['source_s3_download_bytes'] = key_bytes + else: + log_event['source_s3_download'] = download_status + log_event['source_s3_download_bytes'] = -1 + + html = convert_to_html(local_file) + + html_filename = os.path.splitext(key_name)[0] + '.html' + + html_file = '/tmp/{}'.format(html_filename) + + with open(html_file, 'w') as outfile: + outfile.write(html) + + html_upload = upload_html(target_bucket, html_filename, html_file) + + if html_upload == 'ok': + log_event['dest_s3_object'] = 's3://{}/{}'.format(target_bucket, html_filename) + else: + log_event['dest_s3_object'] = '' + + log_event['dest_s3_upload'] = html_upload + except Exception as e: + log_event['error_msg'] = str(e) + print(log_event) + return 'fail' + print(log_event) + return 'ok' diff --git a/src/conversion/requirements.txt b/src/conversion/requirements.txt index 3cda9eb..158fba1 100644 --- a/src/conversion/requirements.txt +++ b/src/conversion/requirements.txt @@ -1 +1,2 @@ +boto3 markdown \ No newline at end of file From 8e4bb5168ef3dcaa98f3738c86893d136dbf081a Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Sun, 29 Sep 2019 15:05:06 -0400 Subject: [PATCH 022/115] Updated to include new sample file --- README.md | 6 +++--- sample.md | 15 +++++++++++++++ 2 files changed, 18 insertions(+), 3 deletions(-) create mode 100644 sample.md diff --git a/README.md b/README.md index 7bf7496..c4f9aa7 100644 --- a/README.md +++ b/README.md @@ -50,7 +50,7 @@ sam package \ Deploy the SAM template -``` +```bash sam deploy \ --template-file packaged-template.yml \ --stack-name lambda-file-refarch \ @@ -65,8 +65,8 @@ After you have created the stack using the CloudFormation template, you can test You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. ``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp ./sample.md s3://$BUCKET/sample.md ``` After the file has been uploaded to the input bucket, you can inspect the output bucket to see the rendered HTML and plain text output files created by the Lambda functions. diff --git a/sample.md b/sample.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/sample.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file From 7f870ceb7f1d054ede2432b640308d917a2f64d0 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Mon, 30 Sep 2019 11:03:21 -0400 Subject: [PATCH 023/115] Tie up conversion functionality incl docs --- README.md | 41 ++++++++---- file_processing.yml | 36 +++++++++-- sample.md => sample-1.md | 0 sample-2.md | 15 +++++ src/conversion/conversion.py | 82 +++++++++++++----------- src/data-processor-1/data-processor-1.js | 75 ---------------------- src/data-processor-2/data-processor-2.js | 75 ---------------------- 7 files changed, 117 insertions(+), 207 deletions(-) rename sample.md => sample-1.md (100%) create mode 100644 sample-2.md delete mode 100644 src/data-processor-1/data-processor-1.js delete mode 100644 src/data-processor-2/data-processor-2.js diff --git a/README.md b/README.md index c4f9aa7..47b3d76 100644 --- a/README.md +++ b/README.md @@ -20,15 +20,6 @@ Choose **Launch Stack** to launch the template in the us-east-1 region in your a [![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -Alternatively, you can use the following command to launch the stack using the AWS CLI. This assumes you have already [installed the AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - ## Using SAM Install the dependencies for lambda @@ -60,13 +51,17 @@ sam deploy \ ## Testing the Example -After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use this README.md file in the repository as an example file. After the file has been uploaded, you can see the resulting HTML and plain text files in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. +After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use the sample-1.md and sample-2.md files in the repository as example files. After the files have been uploaded, you can see the resulting HTML and plain text files in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. ``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp ./sample.md s3://$BUCKET/sample.md +INPUT_BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 cp ./sample-1.md s3://${INPUT_BUCKET}/sample-1.md +aws s3 cp ./sample-2.md s3://${INPUT_BUCKET}/sample-2.md + +OUTPUT_BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ConversionTargetBucket --query "StackResourceDetail.PhysicalResourceId" --output text) +aws s3 ls s3://${OUTPUT_BUCKET} ``` After the file has been uploaded to the input bucket, you can inspect the output bucket to see the rendered HTML and plain text output files created by the Lambda functions. @@ -78,10 +73,30 @@ You can also view the CloudWatch logs generated by the Lambda functions. To remove all resources created by this example, do the following: 1. Delete all objects in the input and output buckets. +```bash +for bucket in InputBucket CloudTrailBucket ConversionTargetBucket; do + echo "Clearing out ${bucket}..." + BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) + aws s3 rm s3://${BUCKET} --recursive + echo +done +``` + 1. Delete the CloudFormation stack. -1. Delete the CloudWatch log groups that contain the execution logs for the two processor functions. +```bash +aws cloudformation delete-stack \ +--stack-name lambda-file-refarch +``` +1. Delete the CloudWatch log groups that contain the execution logs for the two processor functions. The Log Group names can be identified by running the following command: +```bash +for log_group in $(aws logs describe-log-groups --log-group-name-prefix '/aws/lambda/lambda-file-refarch-' --query "logGroups[*].logGroupName" --output text); do + echo "Removing log group ${log_group}..." + aws logs delete-log-group --log-group-name ${log_group} + echo +done +``` ## CloudFormation Template Resources diff --git a/file_processing.yml b/file_processing.yml index 8eac7b1..bc3c051 100644 --- a/file_processing.yml +++ b/file_processing.yml @@ -136,12 +136,36 @@ Resources: - SQSPollerPolicy: QueueName: !GetAtt ConversionQueue.Arn - - S3FullAccessPolicy: - BucketName: - !GetAtt InputBucket.Arn - - S3FullAccessPolicy: - BucketName: - !GetAtt ConversionTargetBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - s3:GetObject + - s3:GetObjectAcl + - s3:GetObjectVersion + Resource: + Fn::Join: + - '' + - - 'arn:aws:s3:::' + - Ref: InputBucket + - '/*' + - Effect: Allow + Action: + - s3:ListBucket + Resource: !GetAtt InputBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: s3:PutObject + Resource: + Fn::Join: + - '' + - - 'arn:aws:s3:::' + - Ref: ConversionTargetBucket + - '/*' + # - S3FullAccessPolicy: + # BucketName: + # !GetAtt ConversionTargetBucket.Arn Environment: Variables: TARGET_BUCKET: !Ref ConversionTargetBucket diff --git a/sample.md b/sample-1.md similarity index 100% rename from sample.md rename to sample-1.md diff --git a/sample-2.md b/sample-2.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/sample-2.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index d2f1e69..9a3f114 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -52,51 +52,57 @@ def upload_html(target_bucket, target_key, source_file): def handler(event, context): - log_event = {} + for record in event['Records']: + log_event = {} - try: - json_body = json.loads(event['Records'][0]['body']) - request_params = json_body['detail']['requestParameters'] - bucket_name = request_params['bucketName'] - key_name = request_params['key'] - log_event['source_s3_bucket_name'] = bucket_name - log_event['source_s3_key_name'] = key_name - - size = check_s3_object_size(bucket_name, key_name) - - download_status = get_s3_object(bucket_name, key_name) - - local_file = '/tmp/{}'.format(key_name) - - if download_status == 'ok': - log_event['source_s3_download'] = 'ok' - key_bytes = os.stat(local_file).st_size - log_event['source_s3_download_bytes'] = key_bytes - else: - log_event['source_s3_download'] = download_status - log_event['source_s3_download_bytes'] = -1 + log_event['request_id'] = context.aws_request_id + log_event['invoked_function_arn'] = context.invoked_function_arn + log_event['sqs_message_id'] = record['messageId'] + log_event['sqs_event_source_arn'] = record['eventSourceARN'] - html = convert_to_html(local_file) + try: + json_body = json.loads(record['body']) + request_params = json_body['detail']['requestParameters'] + bucket_name = request_params['bucketName'] + key_name = request_params['key'] + log_event['source_s3_bucket_name'] = bucket_name + log_event['source_s3_key_name'] = key_name - html_filename = os.path.splitext(key_name)[0] + '.html' + size = check_s3_object_size(bucket_name, key_name) - html_file = '/tmp/{}'.format(html_filename) + download_status = get_s3_object(bucket_name, key_name) - with open(html_file, 'w') as outfile: - outfile.write(html) + local_file = '/tmp/{}'.format(key_name) + + if download_status == 'ok': + log_event['src_s3_download'] = 'ok' + key_bytes = os.stat(local_file).st_size + log_event['src_s3_download_bytes'] = key_bytes + else: + log_event['src_s3_download'] = download_status + log_event['src_s3_download_bytes'] = -1 - html_upload = upload_html(target_bucket, html_filename, html_file) + html = convert_to_html(local_file) - if html_upload == 'ok': - log_event['dest_s3_object'] = 's3://{}/{}'.format(target_bucket, html_filename) - else: - log_event['dest_s3_object'] = '' + html_filename = os.path.splitext(key_name)[0] + '.html' - log_event['dest_s3_upload'] = html_upload + html_file = '/tmp/{}'.format(html_filename) - except Exception as e: - log_event['error_msg'] = str(e) + with open(html_file, 'w') as outfile: + outfile.write(html) + + html_upload = upload_html(target_bucket, html_filename, html_file) + + if html_upload == 'ok': + log_event['dst_s3_object'] = 's3://{}/{}'.format(target_bucket, html_filename) + else: + log_event['dst_s3_object'] = '' + + log_event['dst_s3_upload'] = html_upload + + except Exception as e: + log_event['error_msg'] = str(e) + print(log_event) + return 'fail' print(log_event) - return 'fail' - print(log_event) - return 'ok' + return 'ok' diff --git a/src/data-processor-1/data-processor-1.js b/src/data-processor-1/data-processor-1.js deleted file mode 100644 index 151c70c..0000000 --- a/src/data-processor-1/data-processor-1.js +++ /dev/null @@ -1,75 +0,0 @@ -/* Copyright 2015 Amazon.com, Inc. or its affiliates. All Rights Reserved. - -Licensed under the Apache License, Version 2.0 (the "License"). You may not use -this file except in compliance with the License. A copy of the License is -located at - -http://aws.amazon.com/apache2.0/ - -or in the "license" file accompanying this file. This file is distributed on an -"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or -implied. See the License for the specific language governing permissions and -limitations under the License. */ - -var AWS = require('aws-sdk'); -var marked = require('marked'); -var async = require('async'); - -var s3 = new AWS.S3(); - -function getSNSMessageObject(msgString) { - var x = msgString.replace(/\\/g, ''); - var y = x.substring(1, x.length - 1); - var z = JSON.parse(y); - return z; -} - -exports.handler = function (event, context) { - console.log('event: ' + JSON.stringify(event)); - var snsMsgString = JSON.stringify(event.Records[0].Sns.Message); - var snsMsgObject = getSNSMessageObject(snsMsgString); - - var obj = { - 'bucket': snsMsgObject.Records[0].s3.bucket.name, - 'bucketOut': String(snsMsgObject.Records[0].s3.bucket.name + "-out"), - 'key': snsMsgObject.Records[0].s3.object.key, - }; - - async.waterfall([ - function download(next) { - // get Markdown object - s3.getObject( - { - Bucket: obj.bucket, - Key: obj.key - }, - next); - }, - function transform(response, next) { - // convert md -> html - var data = marked(String(response.Body)); - next(null, data); - }, - function upload(data, next) { - // change file extension - var newFileName = obj.key.split(".")[0] + ".html"; - console.log("Uploading data to: " + obj.bucketOut); - s3.putObject( - { - Bucket: obj.bucketOut, - Key: newFileName, - Body: data, - ContentType: "text/html" // set contentType as HTML - }, - next); - } - ], function (err) { - if (err) { - console.error(err); - } else { - console.log('Success'); - } - context.done(); - }); - -}; diff --git a/src/data-processor-2/data-processor-2.js b/src/data-processor-2/data-processor-2.js deleted file mode 100644 index 7de6bde..0000000 --- a/src/data-processor-2/data-processor-2.js +++ /dev/null @@ -1,75 +0,0 @@ -/* Copyright 2015 Amazon.com, Inc. or its affiliates. All Rights Reserved. - -Licensed under the Apache License, Version 2.0 (the "License"). You may not use -this file except in compliance with the License. A copy of the License is -located at - -http://aws.amazon.com/apache2.0/ - -or in the "license" file accompanying this file. This file is distributed on an -"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or -implied. See the License for the specific language governing permissions and -limitations under the License. */ - -var AWS = require('aws-sdk'); -var removeMD = require('remove-markdown'); -var async = require('async'); - -var s3 = new AWS.S3(); - -function getSNSMessageObject(msgString) { - var x = msgString.replace(/\\/g, ''); - var y = x.substring(1, x.length - 1); - var z = JSON.parse(y); - return z; -} - -exports.handler = function (event, context) { - console.log('event: ' + JSON.stringify(event)); - var snsMsgString = JSON.stringify(event.Records[0].Sns.Message); - var snsMsgObject = getSNSMessageObject(snsMsgString); - - var obj = { - 'bucket': snsMsgObject.Records[0].s3.bucket.name, - 'bucketOut': String(snsMsgObject.Records[0].s3.bucket.name + "-out"), - 'key': snsMsgObject.Records[0].s3.object.key - }; - - async.waterfall([ - function download(next) { - // get Markdown object - s3.getObject( - { - Bucket: obj.bucket, - Key: obj.key - }, - next); - }, - function transform(response, next) { - // strip out md and convert to plaintext - var data = removeMD(String(response.Body)); - next(null, data); - }, - function upload(data, next) { - // change file extension - var newFileName = obj.key.split(".")[0] + ".txt"; - console.log("Uploading data to: " + obj.bucketOut); - s3.putObject( - { - Bucket: obj.bucketOut, - Key: newFileName, - Body: data, - ContentType: "text/plain" // set contentType as plaintext - }, - next); - } - ], function (err) { - if (err) { - console.error(err); - } else { - console.log('Success'); - } - context.done(); - }); - -}; From 05ac4ebef80fc4cd4da4c14241e5b3b45f579a9b Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Mon, 30 Sep 2019 11:58:56 -0400 Subject: [PATCH 024/115] Remove unnecessary space in README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 47b3d76..bb6c726 100644 --- a/README.md +++ b/README.md @@ -26,7 +26,7 @@ Install the dependencies for lambda ```bash cd src/conversion && pip install -r requirements.txt -t . -cd src/sentiment && pip install -r requirements.txt -t . +cd src/sentiment && pip install -r requirements.txt -t . ``` Run SAM package (equivalent to aws cloudformation package) From 21b4716e7c285705a97e9e290c46b488dfba866f Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 2 Oct 2019 14:54:47 -0400 Subject: [PATCH 025/115] Early working version of sentiment analysis --- README.md | 25 +++++---- file_processing.yml | 44 +++++++++++++-- src/conversion/conversion.py | 8 +-- src/sentiment/requirements.txt | 1 + src/sentiment/sentiment.py | 98 ++++++++++++++++++++++++++++++++-- 5 files changed, 154 insertions(+), 22 deletions(-) create mode 100644 src/sentiment/requirements.txt diff --git a/README.md b/README.md index bb6c726..e7b5ab3 100644 --- a/README.md +++ b/README.md @@ -55,7 +55,7 @@ After you have created the stack using the CloudFormation template, you can test You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. -``` +```bash INPUT_BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) aws s3 cp ./sample-1.md s3://${INPUT_BUCKET}/sample-1.md aws s3 cp ./sample-2.md s3://${INPUT_BUCKET}/sample-2.md @@ -72,7 +72,8 @@ You can also view the CloudWatch logs generated by the Lambda functions. To remove all resources created by this example, do the following: -1. Delete all objects in the input and output buckets. +### Delete Objects in the Input and Output Buckets. + ```bash for bucket in InputBucket CloudTrailBucket ConversionTargetBucket; do echo "Clearing out ${bucket}..." @@ -82,13 +83,14 @@ for bucket in InputBucket CloudTrailBucket ConversionTargetBucket; do done ``` -1. Delete the CloudFormation stack. +### Delete the CloudFormation Stack + ```bash aws cloudformation delete-stack \ --stack-name lambda-file-refarch ``` -1. Delete the CloudWatch log groups that contain the execution logs for the two processor functions. The Log Group names can be identified by running the following command: +### Delete the CloudWatch Log Groups ```bash for log_group in $(aws logs describe-log-groups --log-group-name-prefix '/aws/lambda/lambda-file-refarch-' --query "logGroups[*].logGroupName" --output text); do @@ -100,9 +102,6 @@ done ## CloudFormation Template Resources -### Parameters -TBD - ### Resources [The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) creates the following resources: @@ -119,17 +118,21 @@ creates the following resources: - **FileProcessingRule** - A CloudWatch Events Rule that monitors CloudTrail `PubObject` events from the **InputBucket**. -- **ConversionQueue** - TBD. +- **ConversionQueue** - A SQS queue that is used to store events for conversion from markdown to HTML. - **ConversionDlq** - TBD. -- **ConversionFunction** - TBD. +- **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. + +- **ConversionTargetBucket** - A S3 bucket that stores the converted HTML. -- **SentimentQueue** - TBD. +- **SentimentQueue** - A SQS queue that is used to store events for sentiment analysis processing. - **SentimentDlq** - TBD. -- **SentimentFunction** - TBD. +- **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. + +- **SentimentTable** - A DynamoDB table that stores the input file along with the sentiment. ## License diff --git a/file_processing.yml b/file_processing.yml index bc3c051..1c666c7 100644 --- a/file_processing.yml +++ b/file_processing.yml @@ -163,9 +163,6 @@ Resources: - - 'arn:aws:s3:::' - Ref: ConversionTargetBucket - '/*' - # - S3FullAccessPolicy: - # BucketName: - # !GetAtt ConversionTargetBucket.Arn Environment: Variables: TARGET_BUCKET: !Ref ConversionTargetBucket @@ -203,10 +200,49 @@ Resources: - SQSPollerPolicy: QueueName: !GetAtt SentimentQueue.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - s3:GetObject + - s3:GetObjectAcl + - s3:GetObjectVersion + Resource: + Fn::Join: + - '' + - - 'arn:aws:s3:::' + - Ref: InputBucket + - '/*' + - Effect: Allow + Action: + - s3:ListBucket + Resource: !GetAtt InputBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - comprehend:DetectSentiment + Resource: '*' + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - dynamodb:PutItem + Resource: !GetAtt SentimentTable.Arn + Environment: + Variables: + SENTIMENT_TABLE: !Ref SentimentTable Events: SentimentQueueReaderEvent: Type: SQS Properties: Queue: !GetAtt SentimentQueue.Arn - BatchSize: 10 + BatchSize: 10 + + SentimentTable: + Type: AWS::Serverless::SimpleTable + TableName: ref-arch-filearch-document-sentiment + PrimaryKey: + Name: 's3_object' + Type: String \ No newline at end of file diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 9a3f114..8ec6be0 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -1,5 +1,6 @@ import json import os +import sys import boto3 import botocore @@ -81,17 +82,18 @@ def handler(event, context): else: log_event['src_s3_download'] = download_status log_event['src_s3_download_bytes'] = -1 + sys.exit(1) html = convert_to_html(local_file) html_filename = os.path.splitext(key_name)[0] + '.html' - html_file = '/tmp/{}'.format(html_filename) + local_html_file = '/tmp/{}'.format(html_filename) - with open(html_file, 'w') as outfile: + with open(local_html_file, 'w') as outfile: outfile.write(html) - html_upload = upload_html(target_bucket, html_filename, html_file) + html_upload = upload_html(target_bucket, html_filename, local_html_file) if html_upload == 'ok': log_event['dst_s3_object'] = 's3://{}/{}'.format(target_bucket, html_filename) diff --git a/src/sentiment/requirements.txt b/src/sentiment/requirements.txt new file mode 100644 index 0000000..1db657b --- /dev/null +++ b/src/sentiment/requirements.txt @@ -0,0 +1 @@ +boto3 \ No newline at end of file diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 07e04ab..a73ff99 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -1,5 +1,95 @@ +import json +import os +import sys + +import boto3 +import botocore + + +comprehend_client = boto3.client('comprehend') + +s3_resource = boto3.resource('s3') + +ddb_client = boto3.client('dynamodb') + +sentiment_table = os.getenv('SENTIMENT_TABLE') + +def get_s3_object(bucket, key_name): + try: + s3_resource.Bucket(bucket).download_file(key_name, '/tmp/{}'.format(key_name)) + return 'ok' + except botocore.exceptions.ClientError as e: + if e.response['Error']['Code'] == '404': + return 'Error: s3://{}/{} does not exist'.format(bucket, key_name) + else: + return 'Error: {}'.format(str(e)) + +def put_sentiment(table_name, s3_object, sentiment): + try: + result = ddb_client.put_item( + TableName=table_name, + Item={ + 'id': { + 'S': s3_object + }, + 'sentiment': { + 'S': sentiment['Sentiment'] + } + } + ) + except Exception as e: + print('Error: {}'.format(str(e))) + + def handler(event, context): - # records = event['Records'] - # print(records) - print(event) - return('ok') \ No newline at end of file + for record in event['Records']: + log_event = {} + + log_event['request_id'] = context.aws_request_id + log_event['invoked_function_arn'] = context.invoked_function_arn + log_event['sqs_message_id'] = record['messageId'] + log_event['sqs_event_source_arn'] = record['eventSourceARN'] + + try: + json_body = json.loads(record['body']) + request_params = json_body['detail']['requestParameters'] + bucket_name = request_params['bucketName'] + key_name = request_params['key'] + log_event['source_s3_bucket_name'] = bucket_name + log_event['source_s3_key_name'] = key_name + + download_status = get_s3_object(bucket_name, key_name) + + local_file = '/tmp/{}'.format(key_name) + + if download_status == 'ok': + log_event['src_s3_download'] = 'ok' + key_bytes = os.stat(local_file).st_size + log_event['src_s3_download_bytes'] = key_bytes + else: + log_event['src_s3_download'] = download_status + log_event['src_s3_download_bytes'] = -1 + sys.exit(1) + + md_contents = open(local_file, 'r').read() + + sentiment = comprehend_client.detect_sentiment(Text=md_contents, LanguageCode='en') + + log_event['sentiment'] = sentiment['Sentiment'] + log_event['sentiment_score'] = sentiment['SentimentScore'] + + source_s3_object = 's3://{}/{}'.format(bucket_name, key_name) + + put_sentiment_result = put_sentiment(sentiment_table, source_s3_object, sentiment) + + print(put_sentiment_result) + + except Exception as e: + log_event['error_msg'] = str(e) + print(log_event) + return 'fail' + + + print(log_event) + return('ok') + From acf763bf08fec1b0f84ff70bbfe2f1b864ee2ed2 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 2 Oct 2019 15:07:39 -0400 Subject: [PATCH 026/115] Added directions for verifying DynamoDB data --- README.md | 11 ++++++++++- 1 file changed, 10 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index e7b5ab3..ee77e22 100644 --- a/README.md +++ b/README.md @@ -59,12 +59,21 @@ You can use the following commands to copy a sample file from the provided S3 bu INPUT_BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) aws s3 cp ./sample-1.md s3://${INPUT_BUCKET}/sample-1.md aws s3 cp ./sample-2.md s3://${INPUT_BUCKET}/sample-2.md +``` + +Once the input files has been uploaded to the input bucket, a series of events are put into motion. +1. The input Markdown files are converted and stored in a separate S3 bucket. +``` OUTPUT_BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ConversionTargetBucket --query "StackResourceDetail.PhysicalResourceId" --output text) aws s3 ls s3://${OUTPUT_BUCKET} ``` -After the file has been uploaded to the input bucket, you can inspect the output bucket to see the rendered HTML and plain text output files created by the Lambda functions. +2. The input Markdown files are analyzed and their sentiment published to a DynamoDB table. +``` +DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id SentimentTable --query "StackResourceDetail.PhysicalResourceId" --output text) +aws dynamodb scan --table-name ${DYNAMO_TABLE} --query "Items[*]" +``` You can also view the CloudWatch logs generated by the Lambda functions. From d0cc624dc5c7fce6f3a24ed0877abb0adcadecc4 Mon Sep 17 00:00:00 2001 From: Rudge Date: Fri, 11 Oct 2019 15:58:34 +0100 Subject: [PATCH 027/115] updated to comply with pep8 and bandit, also added temporary file cleanup --- src/conversion/conversion.py | 50 ++++++++++++++++++++++++++---------- 1 file changed, 37 insertions(+), 13 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 8ec6be0..9471d67 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -5,8 +5,9 @@ import boto3 import botocore import markdown +import tempfile -max_object_size = 104857600 # 100MB = 104857600 bytes +max_object_size = 104857600 # 100MB = 104857600 bytes target_bucket = os.getenv('TARGET_BUCKET') @@ -19,12 +20,13 @@ def check_s3_object_size(bucket, key_name): except Exception as e: print('Error: {}'.format(str(e))) size = 'NaN' - + return size -def get_s3_object(bucket, key_name): + +def get_s3_object(bucket, key_name, local_file): try: - s3_resource.Bucket(bucket).download_file(key_name, '/tmp/{}'.format(key_name)) + s3_resource.Bucket(bucket).download_file(key_name, local_file) return 'ok' except botocore.exceptions.ClientError as e: if e.response['Error']['Code'] == '404': @@ -32,15 +34,20 @@ def get_s3_object(bucket, key_name): else: return 'Error: {}'.format(str(e)) + def convert_to_html(file): try: - file_string = open(file).read() + file_open = open(file, 'r') + file_string = file_open.read() + file_open.close() + except Exception as e: print('Error: {}'.format(str(e))) raise - + return markdown.markdown(file_string) + def upload_html(target_bucket, target_key, source_file): try: s3_resource.Object(target_bucket, target_key).upload_file(source_file) @@ -48,12 +55,14 @@ def upload_html(target_bucket, target_key, source_file): except Exception as e: print('Error: {}'.format(str(e))) html_upload = 'fail' - + return html_upload def handler(event, context): for record in event['Records']: + tmpdir = tempfile.mkdtemp() + log_event = {} log_event['request_id'] = context.aws_request_id @@ -71,10 +80,10 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) - download_status = get_s3_object(bucket_name, key_name) + local_file = os.path.join(tmpdir, key_name) + + download_status = get_s3_object(bucket_name, key_name, local_file) - local_file = '/tmp/{}'.format(key_name) - if download_status == 'ok': log_event['src_s3_download'] = 'ok' key_bytes = os.stat(local_file).st_size @@ -88,15 +97,20 @@ def handler(event, context): html_filename = os.path.splitext(key_name)[0] + '.html' - local_html_file = '/tmp/{}'.format(html_filename) + local_html_file = os.path.join(tmpdir, html_filename) with open(local_html_file, 'w') as outfile: outfile.write(html) - html_upload = upload_html(target_bucket, html_filename, local_html_file) + outfile.close() + + html_upload = upload_html(target_bucket, + html_filename, + local_html_file) if html_upload == 'ok': - log_event['dst_s3_object'] = 's3://{}/{}'.format(target_bucket, html_filename) + log_event['dst_s3_object'] = 's3://{}/{}'.format(target_bucket, + html_filename) else: log_event['dst_s3_object'] = '' @@ -106,5 +120,15 @@ def handler(event, context): log_event['error_msg'] = str(e) print(log_event) return 'fail' + + finally: + filesToRemove = os.listdir(tmpdir) + for f in filesToRemove: + file_path = os.path.join(tmpdir, f) + print(f'Removing File: {file_path}') + os.remove(file_path) + print(f'Removing Folder: {tmpdir}') + os.rmdir(tmpdir) + print(log_event) return 'ok' From 976cede8a5ef2652583ad73b3d6495689df4f38a Mon Sep 17 00:00:00 2001 From: Rudge Date: Fri, 11 Oct 2019 16:49:19 +0100 Subject: [PATCH 028/115] added try / catch --- src/conversion/conversion.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 9471d67..5a53997 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -123,10 +123,17 @@ def handler(event, context): finally: filesToRemove = os.listdir(tmpdir) + for f in filesToRemove: file_path = os.path.join(tmpdir, f) print(f'Removing File: {file_path}') - os.remove(file_path) + + try: + os.remove(file_path) + except OSError as e: + print(e) + print(f'Error while deleting file {file_path}') + print(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) From 58070d1217538a559211511d7056cd02c1930bbe Mon Sep 17 00:00:00 2001 From: Rudge Date: Fri, 1 Nov 2019 15:38:47 +0000 Subject: [PATCH 029/115] Updated readme for new workflows --- README.md | 49 ++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 46 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index ee77e22..737e8dd 100644 --- a/README.md +++ b/README.md @@ -3,21 +3,64 @@ README Languages: [DE](README/README-DE.md) | [ES](README/README-ES.md) | [FR]( [PT](README/README-PT.md) | [RU](README/README-RU.md) | [CN](README/README-CN.md) | [TW](README/README-TW.md) -The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. This simple architecture is described in this [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) and ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) on the AWS Compute Blog. This sample application demonstrates a Markdown conversion application where Lambda is used to convert Markdown files to HTML and plain text. +The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. + +In this example application we deliver the notes from an interview in markdown format into S3 and we utilise CloudWatch Events to trigger multiple processing flows. ## Architectural Diagram ![Reference Architecture - Real-time File Processing](img/lambda-refarch-fileprocessing-simple.png) +## Application Components + +### Event Trigger +Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilise [CloudWatch Events](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) and [CloudTrail](https://aws.amazon.com/cloudtrail/). We write a CloudWatch Events rule which checks for S3 PutObject API calls into our Source Bucket from CloudTrail. Everytime the PutObject API is called this creates a CloudTrail log which our rule translates into an event represented as a JSON object. In our rule we also define targets which our JSON event object is delivered to, which in this scenario is 4 seperate [SQS Queues](https://aws.amazon.com/sqs/) for 4 different worflows. Other target types include AWS Lambda Functions, Kinesis Data Streams, Simple Notification Service, Step Functions state machines, ECS tasks and more. + +### Conversion WorkFlow + +For this workflow the target of our JSON object decribing the S3 PutObject event is an SQS queue. Sending to SQS first rather than directly to Lambda allows for more control of Lambda invocations and better error handling. + +Lambda uses long polling to poll our queue and when messages are available it will read upto 5 batches and send them to our function. Lambda will automatically scale this process if more messages still remain on the queue. This allows us to simultaneously process upto 1000 batches. + +If our Lambda fails to process the messages we can configure SQS to send to a dead-letter queue for inspection and reprocessing. + +Once the function has the message this is parsed. The JSON event object contains information such as the S3 bucket and object key and object size. + +Our business logic uses this information to retrieve the file from S3 and convert it to HTML finally writing out the new file to the HTML Bucket. + + +### Sentiment Analysis Workflow + +Here we are using our AI/ML service [Amazon Comprehend](https://aws.amazon.com/comprehend/) which is a machine learning powered service that makes it easy to find insights and relationships in text. We can use the Sentiment Analysis API in order to understand if the questions the interviewer asked had positive or negative responses. + +This workflow uses the same SQS to Lambda Function pattern as the coversion workflow. Here our business logic downloads the file and extracts the content of the file and sends it to the Comprehend Sentiment Analysis API. This returns a Sentiment and a confidence Score which Describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. + +Once we have our sentiment we persist the result to our [DynamoDB](https://aws.amazon.com/dynamodb/) table. + + +### Search Indexing Workflow +TODO + +### Replay Workflow + +TODO + + ## Running the Example -You can use the provided [AWS SAM template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *CloudFormation Template Resources* section of this document. +You can use the provided [AWS SAM template] + +TODO **Insert CFN Template Link** + +to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *CloudFormation Template Resources* section of this document. **Important** Because the AWS CloudFormation stack name is used in the name of the Amazon Simple Storage Service (Amazon S3) buckets, that stack name must only contain lowercase letters. Use lowercase letters when typing the stack name. The provided CloudFormation template retrieves its Lambda code from a bucket in the us-east-1 region. To launch this sample in another region, please modify the template and upload the Lambda code to a bucket in that region. Choose **Launch Stack** to launch the template in the us-east-1 region in your account: +TODO Update Link + [![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) ## Using SAM @@ -51,7 +94,7 @@ sam deploy \ ## Testing the Example -After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use the sample-1.md and sample-2.md files in the repository as example files. After the files have been uploaded, you can see the resulting HTML and plain text files in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. +After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use the sample-1.md and sample-2.md files in the repository as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. From 0b097f7d4ec8da4855b672b5c2e41568640dd7b1 Mon Sep 17 00:00:00 2001 From: Rudge Date: Fri, 1 Nov 2019 17:25:34 +0000 Subject: [PATCH 030/115] Changes as per PR suggestions --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 737e8dd..206535e 100644 --- a/README.md +++ b/README.md @@ -14,19 +14,19 @@ In this example application we deliver the notes from an interview in markdown f ## Application Components ### Event Trigger -Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilise [CloudWatch Events](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) and [CloudTrail](https://aws.amazon.com/cloudtrail/). We write a CloudWatch Events rule which checks for S3 PutObject API calls into our Source Bucket from CloudTrail. Everytime the PutObject API is called this creates a CloudTrail log which our rule translates into an event represented as a JSON object. In our rule we also define targets which our JSON event object is delivered to, which in this scenario is 4 seperate [SQS Queues](https://aws.amazon.com/sqs/) for 4 different worflows. Other target types include AWS Lambda Functions, Kinesis Data Streams, Simple Notification Service, Step Functions state machines, ECS tasks and more. +Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilise [CloudWatch Events](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) and [CloudTrail](https://aws.amazon.com/cloudtrail/). We write a CloudWatch Events rule which checks for S3 PutObject API calls into our Source Bucket from CloudTrail. Everytime the PutObject API is called this creates a CloudTrail log which our rule translates into an event represented as a JSON object. In our rule we also define targets which our JSON event object is delivered to, which in this scenario is 4 seperate [SQS Queues](https://aws.amazon.com/sqs/) for 4 different worflows. Other target types include AWS Lambda Functions, Kinesis Data Streams, Simple Notification Service, Step Functions state machines, ECS tasks refer to [What is Amazon CloudWatch Events?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) for more information about eligible targets. ### Conversion WorkFlow For this workflow the target of our JSON object decribing the S3 PutObject event is an SQS queue. Sending to SQS first rather than directly to Lambda allows for more control of Lambda invocations and better error handling. -Lambda uses long polling to poll our queue and when messages are available it will read upto 5 batches and send them to our function. Lambda will automatically scale this process if more messages still remain on the queue. This allows us to simultaneously process upto 1000 batches. +Lambda polls our queue and when messages are available it will send them to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. If our Lambda fails to process the messages we can configure SQS to send to a dead-letter queue for inspection and reprocessing. Once the function has the message this is parsed. The JSON event object contains information such as the S3 bucket and object key and object size. -Our business logic uses this information to retrieve the file from S3 and convert it to HTML finally writing out the new file to the HTML Bucket. +Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new html file to the HTML Bucket. ### Sentiment Analysis Workflow From cbcb05ebb934f3ff502cec657383b55dc2821731 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Tue, 5 Nov 2019 12:50:31 -0500 Subject: [PATCH 031/115] Updates to sentiment, build process Also, add in consistency to Sentiment code. --- .gitignore | 1 + README.md | 51 +++---- README/README-CN.md | 84 ----------- README/README-DE.md | 84 ----------- README/README-ES.md | 84 ----------- README/README-FR.md | 84 ----------- README/README-IT.md | 84 ----------- README/README-JP.md | 84 ----------- README/README-KR.md | 84 ----------- README/README-PT.md | 84 ----------- README/README-RU.md | 84 ----------- README/README-TW.md | 84 ----------- file_processing.yml | 248 ------------------------------ lambda_file_processing.template | 258 -------------------------------- lambda_file_processing.yml | 131 ---------------- src/conversion/conversion.py | 6 + src/sentiment/sentiment.py | 109 +++++++++++--- 17 files changed, 120 insertions(+), 1524 deletions(-) delete mode 100644 README/README-CN.md delete mode 100644 README/README-DE.md delete mode 100644 README/README-ES.md delete mode 100644 README/README-FR.md delete mode 100644 README/README-IT.md delete mode 100644 README/README-JP.md delete mode 100644 README/README-KR.md delete mode 100644 README/README-PT.md delete mode 100644 README/README-RU.md delete mode 100644 README/README-TW.md delete mode 100644 file_processing.yml delete mode 100644 lambda_file_processing.template delete mode 100644 lambda_file_processing.yml diff --git a/.gitignore b/.gitignore index ee50dd7..ed419d9 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ packaged-template.yml post-sam.yml +.aws-sam **/node_modules diff --git a/README.md b/README.md index 206535e..79a6649 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,4 @@ # Serverless Reference Architecture: Real-time File Processing -README Languages: [DE](README/README-DE.md) | [ES](README/README-ES.md) | [FR](README/README-FR.md) | [IT](README/README-IT.md) | [JP](README/README-JP.md) | [KR](README/README-KR.md) | -[PT](README/README-PT.md) | [RU](README/README-RU.md) | -[CN](README/README-CN.md) | [TW](README/README-TW.md) The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. @@ -48,46 +45,50 @@ TODO ## Running the Example -You can use the provided [AWS SAM template] +You can use the provided [AWS SAM template](./template.yml) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *SAM Template Resources* section of this document. -TODO **Insert CFN Template Link** -to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *CloudFormation Template Resources* section of this document. +### Using SAM to Build and Deploy the Application -**Important** Because the AWS CloudFormation stack name is used in the name of the Amazon Simple Storage Service (Amazon S3) buckets, that stack name must only contain lowercase letters. Use lowercase letters when typing the stack name. The provided CloudFormation template retrieves its Lambda code from a bucket in the us-east-1 region. To launch this sample in another region, please modify the template and upload the Lambda code to a bucket in that region. +#### Build +The AWS SAM CLI comes with abstractions for a number of Lambda runtimes to build your dependencies, and copies the source code into staging folders so that everything is ready to be packaged and deployed. The *sam build* command builds any dependencies that your application has, and copies your application source code to folders under aws-sam/build to be zipped and uploaded to Lambda. -Choose **Launch Stack** to launch the template in the us-east-1 region in your account: - -TODO Update Link - -[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +```bash +sam build --use-container +``` -## Using SAM +#### Package -Install the dependencies for lambda +Next, run *sam package*. This command takes your Lambda handler source code and any third-party dependencies, zips everything, and uploads the zip file to your Amazon S3 bucket. That bucket and file location are then noted in the packaged-template.yaml file. You use the generated packaged-template.yaml file to deploy the application in the next step. ```bash -cd src/conversion && pip install -r requirements.txt -t . -cd src/sentiment && pip install -r requirements.txt -t . +sam package \ + --output-template-file packaged-template.yml \ + --s3-bucket bucketname ``` -Run SAM package (equivalent to aws cloudformation package) +**Note** + +For *bucketname* in this command, you need an Amazon S3 bucket that the sam package command can use to store the deployment package. The deployment package is used when you deploy your application in a later step. If you need to create a bucket for this purpose, run the following command to create an Amazon S3 bucket: ```bash -sam package \ - --template-file file_processing.yml \ - --output-template-file packaged-template.yml \ - --s3-bucket +aws s3 mb s3://bucketname --region region # Example regions: us-east-1, ap-east-1, eu-central-1, sa-east-1 ``` +#### Deploy + +This command deploys your application to the AWS Cloud. It's important that this command explicitly includes both of the following: + + * The AWS Region to deploy to. This Region must match the Region of the Amazon S3 source bucket. -Deploy the SAM template + * The CAPABILITY_IAM parameter, because creating new Lambda functions involves creating new IAM roles. ```bash sam deploy \ --template-file packaged-template.yml \ --stack-name lambda-file-refarch \ + --region region \ --capabilities CAPABILITY_IAM ``` @@ -152,10 +153,10 @@ for log_group in $(aws logs describe-log-groups --log-group-name-prefix '/aws/la done ``` -## CloudFormation Template Resources +## SAM Template Resources ### Resources -[The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) +[The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/packaged-template.yml) creates the following resources: - **InputBucket** - An S3 bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger processing functions. @@ -166,7 +167,7 @@ creates the following resources: - **CloudTrailBucketPolicy** - A S3 policy which permits the AWS CloudTrail service to write data to the **CloudTrailBucket**. -- **FileProcessingQueuePolicy** - A SQS policy that allows the **FileProcessingRule** to publish events to the **ConversionQueue** and **SentimentQueue**. +- **FileProcessingQueuePolicy** - A SQS policy that allows the **FileProcessingRule** to publish events to the **ConversionQueue**, **SentimentQueue**, and the **ReplayQueue**. - **FileProcessingRule** - A CloudWatch Events Rule that monitors CloudTrail `PubObject` events from the **InputBucket**. diff --git a/README/README-CN.md b/README/README-CN.md deleted file mode 100644 index 23ac454..0000000 --- a/README/README-CN.md +++ /dev/null @@ -1,84 +0,0 @@ -# 无服务器参考架构：实时文件处理 - -实时文件处理参考架构是一个受事件驱动的通用并行数据处理架构，使用 [AWS Lambda](https://aws.amazon.com/lambda)。该架构非常适合需要某个对象的多种衍生数据的工作负载。此 [示意图](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) 以及 AWS 计算博客上的 ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) 中介绍了这个简单架构。这个示例应用程序演示了一个 Markdown 转换应用程序，该应用程序使用 Lambda 来将 Markdown 文件转换为 HTML 和纯文本。 - -## 运行示例 - -您可以使用提供的 [AWS CloudFormation 模板](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) 启动一个堆栈，该堆栈演示了 Lambda 文件处理参考架构。在本文档的 *CloudFormation 模板资源* 部分中提供了有关通过该模板创建的资源的详细信息。 - -**重要提示** 由于 AWS CloudFormation 堆栈名称在 Amazon Simple Storage Service (Amazon S3) 存储桶的名称中使用，该堆栈名称只能包含小写字母。在键入堆栈名称时，使用小写字母。提供的 CloudFormation 模板会从 us-east-1 区域的存储桶中检索其 Lambda 代码。要在另一个区域中启动此示例，请修改模板并将 Lambda 代码上传到该区域的存储桶中。 - - -选择 **Launch Stack** 以在您账户的 us-east-1 区域中启动模板： - -[![使用 CloudFormation 在北弗吉尼亚区域中启动 Lambda 文件处理](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -此外，您可以通过 AWS CLI 使用以下命令来启动堆栈。这假设您已 [安装 AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)。 - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## 测试示例 - -在您使用 CloudFormation 模板创建堆栈后，可以通过将 Markdown 文件上传到已在堆栈中创建的 InputBucket 来测试系统。您可以使用存储库中的此 README.md 文件作为示例文件。在上传该文件后，您可以在堆栈的输出存储桶中看到生成的 HTML 和纯文本文件。您还可以在 CloudWatch 日志中查看每个函数，以便了解函数执行的详细信息。 - -您可以使用下面的命令，将示例文件从提供的 S3 存储桶复制到您堆栈的输入存储桶中。 - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -在将该文件上传到输入存储桶后，您可以检查输出存储桶，查看 Lambda 函数创建的 HTML 和纯文本格式的输出文件。 - -您还可以查看 Lambda 函数生成的 CloudWatch 日志。 - -## 清理示例资源 - -要删除此示例创建的所有资源，请执行以下操作： - -1.删除输入和输出存储桶中的所有对象。 -1.删除 CloudFormation 堆栈。 -1.删除包含两个处理程序函数的执行日志的 CloudWatch 日志组。 - - - -## CloudFormation 模板资源 - -### 参数 -- **CodeBucket** - 堆栈区域中的 S3 存储桶的名称，该区域包含两个 Lambda 函数 ProcessorFunctionOne 和 ProcessorFunctionTwo 的代码。默认为托管存储桶 `awslambda-reference-architectures`。 - -- **CodeKeyPrefix** - 与 `CodeBucket` 相关的 Lambda 函数代码的键前缀。默认为 `file-processing`。 - -### 资源 -使用 [提供的模板](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -可创建以下资源： - -- **InputBucket** - 一个保存原始 Markdown 文件的 S3 存储桶。将文件上传到此存储桶时，将同时触发两个处理函数。 - -- **OutputBucket** - 一个 S3 存储桶，该存储桶由处理程序函数使用转换的文件填充。 - -- **InputNotificationTopic** - 一个 Amazon Simple Notification Service (Amazon SNS) 主题，该主题用于调用多个 Lambda 函数来响应各个对象创建通知。 - -- **NotificationPolicy** - 一个 Amazon SNS 主题策略，该策略允许 `InputBucket` 对主题调用 `Publish` 操作。 - -- **ProcessorFunctionOne** - 一个用于将 Markdown 文件转换为 HTML 的 AWS Lambda 函数。此函数的部署程序包必须位于 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip` 中。 - -- **ProcessorFunctionTwo** - 一个用于将 Markdown 文件转换为纯文本的 AWS Lambda 函数。此函数的部署程序包必须位于 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip` 中。 - -- **LambdaExecutionRole** - 一个 AWS Identity and Access Management (IAM) 角色，该角色由这两个 Lambda 函数使用。 - -- **RolePolicy** - 一个与 **LambdaExecutionRole** 关联的 IAM 策略，该策略允许函数从 `InputBucket` 获取对象，将对象置入 `OutputBucket`，并记录到 Amazon CloudWatch。 - -- **LambdaInvokePermissionOne** - 一个策略，该策略允许 Amazon SNS 根据来自 InputNotificationTopic 的通知调用 ProcessorFunctionOne。 - -- **LambdaInvokePermissionTwo** - 一个策略，该策略允许 Amazon SNS 根据来自 InputNotificationTopic 的通知调用 ProcessorFunctionTwo。 - - -## 许可证 - -此示例参考架构已获得 Apache 2.0 许可。 diff --git a/README/README-DE.md b/README/README-DE.md deleted file mode 100644 index cc73f50..0000000 --- a/README/README-DE.md +++ /dev/null @@ -1,84 +0,0 @@ -# Serverlose Referenzarchitektur: Dateiverarbeitung in Echtzeit - -Die Referenzarchitektur zur Dateiverarbeitung in Echtzeit ist eine ereignisgesteuerte Architektur zur parallelen Datenverarbeitung für allgemeine Zwecke, die [AWS Lambda](https://aws.amazon.com/lambda) verwendet. Die Architektur eignet sich optimal für Arbeitslasten, die mehr als eine Datenableitung eines Objekts benötigen. Diese einfache Architektur wird in diesem [Diagramm](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) und [im Blogpost "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) auf dem AWS Compute-Blog beschrieben. Diese Beispielanwendung zeigt eine Markdown-Konvertierungsanwendung in Fällen, in denen Lambda zur Markdown-Dateikonvertierung von HTML in Nur-Text verwendet wird. - -## Ausführen der Beispielanwendung - -Mithilfe der bereitgestellten [AWS CloudFormation-Vorlage](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) können Sie einen Stapel starten, der die Referenzarchitektur für die Lambda-Dateiverarbeitung zeigt. Details über die mithilfe dieser Vorlage erstellen Ressourcen finden Sie im Abschnitt *Ressourcen der CloudFormation-Vorlage* in diesem Dokument. - -**Wichtig** Da der AWS CloudFormation-Stapelname im Namen des Amazon Simple Storage Service (Amazon S3)-Buckets verwendet wird, darf dieser Stapelname nur aus Kleinbuchstaben bestehen. Verwenden Sie daher Kleinbuchstaben für den Stapelnamen. Die bereitgestellte CloudFormation-Vorlage ruft den Lambda-Code aus einem Bucket für die Region "us-east-1" ab. Um dieses Beispiel in einer anderen Region zu starten, ändern Sie die Vorlage und laden Sie den Lambda-Code in einen Bucket für diese Region hoch. - - -Wählen Sie **Launch Stack**, um die Vorlage für die Region "us-east-1" in Ihrem Konto zu starten: - -[![Starten der Lambda-Dateiverarbeitung mit CloudFormation in Nord-Virginia](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -Alternativ können Sie den Stapel mit dem folgenden Befehl und mithilfe von AWS CLI starten. Dies setzt jedoch voraus, dass Sie [die AWS CLI bereits installiert haben](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## Testen der Beispielanwendung - -Nachdem Sie den Stapel mithilfe der CloudFormation-Vorlage erstellt haben, können Sie das System testen, indem Sie eine Markdown-Datei in den im Stapel erstellten "InputBucket" hochladen. Sie können die README.md-Datei im Repository als Beispieldatei verwenden. Nachdem die Datei hochgeladen wurde, können Sie die resultierenden HTML- und Nur-Text-Dateien im Ausgabe-Bucket des Stapels sehen. Sie können ebenfalls CloudWatch-Protokolle für die einzelnen Funktionen aufrufen, um Details zu ihrer Ausführung anzuzeigen. - -Mithilfe der folgenden Befehle können Sie eine Beispieldatei vom bereitgestellten S3-Bucket in den Empfangs-Bucket des Stapels kopieren. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -Nachdem die Datei in den Empfangs-Bucket hochgeladen wurde, können Sie den Ausgabe-Bucket überprüfen, um die gerenderten HTML- und Nur-Text-Ausgabedateien zu sehen, die von den Lambda-Funktionen erstellt wurden. - -Ebenfalls können Sie die von den Lamda-Funktionen generierten CloudWatch-Protokolle aufrufen. - -## Bereinigen der Beispielressourcen - -Gehen Sie wie folgt vor, um alle in diesem Beispiel erstellten Ressourcen zu entfernen: - -1. Löschen Sie alle Objekte in den Empfangs- und Ausgabe-Buckets. -1. Löschen Sie den CloudFormation-Stapel. -1. Löschen Sie die CloudWatch-Protokollgruppen, die die Ausführungsprotokolle der zwei Prozessorfunktionen enthalten. - - - -## Ressourcen der CloudFormation-Vorlage - -### Parameter -- **CodeBucket** – Name des S3-Buckets in der Region des Stapels, der den Code für die zwei Lambda-Funktionen, "ProcessorFunctionOne" und "ProcessorFunctionTwo", enthält. Verwendet standardmäßig den verwalteten Bucket "awslambda-reference-architectures". - -- **CodeKeyPrefix** – Schlüsselpräfix für den Lambda-Funktionscode, der sich auf "CodeBucket" bezieht. Verwendet standardmäßig "file-processing". - -### Ressourcen -[Die bereitgestellte Vorlage](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -erstellt die folgenden Ressourcen: - -- **InputBucket** – ein S3-Bucket, der die Markdown-Dateien mit den Rohdaten enthält. Das Hochladen einer Datei in diesen Bucket löst beide Verarbeitungsfunktionen aus. - -- **OutputBucket** – ein S3-Bucket, den die Verarbeitungsfunktionen mit den transformierten Dateien auffüllen. - -- **InputNotificationTopic** – ein Amazon Simple Notification Service (Amazon SNS)-Thema, das verwendet wird, um mehrere Lambda-Funktionen als Reaktion auf die einzelnen Objekterstellungsbenachrichtigungen aufzurufen. - -- **NotificationPolicy** – eine Amazon SNS-Themenrichtlinie, die gestattet, dass "InputBucket" die Aktion "Veröffentlichen" für das Thema aufruft. - -- **ProcessorFunctionOne** – eine AWS Lambda-Funktion, die Markdown-Dateien in HTML umwandelt. Das Bereitstellungspaket für diese Funktion muss sich unter "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip" befinden. - -- **ProcessorFunctionTwo** – eine AWS Lambda-Funktion, die Markdown-Dateien in Nur-Text umwandelt. Das Bereitstellungspaket für diese Funktion muss sich unter "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip" befinden. - -- **LambdaExecutionRole** – eine AWS Identity and Access Management (IAM)-Rolle, die von den zwei Lambda-Funktionen verwendet wird. - -- **RolePolicy** – eine mit **LambdaExecutionRole** verknüpfte IAM-Richtlinie, die ermöglicht, dass Funktionen Objekte aus "InputBucket" abrufen, Objekte in "OutputBucket" platzieren und Protokolle an Amazon CloudWatch ausgeben. - -- **LambdaInvokePermissionOne** – eine Richtlinie, die es Amazon SNS ermöglicht, "ProcessorFunctionOne" basierend auf Benachrichtigungen von "InputNotificationTopic" aufzurufen. - -- **LambdaInvokePermissionTwo** – eine Richtlinie, die es Amazon SNS ermöglicht, "ProcessorFunctionTwo" basierend auf Benachrichtigungen von "InputNotificationTopic" aufzurufen. - - -## Lizensierung - -Dieses Beispiel einer Referenzarchitektur ist unter Apache 2.0 lizensiert. diff --git a/README/README-ES.md b/README/README-ES.md deleted file mode 100644 index 80644a5..0000000 --- a/README/README-ES.md +++ /dev/null @@ -1,84 +0,0 @@ -# Arquitectura de referencia sin servidor: Procesamiento de archivos en tiempo real - -La arquitectura de referencia Procesamiento de archivos en tiempo real es una arquitectura de procesamiento de datos en paralelo controlada por eventos de propósito general que usa [AWS Lambda](https://aws.amazon.com/lambda). Esta arquitectura es ideal para cargas de trabajo que necesitan obtener más de un dato de un objeto. Esta arquitectura sencilla se describe en este [diagrama](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) y en la [entrada de blog "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) del blog AWS Compute. Esta aplicación de ejemplo muestra una aplicación de conversión de Markdown en la que se utiliza Lambda para convertir archivos Markdown en HTML y texto sin formato. - -## Ejecución del ejemplo - -Puede usar la [plantilla de AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) proporcionada para lanzar una pila que muestre la arquitectura de referencia de procesamiento de archivos con Lambda. En la sección *Recursos de la plantilla de CloudFormation* de este documento encontrará información detallada sobre los recursos creados por esta plantilla. - -**Importante** Como el nombre de la pila de AWS CloudFormation se usa en el nombre de los buckets de Amazon Simple Storage Service (Amazon S3), ese nombre de pila solo debe contener letras en minúscula. Use letras en minúscula cuando escriba el nombre de la pila. La plantilla de CloudFormation proporcionada recupera su código Lambda de un bucket de la región us-east-1. Para ejecutar este ejemplo en otra región, modifique la plantilla y cargue el código Lambda en un bucket de esa región. - - -Elija **Launch Stack** para lanzar la plantilla en la región us-east-1 de su cuenta: - -[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -También puede usar el siguiente comando para lanzar la pila mediante el CLI de AWS. Se presupone que ya ha [instalado AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## Probar el ejemplo - -Una vez creada la pila mediante la plantilla de CloudFormation, puede probar el sistema cargando un archivo Markdown en el InputBucket que se creó en la pila. Puede usar este archivo README.md del repositorio como archivo de ejemplo. Después de cargar el archivo, puede ver los archivos HTML y de texto sin formato resultantes en el bucket de salida de la pila. También puede ver los logs de CloudWatch de cada una de las funciones si desea obtener información detallada de la ejecución. - -Puede usar los siguientes comandos para copiar un archivo de ejemplo del bucket de S3 proporcionado en el bucket de entrada de la pila. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -Después de cargar el archivo en el bucket de entrada, puede examinar el bucket de salida para ver los archivos de salida HTML y de texto sin formato resultantes creados por las funciones Lambda. - -También puede ver los logs de CloudWatch generados por las funciones Lambda. - -## Borrado de los recursos del ejemplo - -Para eliminar todos los recursos creados por este ejemplo, proceda del modo siguiente: - -1. Elimine todos los objetos de los buckets de entrada y salida. -1. Elimine la pila de CloudFormation. -1. Elimine los grupos de logs de CloudWatch que contienen los logs de ejecución de las dos funciones de procesamiento. - - - -## Recursos de la plantilla de CloudFormation - -### Parámetros -- **CodeBucket**: nombre del bucket de S3 de la región de la pila que contiene el código de las dos funciones Lambda, ProcessorFunctionOne y ProcessorFunctionTwo. Está establecido de forma predeterminada en el bucket administrado `awslambda-reference-architectures`. - -- **CodeKeyPrefix**: el prefijo de clave del código de la función Lambda correspondiente a `CodeBucket`. De forma predeterminada es `file-processing`. - -### Recursos -[La plantilla proporcionada](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -crea los recursos siguientes: - -- **InputBucket**: un bucket de S3 que almacena los archivos Markdown sin formato. Al cargar un archivo en este bucket se desencadenarán ambas funciones de procesamiento. - -- **OutputBucket**: un bucket de S3 que rellenan las funciones de procesamiento con los archivos convertidos. - -- **InputNotificationTopic**: un tema de Amazon Simple Notification Service (Amazon SNS) usado para invocar a varias funciones Lambda en respuesta a cada notificación de creación de un objeto. - -- **NotificationPolicy**: una política de tema de Amazon SNS que permite a `InputBucket` llamar a la acción `Publish` en el tema. - -- **ProcessorFunctionOne**: una función de AWS Lambda que convierte archivos Markdown en HTML. El paquete de implementación de esta función debe estar ubicado en `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`. - -- **ProcessorFunctionTwo**: una función de AWS Lambda que convierte archivos Markdown en texto sin formato. El paquete de implementación de esta función debe estar ubicado en `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`. - -- **LambdaExecutionRole**: un rol de AWS Identity and Access Management (IAM) usado por las dos funciones Lambda. - -- **RolePolicy**: una política de IAM asociada a **LambdaExecutionRole** que permite que las funciones obtengan objetos de `InputBucket`, coloquen objetos en `OutputBucket` y creen un log en Amazon CloudWatch. - -- **LambdaInvokePermissionOne**: una política que permite a Amazon SNS invocar a ProcessorFunctionOne a partir de las notificaciones de InputNotificationTopic. - -- **LambdaInvokePermissionTwo**: una política que permite a Amazon SNS invocar a ProcessorFunctionTwo a partir de las notificaciones de InputNotificationTopic. - - -## Licencia - -Este ejemplo de arquitectura de referencia tiene licencia de Apache 2.0. diff --git a/README/README-FR.md b/README/README-FR.md deleted file mode 100644 index fc6ec40..0000000 --- a/README/README-FR.md +++ /dev/null @@ -1,84 +0,0 @@ -# Architecture de référence sans serveur : Traitement de fichier en temps réel - -L'architecture de référence de traitement de fichier en temps réel est une architecture à visée générale de traitement de données en parallèle piloté par les événements qui utilise [AWS Lambda](https://aws.amazon.com/lambda). Cette architecture est idéale pour les charges de travail qui ont besoin de plusieurs dérivés de données d'un objet. Cette architecture simple est décrite dans ce [diagramme](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) et le [billet de blog « Fanout S3 Event Notifications to Multiple Endpoints »](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) sur le blog de calcul AWS. Cet exemple d'application illustre une application de conversion Markdown dans laquelle Lambda est utilisé pour convertir des fichiers Markdown en HTML et en texte brut. - -## Exécution de l'exemple - -Vous pouvez utiliser le [template AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) fourni pour lancer une stack qui illustre l'architecture de référence de traitement de fichier Lambda. Vous trouverez des détails sur les ressources créées par ce template dans la section *Ressources de template CloudFormation* de ce document. - -**Important** Comme le nom de stack AWS CloudFormation est utilisé dans le nom des buckets (compartiments) Amazon Simple Storage Service (Amazon S3), le nom de stack ne doit contenir que des lettres minuscules. Utilisez des lettres minuscules lorsque vous tapez le nom de stack. Le template CloudFormation fourni extrait son code Lambda d'un bucket dans la région us-east-1. Pour lancer cet exemple dans une autre région, veuillez modifier le template et charger le code Lambda dans un bucket de cette région. - - -Sélectionnez **Launch Stack** pour lancer le template dans la région us-east-1 dans votre compte : - -[![Lancement de Lambda de traitement de fichier en Virginie du Nord) avec CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -Sinon, vous pouvez utiliser la commande suivante pour lancer la stack à l'aide de l'interface de ligne de commande AWS CLI. Cela présume que vous avez déjà [installé AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## Test de l'exemple - -Une fois que vous avez créé la stack à l'aide du template CloudFormation, vous pouvez tester le système en chargeant un fichier Markdown dans le bucket (compartiment) InputBucket créé dans la stack. Vous pouvez utiliser ce fichier README.md dans le référentiel comme exemple de fichier. Une fois que le fichier a été chargé, vous pouvez afficher les fichiers HTML et en texte brut dans le bucket de sortie de votre stack. Vous pouvez également afficher les journaux CloudWatch pour chacune des fonctions pour voir les détails de leur exécution. - -Vous pouvez utiliser les commandes suivantes pour copier un exemple de fichier depuis le bucket (compartiment) S3 fourni vers le bucket d'entrée de votre stack. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -Une fois que le fichier a été chargé dans le bucket (compartiment) d'entrée, vous pouvez inspecter le bucket de sortie pour afficher les fichiers HTML et en texte brut de sortie créés par les fonctions Lambda. - -Vous pouvez également afficher les journaux CloudWatch générés par les fonctions Lambda. - -## Nettoyage des ressources de l'exemple - -Pour supprimer toutes les ressources créées par cet exemple, procédez comme suit : - -1. Supprimez tous les objets des buckets (compartiments) d'entrée et de sorties. -1. Supprimez la stack CloudFormation. -1. Supprimez les groupes de journaux qui contiennent les journaux d'exécution pour les deux fonctions de traitement. - - - -## Ressources du template CloudFormation - -### Paramètres -- **CodeBucket** - Nom du bucket (compartiment) S3 dans la région de la stack qui contient le code des deux fonctions Lambda, ProcessorFunctionOne et ProcessorFunctionTwo. Par défaut, il s'agit du bucket opéré par `awslambda-reference-architectures`. - -- **CodeKeyPrefix** - Le préfixe de clé pour le code de fonction Lambda relatif à `CodeBucket`. La valeur par défaut est `file-processing`. - -### Ressources -[Le template fourni](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -crée les ressources suivantes : - -- **InputBucket** - Un bucket (compartiment) S3 qui contient les fichiers Markdown bruts. Le chargement d'un fichier dans ce bucket déclenchera les deux fonctions de traitement. - -- **OutputBucket** - Un bucket S3 alimenté par les fonctions de traitement avec les fichiers transformés. - -- **InputNotificationTopic** - Une rubrique Amazon Simple Notification Service (Amazon SNS) utilisée pour appeler plusieurs fonctions Lambda en réponse à chaque notification de création d'objet. - -- **NotificationPolicy** - Une politique de rubrique Amazon SNS qui autorise `InputBucket` à appeler l'action `Publish` sur la rubrique. - -- **ProcessorFunctionOne** - Une fonction AWS Lambda qui convertit des fichiers Markdown en HTML. Le package de déploiement pour cette fonction doit être situé dans `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`. - -- **ProcessorFunctionTwo** - Une fonction AWS Lambda qui convertit des fichiers Markdown en texte brut. Le package de déploiement pour cette fonction doit être situé dans `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`. - -- **LambdaExecutionRole** - Un rôle AWS Identity and Access Management (IAM) utilisé par les deux fonctions Lambda. - -- **RolePolicy** - Une politique IAM associée à **LambdaExecutionRole** qui autorise les fonctions à extraire des objets de `InputBucket`, à les mettre dans `OutputBucket` et à se connecter à Amazon CloudWatch. - -- **LambdaInvokePermissionOne** - Une politique qui permet à Amazon SNS d'appeler ProcessorFunctionOne en fonction de notifications d'InputNotificationTopic. - -- **LambdaInvokePermissionTwo** - Une politique qui permet à Amazon SNS d'appeler ProcessorFunctionTwo en fonction de notifications d'InputNotificationTopic. - - -## Licence - -Cet exemple d'architecture de référence est fourni sous licence sous Apache 2.0. diff --git a/README/README-IT.md b/README/README-IT.md deleted file mode 100644 index b529e19..0000000 --- a/README/README-IT.md +++ /dev/null @@ -1,84 +0,0 @@ -# Architettura di riferimento senza server: elaborazione dei file in tempo reale - -L'architettura di riferimento per l'elaborazione dei file in tempo reale è un'architettura di elaborazione dati parallela, basata sugli eventi e destinata a scopi generici che utilizza [AWS Lambda](https://aws.amazon.com/lambda). Tale architettura è ideale per i carichi di lavoro che necessitano di più di un derivato dati di un oggetto. Questa architettura semplice è descritta in questo [diagramma](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) e nel [post "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) del blog AWS Compute. L'architettura esempio mostra un'applicazione di conversione Markdown in cui Lambda viene utilizzato per convertire file Markdown in HTML e testo semplice. - -## Esecuzione dell'esempio - -È possibile utilizzare il [modello AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) fornito, per avviare uno stack che mostra l'architettura di riferimento per l'elaborazione dei file Lambda. I dettagli sulle risorse create da questo modello sono disponibili nella sezione *CloudFormation Template Resources* di questo documento. - -**Important** Poiché il nome dello stack di AWS CloudFormation è utilizzato nel nome dei bucket di Amazon Simple Storage Service (Amazon S3), il nome di tale stack deve contenere solo lettere minuscole. Utilizzare lettere minuscole durante la digitazione del nome dello stack. Il modello di CloudFormation fornito recupera il suo codice Lambda da un bucket nella regione Stati Uniti orientali 1. Per avviare questo esempio in un'altra regione, modificare il modello e caricare il codice Lambda in un bucket di quella regione. - - -Selezionare **Launch Stack** per avviare il modello nella regione Stati Uniti orientali 1 nell'account personale: - -[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -In alternativa, è possibile utilizzare il comando seguente per avviare lo stack tramite AWS CLI. Ciò presuppone l'[installazione di AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## Test dell'esempio - -Dopo aver creato lo stack tramite il modello di CloudFormation, è possibile eseguire il test del sistema caricando un file Markdown nell'InputBucket creato nello stack. È possibile utilizzare il file README.md nel repository come file di esempio. Una volta caricato il file, è possibile visualizzare i risultanti file HTML e di testo semplice nel bucket di output dello stack. È possibile visualizzare anche i registri di CloudWatch di ciascuna funzione per vedere i dettagli della loro esecuzione. - -È possibile utilizzare i comandi seguenti per copiare un file di esempio dal bucket S3 fornito nel bucket di input dello stack. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -Una volta caricato il file nel bucket di input, è possibile ispezionare il bucket di output per vedere la resa dei file di output HTML e di testo semplice creati dalle funzioni di Lambda. - -È possibile visualizzare anche i registri di CloudWatch generati dalle funzioni di Lambda. - -## Eliminazione delle risorse dell'esempio - -Per eliminare tutte le risorse create da questo esempio, effettuare i seguenti passaggi: - -1. Eliminare tutti gli oggetti nei bucket di input e output. -1. Eliminare lo stack di CloudFormation. -1. Eliminare i gruppi di registro di CloudWatch che contengono i registri di esecuzione per le due funzioni del processore. - - - -## Risorse dei modelli di CloudFormation - -### Parametri -- **CodeBucket**: nome del bucket S3 nella regione dello stack che contiene il codice per le due funzioni di Lambda, ProcessorFunctionOne e ProcessorFunctionTwo. Impostazioni predefinite sul bucket gestito "awslambda-reference-architectures". - -- **CodeKeyPrefix**: prefisso della chiave per il codice delle funzioni di Lambda relativo a "CodeBucket". Impostazioni predefinite su "file-processing". - -### Risorse -[Il modello fornito](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -crea le risorse seguenti: - -- **InputBucket**: bucket S3 che contiene i file Markdown non elaborati. Il caricamento di un file in questo bucket attiva entrambe le funzioni di elaborazione. - -- **OutputBucket**: bucket S3 popolato dalle funzioni del processore con i file trasformati. - -- **InputNotificationTopic**: argomento di Amazon Simple Notification Service (Amazon SNS) utilizzato per richiamare più funzioni di Lambda in risposta alla notifica della creazione di ciascun oggetto. - -- **NotificationPolicy**: policy dell'argomento di Amazon SNS che permette a "InputBucket" di richiedere l'azione "Publish" all'argomento. - -- **ProcessorFunctionOne**: funzione di AWS Lambda che converte i file Markdown in HTML. Il pacchetto di distribuzione per questa funzione deve essere collocato in "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip". - -- **ProcessorFunctionTwo**: funzione di AWS Lambda che converte i file Markdown in testo semplice. Il pacchetto di distribuzione per questa funzione deve essere collocato in "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip". - -- **LambdaExecutionRole**: ruolo di AWS Identity and Access Management (IAM) utilizzato dalle due funzioni di Lambda. - -- **RolePolicy**: policy di IAM associata a **LambdaExecutionRole** che consente alle funzioni di prendere oggetti da "InputBucket", posizionare oggetti in "OutputBucket" e accedere ad Amazon CloudWatch. - -- **LambdaInvokePermissionOne**: policy che consente ad Amazon SNS di richiamare ProcessorFunctionOne in base alle notifiche di InputNotificationTopic. - -- **LambdaInvokePermissionTwo**: policy che consente ad Amazon SNS di richiamare ProcessorFunctionTwo in base alle notifiche di InputNotificationTopic. - - -## Licenza - -La licenza di questo esempio di architettura di riferimento è fornita con Apache 2.0. diff --git a/README/README-JP.md b/README/README-JP.md deleted file mode 100644 index 90a140c..0000000 --- a/README/README-JP.md +++ /dev/null @@ -1,84 +0,0 @@ -# サーバーレスリファレンスアーキテクチャ: リアルタイムのファイル処理 - -リアルタイムのファイル処理リファレンスアーキテクチャは、[AWS Lambda](https://aws.amazon.com/lambda) を使用する、汎用でイベント駆動型の並列データ処理アーキテクチャです。このアーキテクチャは、オブジェクトの複数のデータ派生物を必要とするワークロードに最適です。このシンプルなアーキテクチャについては、この [図](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) および AWS コンピューティングブログの ["Fanout S3 Event Notifications to Multiple Endpoints" ブログの投稿](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) で説明しています。このサンプルアプリケーションは、Markdown ファイルを HTML とプレーンテキストに変換するために Lambda を使用する Markdown 変換アプリケーションを示しています。 - -## 例の実行 - -用意された [AWS CloudFormation テンプレート](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) を使用して、Lambda ファイル処理のリファレンスアーキテクチャを示すスタックを起動できます。このテンプレートで作成されるリソースの詳細は、このドキュメントの「*CloudFormation テンプレートのリソース*」セクションで説明しています。 - -**重要** AWS CloudFormation スタック名が Amazon Simple Storage Service (Amazon S3) バケット名で使用されるため、そのスタック名には小文字のみを含める必要があります。スタック名を入力するときは小文字を使用してください。用意された CloudFormation テンプレートは、us-east-1 region リージョンのバケットからその Lambda コードを取得します。別のリージョンでこのサンプルを起動するには、テンプレートを変更し、そのリージョンのバケットに Lambda コードをアップロードします。 - - -[**Launch Stack**] を選択して、アカウントで us-east-1 リージョンにテンプレートを起動します。 - -[![CloudFormation を使用して Lambda ファイル処理を北バージニアに起動する](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -代わりに、次のコマンドで、AWS CLI を使用してスタックを起動できます。この例では、すでに [AWS CLI をインストール済み](http://docs.aws.amazon.com/cli/latest/userguide/installing.html) であることを前提としています。 - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## 例のテスト - -CloudFormation テンプレートを使用してスタックを作成したら、スタックで作成された InputBucket に Markdown ファイルをアップロードしてシステムをテストできます。レポジトリ内のこの README.md ファイルは、サンプルファイルとして使用できます。ファイルがアップロードされたら、生成される HTML とプレーンテキストファイルをスタックの出力バケットで表示できます。各関数の CloudWatch ログを表示して、実行の詳細を確認することもできます。 - -次のコマンドを使用して、用意された S3 バケットからスタックの入力バケットにサンプルファイルをコピーすることができます。 - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -ファイルが入力バケットにアップロードされたら、出力バケットを検査し、Lambda 関数によって作成され、レンダリングされた HTML およびプレーンテキスト出力ファイルを表示できます。 - -Lambda 関数によって生成された CloudWatch ログを表示することもできます。 - -## リソース例のクリーンアップ - -この例で作成されたすべてのリソースを削除するには、次の操作を行います。 - -1.入出力バケットのすべてのオブジェクトを削除します。 -1.CloudFormation スタックを削除します。 -1.2 つのプロセッサ関数の実行ログを含む CloudWatch ロググループを削除します。 - - - -## CloudFormation テンプレートのリソース - -### パラメーター -- **CodeBucket** - 2 つの Lambda 関数 (ProcessorFunctionOne および ProcessorFunctionTwo) のコードを含む、スタックのリージョンの S3 バケットの名前。デフォルトはマネージドバケット `awslambda-reference-architectures` です。 - -- **CodeKeyPrefix** - `CodeBucket` に相対的な Lambda 関数コードのキープレフィックス。デフォルトは `file-processing` です。 - -### リソース -[用意されたテンプレート](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - では以下のリソースが作成されます。 - -- **InputBucket** - Markdown の raw ファイルを保持する S3 バケット。このバケットにファイルをアップロードすると、両方の処理関数がトリガーされます。 - -- **OutputBucket** - プロセッサ関数によって、変換されたファイルが入力される S3 バケット。 - -- **InputNotificationTopic** - 各オブジェクトの作成通知に応答して複数の Lambda 関数を呼び出すために使用される Amazon Simple Notification Service (Amazon SNS) トピック。 - -- **NotificationPolicy** - トピックで `Publish` アクションを呼び出す `InputBucket` を許可する Amazon SNS トピックポリシー。 - -- **ProcessorFunctionOne** - Markdown ファイルを HTML に変換する AWS Lambda 関数。この関数のデプロイパッケージは `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip` にあります。 - -- **ProcessorFunctionTwo** - Markdown ファイルをプレーンテキストに変換する AWS Lambda 関数。この関数のデプロイパッケージは `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip` にあります。 - -- **LambdaExecutionRole** - 2 つの Lambda 関数によって使用される AWS Identity and Access Management (IAM) ロール。 - -- **RolePolicy** - 関数が `InputBucket` からオブジェクトを取得し、オブジェクトを `OutputBucket` に配置して、Amazon CloudWatch に記録できるようにする **LambdaExecutionRole** に関連付けられた IAM ポリシー。 - -- **LambdaInvokePermissionOne** - Amazon SNS が InputNotificationTopic からの通知に基づいて ProcessorFunctionOne を呼び出せるようにするポリシー。 - -- **LambdaInvokePermissionTwo** - Amazon SNS が InputNotificationTopic からの通知に基づいて ProcessorFunctionTwo を呼び出せるようにするポリシー。 - - -## ライセンス - -このリファレンスアーキテクチャサンプルは Apache 2.0 でライセンスされています。 diff --git a/README/README-KR.md b/README/README-KR.md deleted file mode 100644 index c63e05c..0000000 --- a/README/README-KR.md +++ /dev/null @@ -1,84 +0,0 @@ -# 서버 없는 레퍼런스 아키텍처: 실시간 파일 처리 - -실시간 파일 처리 레퍼런스 아키텍처는 이벤트 중심의 범용 병렬 데이터 처리 아키텍처이며 [AWS Lambda](https://aws.amazon.com/lambda)를 사용합니다. 이 아키텍처는 객체의 데이터 파생이 하나 이상 필요한 워크로드에 적합합니다. 이 간단한 아키텍처는 이 [diagram](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) 및 AWS Compute 블로그의 ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/)에 설명되어 있습니다. 이 단순한 애플리케이션은 Lambda를 사용하여 Markdown 파일을 HTML 및 일반 텍스트로 변환하는 Markdown 변환 애플리케이션을 보여줍니다. - -## 예제 실행 - -제공된 [AWS CloudFormation template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template)을 사용하여 Lambda 파일 처리 레퍼런스 아키텍처를 보여주는 스택을 시작할 수 있습니다. 이 템플릿을 통해 생성된 리소스에 대한 세부 정보는 본 문서의 *CloudFormation 템플릿 리소스* 단원에서 제공됩니다. - -**중요** AWS CloudFormation 스택 이름은 Amazon Simple Storage Service(Amazon S3) 버킷에서 사용되므로 이 스택 이름은 소문자만 포함해야 합니다. 스택 이름을 입력할 때는 소문자만 사용하십시오. 제공된 CloudFormation 템플릿은 us-east-1 리전의 버킷에서 Lambda 코드를 가져옵니다. 이 샘플을 다른 리전에서 시작하려면 템플릿을 수정하고 Lambda 코드를 해당 리전의 버킷에 업로드하십시오. - - -**Launch Stack**을 선택하여 계정의 us-east-1 리전에서 템플릿을 시작합니다. - -[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -그 밖에도 다음 명령을 사용하여 AWS CLI를 사용하여 스택을 시작할 수 있습니다. 이 단계를 실행하기 위해 이미 [installed the AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)를 완료했다고 가정합니다. - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## 예제 테스트 - -CloudFormation 템플릿을 사용하여 스택을 만든 후 Markdown 파일을 스택에 만들어진 InputBucket으로 업로드하여 시스템을 테스트할 수 있습니다. 리포지토리의 이 README.md 파일을 예제 파일로 사용할 수 있습니다. 파일을 업로드한 후 스택의 출력 버킷에서 결과 HTML과 일반 텍스트 파일을 확인할 수 있습니다. 각 함수의 CloudWatch 로그를 통해 각각의 실행 세부 정보를 볼 수도 있습니다. - -다음 명령을 사용하여 제공된 S3 버킷에서 샘플 파일을 스택의 입력 버킷으로 복사할 수 있습니다. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -파일을 입력 버킷으로 업로드한 후 출력 버킷을 검사하여 렌더링된 HTML과 Lambda 함수에 의해 생성된 일반 텍스트 출력 파일을 확인할 수 있습니다. - -Lambda 함수에 의해 생성된 CloudWatch 로그도 볼 수 있습니다. - -## 예제 리소스 정리 - -이 예제에서 생성된 모든 리소스를 제거하려면 다음을 수행합니다. - -1. 입력 및 출력 버킷에서 모든 객체를 삭제합니다. -1. CloudFormation 스택을 삭제합니다. -1. 두 프로세서 함수에 대한 실행 정보가 포함된 CloudWatch 로그 그룹을 삭제합니다. - - - -## CloudFormation 템플릿 리소스 - -### 파라미터 -- **CodeBucket** - 스택의 리전에 있는 S3 버킷의 이름이며 두 Lambda 함수(ProcessorFunctionOne 및 ProcessorFunctionTwo)에 대한 코드가 포함되어 있습니다. 관리형 버킷 `awslambda-reference-architectures`의 기본값입니다. - -- **CodeKeyPrefix** - `CodeBucket`과 관련된 Lambda 함수 코드의 키 접두사입니다. `file-processing`의 기본값입니다. - -### 리소스 -[The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template)은 -다음 리소스를 만듭니다. - -- **InputBucket** - 원시 Markdown 파일이 저장된 S3 버킷입니다. 이 버킷에 파일을 업로드하면 두 처리 함수가 트리거됩니다. - -- **OutputBucket** - 변형된 파일이 있는 프로세서 함수에 의해 채워지는 S3 버킷입니다. - -- **InputNotificationTopic** - 각 객체 생성 알림에 대한 응답으로 여러 Lambda 함수를 호출하는 Amazon Simple Notification Service(Amazon SNS) 주제입니다. - -- **NotificationPolicy** - `InputBucket`이 주제에 대한 `Publish` 작업을 호출할 수 있도록 허용하는 Amazon SNS 주제 정책입니다. - -- **ProcessorFunctionOne** - Markdown 파일을 HTML로 변환하는 AWS Lambda 함수입니다. 이 함수의 배포 패키지가 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip`에 있어야 합니다. - -- **ProcessorFunctionTwo** - Markdown 파일을 일반 텍스트로 변환하는 AWS Lambda 함수입니다. 이 함수의 배포 패키지가 `s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip`에 있어야 합니다. - -- **LambdaExecutionRole** - 두 Lambda 함수에서 사용하는 AWS Identity and Access Management(IAM) 역할입니다. - -- **RolePolicy** - **LambdaExecutionRole**과 연결된 IAM 정책이며 함수가 `InputBucket`으로부터 객체를 얻고, `OutputBucket`에 객체를 추가하고 Amazon CloudWatch에 로그를 기록할 수 있도록 허용합니다. - -- **LambdaInvokePermissionOne** - Amazon SNS가 InputNotificationTopic의 알림을 기반으로 ProcessorFunctionOne을 호출할 수 있게 하는 정책입니다. - -- **LambdaInvokePermissionTwo** - Amazon SNS가 InputNotificationTopic의 알림을 기반으로 ProcessorFunctionTwo를 호출할 수 있게 하는 정책입니다. - - -## 라이선스 - -이 레퍼런스 아키텍처 샘플은 Apache 2.0에서 라이선스가 부여되었습니다. diff --git a/README/README-PT.md b/README/README-PT.md deleted file mode 100644 index e84ee94..0000000 --- a/README/README-PT.md +++ /dev/null @@ -1,84 +0,0 @@ -# Arquitetura de referência sem servidor: processamento de arquivos em tempo real - -A arquitetura de referência de Processamento de arquivos em tempo real é uma arquitetura de processamento de uso geral, com base em evento e com dados paralelos que usa [AWS Lambda](https://aws.amazon.com/lambda). Esta arquitetura é ideal para cargas de trabalho que precisam de mais de um derivado de dados de um objeto. Esta arquitetura simples está descrita neste [diagrama](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) e em [postagem do blog "Fanout S3 Event Notifications to Multiple Endpoints"](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) no Blog de computação da AWS. Esta aplicação da amostra demonstra uma aplicação de conversão Markdown em que o Lambda é usado para converter arquivos Markdown para HTML e texto sem formatação. - -## Executando o exemplo - -Você pode usar o [modelo AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) fornecido para iniciar uma pilha que demonstra a arquitetura de referência de processamento de arquivo Lambda. Os detalhes sobre os recursos criados por este modelo são fornecidos na seção *Recursos do modelo do CloudFormation* deste documento. - -**Importante** Como o nome da pilha do AWS CloudFormation é usado no nome dos buckets Amazon Simple Storage Service (Amazon S3), o nome da pilha deve conter apenas letras minúsculas. Use letras minúsculas ao digitar o nome da pilha. O modelo do CloudFormation fornecido recupera seu código do Lambda de um bucket na região us-east-1. Para iniciar esta amostra em outra região, modifique o modelo e faça o upload do código do Lambda em um bucket nessa região. - - -Escolha **Launch Stack** para iniciar o modelo na região us-east-1 em sua conta: - -[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -Alternativamente, você pode usar o seguinte comando para iniciar a pilha usando o AWS CLI. Isso pressupõe que você já [instalou o AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## Testando o exemplo - -Depois de ter criado a pilha usando o modelo CloudFormation, você pode testar o sistema de upload de um arquivo Markdown para o InputBucket que foi criado na pilha. Você pode usar esse arquivo README.md no repositório como um arquivo de exemplo. Depois que o arquivo foi carregado, você pode ver os arquivos HTML e os textos sem formatação resultantes do bucket de saída da pilha. Você também pode visualizar os registros de CloudWatch para cada uma das funções, a fim de ver os detalhes da sua execução. - -Você pode usar os seguintes comandos para copiar um arquivo de amostra do bucket S3 fornecido dentro do bucket de entrada da sua pilha. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -Depois que o arquivo foi carregado para o bucket de entrada, você pode inspecionar o bucket de saída para ver os arquivos de saída HTML e texto sem formatação criados pelas funções lambda. - -Você também pode visualizar os registros do CloudWatch gerados pelas funções lambda. - -## Limpando os recursos de exemplo - -Para remover todos os recursos criados por este exemplo, faça o seguinte: - -1. Exclua todos os objetos nos buckets de entrada e saída. -1. Exclua a pilha do CloudFormation. -1. Exclua os grupos de registro do CloudWatch que contêm os registros de execução para as duas funções de processador. - - - -## Recursos do modelo do CloudFormation - -### Parâmetros -- **CodeBucket** - Nome do bucket S3 na região da pilha que contém o código para as duas funções Lambda, ProcessorFunctionOne e ProcessorFunctionTwo. O padrão para o bucket gerenciado é "awslambda-reference-architectures". - -- **CodeKeyPrefix** - O prefixo de chaves para o código da função Lambda em relação ao "CodeBucket". O padrão é "file-processing". - -### Recursos -[O modelo fornecido](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -cria os seguintes recursos: - -- **InputBucket** - Um bucket S3 que contém os arquivos Markdown não processados. Fazer upload de um arquivo para este bucket irá desencadear ambas as funções de processamento. - -- **OutputBucket** - Um bucket S3 que é preenchido pelas funções do processador com os arquivos transformados. - -- **InputNotificationTopic** - Um tópico Amazon Simple Notification Service (Amazon SNS) usado para chamar múltiplas funções Lambda em resposta a cada notificação de criação do objeto. - -- **NotificationPolicy** - Uma política de tópico Amazon SNS que permite "Input Bucket" para chamar a ação "Publish" sobre o tema. - -- **ProcessorFunctionOne** - Uma função Lambda AWS que converte os arquivos Markdown para HTML. O pacote de implementação para esta função deve estar localizado em "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip". - -- **ProcessorFunctionTwo** - Uma função Lambda da AWS que converte arquivos Markdown para texto sem formatação. O pacote de implementação para esta função deve estar localizado em "s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip". - -- **LambdaExecutionRole** - Uma função AWS Identity and Access Management (IAM) usada pelas duas funções Lambda. - -- **RolePolicy** - Uma política de IAM associada ao **LambdaExecutionRole** que permite às funções obter objetos do "InputBucket", colocar objeto para "OutputBucket" e registro para o Amazon CloudWatch. - -- **LambdaInvokePermissionOne** - Uma política que permite ao Amazon SNS invocar ProcessorFunctionOne com base em notificações dos InputNotificationTopic. - -- **LambdaInvokePermissionTwo** - Uma política que permite ao Amazon SNS invocar ProcessorFunctionTwo com base nas notificações do InputNotificationTopic. - - -## Licença - -Este exemplo de arquitetura de referência é licenciado sob a licença do Apache 2.0. diff --git a/README/README-RU.md b/README/README-RU.md deleted file mode 100644 index 716621a..0000000 --- a/README/README-RU.md +++ /dev/null @@ -1,84 +0,0 @@ -# Эталонная бессерверная архитектура: обработка файлов в реальном времени - -Эталонная архитектура для обработки файлов в реальном времени – это универсальная архитектура параллельной обработки данных на основе событий, которая использует [AWS Lambda](https://aws.amazon.com/lambda). Она идеально подходит для рабочих нагрузок, для которых требуется несколько производных данных объекта. Эта простая архитектура описана на этой [схеме](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) и в ["Fanout S3 Event Notifications to Multiple Endpoints" blog post](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) в блоге AWS Compute. В примере приложения Lambda используется для преобразования файлов Markdown в HTML и текст. - -## Запуск примера - -Вы можете использовать предоставленный [шаблон AWS CloudFormation](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template), чтобы запустить стек, демонстрирующий эталонную архитектуру для обработки файлов с помощью Lambda. Сведения о ресурсах, созданных этим шаблоном, представлены в разделе «Ресурсы шаблона CloudFormation» этого документа. - -**Важно!** Так как имя стека AWS CloudFormation используется в имени корзин Amazon Simple Storage Service (Amazon S3), оно должно содержать только строчные буквы. При вводе имени стека используйте только строчные буквы. Предоставленный шаблон CloudFormation извлекает код Lambda из корзины в регионе us-east-1. Чтобы запустить пример в другом регионе, измените шаблон и загрузите код Lambda в корзину в этом регионе. - - -Выберите **Launch Stack**, чтобы запустить шаблон в регионе us-east-1 в вашем аккаунте: - -[![Запуск обработки файлов Lambda в Северной Вирджинии с помощью CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -Или же выполните следующую команду, чтобы запустить стек с помощью AWS CLI. При этом предполагается, что вы уже [установили AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html). - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## Тестирование примера - -После создания стека с помощью шаблона CloudFormation вы можете проверить систему, загрузив файл Markdown в корзину InputBucket, созданную стеком. Для примера можно использовать файл README.md в этом репозитории. После передачи файла вы увидите полученные HTML-файл и текстовый файл в выходной корзине стека. Вы также можете просмотреть сведения о выполнении каждой функции в журналах CloudWatch. - -Выполните следующие команды, чтобы скопировать пример файла из корзины S3 во входную корзину вашего стека. - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -После передачи файла во входную корзину вы можете просмотреть выходную корзину, где расположены полученные HTML-файл и текстовый файл, созданные функциями Lambda. - -Вы также можете просмотреть журналы CloudWatch, созданные функциями Lambda. - -## Очистка ресурсов примера - -Чтобы удалить все ресурсы, созданные этим примером, выполните следующие действия. - -1. Удалите все объекты во входной и выходной корзинах. -1. Удалите стек CloudFormation. -1. Удалите группы журналов CloudWatch, содержащие журналы выполнения двух функций обработки. - - - -## Ресурсы шаблона CloudFormation - -### Параметры -- **CodeBucket** – имя корзины S3 в регионе стека, содержащей код для двух функций Lambda: ProcessorFunctionOne и ProcessorFunctionTwo. По умолчанию используется управляемая корзина awslambda-reference-architectures. - -- **CodeKeyPrefix** – префикс ключа для кода функции Lambda относительно CodeBucket. Значение по умолчанию: file-processing. - -### Ресурсы -[Предоставленный шаблон](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -создает следующие ресурсы. - -- **InputBucket** – это корзина S3, в которой размещены файлы Markdown. При загрузке файла в эту корзину вызываются обе функции обработки. - -- **OutputBucket** – в эту корзину S3 функции обработки добавляют преобразованные файлы. - -- **InputNotificationTopic** – тема Amazon Simple Notification Service (Amazon SNS), используемая для вызова нескольких функций Lambda в ответ на каждое оповещение о создании объекта. - -- **NotificationPolicy** – политика темы Amazon SNS, позволяющая InputBucket вызвать действие Publish для темы. - -- **ProcessorFunctionOne** – эта функция AWS Lambda преобразует файлы Markdown в HTML. Пакет развертывания для нее должен быть расположен по следующему пути: s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip. - -- **ProcessorFunctionTwo** – эта функция AWS Lambda преобразует файлы Markdown в текстовые файлы. Пакет развертывания для нее должен быть расположен по следующему пути: s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip. - -- **LambdaExecutionRole** – эту роль AWS Identity and Access Management (IAM) используют две функции Lambda. - -- **RolePolicy** – политика IAM, связанная с ролью LambdaExecutionRole, которая позволяет функциям извлекать объекты из корзины InputBucket, добавлять объекты в корзину OutputBucket и вести журнал в Amazon CloudWatch. - -- **LambdaInvokePermissionOne** – политика, позволяющая Amazon SNS вызывать функцию ProcessorFunctionOne в ответ на оповещения от InputNotificationTopic. - -- **LambdaInvokePermissionTwo** – политика, позволяющая Amazon SNS вызывать функцию ProcessorFunctionTwo в ответ на оповещения от InputNotificationTopic. - - -## Лицензия - -Данная эталонная архитектура лицензирована в соответствии с лицензией Apache 2.0. diff --git a/README/README-TW.md b/README/README-TW.md deleted file mode 100644 index 7627ab4..0000000 --- a/README/README-TW.md +++ /dev/null @@ -1,84 +0,0 @@ -# 無伺服器參考架構：即時檔案處理 - -即時檔案處理參考架構是利用 [AWS Lambda](https://aws.amazon.com/lambda) 運作的一般用途、事件驅動的平行資料處理架構。此架構很適合需要一個以上的物件資料衍生物的工作負載。在 [示意圖](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda-refarch-fileprocessing.pdf) 與 AWS 運算部落格的 ["Fanout S3 Event Notifications to Multiple Endpoints" 部落格文章](https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/) 中，有關於此簡易架構的說明。此簡易的應用程式示範 Markdown 轉換應用程式，Lambda 使用此應用程式將 Markdown 檔案轉換為 HTML 與純文字。 - -## 執行範例 - -您可以使用系統提供的 [AWS CloudFormation 範本](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) 啟動示範 Lambda 檔案處理參考架構的堆疊。本文件的 *CloudFormation 範本資源* 章節中有提供關於此範例所建立資源的詳細資訊。 - -**重要** 由於 AWS CloudFormation 堆疊名稱將使用於 Amazon Simple Storage Service (Amazon S3) 儲存貯體的名稱，因此堆疊名稱只能包含小寫字母。輸入堆疊名稱時，請使用小寫字母。系統提供的 CloudFormation 範本會從 us-east-1 區域的儲存貯體取回其 Lambda 程式碼。若要在其他區域啟動此範例，請修改範本並將 Lambda 程式碼上傳至該區域的儲存貯體。 - - -選擇 **Launch Stack** 以啟動您帳戶的 us-east-1 區域中的範本。 - -[![Launch Lambda File Processing into North Virginia with CloudFormation](http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/images/cloudformation-launch-stack-button.png)](https://console.aws.amazon.com/cloudformation/home?region=us-east-1#/stacks/new?stackName=lambda-file-processing&templateURL=https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) - -或者，您可以使用以下命令啟動堆疊以使用 AWS CLI。這裡假設您已 [安裝 AWS CLI](http://docs.aws.amazon.com/cli/latest/userguide/installing.html)。 - -```bash -aws cloudformation create-stack \ - --stack-name lambda-file-processing \ - --template-url https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template \ - --capabilities CAPABILITY_IAM -``` - -## 測試範例 - -在您使用 CloudFormation 範本建立堆疊之後，可藉由將 Markdown 檔案上傳至於堆疊中建立的 InputBucket 以測試系統。您可以使用儲存庫中的 README.md 檔案做為範例檔案。在檔案上傳之後，可在您的堆疊的輸出儲存貯體中看到結果的 HTML 與純文字檔案。您亦可檢視各項功能的 CloudWatch 記錄以查看其執行的詳細資訊。 - -您可以使用以下命令，將範例檔案從系統提供的 S3 儲存貯體複製至您的堆疊的輸入儲存貯體。 - -``` -BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-processing --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp s3://awslambda-reference-architectures/file-processing/example.md s3://$BUCKET/example.md -``` - -在檔案上傳至輸入儲存貯體之後，您可以檢查輸出儲存貯體以查看經過 Lambda 功能處理的 HTML 與純文字輸出檔案。 - -您亦可檢視由 Lambda 功能產生的 CloudWatch 記錄。 - -## 清除應用範例資源 - -若要移除此範例建立的所有資源，請執行以下動作： - -1.刪除輸入與輸出儲存貯體中的所有物件。 -1.刪除 CloudFormation 堆疊。 -1.刪除包含兩個處理器功能的執行記錄的 CloudWatch 記錄群組。 - - - -## CloudFormation 範本資源 - -### 參數 -- **CodeBucket** - 包含兩個 Lambda 功能 ProcessorFunctionOne 與 ProcessorFunctionTwo 的堆疊區域中的 S3 儲存貯體的名稱。預設為受管儲存貯體「awslambda-reference-architectures」。 - -- **CodeKeyPrefix** - 與「CodeBucket」相關的 Lambda 功能程式碼的金鑰前綴。預設為「file-processing」。 - -### 資源 -[系統提供的範本](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/lambda_file_processing.template) -建立以下資源： - -- **InputBucket** - 存放原始 Markdown 檔案的 S3 儲存貯體。上傳檔案至此儲存貯體將觸發兩個處理功能。 - -- **OutputBucket** - 由處理器功能與轉換後的檔案所填入的 S3 儲存貯體。 - -- **InputNotificationTopic** - 用於呼叫多個 Lambda 功能以回應各個物件建立通知的 Amazon Simple Notification Service (Amazon SNS) 主題。 - -- **NotificationPolicy** - 允許「InputBucket」呼叫主題上的「Publish」動作的 Amazon SNS 主題政策。 - -- **ProcessorFunctionOne** - 可將 Markdown 檔案轉換為 HTML 的 AWS Lambda 功能。此功能的部署套件必須位於「s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-1.zip」。 - -- **ProcessorFunctionTwo** - 可將 Markdown 檔案轉換為純文字的 AWS Lambda 功能。此功能的部署套件必須位於「s3://[CodeBucket]/[CodeKeyPrefix]/data-processor-2.zip」。 - -- **LambdaExecutionRole** - 由兩個 Lambda 功能使用的 AWS Identity and Access Management (IAM) 角色。 - -- **RolePolicy** - 與 **LambdaExecutionRole** 關聯的 IAM 政策，它允許功能從「InputBucket」取得物件、將物件放入「OutputBucket」，以及記錄至 Amazon CloudWatch。 - -- **LambdaInvokePermissionOne** - 可讓 Amazon SNS 依據來自 InputNotificationTopic 的通知以呼叫 ProcessorFunctionOne 的一個政策。 - -- **LambdaInvokePermissionTwo** - 可讓 Amazon SNS 依據來自 InputNotificationTopic 的通知以呼叫 ProcessorFunctionTwo 的一個政策。 - - -## 授權 - -此參考架構範例依據 Apache 2.0 授權。 diff --git a/file_processing.yml b/file_processing.yml deleted file mode 100644 index 1c666c7..0000000 --- a/file_processing.yml +++ /dev/null @@ -1,248 +0,0 @@ -AWSTemplateFormatVersion: '2010-09-09' -Transform: 'AWS::Serverless-2016-10-31' -Description: SAM template to create file processing architecture represented at TBD. - -Resources: - InputBucket: - Type: AWS::S3::Bucket - - CloudTrailBucket: - Type: AWS::S3::Bucket - - InputBucketTrail: - DependsOn: CloudTrailBucketPolicy - Type: AWS::CloudTrail::Trail - Properties: - S3BucketName: !Ref CloudTrailBucket - EventSelectors: - - DataResources: - - Type: 'AWS::S3::Object' - Values: - - !Sub |- - arn:aws:s3:::${InputBucket}/ - IncludeManagementEvents: false - ReadWriteType: WriteOnly - IsLogging: true - - CloudTrailBucketPolicy: - Type: AWS::S3::BucketPolicy - DependsOn: CloudTrailBucket - Properties: - Bucket: !Ref CloudTrailBucket - PolicyDocument: - Version: "2012-10-17" - Statement: - - - Sid: "AWSCloudTrailAclCheck" - Effect: "Allow" - Principal: - Service: "cloudtrail.amazonaws.com" - Action: "s3:GetBucketAcl" - Resource: !Sub |- - arn:aws:s3:::${CloudTrailBucket} - - - Sid: "AWSCloudTrailWrite" - Effect: "Allow" - Principal: - Service: "cloudtrail.amazonaws.com" - Action: "s3:PutObject" - Resource: - !Sub |- - arn:aws:s3:::${CloudTrailBucket}/AWSLogs/${AWS::AccountId}/* - Condition: - StringEquals: - s3:x-amz-acl: "bucket-owner-full-control" - - FileProcessingQueuePolicy: - # https://forums.aws.amazon.com/message.jspa?messageID=743094 - Type: AWS::SQS::QueuePolicy - Properties: - Queues: - - !Ref ConversionQueue - - !Ref SentimentQueue - PolicyDocument: - Version: '2012-10-17' - Statement: - - - Effect: Allow - Principal: - AWS: '*' - Action: - - sqs:SendMessage - Resource: !GetAtt ConversionQueue.Arn - Condition: - ArnEquals: - aws:SourceArn: !GetAtt FileProcessingRule.Arn - - - Effect: Allow - Principal: - AWS: '*' - Action: - - sqs:SendMessage - Resource: !GetAtt SentimentQueue.Arn - Condition: - ArnEquals: - aws:SourceArn: !GetAtt FileProcessingRule.Arn - - FileProcessingRule: - Type: AWS::Events::Rule - DependsOn: - - ConversionQueue - - SentimentQueue - Properties: - Description: Rule to capture S3 PutObject events - EventPattern: - source: - - aws.s3 - detail-type: - - AWS API Call via CloudTrail - detail: - eventSource: - - s3.amazonaws.com - eventName: - - PutObject - requestParameters: - bucketName: - - !Ref InputBucket - State: 'ENABLED' - Targets: - - Arn: !GetAtt ConversionQueue.Arn - Id: Convert - - Arn: !GetAtt SentimentQueue.Arn - Id: Sentiment - - ConversionQueue: - Type: AWS::SQS::Queue - DependsOn: ConversionDlq - Properties: - VisibilityTimeout: 300 - RedrivePolicy: - deadLetterTargetArn: !GetAtt ConversionDlq.Arn - maxReceiveCount: 5 - - ConversionDlq: - Type: AWS::SQS::Queue - Properties: - VisibilityTimeout: 300 - - ConversionFunction: - Type: 'AWS::Serverless::Function' - DependsOn: ConversionTargetBucket - Properties: - Handler: conversion.handler - Runtime: python3.6 - CodeUri: ./src/conversion/ - Policies: - - SQSPollerPolicy: - QueueName: - !GetAtt ConversionQueue.Arn - - Version: '2012-10-17' - Statement: - - Effect: Allow - Action: - - s3:GetObject - - s3:GetObjectAcl - - s3:GetObjectVersion - Resource: - Fn::Join: - - '' - - - 'arn:aws:s3:::' - - Ref: InputBucket - - '/*' - - Effect: Allow - Action: - - s3:ListBucket - Resource: !GetAtt InputBucket.Arn - - Version: '2012-10-17' - Statement: - - Effect: Allow - Action: s3:PutObject - Resource: - Fn::Join: - - '' - - - 'arn:aws:s3:::' - - Ref: ConversionTargetBucket - - '/*' - Environment: - Variables: - TARGET_BUCKET: !Ref ConversionTargetBucket - Events: - ConversionQueueReaderEvent: - Type: SQS - Properties: - Queue: !GetAtt ConversionQueue.Arn - BatchSize: 10 - - ConversionTargetBucket: - Type: AWS::S3::Bucket - - SentimentQueue: - Type: AWS::SQS::Queue - DependsOn: SentimentDlq - Properties: - VisibilityTimeout: 300 - RedrivePolicy: - deadLetterTargetArn: !GetAtt SentimentDlq.Arn - maxReceiveCount: 5 - - SentimentDlq: - Type: AWS::SQS::Queue - Properties: - VisibilityTimeout: 300 - - SentimentFunction: - Type: 'AWS::Serverless::Function' - Properties: - Handler: sentiment.handler - Runtime: python3.6 - CodeUri: ./src/sentiment/ - Policies: - - SQSPollerPolicy: - QueueName: - !GetAtt SentimentQueue.Arn - - Version: '2012-10-17' - Statement: - - Effect: Allow - Action: - - s3:GetObject - - s3:GetObjectAcl - - s3:GetObjectVersion - Resource: - Fn::Join: - - '' - - - 'arn:aws:s3:::' - - Ref: InputBucket - - '/*' - - Effect: Allow - Action: - - s3:ListBucket - Resource: !GetAtt InputBucket.Arn - - Version: '2012-10-17' - Statement: - - Effect: Allow - Action: - - comprehend:DetectSentiment - Resource: '*' - - Version: '2012-10-17' - Statement: - - Effect: Allow - Action: - - dynamodb:PutItem - Resource: !GetAtt SentimentTable.Arn - Environment: - Variables: - SENTIMENT_TABLE: !Ref SentimentTable - Events: - SentimentQueueReaderEvent: - Type: SQS - Properties: - Queue: !GetAtt SentimentQueue.Arn - BatchSize: 10 - - SentimentTable: - Type: AWS::Serverless::SimpleTable - TableName: ref-arch-filearch-document-sentiment - PrimaryKey: - Name: 's3_object' - Type: String - \ No newline at end of file diff --git a/lambda_file_processing.template b/lambda_file_processing.template deleted file mode 100644 index dac389a..0000000 --- a/lambda_file_processing.template +++ /dev/null @@ -1,258 +0,0 @@ -{ - "AWSTemplateFormatVersion": "2010-09-09", - "Description": "CFN template to create architecture represented at https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/.", - "Parameters": { - "CodeBucket": { - "Description": "S3 Bucket containing Lambda deployment packages and sub-stack templates", - "Type": "String", - "Default" : "awslambda-reference-architectures" - }, - "CodeKeyPrefix": { - "Description": "The key prefix for all deployment packages and sub-stack templates within CodeBucket", - "Type": "String", - "Default" : "file-processing" - } - }, - "Resources": { - "InputBucket": { - "Type": "AWS::S3::Bucket", - "Properties": { - "BucketName": {"Fn::Join" : ["-", [{"Ref" : "AWS::StackName"}, {"Ref" : "AWS::AccountId"}, "files"]]}, - "NotificationConfiguration": { - "TopicConfigurations": [ - { - "Event": "s3:ObjectCreated:*", - "Topic": { "Ref" : "InputNotificationTopic" } - } - ] - } - }, - "DependsOn": "NotificationPolicy" - }, - "OutputBucket": { - "Type": "AWS::S3::Bucket", - "Properties": { - "BucketName": {"Fn::Join" : ["-", [{"Ref" : "InputBucket"}, "out"]]} - } - }, - "InputNotificationTopic": { - "Type": "AWS::SNS::Topic", - "Properties": { - "Subscription": [ - { - "Endpoint": { - "Fn::GetAtt": [ - "ProcessorFunctionOne", - "Arn" - ] - }, - "Protocol": "lambda" - }, - { - "Endpoint": { - "Fn::GetAtt": [ - "ProcessorFunctionTwo", - "Arn" - ] - }, - "Protocol": "lambda" - } - ] - } - }, - "NotificationPolicy": { - "Type": "AWS::SNS::TopicPolicy", - "Properties": { - "PolicyDocument": { - "Id": "PushBucketNotificationPolicy", - "Version": "2012-10-17", - "Statement": [ - { - "Sid": "AllowBucketToPushNotificationEffect", - "Effect": "Allow", - "Principal": { - "Service": "s3.amazonaws.com" - }, - "Action": "sns:Publish", - "Resource": { - "Ref": "InputNotificationTopic" - }, - "Condition": { - "ArnLike": { - "aws:SourceArn": { - "Fn::Join": [ - "", - [ - "arn:aws:s3:*:*:", - {"Fn::Join" : ["-", [{"Ref" : "AWS::StackName"}, {"Ref" : "AWS::AccountId"}, "files"]]} - ] - ] - } - } - } - } - ] - }, - "Topics": [ - { - "Ref": "InputNotificationTopic" - } - ] - } - }, - "ProcessorFunctionOne": { - "Type": "AWS::Lambda::Function", - "Properties": { - "Code": { - "S3Bucket": { "Ref": "CodeBucket" }, - "S3Key": {"Fn::Join" : ["/", [{"Ref": "CodeKeyPrefix"}, "data-processor-1.zip"]]} - }, - "Description": "Data Processor One", - "Handler": "data-processor-1.handler", - "Role": { - "Fn::GetAtt": [ - "LambdaExecutionRole", - "Arn" - ] - }, - "Runtime": "nodejs6.10", - "MemorySize": 128, - "Timeout": 3 - } - }, - "ProcessorFunctionTwo": { - "Type": "AWS::Lambda::Function", - "Properties": { - "Code": { - "S3Bucket": { "Ref": "CodeBucket" }, - "S3Key": {"Fn::Join" : ["/", [{"Ref": "CodeKeyPrefix"}, "data-processor-2.zip"]]} - }, - "Description": "Data Processor Two", - "Handler": "data-processor-2.handler", - "Role": { - "Fn::GetAtt": [ - "LambdaExecutionRole", - "Arn" - ] - }, - "Runtime": "nodejs6.10", - "MemorySize": 128, - "Timeout": 3 - } - }, - "LambdaExecutionRole": { - "Type": "AWS::IAM::Role", - "Properties": { - "AssumeRolePolicyDocument": { - "Version": "2012-10-17", - "Statement": [ - { - "Effect": "Allow", - "Principal": { - "Service": [ - "lambda.amazonaws.com" - ] - }, - "Action": [ - "sts:AssumeRole" - ] - } - ] - }, - "Path": "/" - } - }, - "RolePolicy": { - "Type": "AWS::IAM::Policy", - "Properties": { - "PolicyName": "root", - "PolicyDocument": { - "Version": "2012-10-17", - "Statement": [ - { - "Effect": "Allow", - "Action": [ - "logs:CreateLogGroup", - "logs:CreateLogStream", - "logs:PutLogEvents" - ], - "Resource": "arn:aws:logs:*:*:*" - }, - { - "Effect": "Allow", - "Action": [ - "s3:GetObject" - ], - "Resource": { "Fn::Join": ["", ["arn:aws:s3:::", { "Ref" : "InputBucket" }, "/*"]]} - }, - { - "Effect": "Allow", - "Action": [ - "s3:PutObject" - ], - "Resource": { "Fn::Join": ["", ["arn:aws:s3:::", { "Ref" : "OutputBucket" }, "/*"]]} - } - ] - }, - "Roles": [ - { - "Ref": "LambdaExecutionRole" - } - ] - } - }, - - "LambdaInvokePermissionOne": { - "Type": "AWS::Lambda::Permission", - "Properties": { - "FunctionName" : { "Fn::GetAtt" : ["ProcessorFunctionOne", "Arn"] }, - "Action": "lambda:InvokeFunction", - "Principal": "sns.amazonaws.com", - "SourceArn" : { "Ref" : "InputNotificationTopic" } - } - }, - - - "LambdaInvokePermissionTwo": { - "Type": "AWS::Lambda::Permission", - "Properties": { - "FunctionName" : { "Fn::GetAtt" : ["ProcessorFunctionTwo", "Arn"] }, - "Action": "lambda:InvokeFunction", - "Principal": "sns.amazonaws.com", - "SourceArn" : { "Ref" : "InputNotificationTopic" } - } - } - }, - "Outputs": { - "Bucket": { - "Description": "Storage location for data which is to be processed by Lambda functions", - "Value": { - "Ref": "InputBucket" - } - }, - "BucketOut": { - "Description": "Storage location for data which is to be processed by Lambda functions", - "Value": { - "Ref": "OutputBucket" - } - }, - "Topic": { - "Description": "SNS topic to fanout S3 Event notifications to Lambda functions", - "Value": { - "Ref": "InputNotificationTopic" - } - }, - "ProcessorFxOne": { - "Description": "Lambda function receiving SNS messages of S3 events", - "Value": { - "Ref": "ProcessorFunctionOne" - } - }, - "ProcessorFxTwo": { - "Description": "Lambda function receiving SNS messages of S3 events", - "Value": { - "Ref": "ProcessorFunctionTwo" - } - } - } -} diff --git a/lambda_file_processing.yml b/lambda_file_processing.yml deleted file mode 100644 index ca656d7..0000000 --- a/lambda_file_processing.yml +++ /dev/null @@ -1,131 +0,0 @@ -AWSTemplateFormatVersion: '2010-09-09' -Transform: 'AWS::Serverless-2016-10-31' -Description: CFN template to create architecture represented at https://aws.amazon.com/blogs/compute/fanout-s3-event-notifications-to-multiple-endpoints/. -Resources: - ProcessorFunctionOne: - Type: 'AWS::Serverless::Function' - Properties: - Handler: data-processor-1.handler - Runtime: nodejs6.10 - CodeUri: ./src/data-processor-1/ - Role: !GetAtt [LambdaExecutionRole, Arn] - - ProcessorFunctionTwo: - Type: 'AWS::Serverless::Function' - Properties: - Handler: data-processor-2.handler - Runtime: nodejs6.10 - CodeUri: ./src/data-processor-2/ - Role: !GetAtt [LambdaExecutionRole, Arn] - - InputBucket: - Type: AWS::S3::Bucket - Properties: - BucketName: !Join ['-', [!Ref 'AWS::StackName', !Ref 'AWS::AccountId', files]] - NotificationConfiguration: - TopicConfigurations: - - Event: s3:ObjectCreated:* - Topic: !Ref 'InputNotificationTopic' - DependsOn: NotificationPolicy - OutputBucket: - Type: AWS::S3::Bucket - Properties: - BucketName: !Join ['-', [!Ref 'InputBucket', out]] - InputNotificationTopic: - Type: AWS::SNS::Topic - Properties: - Subscription: - - Endpoint: !GetAtt [ProcessorFunctionOne, Arn] - Protocol: lambda - - Endpoint: !GetAtt [ProcessorFunctionTwo, Arn] - Protocol: lambda - NotificationPolicy: - Type: AWS::SNS::TopicPolicy - Properties: - PolicyDocument: - Id: PushBucketNotificationPolicy - Version: '2012-10-17' - Statement: - - Sid: AllowBucketToPushNotificationEffect - Effect: Allow - Principal: - Service: s3.amazonaws.com - Action: sns:Publish - Resource: !Ref 'InputNotificationTopic' - Condition: - ArnLike: - aws:SourceArn: !Join ['', ['arn:aws:s3:*:*:', !Join ['-', [!Ref 'AWS::StackName', - !Ref 'AWS::AccountId', files]]]] - Topics: - - !Ref 'InputNotificationTopic' - LambdaExecutionRole: - Type: AWS::IAM::Role - Properties: - AssumeRolePolicyDocument: - Version: '2012-10-17' - Statement: - - Effect: Allow - Principal: - Service: - - lambda.amazonaws.com - Action: - - sts:AssumeRole - Path: / - RolePolicy: - Type: AWS::IAM::Policy - Properties: - PolicyName: root - PolicyDocument: - Version: '2012-10-17' - Statement: - - Effect: Allow - Action: - - logs:CreateLogGroup - - logs:CreateLogStream - - logs:PutLogEvents - Resource: arn:aws:logs:*:*:* - - Effect: Allow - Action: - - s3:GetObject - Resource: !Join ['', ['arn:aws:s3:::', !Ref 'InputBucket', /*]] - - Effect: Allow - Action: - - s3:PutObject - Resource: !Join ['', ['arn:aws:s3:::', !Ref 'OutputBucket', /*]] - Roles: - - !Ref 'LambdaExecutionRole' - LambdaInvokePermissionOne: - Type: AWS::Lambda::Permission - Properties: - FunctionName: !GetAtt [ProcessorFunctionOne, Arn] - Action: lambda:InvokeFunction - Principal: sns.amazonaws.com - SourceArn: !Ref 'InputNotificationTopic' - LambdaInvokePermissionTwo: - Type: AWS::Lambda::Permission - Properties: - FunctionName: !GetAtt [ProcessorFunctionTwo, Arn] - Action: lambda:InvokeFunction - Principal: sns.amazonaws.com - SourceArn: !Ref 'InputNotificationTopic' -Outputs: - Bucket: - Description: Storage location for data which is to be processed by Lambda functions - Value: !Ref 'InputBucket' - BucketOut: - Description: Storage location for data which is to be processed by Lambda functions - Value: !Ref 'OutputBucket' - Topic: - Description: SNS topic to fanout S3 Event notifications to Lambda functions - Value: !Ref 'InputNotificationTopic' - ProcessorFnOne: - Description: Lambda function receiving SNS messages of S3 events - Value: !Ref 'ProcessorFunctionOne' - ProcessorFnTwo: - Description: Lambda function receiving SNS messages of S3 events - Value: !Ref 'ProcessorFunctionTwo' - - - - - \ No newline at end of file diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 5a53997..b63cd37 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -80,6 +80,12 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) + if size >= max_object_size: + log_event['source_s3_object_size'] = size + log_event['error_msg'] = 'source s3 object too large' + print(log_event) + return 'fail' + local_file = os.path.join(tmpdir, key_name) download_status = get_s3_object(bucket_name, key_name, local_file) diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index a73ff99..b8be50e 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -1,22 +1,41 @@ +from datetime import datetime import json import os import sys +import tempfile import boto3 import botocore +max_object_size = 104857600 # 100MB = 104857600 bytes + +sentiment_table = os.getenv('SENTIMENT_TABLE') +sentiment_queue = os.getenv('SENTIMENT_QUEUE') + comprehend_client = boto3.client('comprehend') s3_resource = boto3.resource('s3') -ddb_client = boto3.client('dynamodb') +dynamodb_resource = boto3.resource('dynamodb') +table = dynamodb_resource.Table(sentiment_table) + +sqs_client = boto3.client('sqs') + + +def check_s3_object_size(bucket, key_name): + try: + size = s3_resource.Object(bucket, key_name).content_length + except Exception as e: + print('Error: {}'.format(str(e))) + size = 'NaN' + + return size -sentiment_table = os.getenv('SENTIMENT_TABLE') -def get_s3_object(bucket, key_name): +def get_s3_object(bucket, key_name, local_file): try: - s3_resource.Bucket(bucket).download_file(key_name, '/tmp/{}'.format(key_name)) + s3_resource.Bucket(bucket).download_file(key_name, local_file) return 'ok' except botocore.exceptions.ClientError as e: if e.response['Error']['Code'] == '404': @@ -24,25 +43,33 @@ def get_s3_object(bucket, key_name): else: return 'Error: {}'.format(str(e)) -def put_sentiment(table_name, s3_object, sentiment): + +def put_sentiment(s3_object, sentiment): try: - result = ddb_client.put_item( - TableName=table_name, + response = table.put_item( Item={ - 'id': { - 'S': s3_object - }, - 'sentiment': { - 'S': sentiment['Sentiment'] - } + 'id': s3_object, + 'last_modified': datetime.utcnow().isoformat(), + 'overall_sentiment': sentiment['Sentiment'], + 'positive': str(sentiment['SentimentScore']['Positive']), + 'negative': str(sentiment['SentimentScore']['Negative']), + 'neutral': str(sentiment['SentimentScore']['Neutral']), + 'mixed': str(sentiment['SentimentScore']['Mixed']) } ) + + result = 'ok' + except Exception as e: - print('Error: {}'.format(str(e))) + result = str(e) + + return result def handler(event, context): for record in event['Records']: + tmpdir = tempfile.mkdtemp() + log_event = {} log_event['request_id'] = context.aws_request_id @@ -50,6 +77,8 @@ def handler(event, context): log_event['sqs_message_id'] = record['messageId'] log_event['sqs_event_source_arn'] = record['eventSourceARN'] + sqs_receipt_handle = record['receiptHandle'] + try: json_body = json.loads(record['body']) request_params = json_body['detail']['requestParameters'] @@ -58,9 +87,17 @@ def handler(event, context): log_event['source_s3_bucket_name'] = bucket_name log_event['source_s3_key_name'] = key_name - download_status = get_s3_object(bucket_name, key_name) + size = check_s3_object_size(bucket_name, key_name) - local_file = '/tmp/{}'.format(key_name) + if size >= max_object_size: + log_event['source_s3_object_size'] = size + log_event['error_msg'] = 'source s3 object too large' + print(log_event) + return 'fail' + + local_file = os.path.join(tmpdir, key_name) + + download_status = get_s3_object(bucket_name, key_name, local_file) if download_status == 'ok': log_event['src_s3_download'] = 'ok' @@ -70,26 +107,54 @@ def handler(event, context): log_event['src_s3_download'] = download_status log_event['src_s3_download_bytes'] = -1 sys.exit(1) - + md_contents = open(local_file, 'r').read() - sentiment = comprehend_client.detect_sentiment(Text=md_contents, LanguageCode='en') + sentiment = comprehend_client.detect_sentiment( + Text=md_contents, + LanguageCode='en' + ) log_event['sentiment'] = sentiment['Sentiment'] log_event['sentiment_score'] = sentiment['SentimentScore'] source_s3_object = 's3://{}/{}'.format(bucket_name, key_name) - - put_sentiment_result = put_sentiment(sentiment_table, source_s3_object, sentiment) + + put_sentiment_result = put_sentiment(source_s3_object, sentiment) + + if put_sentiment_result == 'ok': + '''If function could put the sentiment to the DDB table then remove message + from SQS queue.''' + try: + sqs_client.delete_message( + QueueUrl=sentiment_queue, + ReceiptHandle=sqs_receipt_handle + ) + except Exception as e: + print('Error: {}'.str(e)) print(put_sentiment_result) - + except Exception as e: log_event['error_msg'] = str(e) print(log_event) return 'fail' + finally: + filesToRemove = os.listdir(tmpdir) + + for f in filesToRemove: + file_path = os.path.join(tmpdir, f) + print(f'Removing File: {file_path}') + + try: + os.remove(file_path) + except OSError as e: + print(e) + print(f'Error while deleting file {file_path}') + + print(f'Removing Folder: {tmpdir}') + os.rmdir(tmpdir) print(log_event) return('ok') - From 8202eebbbc4cc81df1750452b63761052fc990ad Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Tue, 12 Nov 2019 16:23:32 -0500 Subject: [PATCH 032/115] Update to logging --- README.md | 3 +- src/conversion/conversion.py | 76 +++++--- src/conversion/requirements.txt | 1 + src/sentiment/requirements.txt | 1 + src/sentiment/sentiment.py | 55 +++--- template.yml | 302 ++++++++++++++++++++++++++++++++ 6 files changed, 387 insertions(+), 51 deletions(-) create mode 100644 template.yml diff --git a/README.md b/README.md index 79a6649..4a87bb4 100644 --- a/README.md +++ b/README.md @@ -65,7 +65,7 @@ Next, run *sam package*. This command takes your Lambda handler source code and ```bash sam package \ --output-template-file packaged-template.yml \ - --s3-bucket bucketname + --s3-bucket bucketname ``` **Note** @@ -89,6 +89,7 @@ sam deploy \ --template-file packaged-template.yml \ --stack-name lambda-file-refarch \ --region region \ + --tags Project=lambda-refarch-fileprocessing --capabilities CAPABILITY_IAM ``` diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index b63cd37..bf07ad7 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -1,18 +1,29 @@ import json +import logging import os import sys +import aws_lambda_logging import boto3 import botocore import markdown import tempfile + max_object_size = 104857600 # 100MB = 104857600 bytes +conversion_queue = os.getenv('CONVERSION_QUEUE') + target_bucket = os.getenv('TARGET_BUCKET') +log_level = os.getenv('LOG_LEVEL') + s3_resource = boto3.resource('s3') +sqs_client = boto3.client('sqs') + +log = logging.getLogger() + def check_s3_object_size(bucket, key_name): try: @@ -60,44 +71,46 @@ def upload_html(target_bucket, target_key, source_file): def handler(event, context): + aws_lambda_logging.setup(level=log_level, + aws_request_id=context.aws_request_id) + for record in event['Records']: tmpdir = tempfile.mkdtemp() - log_event = {} + sqs_message_id = record['messageId'] + sqs_event_source_arn = record['eventSourceARN'] - log_event['request_id'] = context.aws_request_id - log_event['invoked_function_arn'] = context.invoked_function_arn - log_event['sqs_message_id'] = record['messageId'] - log_event['sqs_event_source_arn'] = record['eventSourceARN'] + sqs_receipt_handle = record['receiptHandle'] try: json_body = json.loads(record['body']) request_params = json_body['detail']['requestParameters'] bucket_name = request_params['bucketName'] key_name = request_params['key'] - log_event['source_s3_bucket_name'] = bucket_name - log_event['source_s3_key_name'] = key_name size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - log_event['source_s3_object_size'] = size - log_event['error_msg'] = 'source s3 object too large' - print(log_event) - return 'fail' + log.error('''Source S3 object s3://{}/{} is larger ({} bytes) + than {} max object bytes'''.format( + bucket_name, + key_name, + size, + max_object_size)) + raise Exception("Source S3 object too large") local_file = os.path.join(tmpdir, key_name) download_status = get_s3_object(bucket_name, key_name, local_file) if download_status == 'ok': - log_event['src_s3_download'] = 'ok' key_bytes = os.stat(local_file).st_size - log_event['src_s3_download_bytes'] = key_bytes + src_s3_download_bytes = key_bytes + log.info("Success: Download to {} for conversion".format( + local_file, + key_bytes)) else: - log_event['src_s3_download'] = download_status - log_event['src_s3_download_bytes'] = -1 - sys.exit(1) + raise Exception("Fail to put object to {}".format(local_file)) html = convert_to_html(local_file) @@ -107,24 +120,36 @@ def handler(event, context): with open(local_html_file, 'w') as outfile: outfile.write(html) - + log.info("Success: Converted s3://{}/{} to {}".format( + bucket_name, + key_name, + local_html_file)) outfile.close() html_upload = upload_html(target_bucket, html_filename, local_html_file) - if html_upload == 'ok': - log_event['dst_s3_object'] = 's3://{}/{}'.format(target_bucket, - html_filename) + '''If function could put the converted file to the S3 bucket then + remove message from the SQS queue''' + try: + sqs_client.delete_message( + QueueUrl=conversion_queue, + ReceiptHandle=sqs_receipt_handle + ) + except Exception as e: + raise Exception(str(e)) + dst_s3_object = 's3://{}/{}'.format(target_bucket, + html_filename) + log.info("Success: Uploaded {} to {}".format( + local_html_file, + dst_s3_object + )) else: - log_event['dst_s3_object'] = '' - - log_event['dst_s3_upload'] = html_upload + raise Exception("Error: {}".format(str(e))) except Exception as e: - log_event['error_msg'] = str(e) - print(log_event) + raise Exception("Could not convert record: {}".format(str(e))) return 'fail' finally: @@ -143,5 +168,4 @@ def handler(event, context): print(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) - print(log_event) return 'ok' diff --git a/src/conversion/requirements.txt b/src/conversion/requirements.txt index 158fba1..5a75021 100644 --- a/src/conversion/requirements.txt +++ b/src/conversion/requirements.txt @@ -1,2 +1,3 @@ +aws-lambda-logging boto3 markdown \ No newline at end of file diff --git a/src/sentiment/requirements.txt b/src/sentiment/requirements.txt index 1db657b..9445505 100644 --- a/src/sentiment/requirements.txt +++ b/src/sentiment/requirements.txt @@ -1 +1,2 @@ +aws-lambda-logging boto3 \ No newline at end of file diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index b8be50e..5805aae 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -1,9 +1,11 @@ from datetime import datetime import json +import logging import os import sys import tempfile +import aws_lambda_logging import boto3 import botocore @@ -13,6 +15,8 @@ sentiment_table = os.getenv('SENTIMENT_TABLE') sentiment_queue = os.getenv('SENTIMENT_QUEUE') +log_level = os.getenv('LOG_LEVEL') + comprehend_client = boto3.client('comprehend') s3_resource = boto3.resource('s3') @@ -22,6 +26,8 @@ sqs_client = boto3.client('sqs') +log = logging.getLogger() + def check_s3_object_size(bucket, key_name): try: @@ -67,15 +73,14 @@ def put_sentiment(s3_object, sentiment): def handler(event, context): + aws_lambda_logging.setup(level=log_level, + aws_request_id=context.aws_request_id) + for record in event['Records']: tmpdir = tempfile.mkdtemp() - log_event = {} - - log_event['request_id'] = context.aws_request_id - log_event['invoked_function_arn'] = context.invoked_function_arn - log_event['sqs_message_id'] = record['messageId'] - log_event['sqs_event_source_arn'] = record['eventSourceARN'] + sqs_message_id = record['messageId'] + sqs_event_source_arn = record['eventSourceARN'] sqs_receipt_handle = record['receiptHandle'] @@ -84,29 +89,30 @@ def handler(event, context): request_params = json_body['detail']['requestParameters'] bucket_name = request_params['bucketName'] key_name = request_params['key'] - log_event['source_s3_bucket_name'] = bucket_name - log_event['source_s3_key_name'] = key_name size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - log_event['source_s3_object_size'] = size - log_event['error_msg'] = 'source s3 object too large' - print(log_event) - return 'fail' + log.error('''Source S3 object s3://{}/{} is larger ({} bytes) + than {} max object bytes'''.format( + bucket_name, + key_name, + size, + max_object_size)) + raise Exception("Source S3 object too large") local_file = os.path.join(tmpdir, key_name) download_status = get_s3_object(bucket_name, key_name, local_file) if download_status == 'ok': - log_event['src_s3_download'] = 'ok' key_bytes = os.stat(local_file).st_size - log_event['src_s3_download_bytes'] = key_bytes + src_s3_download_bytes = key_bytes + log.info('''Download to {} for sentiment analysis'''.format( + local_file + )) else: - log_event['src_s3_download'] = download_status - log_event['src_s3_download_bytes'] = -1 - sys.exit(1) + raise Exception("Download failure to {}".format(local_file)) md_contents = open(local_file, 'r').read() @@ -115,8 +121,10 @@ def handler(event, context): LanguageCode='en' ) - log_event['sentiment'] = sentiment['Sentiment'] - log_event['sentiment_score'] = sentiment['SentimentScore'] + log.info('Overall sentiment: {} ({})'.format( + sentiment['Sentiment'], + sentiment['SentimentScore'] + )) source_s3_object = 's3://{}/{}'.format(bucket_name, key_name) @@ -131,13 +139,13 @@ def handler(event, context): ReceiptHandle=sqs_receipt_handle ) except Exception as e: - print('Error: {}'.str(e)) + raise Exception(str(e)) - print(put_sentiment_result) + log.info('Put sentiment of {} to table {}'.format( + local_file, sentiment_table)) except Exception as e: - log_event['error_msg'] = str(e) - print(log_event) + raise Exception("Could not get sentiment: {}".format(str(e))) return 'fail' finally: @@ -156,5 +164,4 @@ def handler(event, context): print(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) - print(log_event) return('ok') diff --git a/template.yml b/template.yml new file mode 100644 index 0000000..6d7e47d --- /dev/null +++ b/template.yml @@ -0,0 +1,302 @@ +AWSTemplateFormatVersion: '2010-09-09' +Transform: 'AWS::Serverless-2016-10-31' +Description: SAM template to create file processing architecture represented at https://github.com/aws-samples/lambda-refarch-fileprocessing. + +Parameters: + ConversionLogLevel: + Type: String + Default: "INFO" + AllowedValues: + - "INFO" + - "DEBUG" + + SentimentLogLevel: + Type: String + Default: "INFO" + AllowedValues: + - "INFO" + - "DEBUG" + +Resources: + InputBucket: + Type: AWS::S3::Bucket + + CloudTrailBucket: + Type: AWS::S3::Bucket + + InputBucketTrail: + DependsOn: CloudTrailBucketPolicy + Type: AWS::CloudTrail::Trail + Properties: + S3BucketName: !Ref CloudTrailBucket + EventSelectors: + - DataResources: + - Type: 'AWS::S3::Object' + Values: + - !Sub |- + arn:aws:s3:::${InputBucket}/ + IncludeManagementEvents: false + ReadWriteType: WriteOnly + IsLogging: true + + CloudTrailBucketPolicy: + Type: AWS::S3::BucketPolicy + DependsOn: CloudTrailBucket + Properties: + Bucket: !Ref CloudTrailBucket + PolicyDocument: + Version: "2012-10-17" + Statement: + - + Sid: "AWSCloudTrailAclCheck" + Effect: "Allow" + Principal: + Service: "cloudtrail.amazonaws.com" + Action: "s3:GetBucketAcl" + Resource: !Sub |- + arn:aws:s3:::${CloudTrailBucket} + - + Sid: "AWSCloudTrailWrite" + Effect: "Allow" + Principal: + Service: "cloudtrail.amazonaws.com" + Action: "s3:PutObject" + Resource: + !Sub |- + arn:aws:s3:::${CloudTrailBucket}/AWSLogs/${AWS::AccountId}/* + Condition: + StringEquals: + s3:x-amz-acl: "bucket-owner-full-control" + + FileProcessingQueuePolicy: + # https://forums.aws.amazon.com/message.jspa?messageID=743094 + Type: AWS::SQS::QueuePolicy + Properties: + Queues: + - !Ref ConversionQueue + - !Ref SentimentQueue + - !Ref ReplayQueue + PolicyDocument: + Version: '2012-10-17' + Statement: + - + Effect: Allow + Principal: + AWS: '*' + Action: + - sqs:SendMessage + Resource: !GetAtt ConversionQueue.Arn + Condition: + ArnEquals: + aws:SourceArn: !GetAtt FileProcessingRule.Arn + - + Effect: Allow + Principal: + AWS: '*' + Action: + - sqs:SendMessage + Resource: !GetAtt SentimentQueue.Arn + Condition: + ArnEquals: + aws:SourceArn: !GetAtt FileProcessingRule.Arn + - + Effect: Allow + Principal: + AWS: '*' + Action: + - sqs:SendMessage + Resource: !GetAtt ReplayQueue.Arn + Condition: + ArnEquals: + aws:SourceArn: !GetAtt FileProcessingRule.Arn + + FileProcessingRule: + Type: AWS::Events::Rule + DependsOn: + - ConversionQueue + - SentimentQueue + - ReplayQueue + Properties: + Description: Rule to capture S3 PutObject events + EventPattern: + source: + - aws.s3 + detail-type: + - AWS API Call via CloudTrail + detail: + eventSource: + - s3.amazonaws.com + eventName: + - PutObject + requestParameters: + bucketName: + - !Ref InputBucket + State: 'ENABLED' + Targets: + - Arn: !GetAtt ConversionQueue.Arn + Id: Convert + - Arn: !GetAtt SentimentQueue.Arn + Id: Sentiment + - Arn: !GetAtt ReplayQueue.Arn + Id: Replay + + ConversionQueue: + Type: AWS::SQS::Queue + DependsOn: ConversionDlq + Properties: + VisibilityTimeout: 300 + RedrivePolicy: + deadLetterTargetArn: !GetAtt ConversionDlq.Arn + maxReceiveCount: 5 + + ConversionDlq: + Type: AWS::SQS::Queue + Properties: + VisibilityTimeout: 300 + + ConversionFunction: + Type: 'AWS::Serverless::Function' + DependsOn: ConversionTargetBucket + Properties: + Description: Convert and store HTML representation of uploaded S3 objects + Handler: conversion.handler + Runtime: python3.6 + CodeUri: ./src/conversion/ + Policies: + - SQSPollerPolicy: + QueueName: + !GetAtt ConversionQueue.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - s3:GetObject + - s3:GetObjectAcl + - s3:GetObjectVersion + Resource: + Fn::Join: + - '' + - - 'arn:aws:s3:::' + - Ref: InputBucket + - '/*' + - Effect: Allow + Action: + - s3:ListBucket + Resource: !GetAtt InputBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: s3:PutObject + Resource: + Fn::Join: + - '' + - - 'arn:aws:s3:::' + - Ref: ConversionTargetBucket + - '/*' + Environment: + Variables: + TARGET_BUCKET: !Ref ConversionTargetBucket + CONVERSION_QUEUE: !Ref ConversionQueue + LOG_LEVEL: !Ref ConversionLogLevel + Events: + ConversionQueueReaderEvent: + Type: SQS + Properties: + Queue: !GetAtt ConversionQueue.Arn + BatchSize: 10 + + ConversionTargetBucket: + Type: AWS::S3::Bucket + + SentimentQueue: + Type: AWS::SQS::Queue + DependsOn: SentimentDlq + Properties: + VisibilityTimeout: 300 + RedrivePolicy: + deadLetterTargetArn: !GetAtt SentimentDlq.Arn + maxReceiveCount: 5 + + SentimentDlq: + Type: AWS::SQS::Queue + Properties: + VisibilityTimeout: 300 + + SentimentFunction: + Type: 'AWS::Serverless::Function' + Properties: + Description: Detect and store sentiment from uploaded S3 objects + Handler: sentiment.handler + Runtime: python3.6 + CodeUri: ./src/sentiment/ + Policies: + - SQSPollerPolicy: + QueueName: + !GetAtt SentimentQueue.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - s3:GetObject + - s3:GetObjectAcl + - s3:GetObjectVersion + Resource: + Fn::Join: + - '' + - - 'arn:aws:s3:::' + - Ref: InputBucket + - '/*' + - Effect: Allow + Action: + - s3:ListBucket + Resource: !GetAtt InputBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - comprehend:DetectSentiment + Resource: '*' + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - dynamodb:PutItem + Resource: !GetAtt SentimentTable.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - sqs:DeleteMessage + Resource: !GetAtt SentimentQueue.Arn + Environment: + Variables: + SENTIMENT_TABLE: !Ref SentimentTable + SENTIMENT_QUEUE: !Ref SentimentQueue + LOG_LEVEL: !Ref SentimentLogLevel + Events: + SentimentQueueReaderEvent: + Type: SQS + Properties: + Queue: !GetAtt SentimentQueue.Arn + BatchSize: 10 + + SentimentTable: + Type: AWS::Serverless::SimpleTable + TableName: ref-arch-filearch-document-sentiment + PrimaryKey: + Name: 's3_object' + Type: String + + ReplayQueue: + Type: AWS::SQS::Queue + DependsOn: ReplayDlq + Properties: + VisibilityTimeout: 300 + RedrivePolicy: + deadLetterTargetArn: !GetAtt ReplayDlq.Arn + maxReceiveCount: 5 + + ReplayDlq: + Type: AWS::SQS::Queue + Properties: + VisibilityTimeout: 300 From 8bc9bcb46fc267e9e0c74bd1d86a920828e0c341 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 13 Nov 2019 11:55:02 -0500 Subject: [PATCH 033/115] Update to use python3 f-strings --- src/conversion/conversion.py | 53 ++++++++++++++---------------------- src/sentiment/sentiment.py | 51 ++++++++++++++++------------------ 2 files changed, 43 insertions(+), 61 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index bf07ad7..63dfa5f 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -29,21 +29,21 @@ def check_s3_object_size(bucket, key_name): try: size = s3_resource.Object(bucket, key_name).content_length except Exception as e: - print('Error: {}'.format(str(e))) + print(f'Error: {str(e)}') size = 'NaN' - return size + return(size) def get_s3_object(bucket, key_name, local_file): try: s3_resource.Bucket(bucket).download_file(key_name, local_file) - return 'ok' + return('ok') except botocore.exceptions.ClientError as e: if e.response['Error']['Code'] == '404': - return 'Error: s3://{}/{} does not exist'.format(bucket, key_name) + return(f'Error: s3://{bucket}/{key_name} does not exist') else: - return 'Error: {}'.format(str(e)) + return(f'Error: {str(e)}') def convert_to_html(file): @@ -56,7 +56,7 @@ def convert_to_html(file): print('Error: {}'.format(str(e))) raise - return markdown.markdown(file_string) + return(markdown.markdown(file_string)) def upload_html(target_bucket, target_key, source_file): @@ -67,7 +67,7 @@ def upload_html(target_bucket, target_key, source_file): print('Error: {}'.format(str(e))) html_upload = 'fail' - return html_upload + return(html_upload) def handler(event, context): @@ -91,13 +91,9 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - log.error('''Source S3 object s3://{}/{} is larger ({} bytes) - than {} max object bytes'''.format( - bucket_name, - key_name, - size, - max_object_size)) - raise Exception("Source S3 object too large") + log.error(f'''Source S3 object s3://{bucket_name}/{key_name} is larger ({size} bytes) + than {max_object_size} (max object bytes)''') + raise Exception('Source S3 object too large') local_file = os.path.join(tmpdir, key_name) @@ -105,12 +101,9 @@ def handler(event, context): if download_status == 'ok': key_bytes = os.stat(local_file).st_size - src_s3_download_bytes = key_bytes - log.info("Success: Download to {} for conversion".format( - local_file, - key_bytes)) + log.info(f'Success: Download to {local_file} for conversion') else: - raise Exception("Fail to put object to {}".format(local_file)) + raise Exception(f'Fail to put object to {local_file}') html = convert_to_html(local_file) @@ -120,10 +113,8 @@ def handler(event, context): with open(local_html_file, 'w') as outfile: outfile.write(html) - log.info("Success: Converted s3://{}/{} to {}".format( - bucket_name, - key_name, - local_html_file)) + log.info(f'''Success: Converted s3://{bucket_name}/{key_name} + to {local_html_file}''') outfile.close() html_upload = upload_html(target_bucket, @@ -139,18 +130,14 @@ def handler(event, context): ) except Exception as e: raise Exception(str(e)) - dst_s3_object = 's3://{}/{}'.format(target_bucket, - html_filename) - log.info("Success: Uploaded {} to {}".format( - local_html_file, - dst_s3_object - )) + dst_s3_object = f's3://{target_bucket}/{html_filename}' + log.info(f'''Success: Uploaded {local_html_file} to + {dst_s3_object}''') else: - raise Exception("Error: {}".format(str(e))) + raise Exception(f'Error: {str(e)}') except Exception as e: - raise Exception("Could not convert record: {}".format(str(e))) - return 'fail' + raise Exception(f'Could not convert record: {str(e)}') finally: filesToRemove = os.listdir(tmpdir) @@ -168,4 +155,4 @@ def handler(event, context): print(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) - return 'ok' + return('ok') diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 5805aae..84b540f 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -33,21 +33,22 @@ def check_s3_object_size(bucket, key_name): try: size = s3_resource.Object(bucket, key_name).content_length except Exception as e: - print('Error: {}'.format(str(e))) + # print('Error: {}'.format(str(e))) + print(f'Error: {str(e)}') size = 'NaN' - return size + return(size) def get_s3_object(bucket, key_name, local_file): try: s3_resource.Bucket(bucket).download_file(key_name, local_file) - return 'ok' + return('ok') except botocore.exceptions.ClientError as e: if e.response['Error']['Code'] == '404': - return 'Error: s3://{}/{} does not exist'.format(bucket, key_name) + return(f'Error: s3://{bucket}/{key_name} does not exist') else: - return 'Error: {}'.format(str(e)) + return(f'Error: {str(e)}') def put_sentiment(s3_object, sentiment): @@ -69,7 +70,7 @@ def put_sentiment(s3_object, sentiment): except Exception as e: result = str(e) - return result + return(result) def handler(event, context): @@ -93,13 +94,9 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - log.error('''Source S3 object s3://{}/{} is larger ({} bytes) - than {} max object bytes'''.format( - bucket_name, - key_name, - size, - max_object_size)) - raise Exception("Source S3 object too large") + log.error(f'''Source S3 object s3://{bucket_name}/{key_name} is larger ({size} bytes) + than {max_object_size} (max object bytes)''') + raise Exception('Source S3 object too large') local_file = os.path.join(tmpdir, key_name) @@ -108,11 +105,9 @@ def handler(event, context): if download_status == 'ok': key_bytes = os.stat(local_file).st_size src_s3_download_bytes = key_bytes - log.info('''Download to {} for sentiment analysis'''.format( - local_file - )) + log.info(f'Download to {local_file} for sentiment analysis') else: - raise Exception("Download failure to {}".format(local_file)) + raise Exception(f'Download failure to {local_file}') md_contents = open(local_file, 'r').read() @@ -121,18 +116,19 @@ def handler(event, context): LanguageCode='en' ) - log.info('Overall sentiment: {} ({})'.format( - sentiment['Sentiment'], - sentiment['SentimentScore'] - )) + overall_sentiment = sentiment['Sentiment'] + sentiment_score = sentiment['SentimentScore'] + + log.info(f'''Overall sentiment: {overall_sentiment} + ({sentiment_score})''') - source_s3_object = 's3://{}/{}'.format(bucket_name, key_name) + source_s3_object = f's3://{bucket_name}/{key_name}' put_sentiment_result = put_sentiment(source_s3_object, sentiment) if put_sentiment_result == 'ok': - '''If function could put the sentiment to the DDB table then remove message - from SQS queue.''' + '''If function could put the sentiment to the DDB table then + remove message from SQS queue.''' try: sqs_client.delete_message( QueueUrl=sentiment_queue, @@ -141,12 +137,11 @@ def handler(event, context): except Exception as e: raise Exception(str(e)) - log.info('Put sentiment of {} to table {}'.format( - local_file, sentiment_table)) + log.info(f'''Put sentiment of {local_file} to + table {sentiment_table}''') except Exception as e: - raise Exception("Could not get sentiment: {}".format(str(e))) - return 'fail' + raise Exception(f'Could not get sentiment: {str(e)}') finally: filesToRemove = os.listdir(tmpdir) From 7f9052fac2a18b58c40f7dde5730283e8286e8e2 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Thu, 14 Nov 2019 09:28:16 -0500 Subject: [PATCH 034/115] Clean-up of .format string, add in additional error logging --- src/conversion/conversion.py | 10 +++++++--- src/sentiment/sentiment.py | 7 +++++-- 2 files changed, 12 insertions(+), 5 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 63dfa5f..11bd342 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -53,7 +53,7 @@ def convert_to_html(file): file_open.close() except Exception as e: - print('Error: {}'.format(str(e))) + print(f'Error: {str(e)}') raise return(markdown.markdown(file_string)) @@ -64,7 +64,7 @@ def upload_html(target_bucket, target_key, source_file): s3_resource.Object(target_bucket, target_key).upload_file(source_file) html_upload = 'ok' except Exception as e: - print('Error: {}'.format(str(e))) + print(f'Error: {str(e)}') html_upload = 'fail' return(html_upload) @@ -103,6 +103,7 @@ def handler(event, context): key_bytes = os.stat(local_file).st_size log.info(f'Success: Download to {local_file} for conversion') else: + log.error(f'Fail to put object to {local_file}') raise Exception(f'Fail to put object to {local_file}') html = convert_to_html(local_file) @@ -129,14 +130,17 @@ def handler(event, context): ReceiptHandle=sqs_receipt_handle ) except Exception as e: + log.error(f'{str(e)}') raise Exception(str(e)) dst_s3_object = f's3://{target_bucket}/{html_filename}' log.info(f'''Success: Uploaded {local_html_file} to {dst_s3_object}''') else: - raise Exception(f'Error: {str(e)}') + log.error(f'{str(e)}') + raise Exception(f'{str(e)}') except Exception as e: + log.error(f'Could not convert record: {str(e)}') raise Exception(f'Could not convert record: {str(e)}') finally: diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 84b540f..0507727 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -33,7 +33,6 @@ def check_s3_object_size(bucket, key_name): try: size = s3_resource.Object(bucket, key_name).content_length except Exception as e: - # print('Error: {}'.format(str(e))) print(f'Error: {str(e)}') size = 'NaN' @@ -107,6 +106,7 @@ def handler(event, context): src_s3_download_bytes = key_bytes log.info(f'Download to {local_file} for sentiment analysis') else: + log.error(f'Download failure to {local_file}') raise Exception(f'Download failure to {local_file}') md_contents = open(local_file, 'r').read() @@ -135,12 +135,15 @@ def handler(event, context): ReceiptHandle=sqs_receipt_handle ) except Exception as e: - raise Exception(str(e)) + log.error(f'Could not remove message from queue: {str(e)}') + raise Exception(f'''Could not remove message from queue: + {str(e)}''') log.info(f'''Put sentiment of {local_file} to table {sentiment_table}''') except Exception as e: + log.error(f'Could not get sentiment: {str(e)}') raise Exception(f'Could not get sentiment: {str(e)}') finally: From d471b5910e5f2588675c4bfd5afb85af8de6271e Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Fri, 15 Nov 2019 12:12:18 -0500 Subject: [PATCH 035/115] Use logging statements instead of print, fix return bug --- src/conversion/conversion.py | 13 ++++++------- src/sentiment/sentiment.py | 35 +++++++++++++++++++---------------- 2 files changed, 25 insertions(+), 23 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 11bd342..44ee45a 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -29,7 +29,7 @@ def check_s3_object_size(bucket, key_name): try: size = s3_resource.Object(bucket, key_name).content_length except Exception as e: - print(f'Error: {str(e)}') + log.error(f'Error: {str(e)}') size = 'NaN' return(size) @@ -53,7 +53,7 @@ def convert_to_html(file): file_open.close() except Exception as e: - print(f'Error: {str(e)}') + log.error(f'Could not open or read {file}: {str(e)}') raise return(markdown.markdown(file_string)) @@ -64,7 +64,7 @@ def upload_html(target_bucket, target_key, source_file): s3_resource.Object(target_bucket, target_key).upload_file(source_file) html_upload = 'ok' except Exception as e: - print(f'Error: {str(e)}') + log.error(f'Could not upload {source_file} to {target_bucket}: {str(e)}') html_upload = 'fail' return(html_upload) @@ -148,15 +148,14 @@ def handler(event, context): for f in filesToRemove: file_path = os.path.join(tmpdir, f) - print(f'Removing File: {file_path}') + log.info(f'Removing File: {file_path}') try: os.remove(file_path) except OSError as e: - print(e) - print(f'Error while deleting file {file_path}') + log.error(f'Could not delete file {file_path}: {str(e)}') - print(f'Removing Folder: {tmpdir}') + log.info(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) return('ok') diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 0507727..dd4f1f5 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -33,7 +33,7 @@ def check_s3_object_size(bucket, key_name): try: size = s3_resource.Object(bucket, key_name).content_length except Exception as e: - print(f'Error: {str(e)}') + log.error(f'Error: {str(e)}') size = 'NaN' return(size) @@ -93,9 +93,13 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - log.error(f'''Source S3 object s3://{bucket_name}/{key_name} is larger ({size} bytes) - than {max_object_size} (max object bytes)''') - raise Exception('Source S3 object too large') + max_err_msg = f'Source object is too large' + log.error(max_err_msg) + raise Exception(max_err_msg) + + if size == 'NaN': + exc = f'Could not get size for s3://{bucket_name}/{key_name}' + raise Exception(exc) local_file = os.path.join(tmpdir, key_name) @@ -119,8 +123,8 @@ def handler(event, context): overall_sentiment = sentiment['Sentiment'] sentiment_score = sentiment['SentimentScore'] - log.info(f'''Overall sentiment: {overall_sentiment} - ({sentiment_score})''') + sentiment_message = f'{overall_sentiment} ({sentiment_score})' + log.info(sentiment_message) source_s3_object = f's3://{bucket_name}/{key_name}' @@ -135,12 +139,12 @@ def handler(event, context): ReceiptHandle=sqs_receipt_handle ) except Exception as e: - log.error(f'Could not remove message from queue: {str(e)}') - raise Exception(f'''Could not remove message from queue: - {str(e)}''') + err_msg = f'Could not remove message from queue: {str(e)}' + log.error(err_msg) + raise Exception(err_msg) - log.info(f'''Put sentiment of {local_file} to - table {sentiment_table}''') + sentiment_db_msg = f'Put sentiment to {sentiment_table}' + log.info(sentiment_db_msg) except Exception as e: log.error(f'Could not get sentiment: {str(e)}') @@ -151,15 +155,14 @@ def handler(event, context): for f in filesToRemove: file_path = os.path.join(tmpdir, f) - print(f'Removing File: {file_path}') + log.info(f'Removing File: {file_path}') try: os.remove(file_path) except OSError as e: - print(e) - print(f'Error while deleting file {file_path}') + log.error(f'Could not delete file {file_path}: {str(e)}') - print(f'Removing Folder: {tmpdir}') + log.info(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) - return('ok') + return('ok') From ea4e04ac6b1fd7e5fb3b307f24a8643f6b7748a0 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Fri, 15 Nov 2019 13:25:53 -0500 Subject: [PATCH 036/115] Update indentation error on conversion, remove replay resources --- src/conversion/conversion.py | 2 +- template.yml | 28 ---------------------------- 2 files changed, 1 insertion(+), 29 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 44ee45a..6d960f1 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -158,4 +158,4 @@ def handler(event, context): log.info(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) - return('ok') + return('ok') diff --git a/template.yml b/template.yml index 6d7e47d..e1ce3c9 100644 --- a/template.yml +++ b/template.yml @@ -75,7 +75,6 @@ Resources: Queues: - !Ref ConversionQueue - !Ref SentimentQueue - - !Ref ReplayQueue PolicyDocument: Version: '2012-10-17' Statement: @@ -99,23 +98,12 @@ Resources: Condition: ArnEquals: aws:SourceArn: !GetAtt FileProcessingRule.Arn - - - Effect: Allow - Principal: - AWS: '*' - Action: - - sqs:SendMessage - Resource: !GetAtt ReplayQueue.Arn - Condition: - ArnEquals: - aws:SourceArn: !GetAtt FileProcessingRule.Arn FileProcessingRule: Type: AWS::Events::Rule DependsOn: - ConversionQueue - SentimentQueue - - ReplayQueue Properties: Description: Rule to capture S3 PutObject events EventPattern: @@ -137,8 +125,6 @@ Resources: Id: Convert - Arn: !GetAtt SentimentQueue.Arn Id: Sentiment - - Arn: !GetAtt ReplayQueue.Arn - Id: Replay ConversionQueue: Type: AWS::SQS::Queue @@ -286,17 +272,3 @@ Resources: PrimaryKey: Name: 's3_object' Type: String - - ReplayQueue: - Type: AWS::SQS::Queue - DependsOn: ReplayDlq - Properties: - VisibilityTimeout: 300 - RedrivePolicy: - deadLetterTargetArn: !GetAtt ReplayDlq.Arn - maxReceiveCount: 5 - - ReplayDlq: - Type: AWS::SQS::Queue - Properties: - VisibilityTimeout: 300 From e90074b83d886cfe553eb6a8b85e8a36e393f537 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Mon, 18 Nov 2019 17:39:24 -0500 Subject: [PATCH 037/115] First revision of alarming --- README.md | 4 +++- template.yml | 48 ++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 51 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 4a87bb4..e4ee912 100644 --- a/README.md +++ b/README.md @@ -89,10 +89,12 @@ sam deploy \ --template-file packaged-template.yml \ --stack-name lambda-file-refarch \ --region region \ - --tags Project=lambda-refarch-fileprocessing + --tags Project=lambda-refarch-fileprocessing \ + --parameter-overrides AlarmRecipientEmailAddress= \ --capabilities CAPABILITY_IAM ``` +You will receive an email asking you to confirm subscription to the `lambda-file-refarch-AlarmTopic` SNS topic that will receive alerts should either the `ConversionDlq` SQS queue or `SentimentDlq` SQS queue receive messages. ## Testing the Example diff --git a/template.yml b/template.yml index e1ce3c9..b006a36 100644 --- a/template.yml +++ b/template.yml @@ -17,6 +17,11 @@ Parameters: - "INFO" - "DEBUG" + AlarmRecipientEmailAddress: + Type: String + AllowedPattern: '[^\s@]+@[^\s@]+\.[^\s@]+' + ConstraintDescription: Enter a valid email address + Resources: InputBucket: Type: AWS::S3::Bucket @@ -272,3 +277,46 @@ Resources: PrimaryKey: Name: 's3_object' Type: String + + AlarmTopic: + Type: AWS::SNS::Topic + Properties: + Subscription: + - Protocol: email + Endpoint: !Ref AlarmRecipientEmailAddress + + ConversionDlqAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: Conversion DLQ messages + AlarmActions: + - Ref: AlarmTopic + MetricName: ApproximateNumberOfMessagesVisible + Namespace: AWS/SQS + Statistic: Sum + Period: '60' + EvaluationPeriods: '1' + Threshold: '1' + ComparisonOperator: GreaterThanThreshold + Dimensions: + - Name: QueueName + Value: + Ref: ConversionDlq + + SentimentDlqAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: Sentiment DLQ messages + AlarmActions: + - Ref: AlarmTopic + MetricName: ApproximateNumberOfMessagesVisible + Namespace: AWS/SQS + Statistic: Sum + Period: '60' + EvaluationPeriods: '1' + Threshold: '1' + ComparisonOperator: GreaterThanThreshold + Dimensions: + - Name: QueueName + Value: + Ref: SentimentDlq From 0cab5cacd989361da6bd2ef0db533bb83047a478 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Tue, 19 Nov 2019 13:15:10 -0500 Subject: [PATCH 038/115] Updated ComparisonOperator and Description for Alarms --- template.yml | 38 ++++++++++++++++++++------------------ 1 file changed, 20 insertions(+), 18 deletions(-) diff --git a/template.yml b/template.yml index b006a36..5a8f003 100644 --- a/template.yml +++ b/template.yml @@ -288,35 +288,37 @@ Resources: ConversionDlqAlarm: Type: AWS::CloudWatch::Alarm Properties: - AlarmDescription: Conversion DLQ messages + AlarmDescription: Alarm if Conversion DLQ queue depth is more than 1 message AlarmActions: - - Ref: AlarmTopic + - Ref: AlarmTopic MetricName: ApproximateNumberOfMessagesVisible Namespace: AWS/SQS Statistic: Sum - Period: '60' - EvaluationPeriods: '1' - Threshold: '1' - ComparisonOperator: GreaterThanThreshold + Period: 60 + EvaluationPeriods: 1 + Threshold: 1 + ComparisonOperator: GreaterThanOrEqualToThreshold + TreatMissingData: notBreaching Dimensions: - - Name: QueueName - Value: - Ref: ConversionDlq + - Name: QueueName + Value: + Ref: ConversionDlq SentimentDlqAlarm: Type: AWS::CloudWatch::Alarm Properties: - AlarmDescription: Sentiment DLQ messages + AlarmDescription: Alarm if Sentiment DLQ queue depth is more than 1 message AlarmActions: - - Ref: AlarmTopic + - Ref: AlarmTopic MetricName: ApproximateNumberOfMessagesVisible Namespace: AWS/SQS Statistic: Sum - Period: '60' - EvaluationPeriods: '1' - Threshold: '1' - ComparisonOperator: GreaterThanThreshold + Period: 60 + EvaluationPeriods: 1 + Threshold: 1 + ComparisonOperator: GreaterThanOrEqualToThreshold + TreatMissingData: notBreaching Dimensions: - - Name: QueueName - Value: - Ref: SentimentDlq + - Name: QueueName + Value: + Ref: SentimentDlq From a3f35d7f6f182d443ff51644ed4232e723e89c41 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 20 Nov 2019 10:50:06 -0500 Subject: [PATCH 039/115] Update dimensions of Alarms --- template.yml | 18 ++++++++---------- 1 file changed, 8 insertions(+), 10 deletions(-) diff --git a/template.yml b/template.yml index 5a8f003..69e2891 100644 --- a/template.yml +++ b/template.yml @@ -288,7 +288,7 @@ Resources: ConversionDlqAlarm: Type: AWS::CloudWatch::Alarm Properties: - AlarmDescription: Alarm if Conversion DLQ queue depth is more than 1 message + AlarmDescription: Alarm if Conversion DLQ has any messages AlarmActions: - Ref: AlarmTopic MetricName: ApproximateNumberOfMessagesVisible @@ -296,18 +296,17 @@ Resources: Statistic: Sum Period: 60 EvaluationPeriods: 1 - Threshold: 1 - ComparisonOperator: GreaterThanOrEqualToThreshold + Threshold: 0 + ComparisonOperator: GreaterThanThreshold TreatMissingData: notBreaching Dimensions: - Name: QueueName - Value: - Ref: ConversionDlq + Value: !GetAtt ConversionDlq.QueueName SentimentDlqAlarm: Type: AWS::CloudWatch::Alarm Properties: - AlarmDescription: Alarm if Sentiment DLQ queue depth is more than 1 message + AlarmDescription: Alarm if Sentiment DLQ has any messages AlarmActions: - Ref: AlarmTopic MetricName: ApproximateNumberOfMessagesVisible @@ -315,10 +314,9 @@ Resources: Statistic: Sum Period: 60 EvaluationPeriods: 1 - Threshold: 1 - ComparisonOperator: GreaterThanOrEqualToThreshold + Threshold: 0 + ComparisonOperator: GreaterThanThreshold TreatMissingData: notBreaching Dimensions: - Name: QueueName - Value: - Ref: SentimentDlq + Value: !GetAtt SentimentDlq.QueueName From 60381d4e613d8206654f323deee9f3604d66466f Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 20 Nov 2019 11:49:42 -0500 Subject: [PATCH 040/115] Update error handling when failure to put message to db --- src/sentiment/sentiment.py | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index dd4f1f5..5df3ca2 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -12,8 +12,8 @@ max_object_size = 104857600 # 100MB = 104857600 bytes -sentiment_table = os.getenv('SENTIMENT_TABLE') -sentiment_queue = os.getenv('SENTIMENT_QUEUE') +s_table = os.getenv('s_table') +s_queue = os.getenv('s_queue') log_level = os.getenv('LOG_LEVEL') @@ -22,7 +22,7 @@ s3_resource = boto3.resource('s3') dynamodb_resource = boto3.resource('dynamodb') -table = dynamodb_resource.Table(sentiment_table) +table = dynamodb_resource.Table(s_table) sqs_client = boto3.client('sqs') @@ -135,7 +135,7 @@ def handler(event, context): remove message from SQS queue.''' try: sqs_client.delete_message( - QueueUrl=sentiment_queue, + QueueUrl=s_queue, ReceiptHandle=sqs_receipt_handle ) except Exception as e: @@ -143,9 +143,13 @@ def handler(event, context): log.error(err_msg) raise Exception(err_msg) - sentiment_db_msg = f'Put sentiment to {sentiment_table}' + sentiment_db_msg = f'Put sentiment to {s_table}' log.info(sentiment_db_msg) - + else: + db_put_error_msg = f'Could not put sentiment to {s_table}: ' + db_put_error_msg += f'{put_sentiment_result}' + log.error(db_put_error_msg) + raise Exception(db_put_error_msg) except Exception as e: log.error(f'Could not get sentiment: {str(e)}') raise Exception(f'Could not get sentiment: {str(e)}') From e1c956602c18aa2e7bbaa7aecbb4eb03c32c4d07 Mon Sep 17 00:00:00 2001 From: Rudge Date: Thu, 21 Nov 2019 11:05:17 +0000 Subject: [PATCH 041/115] updated diagram with 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From dcd11e822fbd2b528b19264887b47dd6d46110df Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Fri, 22 Nov 2019 11:42:45 -0500 Subject: [PATCH 042/115] Add tracing capability, update readme, fix sentiment bug --- README.md | 47 +++++++++++++++++++------------------- src/sentiment/sentiment.py | 4 ++-- template.yml | 22 ++++++++++++++++++ 3 files changed, 47 insertions(+), 26 deletions(-) diff --git a/README.md b/README.md index e4ee912..6486b9f 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. -In this example application we deliver the notes from an interview in markdown format into S3 and we utilise CloudWatch Events to trigger multiple processing flows. +In this example application we deliver the notes from an interview in Markdown format to S3. CloudWatch Events is used to trigger multiple processing flows - one to convert and persist Markdown files to HTML and another to detect and persist sentiment. ## Architectural Diagram @@ -11,36 +11,29 @@ In this example application we deliver the notes from an interview in markdown f ## Application Components ### Event Trigger -Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilise [CloudWatch Events](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) and [CloudTrail](https://aws.amazon.com/cloudtrail/). We write a CloudWatch Events rule which checks for S3 PutObject API calls into our Source Bucket from CloudTrail. Everytime the PutObject API is called this creates a CloudTrail log which our rule translates into an event represented as a JSON object. In our rule we also define targets which our JSON event object is delivered to, which in this scenario is 4 seperate [SQS Queues](https://aws.amazon.com/sqs/) for 4 different worflows. Other target types include AWS Lambda Functions, Kinesis Data Streams, Simple Notification Service, Step Functions state machines, ECS tasks refer to [What is Amazon CloudWatch Events?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) for more information about eligible targets. -### Conversion WorkFlow +Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilise [CloudWatch Events](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) and [CloudTrail](https://aws.amazon.com/cloudtrail/). A CloudWatch Events rule checks for S3 PutObject API calls into our Source Bucket using CloudTrail data. CloudTrail records when PutObject API is called. Our rule translates this record into an event, represented as a JSON object. We also define targets in our rule and deliver our JSON event to 2 seperate [SQS Queues](https://aws.amazon.com/sqs/), representing 2 different worflows. Other target types include AWS Lambda Functions, Kinesis Data Streams, Simple Notification Service, Step Functions state machines, and ECS tasks. Refer to [What is Amazon CloudWatch Events?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) for more information about eligible targets. -For this workflow the target of our JSON object decribing the S3 PutObject event is an SQS queue. Sending to SQS first rather than directly to Lambda allows for more control of Lambda invocations and better error handling. +### Conversion Workflow -Lambda polls our queue and when messages are available it will send them to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. +We target a SQS queue for this workflow. Sending the JSON event to SQS first rather than directly to Lambda allows for more control of Lambda invocations and better error handling. -If our Lambda fails to process the messages we can configure SQS to send to a dead-letter queue for inspection and reprocessing. +The Lambda service polls our queue. When messages are available it will send them to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. -Once the function has the message this is parsed. The JSON event object contains information such as the S3 bucket and object key and object size. +If our Conversion Lambda function fails to process the messages, SQS sends the event to a dead-letter queue (DLQ) for inspection and reprocessing. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Conversion DLQ. -Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new html file to the HTML Bucket. +Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function execution environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new html file to the HTML Bucket. ### Sentiment Analysis Workflow -Here we are using our AI/ML service [Amazon Comprehend](https://aws.amazon.com/comprehend/) which is a machine learning powered service that makes it easy to find insights and relationships in text. We can use the Sentiment Analysis API in order to understand if the questions the interviewer asked had positive or negative responses. +We are using AWS' AI/ML service [Amazon Comprehend](https://aws.amazon.com/comprehend/) which is a machine learning powered service that makes it easy to find insights and relationships in text. We use the Sentiment Analysis API to understand whether interview responses are positive or negative. -This workflow uses the same SQS to Lambda Function pattern as the coversion workflow. Here our business logic downloads the file and extracts the content of the file and sends it to the Comprehend Sentiment Analysis API. This returns a Sentiment and a confidence Score which Describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. +The Sentiment workflow uses the same SQS-to-Lambda Function pattern as the Coversion workflow. Our function downloads the interview file, extracts the content, and sends it to the Comprehend Sentiment Analysis API. This returns a Sentiment and a confidence score which describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. -Once we have our sentiment we persist the result to our [DynamoDB](https://aws.amazon.com/dynamodb/) table. +Once we have our sentiment we persist the result to our [DynamoDB](https://aws.amazon.com/dynamodb/) table. - -### Search Indexing Workflow -TODO - -### Replay Workflow - -TODO +If our Sentiment Lambda function fails to process the messages, SQS sends the event to a dead-letter queue (DLQ) for inspection and reprocessing. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Sentiment DLQ. ## Running the Example @@ -52,7 +45,7 @@ You can use the provided [AWS SAM template](./template.yml) to launch a stack th #### Build -The AWS SAM CLI comes with abstractions for a number of Lambda runtimes to build your dependencies, and copies the source code into staging folders so that everything is ready to be packaged and deployed. The *sam build* command builds any dependencies that your application has, and copies your application source code to folders under aws-sam/build to be zipped and uploaded to Lambda. +The AWS SAM CLI comes with abstractions for a number of Lambda runtimes to build your dependencies, and copies the source code into staging folders so that everything is ready to be packaged and deployed. The *sam build* command builds any dependencies that your application has, and copies your application source code to folders under *.aws-sam/build* to be zipped and uploaded to Lambda. ```bash sam build --use-container @@ -170,13 +163,13 @@ creates the following resources: - **CloudTrailBucketPolicy** - A S3 policy which permits the AWS CloudTrail service to write data to the **CloudTrailBucket**. -- **FileProcessingQueuePolicy** - A SQS policy that allows the **FileProcessingRule** to publish events to the **ConversionQueue**, **SentimentQueue**, and the **ReplayQueue**. +- **FileProcessingQueuePolicy** - A SQS policy that allows the **FileProcessingRule** to publish events to the **ConversionQueue** and **SentimentQueue**. -- **FileProcessingRule** - A CloudWatch Events Rule that monitors CloudTrail `PubObject` events from the **InputBucket**. +- **FileProcessingRule** - A CloudWatch Events Rule that monitors CloudTrail `PutObject` events to the **InputBucket**. -- **ConversionQueue** - A SQS queue that is used to store events for conversion from markdown to HTML. +- **ConversionQueue** - A SQS queue that is used to store events for conversion from Markdown to HTML. -- **ConversionDlq** - TBD. +- **ConversionDlq** - A SQS queue that is used to capture messages that cannot be processed by the **ConversionFunction**. The *RedrivePolicy* on the **ConversionQueue** is used to manage how traffic makes it to this queue. - **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. @@ -184,12 +177,18 @@ creates the following resources: - **SentimentQueue** - A SQS queue that is used to store events for sentiment analysis processing. -- **SentimentDlq** - TBD. +- **SentimentDlq** - A SQS queue that is used to capture messages that cannot be processed by the **SentimentFunction**. The *RedrivePolicy* on the **SentimentQueue** is used to manage how traffic makes it to this queue. - **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. - **SentimentTable** - A DynamoDB table that stores the input file along with the sentiment. +- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive alarms from the **ConversionDlqAlarm** and **SentimentDlqAlarm**. + +- **ConversionDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **ConvesionDlq** within a 1 minute period and sends notification to the **AlarmTopic**. + +- **SentimentDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **SentimentDlq** within a 1 minute period and sends notification to the **AlarmTopic**. + ## License diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 5df3ca2..e26058a 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -12,8 +12,8 @@ max_object_size = 104857600 # 100MB = 104857600 bytes -s_table = os.getenv('s_table') -s_queue = os.getenv('s_queue') +s_table = os.getenv('SENTIMENT_TABLE') +s_queue = os.getenv('SENTIMENT_QUEUE') log_level = os.getenv('LOG_LEVEL') diff --git a/template.yml b/template.yml index 69e2891..3ade329 100644 --- a/template.yml +++ b/template.yml @@ -153,6 +153,7 @@ Resources: Handler: conversion.handler Runtime: python3.6 CodeUri: ./src/conversion/ + Tracing: Active Policies: - SQSPollerPolicy: QueueName: @@ -174,6 +175,16 @@ Resources: Action: - s3:ListBucket Resource: !GetAtt InputBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - xray:PutTraceSegments + - xray:PutTelemetryRecords + - xray:GetSamplingRules + - xray:GetSamplingTargets + - xray:GetSamplingStatisticSummaries + Resource: '*' - Version: '2012-10-17' Statement: - Effect: Allow @@ -220,6 +231,7 @@ Resources: Handler: sentiment.handler Runtime: python3.6 CodeUri: ./src/sentiment/ + Tracing: Active Policies: - SQSPollerPolicy: QueueName: @@ -241,6 +253,16 @@ Resources: Action: - s3:ListBucket Resource: !GetAtt InputBucket.Arn + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: + - xray:PutTraceSegments + - xray:PutTelemetryRecords + - xray:GetSamplingRules + - xray:GetSamplingTargets + - xray:GetSamplingStatisticSummaries + Resource: '*' - Version: '2012-10-17' Statement: - Effect: Allow From 0635c5d333249bbf8952ee44f14bb0efb317a0ef Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Tue, 26 Nov 2019 10:51:39 -0500 Subject: [PATCH 043/115] Update with X-Ray, more sensible timeouts --- src/conversion/conversion.py | 143 +++++++++++++++++++++++++++----- src/conversion/requirements.txt | 1 + src/sentiment/requirements.txt | 1 + src/sentiment/sentiment.py | 98 ++++++++++++++++++++-- template.yml | 8 +- 5 files changed, 222 insertions(+), 29 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index 6d960f1..dc6123a 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -4,11 +4,15 @@ import sys import aws_lambda_logging +from aws_xray_sdk.core import xray_recorder +from aws_xray_sdk.core import patch_all import boto3 import botocore import markdown import tempfile +patch_all() + max_object_size = 104857600 # 100MB = 104857600 bytes @@ -26,48 +30,143 @@ def check_s3_object_size(bucket, key_name): + """Take in a bucket and key and return the number of bytes + + Parameters + ---------- + bucket: string, required + Bucket name where object is stored + + key_name: string, required + Key name of object + + Returns + ------- + size: integer + Size of key_name in bucket + """ + + xray_recorder.begin_subsegment('## get_object_size') + subsegment = xray_recorder.current_subsegment() + subsegment.put_metadata('object', f's3://{bucket}/{key_name}') + try: size = s3_resource.Object(bucket, key_name).content_length + subsegment.put_metadata('object_size', size) except Exception as e: log.error(f'Error: {str(e)}') size = 'NaN' + subsegment.put_metadata('object_size', size) + xray_recorder.end_subsegment() return(size) def get_s3_object(bucket, key_name, local_file): + """Download object in S3 to local file + + Parameters + ---------- + bucket: string, required + Bucket name where object is stored + + key_name: string, required + Key name of object + + local_file: string, required + + Returns + ------- + result: string + Result of operation ('ok' or exception) + """ + + xray_recorder.begin_subsegment('## get_object_to_convert') + subsegment = xray_recorder.current_subsegment() + subsegment.put_metadata('object', f's3://{bucket}/{key_name}') + try: s3_resource.Bucket(bucket).download_file(key_name, local_file) - return('ok') + result = 'ok' + subsegment.put_annotation('OBJECT_DOWNLOAD', 'SUCCESS') except botocore.exceptions.ClientError as e: + subsegment.put_annotation('OBJECT_DOWNLOAD', 'FAILURE') if e.response['Error']['Code'] == '404': - return(f'Error: s3://{bucket}/{key_name} does not exist') + result = f'Error: s3://{bucket}/{key_name} does not exist' else: - return(f'Error: {str(e)}') + result = f'Error: {str(e)}' + + xray_recorder.end_subsegment() + return(result) def convert_to_html(file): + """Convert Markdown in file to HTML + + Parameters + ---------- + file: string, required + Local file to be converted + + Returns + ------- + string + Resulting HTML5 + """ + + xray_recorder.begin_subsegment('## convert_to_html') + subsegment = xray_recorder.current_subsegment() + subsegment.put_metadata('file', file) + try: file_open = open(file, 'r') file_string = file_open.read() + subsegment.put_annotation('MARKDOWN_CONVERSION', 'SUCCESS') + xray_recorder.end_subsegment() file_open.close() - + return(markdown.markdown(file_string)) except Exception as e: log.error(f'Could not open or read {file}: {str(e)}') + subsegment.put_annotation('MARKDOWN_CONVERSION', 'FAILURE') + xray_recorder.end_subsegment() raise - return(markdown.markdown(file_string)) +def upload_html(bucket, key, source_file): + """Upload local file to S3 bucket + + Parameters + ---------- + target_bucket: string, required + S3 bucket where object is stored + + key_name: string, required + Key name of object + + source_file: string, required + Name of local file + + Returns + ------- + result: string + Result of operation ('ok' or exception) + """ + + xray_recorder.begin_subsegment('## upload_html_to_s3') + subsegment = xray_recorder.current_subsegment() + subsegment.put_metadata('object', f's3://{bucket}/{key}') -def upload_html(target_bucket, target_key, source_file): try: - s3_resource.Object(target_bucket, target_key).upload_file(source_file) - html_upload = 'ok' + s3_resource.Object(bucket, key).upload_file(source_file) + result = 'ok' + subsegment.put_annotation('OBJECT_DOWNLOAD', 'SUCCESS') except Exception as e: - log.error(f'Could not upload {source_file} to {target_bucket}: {str(e)}') - html_upload = 'fail' + subsegment.put_annotation('OBJECT_DOWNLOAD', 'FAILURE') + log.error(f'Could not upload {source_file} to {bucket}: {str(e)}') + result = 'fail' - return(html_upload) + xray_recorder.end_subsegment() + return(result) def handler(event, context): @@ -91,9 +190,11 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - log.error(f'''Source S3 object s3://{bucket_name}/{key_name} is larger ({size} bytes) - than {max_object_size} (max object bytes)''') + error_message = f'Source S3 object s3://{bucket_name}/{key_name} is larger ' + error_message += f'than {max_object_size} (max object bytes)' + log.error(error_message) raise Exception('Source S3 object too large') + sys.exit(1) local_file = os.path.join(tmpdir, key_name) @@ -105,6 +206,7 @@ def handler(event, context): else: log.error(f'Fail to put object to {local_file}') raise Exception(f'Fail to put object to {local_file}') + sys.exit(1) html = convert_to_html(local_file) @@ -132,17 +234,20 @@ def handler(event, context): except Exception as e: log.error(f'{str(e)}') raise Exception(str(e)) + sys.exit(1) dst_s3_object = f's3://{target_bucket}/{html_filename}' - log.info(f'''Success: Uploaded {local_html_file} to - {dst_s3_object}''') + success_message = f'Success: Uploaded {local_html_file} to ' + success_message += f'{dst_s3_object}' + log.info(success_message) else: - log.error(f'{str(e)}') - raise Exception(f'{str(e)}') - + error_message = f'Could not upload file to ' + error_message += f'{dst_s3_object}: {str(e)}' + log.error(error_message) + raise Exception(error_message) except Exception as e: log.error(f'Could not convert record: {str(e)}') raise Exception(f'Could not convert record: {str(e)}') - + sys.exit(1) finally: filesToRemove = os.listdir(tmpdir) diff --git a/src/conversion/requirements.txt b/src/conversion/requirements.txt index 5a75021..8a8bea7 100644 --- a/src/conversion/requirements.txt +++ b/src/conversion/requirements.txt @@ -1,3 +1,4 @@ aws-lambda-logging +aws-xray-sdk boto3 markdown \ No newline at end of file diff --git a/src/sentiment/requirements.txt b/src/sentiment/requirements.txt index 9445505..f3b429b 100644 --- a/src/sentiment/requirements.txt +++ b/src/sentiment/requirements.txt @@ -1,2 +1,3 @@ aws-lambda-logging +aws-xray-sdk boto3 \ No newline at end of file diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index e26058a..06367a1 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -6,9 +6,13 @@ import tempfile import aws_lambda_logging +from aws_xray_sdk.core import xray_recorder +from aws_xray_sdk.core import patch_all import boto3 import botocore +patch_all() + max_object_size = 104857600 # 100MB = 104857600 bytes @@ -30,27 +34,96 @@ def check_s3_object_size(bucket, key_name): + """Take in a bucket and key and return the number of bytes + + Parameters + ---------- + bucket: string, required + Bucket name where object is stored + + key_name: string, required + Key name of object + + Returns + ------- + size: integer + Size of key_name in bucket + """ + + xray_recorder.begin_subsegment('## get_object_size') + subsegment = xray_recorder.current_subsegment() + subsegment.put_metadata('object', f's3://{bucket}/{key_name}') + try: size = s3_resource.Object(bucket, key_name).content_length + subsegment.put_metadata('object_size', size) except Exception as e: log.error(f'Error: {str(e)}') size = 'NaN' + subsegment.put_metadata('object_size', size) + xray_recorder.end_subsegment() return(size) def get_s3_object(bucket, key_name, local_file): + """Download object in S3 to local file + + Parameters + ---------- + bucket: string, required + Bucket name where object is stored + + key_name: string, required + Key name of object + + local_file: string, required + + Returns + ------- + result: string + Result of operation ('ok' or exception) + """ + + xray_recorder.begin_subsegment('## get_object_to_analyze') + subsegment = xray_recorder.current_subsegment() + subsegment.put_metadata('object', f's3://{bucket}/{key_name}') + try: s3_resource.Bucket(bucket).download_file(key_name, local_file) - return('ok') + result = 'ok' + subsegment.put_annotation('OBJECT_DOWNLOAD', 'SUCCESS') except botocore.exceptions.ClientError as e: + subsegment.put_annotation('OBJECT_DOWNLOAD', 'FAILURE') if e.response['Error']['Code'] == '404': - return(f'Error: s3://{bucket}/{key_name} does not exist') + result = f'Error: s3://{bucket}/{key_name} does not exist' else: - return(f'Error: {str(e)}') + result = f'Error: {str(e)}' + + xray_recorder.end_subsegment() + return(result) def put_sentiment(s3_object, sentiment): + """Put the sentiment of a object to DynamoDB + + Parameters + ---------- + s3_object: string, required + Location of the S3 object to analyze + + sentiment: dict, required + Sentiment dictionary from Comprehend + + Returns + ------- + result: string + Result of operation ('ok' or exception) + """ + + xray_recorder.begin_subsegment('## put_sentiment_to_db') + subsegment = xray_recorder.current_subsegment() + try: response = table.put_item( Item={ @@ -65,10 +138,12 @@ def put_sentiment(s3_object, sentiment): ) result = 'ok' - + subsegment.put_annotation('PUT_SENTIMENT_TO_DB', 'SUCCESS') except Exception as e: result = str(e) + subsegment.put_annotation('PUT_SENTIMENT_TO_DB', 'FAILURE') + xray_recorder.end_subsegment() return(result) @@ -93,13 +168,17 @@ def handler(event, context): size = check_s3_object_size(bucket_name, key_name) if size >= max_object_size: - max_err_msg = f'Source object is too large' - log.error(max_err_msg) - raise Exception(max_err_msg) + error_message = f'Source S3 object ' + error_message += f's3://{bucket_name}/{key_name} is larger ' + error_message += f'than {max_object_size} (max object bytes)' + log.error(error_message) + raise Exception(error_message) + sys.exit(1) if size == 'NaN': exc = f'Could not get size for s3://{bucket_name}/{key_name}' raise Exception(exc) + sys.exit(1) local_file = os.path.join(tmpdir, key_name) @@ -112,6 +191,7 @@ def handler(event, context): else: log.error(f'Download failure to {local_file}') raise Exception(f'Download failure to {local_file}') + sys.exit(1) md_contents = open(local_file, 'r').read() @@ -142,6 +222,7 @@ def handler(event, context): err_msg = f'Could not remove message from queue: {str(e)}' log.error(err_msg) raise Exception(err_msg) + sys.exit(1) sentiment_db_msg = f'Put sentiment to {s_table}' log.info(sentiment_db_msg) @@ -150,10 +231,11 @@ def handler(event, context): db_put_error_msg += f'{put_sentiment_result}' log.error(db_put_error_msg) raise Exception(db_put_error_msg) + sys.exit(1) except Exception as e: log.error(f'Could not get sentiment: {str(e)}') raise Exception(f'Could not get sentiment: {str(e)}') - + sys.exit(1) finally: filesToRemove = os.listdir(tmpdir) diff --git a/template.yml b/template.yml index 3ade329..dce3529 100644 --- a/template.yml +++ b/template.yml @@ -135,7 +135,7 @@ Resources: Type: AWS::SQS::Queue DependsOn: ConversionDlq Properties: - VisibilityTimeout: 300 + VisibilityTimeout: 20 RedrivePolicy: deadLetterTargetArn: !GetAtt ConversionDlq.Arn maxReceiveCount: 5 @@ -153,6 +153,8 @@ Resources: Handler: conversion.handler Runtime: python3.6 CodeUri: ./src/conversion/ + MemorySize: 256 + Timeout: 3 Tracing: Active Policies: - SQSPollerPolicy: @@ -214,7 +216,7 @@ Resources: Type: AWS::SQS::Queue DependsOn: SentimentDlq Properties: - VisibilityTimeout: 300 + VisibilityTimeout: 20 RedrivePolicy: deadLetterTargetArn: !GetAtt SentimentDlq.Arn maxReceiveCount: 5 @@ -231,6 +233,8 @@ Resources: Handler: sentiment.handler Runtime: python3.6 CodeUri: ./src/sentiment/ + MemorySize: 128 + Timeout: 3 Tracing: Active Policies: - SQSPollerPolicy: From 2566af0d3f347a792573c5e90233401e4321c5d1 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 27 Nov 2019 11:34:14 -0500 Subject: [PATCH 044/115] Updating memory for sentiment, adjusting timeouts --- template.yml | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/template.yml b/template.yml index dce3529..f1b3c6b 100644 --- a/template.yml +++ b/template.yml @@ -135,7 +135,7 @@ Resources: Type: AWS::SQS::Queue DependsOn: ConversionDlq Properties: - VisibilityTimeout: 20 + VisibilityTimeout: 60 RedrivePolicy: deadLetterTargetArn: !GetAtt ConversionDlq.Arn maxReceiveCount: 5 @@ -154,7 +154,7 @@ Resources: Runtime: python3.6 CodeUri: ./src/conversion/ MemorySize: 256 - Timeout: 3 + Timeout: 10 Tracing: Active Policies: - SQSPollerPolicy: @@ -216,7 +216,7 @@ Resources: Type: AWS::SQS::Queue DependsOn: SentimentDlq Properties: - VisibilityTimeout: 20 + VisibilityTimeout: 60 RedrivePolicy: deadLetterTargetArn: !GetAtt SentimentDlq.Arn maxReceiveCount: 5 @@ -233,8 +233,8 @@ Resources: Handler: sentiment.handler Runtime: python3.6 CodeUri: ./src/sentiment/ - MemorySize: 128 - Timeout: 3 + MemorySize: 256 + Timeout: 10 Tracing: Active Policies: - SQSPollerPolicy: From f67b5c984e1057b87e67ef5b7e946314a6eb1fe3 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 9 Jan 2020 16:20:38 +0000 Subject: [PATCH 045/115] Changed some INFO logging to DEBUG --- src/conversion/conversion.py | 10 +++++----- src/sentiment/sentiment.py | 6 +++--- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index dc6123a..c70c9bc 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -159,9 +159,9 @@ def upload_html(bucket, key, source_file): try: s3_resource.Object(bucket, key).upload_file(source_file) result = 'ok' - subsegment.put_annotation('OBJECT_DOWNLOAD', 'SUCCESS') + subsegment.put_annotation('OBJECT_UPLOAD', 'SUCCESS') except Exception as e: - subsegment.put_annotation('OBJECT_DOWNLOAD', 'FAILURE') + subsegment.put_annotation('OBJECT_UPLOAD', 'FAILURE') log.error(f'Could not upload {source_file} to {bucket}: {str(e)}') result = 'fail' @@ -217,7 +217,7 @@ def handler(event, context): with open(local_html_file, 'w') as outfile: outfile.write(html) log.info(f'''Success: Converted s3://{bucket_name}/{key_name} - to {local_html_file}''') + to {local_html_file}''') outfile.close() html_upload = upload_html(target_bucket, @@ -253,14 +253,14 @@ def handler(event, context): for f in filesToRemove: file_path = os.path.join(tmpdir, f) - log.info(f'Removing File: {file_path}') + log.debug(f'Removing File: {file_path}') try: os.remove(file_path) except OSError as e: log.error(f'Could not delete file {file_path}: {str(e)}') - log.info(f'Removing Folder: {tmpdir}') + log.debug(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) return('ok') diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 06367a1..4b60062 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -212,7 +212,7 @@ def handler(event, context): if put_sentiment_result == 'ok': '''If function could put the sentiment to the DDB table then - remove message from SQS queue.''' + remove message from SQS queue.''' try: sqs_client.delete_message( QueueUrl=s_queue, @@ -241,14 +241,14 @@ def handler(event, context): for f in filesToRemove: file_path = os.path.join(tmpdir, f) - log.info(f'Removing File: {file_path}') + log.debug(f'Removing File: {file_path}') try: os.remove(file_path) except OSError as e: log.error(f'Could not delete file {file_path}: {str(e)}') - log.info(f'Removing Folder: {tmpdir}') + log.debug(f'Removing Folder: {tmpdir}') os.rmdir(tmpdir) return('ok') From 076d00c2630e1c3b2a24582535a4c575d868d7f3 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 14 Jan 2020 15:45:41 +0000 Subject: [PATCH 046/115] Corrected linting errors --- src/conversion/conversion.py | 20 +++++++------------- src/sentiment/sentiment.py | 14 +++----------- 2 files changed, 10 insertions(+), 24 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index c70c9bc..a4c4f77 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -170,15 +170,11 @@ def upload_html(bucket, key, source_file): def handler(event, context): - aws_lambda_logging.setup(level=log_level, - aws_request_id=context.aws_request_id) + aws_lambda_logging.setup(level=log_level, aws_request_id=context.aws_request_id) for record in event['Records']: tmpdir = tempfile.mkdtemp() - sqs_message_id = record['messageId'] - sqs_event_source_arn = record['eventSourceARN'] - sqs_receipt_handle = record['receiptHandle'] try: @@ -194,19 +190,16 @@ def handler(event, context): error_message += f'than {max_object_size} (max object bytes)' log.error(error_message) raise Exception('Source S3 object too large') - sys.exit(1) local_file = os.path.join(tmpdir, key_name) download_status = get_s3_object(bucket_name, key_name, local_file) if download_status == 'ok': - key_bytes = os.stat(local_file).st_size log.info(f'Success: Download to {local_file} for conversion') else: log.error(f'Fail to put object to {local_file}') raise Exception(f'Fail to put object to {local_file}') - sys.exit(1) html = convert_to_html(local_file) @@ -220,9 +213,11 @@ def handler(event, context): to {local_html_file}''') outfile.close() - html_upload = upload_html(target_bucket, - html_filename, - local_html_file) + html_upload = upload_html( + target_bucket, + html_filename, + local_html_file) + if html_upload == 'ok': '''If function could put the converted file to the S3 bucket then remove message from the SQS queue''' @@ -234,7 +229,7 @@ def handler(event, context): except Exception as e: log.error(f'{str(e)}') raise Exception(str(e)) - sys.exit(1) + dst_s3_object = f's3://{target_bucket}/{html_filename}' success_message = f'Success: Uploaded {local_html_file} to ' success_message += f'{dst_s3_object}' @@ -247,7 +242,6 @@ def handler(event, context): except Exception as e: log.error(f'Could not convert record: {str(e)}') raise Exception(f'Could not convert record: {str(e)}') - sys.exit(1) finally: filesToRemove = os.listdir(tmpdir) diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 4b60062..7d5184b 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -142,6 +142,9 @@ def put_sentiment(s3_object, sentiment): except Exception as e: result = str(e) subsegment.put_annotation('PUT_SENTIMENT_TO_DB', 'FAILURE') + result = f'Error: {str(e)}' + log.error(response) + xray_recorder.end_subsegment() return(result) @@ -154,9 +157,6 @@ def handler(event, context): for record in event['Records']: tmpdir = tempfile.mkdtemp() - sqs_message_id = record['messageId'] - sqs_event_source_arn = record['eventSourceARN'] - sqs_receipt_handle = record['receiptHandle'] try: @@ -173,25 +173,20 @@ def handler(event, context): error_message += f'than {max_object_size} (max object bytes)' log.error(error_message) raise Exception(error_message) - sys.exit(1) if size == 'NaN': exc = f'Could not get size for s3://{bucket_name}/{key_name}' raise Exception(exc) - sys.exit(1) local_file = os.path.join(tmpdir, key_name) download_status = get_s3_object(bucket_name, key_name, local_file) if download_status == 'ok': - key_bytes = os.stat(local_file).st_size - src_s3_download_bytes = key_bytes log.info(f'Download to {local_file} for sentiment analysis') else: log.error(f'Download failure to {local_file}') raise Exception(f'Download failure to {local_file}') - sys.exit(1) md_contents = open(local_file, 'r').read() @@ -222,7 +217,6 @@ def handler(event, context): err_msg = f'Could not remove message from queue: {str(e)}' log.error(err_msg) raise Exception(err_msg) - sys.exit(1) sentiment_db_msg = f'Put sentiment to {s_table}' log.info(sentiment_db_msg) @@ -231,11 +225,9 @@ def handler(event, context): db_put_error_msg += f'{put_sentiment_result}' log.error(db_put_error_msg) raise Exception(db_put_error_msg) - sys.exit(1) except Exception as e: log.error(f'Could not get sentiment: {str(e)}') raise Exception(f'Could not get sentiment: {str(e)}') - sys.exit(1) finally: filesToRemove = os.listdir(tmpdir) From 9f76870c6e003a7aaadc5b76c59161e4b911aa6d Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 15 Jan 2020 16:29:47 -0500 Subject: [PATCH 047/115] Updates to monitoring capabilities Include dashboard creation. --- .gitignore | 3 +- README.md | 10 +- template.yml | 358 +++++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 368 insertions(+), 3 deletions(-) diff --git a/.gitignore b/.gitignore index ed419d9..5cbe22e 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,3 @@ packaged-template.yml -post-sam.yml .aws-sam -**/node_modules +__pycache__ \ No newline at end of file diff --git a/README.md b/README.md index 6486b9f..e158e72 100644 --- a/README.md +++ b/README.md @@ -183,12 +183,20 @@ creates the following resources: - **SentimentTable** - A DynamoDB table that stores the input file along with the sentiment. -- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive alarms from the **ConversionDlqAlarm** and **SentimentDlqAlarm**. +- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive CloudWatch Alarms. - **ConversionDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **ConvesionDlq** within a 1 minute period and sends notification to the **AlarmTopic**. - **SentimentDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **SentimentDlq** within a 1 minute period and sends notification to the **AlarmTopic**. +- **ConversionQueueAlarm** - A CloudWatch Alarm that detect when there are too many messages in the **ConversionQueue** and sends notification to the **AlarmTopic**. + +- **SentimentQueueAlarm** - A CloudWatch Alarm that detect when there are too many messages in the **SentimentQueue** and sends notification to the **AlarmTopic**. + +- **ConversionFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when the error rate for **ConversionFunction** is too high and sends notification to the **AlarmTopic**. + +- **SentimentFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when the error rate for **SentimentFunction** is too high and sends notification to the **AlarmTopic**. + ## License diff --git a/template.yml b/template.yml index f1b3c6b..6833dfb 100644 --- a/template.yml +++ b/template.yml @@ -346,3 +346,361 @@ Resources: Dimensions: - Name: QueueName Value: !GetAtt SentimentDlq.QueueName + + ConverstionQueueAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: Conversion queue has too many messages + AlarmActions: + - Ref: AlarmTopic + MetricName: ApproximateNumberOfMessagesVisible + Namespace: AWS/SQS + Statistic: Sum + Period: 60 + EvaluationPeriods: 1 + Threshold: 20 + ComparisonOperator: GreaterThanThreshold + TreatMissingData: notBreaching + Dimensions: + - Name: QueueName + Value: !GetAtt ConversionQueue.QueueName + + SentimentQueueAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: Sentiment queue has too many messages + AlarmActions: + - Ref: AlarmTopic + MetricName: ApproximateNumberOfMessagesVisible + Namespace: AWS/SQS + Statistic: Sum + Period: 60 + EvaluationPeriods: 1 + Threshold: 20 + ComparisonOperator: GreaterThanThreshold + TreatMissingData: notBreaching + Dimensions: + - Name: QueueName + Value: !GetAtt SentimentQueue.QueueName + + ConversionFunctionErrorRateAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: High error rate for Conversion Function + AlarmActions: + - Ref: AlarmTopic + Metrics: + - Id: e1 + Expression: '(m1/m2) * 100' + Label: ConversionFunctionErrorRate + - Id: m1 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Errors + Dimensions: + - Name: FunctionName + Value: !Ref ConversionFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + - Id: m2 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Invocations + Dimensions: + - Name: FunctionName + Value: !Ref ConversionFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + EvaluationPeriods: 1 + Threshold: 5.0 + ComparisonOperator: GreaterThanOrEqualToThreshold + TreatMissingData: notBreaching + + SentimentFunctionErrorRateAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: High error rate for Sentiment Function + AlarmActions: + - Ref: AlarmTopic + Metrics: + - Id: e1 + Expression: '(m1/m2) * 100' + Label: SentimentFunctionErrorRate + - Id: m1 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Errors + Dimensions: + - Name: FunctionName + Value: !Ref SentimentFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + - Id: m2 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Invocations + Dimensions: + - Name: FunctionName + Value: !Ref SentimentFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + EvaluationPeriods: 1 + Threshold: 5.0 + ComparisonOperator: GreaterThanOrEqualToThreshold + TreatMissingData: notBreaching + + ConversionFunctionThrottleRateAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: High throttle rate for Conversion Function + AlarmActions: + - Ref: AlarmTopic + Metrics: + - Id: e1 + Expression: '(m1/m2) * 100' + Label: ConversionFunctionThrottleRate + - Id: m1 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Throttles + Dimensions: + - Name: FunctionName + Value: !Ref ConversionFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + - Id: m2 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Invocations + Dimensions: + - Name: FunctionName + Value: !Ref ConversionFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + EvaluationPeriods: 1 + Threshold: 1.0 + ComparisonOperator: GreaterThanOrEqualToThreshold + TreatMissingData: notBreaching + + SentimentFunctionThrottleRateAlarm: + Type: AWS::CloudWatch::Alarm + Properties: + AlarmDescription: High throttle rate for Sentiment Function + AlarmActions: + - Ref: AlarmTopic + Metrics: + - Id: e1 + Expression: '(m1/m2) * 100' + Label: SentimentFunctionThrottleRate + - Id: m1 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Throttles + Dimensions: + - Name: FunctionName + Value: !Ref SentimentFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + - Id: m2 + MetricStat: + Metric: + Namespace: AWS/Lambda + MetricName: Invocations + Dimensions: + - Name: FunctionName + Value: !Ref SentimentFunction + Period: 300 + Stat: Average + Unit: Count + ReturnData: false + EvaluationPeriods: 1 + Threshold: 1.0 + ComparisonOperator: GreaterThanOrEqualToThreshold + TreatMissingData: notBreaching + + ApplicationDashboard: + Type: AWS::CloudWatch::Dashboard + Properties: + DashboardName: !Ref AWS::StackName + DashboardBody: !Sub '{ + "widgets": + [ + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ + "AWS/Lambda", + "Invocations", + "FunctionName", + "${ConversionFunction}" + ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Conversion Function Invocations" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ "AWS/Lambda", "Errors", "FunctionName", "${ConversionFunction}", { "id": "m1", "visible": false } ], + [ { "expression": "100*(m1/m2)", "label": "Error Rate", "id": "e1", "region": "${AWS::Region}" } ], + [ "AWS/Lambda", "Invocations", "FunctionName", "${ConversionFunction}", { "id": "m2", "visible": false } ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Conversion Function Error Rate" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ "AWS/Lambda", "Throttles", "FunctionName", "${ConversionFunction}", { "id": "m1", "visible": false } ], + [ { "expression": "100*(m1/m2)", "label": "Throttle Rate", "id": "e1", "region": "${AWS::Region}" } ], + [ "AWS/Lambda", "Invocations", "FunctionName", "${ConversionFunction}", { "id": "m2", "visible": false } ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Conversion Function Throttle Rate" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ + "AWS/SQS", + "ApproximateNumberOfMessagesVisible", + "QueueName", + "${ConversionDlq.QueueName}" + ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Conversion DLQ Length" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ + "AWS/Lambda", + "Invocations", + "FunctionName", + "${SentimentFunction}" + ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Sentiment Function Invocations" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ "AWS/Lambda", "Errors", "FunctionName", "${SentimentFunction}", { "id": "m1", "visible": false } ], + [ { "expression": "100*(m1/m2)", "label": "Error Rate", "id": "e1", "region": "${AWS::Region}" } ], + [ "AWS/Lambda", "Invocations", "FunctionName", "${SentimentFunction}", { "id": "m2", "visible": false } ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Sentiment Function Error Rate" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ "AWS/Lambda", "Throttles", "FunctionName", "${SentimentFunction}", { "id": "m1", "visible": false } ], + [ { "expression": "100*(m1/m2)", "label": "Throttle Rate", "id": "e1", "region": "${AWS::Region}" } ], + [ "AWS/Lambda", "Invocations", "FunctionName", "${SentimentFunction}", { "id": "m2", "visible": false } ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Sentiment Function Throttle Rate" + } + }, + { + "type":"metric", + "x":0, + "y":0, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ + "AWS/SQS", + "ApproximateNumberOfMessagesVisible", + "QueueName", + "${SentimentDlq.QueueName}" + ] + ], + "period":60, + "stat":"Average", + "region": "${AWS::Region}", + "title":"Sentiment DLQ Length" + } + } + ] + }' From b2c8361ad15d88d80bdeb7d23dc6705bc2284f8c Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Fri, 17 Jan 2020 10:10:18 -0500 Subject: [PATCH 048/115] Update README with new template resources --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index e158e72..2ab634c 100644 --- a/README.md +++ b/README.md @@ -197,6 +197,11 @@ creates the following resources: - **SentimentFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when the error rate for **SentimentFunction** is too high and sends notification to the **AlarmTopic**. +- **ConversionFunctionThrottleRateAlarm** - A CloudWatch Alarm that detects when the throttle rate for **ConversionFunction** is too high and sends notification to the **AlarmTopic**. + +- **SentimentFunctionThrottleRateAlarm** - A CloudWatch Alarm that detects when the throttle rate for **SentimentFunction** is too high and sends notification to the **AlarmTopic**. + +- **ApplicationDashboard** - A CloudWatch Dashboard that presents Lambda function Invocations, Lambda function error and throttle rates, and visible SQS messages. ## License From be28707977aaeaef93a993dee84313687a2c9776 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 17 Jan 2020 15:36:10 +0000 Subject: [PATCH 049/115] Updated pipeline code --- buildspec.yml | 30 ++++---- pipeline/pipeline.yaml | 158 +++++++++++++++++++++++++++++++++++------ 2 files changed, 156 insertions(+), 32 deletions(-) diff --git a/buildspec.yml b/buildspec.yml index d30b0d2..af69355 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -1,12 +1,18 @@ -version: 0.0 -containers: - LambdaFunctions: - phases: - during_build: - commands: - - cd src/data-processor-1 && pwd && npm install async marked - - cd src/data-processor-2 && npm install async marked && ls - - aws cloudformation package --template $INPUT_FILE --s3-bucket $S3_BUCKET --output-template post-sam.yaml - artifacts: - files: - - post-sam.yaml +version: 0.2 + +env: + variables: + ARTIFACT_BUCKET: "jr-amz-test" +phases: + install: + runtime-versions: + python: 3.7 + build: + commands: + - sam build --use-container + post_build: + commands: + - sam package --output-template-file packaged-template.yml --s3-bucket $ARTIFACT_BUCKET +artifacts: + files: + - packaged-template.yml diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 826e9c0..59dad02 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -6,13 +6,15 @@ Parameters: Description: Name of the application. SAMInputFile: Type: String + Default: "" Description: The filename for the SAM file. SAMOutputFile: Type: String + Default: "packaged-template.yml" Description: The filename for the output SAM file from the buildspec file CodeBuildImage: Type: String - Default: "aws/codebuild/nodejs:4.3.2" + Default: "aws/codebuild/amazonlinux2-x86_64-standard:1.0" Description: Image used for CodeBuild project. GitHubRepoName: Type: String @@ -21,25 +23,13 @@ Parameters: Type: String Description: The GitHub repo branch code pipelines should watch for changes on Default: master - GitHubUser: + GitHubRepoOwner: Type: String - Description: GitHub UserName. This username must have access to the GitHubToken. + Description: GitHub Repository Owner. GitHubToken: NoEcho: true Type: String Description: "Secret. OAuthToken with access to Repo. Long string of characters and digits. Go to https://github.com/settings/tokens" - CodePipelineRole: - Type: String - Description: Role the pipeline will use - CloudformationRole: - Type: String - Description: Role for cloudformation - CodeBuildRole: - Type: String - Description: Role for code build - CICDS3BucketName: - Type: String - Description: S3 Bucket where the pipeline templates live Resources: CodeBuildProject: DependsOn: [S3Bucket] @@ -59,7 +49,7 @@ Resources: Image: !Ref CodeBuildImage Type: LINUX_CONTAINER Name: !Sub "${AppName}-build" - ServiceRole: !Ref CodeBuildRole + ServiceRole: !GetAtt CodeBuildTrustRole.Arn Source: Type: CODEPIPELINE Tags: @@ -98,7 +88,7 @@ Resources: Type: AWS::CodePipeline::Pipeline Properties: Name: !Sub "${AppName}-pipeline" - RoleArn: !Ref CodePipelineRole + RoleArn: !GetAtt CodePipelineTrustRole.Arn Stages: - Name: Source Actions: @@ -115,7 +105,7 @@ Resources: Repo: !Ref GitHubRepoName Branch: !Ref GitHubRepoBranch OAuthToken: !Ref GitHubToken - Owner: !Ref GitHubUser + Owner: !Ref GitHubRepoOwner RunOrder: 1 - Name: Build Actions: @@ -146,11 +136,10 @@ Resources: Configuration: StackName: !Sub "${AppName}-serverless-stack" ActionMode: CHANGE_SET_REPLACE - RoleArn: !Ref CloudformationRole + RoleArn: !GetAtt CloudFormationTrustRole.Arn ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" - #ParameterOverrides: !Sub '{"CICDS3BucketName":"${CICDS3BucketName}"}' RunOrder: 1 - Name: execute-changeset InputArtifacts: [] @@ -168,3 +157,132 @@ Resources: ArtifactStore: Type: S3 Location: !Ref S3Bucket + CodeBuildTrustRole: + Description: Creating service role in IAM for AWS CodeBuild + Type: AWS::IAM::Role + Properties: + RoleName: !Sub "${AppName}-codebuild-role" + AssumeRolePolicyDocument: + Statement: + - Effect: Allow + Principal: + Service: [codebuild.amazonaws.com] + Action: sts:AssumeRole + Path: / + CodeBuildRolePolicy: + Type: AWS::IAM::Policy + DependsOn: CodeBuildTrustRole + Description: Setting IAM policy for the service role for AWS CodeBuild + Properties: + PolicyName: CodeBuildRolePolicy + PolicyDocument: + Statement: + - Effect: Allow + Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] + Resource: ["*"] + - Effect: Allow + Resource: ["*"] + Action: ["s3:*"] + - Effect: Allow + Resource: ["*"] + Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] + - Effect: Allow + Resource: ["*"] + Action: ["sns:SendMessage"] + Roles: [!Ref CodeBuildTrustRole] + CloudFormationTrustRole: + Description: Creating service role in IAM for AWS CloudFormation + Type: AWS::IAM::Role + Properties: + RoleName: !Sub "${AppName}-cloudformation-role" + AssumeRolePolicyDocument: + Statement: + - Effect: Allow + Principal: + Service: [cloudformation.amazonaws.com] + Action: sts:AssumeRole + Path: / + CloudFormationRolePolicy: + Type: AWS::IAM::Policy + DependsOn: CloudFormationTrustRole + Description: Setting IAM policy for the service role for AWS CloudFormation + Properties: + PolicyName: CloudFormationRolePolicy + PolicyDocument: + Statement: + - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] + Resource: "*" + Effect: Allow + - Action: ["s3:PutObject"] + Resource: ["arn:aws:s3:::codepipeline*"] + Effect: Allow + - Action: ["lambda:*"] + Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" + Effect: Allow + - Action: ["dynamo:*"] + Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Effect: Allow + - Action: ["sqs:*"] + Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Effect: Allow + - Action: ["cloudwatch:*"] + Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Effect: Allow + - Action: ["cloudtrail:*"] + Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Effect: Allow + - Action: ["sns:*"] + Resource: !Sub "arn:aws:sns:${AWS::Region}:*:*" + Effect: Allow + - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Effect: Allow + - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy"] + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Effect: Allow + - Action: ["iam:PassRole"] + Resource: ["*"] + Effect: Allow + - Action: ["cloudformation:CreateChangeSet"] + Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" + Effect: Allow + - Action: ["cloudformation:CreateChangeSet"] + Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Include" + Effect: Allow + Roles: [!Ref CloudFormationTrustRole] + CodePipelineTrustRole: + Description: Creating service role in IAM for AWS CodePipeline + Type: AWS::IAM::Role + Properties: + RoleName: !Sub "${AppName}-codepipeline-role" + AssumeRolePolicyDocument: + Statement: + - Effect: Allow + Principal: + Service: [codepipeline.amazonaws.com] + Action: sts:AssumeRole + Path: / + CodePipelineRolePolicy: + Type: AWS::IAM::Policy + DependsOn: CodePipelineTrustRole + Description: Setting IAM policy for the service role for AWS CodePipeline + Properties: + PolicyName: CodePipelineRolePolicy + PolicyDocument: + Statement: + - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] + Resource: "*" + Effect: Allow + - Action: ["s3:PutObject"] + Resource: ["arn:aws:s3:::codepipeline*"] + Effect: Allow + - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] + Resource: "*" + Effect: Allow + - Action: ["cloudwatch:*", "s3:*", "sns:*", "cloudformation:*", "rds:*", "sqs:*", "iam:PassRole"] + Resource: "*" + Effect: Allow + - Action: ["lambda:InvokeFunction", "lambda:ListFunctions"] + Resource: "*" + Effect: Allow + Roles: [!Ref CodePipelineTrustRole] \ No newline at end of file From 717a5957b19358d03a64630a98f82e166af7e074 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 17 Jan 2020 15:37:08 +0000 Subject: [PATCH 050/115] Removed redundant files --- pipeline/main.yaml | 68 ----------------- pipeline/pipeline-roles.yaml | 139 ----------------------------------- 2 files changed, 207 deletions(-) delete mode 100644 pipeline/main.yaml delete mode 100644 pipeline/pipeline-roles.yaml diff --git a/pipeline/main.yaml b/pipeline/main.yaml deleted file mode 100644 index 5786400..0000000 --- a/pipeline/main.yaml +++ /dev/null @@ -1,68 +0,0 @@ -AWSTemplateFormatVersion: "2010-09-09" -Description: "Main template for a CI/CD Serverless application." -Parameters: - AppName: - Type: String - Description: Name of the application - MinLength: "1" - MaxLength: "80" - AllowedPattern: "[A-Za-z0-9-]+" - ConstraintDescription: Malformed input parameter. AppName must only contain upper and lower case letters, numbers, and -. - SAMInputFile: - Type: String - Description: The filename for the SAM file. - Default: lambda_file_processing.yml - SAMOutputFile: - Type: String - Description: The filename for the output SAM file from the buildspec file. - Default: post-sam.yaml - CodeBuildImage: - Type: String - Default: "aws/codebuild/nodejs:4.3.2" - Description: Image used for CodeBuild project. - CICDS3BucketName: - Type: String - Default: "sam-stuff" - Description: S3 Bucket where the pipeline templates live - GitHubRepoName: - Type: String - Default: "" - Description: The GitHub repo name - GitHubRepoBranch: - Type: String - Description: The GitHub repo branch code pipelines should watch for changes on - Default: master - GitHubUser: - Type: String - Description: GitHub UserName. This username must have access to the GitHubToken. - GitHubToken: - NoEcho: true - Type: String - Description: "Secret. OAuthToken with access to Repo. Long string of characters and digits. Go to https://github.com/settings/tokens" -Resources: - ServerlessRoles: - Type: "AWS::CloudFormation::Stack" - Properties: - Parameters: - AppName: !Ref AppName - TemplateURL: - Fn::Sub: https://${CICDS3BucketName}.s3.amazonaws.com/templates/pipeline-roles.yaml - ServerlessPipeline: - Type: "AWS::CloudFormation::Stack" - DependsOn: [ServerlessRoles] - Properties: - Parameters: - AppName: !Ref AppName - SAMInputFile: !Ref SAMInputFile - SAMOutputFile: !Ref SAMOutputFile - CodeBuildImage: !Ref CodeBuildImage - GitHubRepoName: !Ref GitHubRepoName - GitHubRepoBranch: !Ref GitHubRepoBranch - GitHubUser: !Ref GitHubUser - GitHubToken: !Ref GitHubToken - CICDS3BucketName: !Ref CICDS3BucketName - CodePipelineRole: !GetAtt ServerlessRoles.Outputs.CodePipelineRole - CloudformationRole: !GetAtt ServerlessRoles.Outputs.CloudformationDeployRole - CodeBuildRole: !GetAtt ServerlessRoles.Outputs.CodeBuildRole - TemplateURL: - Fn::Sub: https://${CICDS3BucketName}.s3.amazonaws.com/templates/pipeline.yaml diff --git a/pipeline/pipeline-roles.yaml b/pipeline/pipeline-roles.yaml deleted file mode 100644 index 5d2e759..0000000 --- a/pipeline/pipeline-roles.yaml +++ /dev/null @@ -1,139 +0,0 @@ -AWSTemplateFormatVersion: "2010-09-09" -Description: Common resources for application deployed to Lambda -Parameters: - AppName: - Type: String - Description: Name of the application. - MinLength: "1" - MaxLength: "100" -Resources: - CodeBuildTrustRole: - Description: Creating service role in IAM for AWS CodeBuild - Type: AWS::IAM::Role - Properties: - RoleName: !Sub "${AppName}-codebuild-role" - AssumeRolePolicyDocument: - Statement: - - Effect: Allow - Principal: - Service: [codebuild.amazonaws.com] - Action: sts:AssumeRole - Path: / - CodeBuildRolePolicy: - Type: AWS::IAM::Policy - DependsOn: CodeBuildTrustRole - Description: Setting IAM policy for the service role for AWS CodeBuild - Properties: - PolicyName: CodeBuildRolePolicy - PolicyDocument: - Statement: - - Effect: Allow - Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] - Resource: ["*"] - - Effect: Allow - Resource: ["*"] - Action: ["s3:*"] - - Effect: Allow - Resource: ["*"] - Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] - - Effect: Allow - Resource: ["*"] - Action: ["sns:SendMessage"] - Roles: [!Ref CodeBuildTrustRole] - CloudFormationTrustRole: - Description: Creating service role in IAM for AWS CloudFormation - Type: AWS::IAM::Role - Properties: - RoleName: !Sub "${AppName}-cloudformation-role" - AssumeRolePolicyDocument: - Statement: - - Effect: Allow - Principal: - Service: [cloudformation.amazonaws.com] - Action: sts:AssumeRole - Path: / - CloudFormationRolePolicy: - Type: AWS::IAM::Policy - DependsOn: CloudFormationTrustRole - Description: Setting IAM policy for the service role for AWS CloudFormation - Properties: - PolicyName: CloudFormationRolePolicy - PolicyDocument: - Statement: - - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] - Resource: "*" - Effect: Allow - - Action: ["s3:PutObject"] - Resource: ["arn:aws:s3:::codepipeline*"] - Effect: Allow - - Action: ["lambda:*"] - Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" - Effect: Allow - - Action: ["apigateway:*"] - Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" - Effect: Allow - - Action: ["sns:*"] - Resource: !Sub "arn:aws:sns:${AWS::Region}:*:*" - Effect: Allow - - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" - Effect: Allow - - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" - Effect: Allow - - Action: ["iam:PassRole"] - Resource: ["*"] - Effect: Allow - - Action: ["cloudformation:CreateChangeSet"] - Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" - Effect: Allow - - Action: ["cloudformation:CreateChangeSet"] - Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Include" - Effect: Allow - Roles: [!Ref CloudFormationTrustRole] - CodePipelineTrustRole: - Description: Creating service role in IAM for AWS CodePipeline - Type: AWS::IAM::Role - Properties: - RoleName: !Sub "${AppName}-codepipeline-role" - AssumeRolePolicyDocument: - Statement: - - Effect: Allow - Principal: - Service: [codepipeline.amazonaws.com] - Action: sts:AssumeRole - Path: / - CodePipelineRolePolicy: - Type: AWS::IAM::Policy - DependsOn: CodePipelineTrustRole - Description: Setting IAM policy for the service role for AWS CodePipeline - Properties: - PolicyName: CodePipelineRolePolicy - PolicyDocument: - Statement: - - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] - Resource: "*" - Effect: Allow - - Action: ["s3:PutObject"] - Resource: ["arn:aws:s3:::codepipeline*"] - Effect: Allow - - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] - Resource: "*" - Effect: Allow - - Action: ["cloudwatch:*", "s3:*", "sns:*", "cloudformation:*", "rds:*", "sqs:*", "iam:PassRole"] - Resource: "*" - Effect: Allow - - Action: ["lambda:InvokeFunction", "lambda:ListFunctions"] - Resource: "*" - Effect: Allow - Roles: [!Ref CodePipelineTrustRole] -Outputs: - CodePipelineRole: - Description: "Role for code pipeline" - Value: !GetAtt CodePipelineTrustRole.Arn - CloudformationDeployRole: - Description: "Role for cloudformation to deploy with." - Value: !GetAtt CloudFormationTrustRole.Arn - CodeBuildRole: - Description: "Role for code build to build" - Value: !GetAtt CodeBuildTrustRole.Arn From ed768d2b569b0663bf4763871ae0f06f84eb88a0 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 17 Jan 2020 15:56:42 +0000 Subject: [PATCH 051/115] added variables to make it more generic --- buildspec.yml | 7 ++----- pipeline/pipeline.yaml | 11 +++++------ 2 files changed, 7 insertions(+), 11 deletions(-) diff --git a/buildspec.yml b/buildspec.yml index af69355..31438eb 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -1,8 +1,5 @@ version: 0.2 -env: - variables: - ARTIFACT_BUCKET: "jr-amz-test" phases: install: runtime-versions: @@ -12,7 +9,7 @@ phases: - sam build --use-container post_build: commands: - - sam package --output-template-file packaged-template.yml --s3-bucket $ARTIFACT_BUCKET + - sam package --output-template-file $SAM_OUTPUT_TEMPLATE --s3-bucket $ARTIFACT_BUCKET artifacts: files: - - packaged-template.yml + - $SAM_OUTPUT_TEMPLATE diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 59dad02..39db6d2 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -4,10 +4,10 @@ Parameters: AppName: Type: String Description: Name of the application. - SAMInputFile: + SAMTemplateFile: Type: String - Default: "" - Description: The filename for the SAM file. + Default: "packaged-template.yml" + Description: The filename for the SAM Template file. SAMOutputFile: Type: String Default: "packaged-template.yml" @@ -41,11 +41,10 @@ Resources: Description: !Sub "Building stage for ${AppName}." Environment: ComputeType: BUILD_GENERAL1_SMALL + PrivilegedMode: True EnvironmentVariables: - - Name: S3_BUCKET + - Name: ARTIFACT_BUCKET Value: !Ref S3Bucket - - Name: INPUT_FILE - Value: !Ref SAMInputFile Image: !Ref CodeBuildImage Type: LINUX_CONTAINER Name: !Sub "${AppName}-build" From cec7752b9cea8c562d5b076e20d6c39d9c448d9c Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 20 Jan 2020 11:28:39 +0000 Subject: [PATCH 052/115] improved permissions --- pipeline/pipeline.yaml | 32 ++++++++++++++++++++------------ 1 file changed, 20 insertions(+), 12 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 39db6d2..3298634 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -4,10 +4,6 @@ Parameters: AppName: Type: String Description: Name of the application. - SAMTemplateFile: - Type: String - Default: "packaged-template.yml" - Description: The filename for the SAM Template file. SAMOutputFile: Type: String Default: "packaged-template.yml" @@ -30,6 +26,9 @@ Parameters: NoEcho: true Type: String Description: "Secret. OAuthToken with access to Repo. Long string of characters and digits. Go to https://github.com/settings/tokens" + AlarmRecipientEmailAddress: + Type: String + Description: Email address for any alerts. Resources: CodeBuildProject: DependsOn: [S3Bucket] @@ -45,6 +44,8 @@ Resources: EnvironmentVariables: - Name: ARTIFACT_BUCKET Value: !Ref S3Bucket + - Name: SAM_OUTPUT_TEMPLATE + Value: !Ref SAMOutputFile Image: !Ref CodeBuildImage Type: LINUX_CONTAINER Name: !Sub "${AppName}-build" @@ -139,6 +140,7 @@ Resources: ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" + ParameterOverrides: !Sub '{"AlarmRecipientEmailAddress": "${AlarmRecipientEmailAddress}"}' RunOrder: 1 - Name: execute-changeset InputArtifacts: [] @@ -209,7 +211,7 @@ Resources: PolicyName: CloudFormationRolePolicy PolicyDocument: Statement: - - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] + - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] Resource: "*" Effect: Allow - Action: ["s3:PutObject"] @@ -218,25 +220,31 @@ Resources: - Action: ["lambda:*"] Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" Effect: Allow - - Action: ["dynamo:*"] - Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + - Action: ["lambda:CreateEventSourceMapping", "lambda:DeleteEventSourceMapping", "lambda:GetEventSourceMapping", "lambda:UpdateEventSourceMapping" ] + Resource: "*" + Effect: Allow + - Action: ["dynamodb:*"] + Resource: "*" Effect: Allow - Action: ["sqs:*"] - Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Resource: "*" Effect: Allow - Action: ["cloudwatch:*"] - Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Resource: "*" Effect: Allow - Action: ["cloudtrail:*"] - Resource: !Sub "arn:aws:apigateway:${AWS::Region}::*" + Resource: "*" + Effect: Allow + - Action: ["events:*"] + Resource: "*" Effect: Allow - Action: ["sns:*"] Resource: !Sub "arn:aws:sns:${AWS::Region}:*:*" Effect: Allow - - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole"] + - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy"] + - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy", "iam:DeleteRolePolicy", "iam:getRolePolicy", "iam:PutRolePolicy"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - Action: ["iam:PassRole"] From 34179f617b25ec29df49007dee745058dcf5180a Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 22 Jan 2020 15:11:23 +0000 Subject: [PATCH 053/115] Updated roles for least privilage --- pipeline/pipeline.yaml | 85 ++++++++++++++++++++++-------------------- 1 file changed, 45 insertions(+), 40 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 3298634..3e77c60 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -3,6 +3,7 @@ Description: "Template for full CI/CD serverless applications." Parameters: AppName: Type: String + Default: "lambda-file-refarch" Description: Name of the application. SAMOutputFile: Type: String @@ -32,7 +33,7 @@ Parameters: Resources: CodeBuildProject: DependsOn: [S3Bucket] - Description: Creating AWS CodeBuild project + Description: AWS CodeBuild project Type: AWS::CodeBuild::Project Properties: Artifacts: @@ -57,16 +58,15 @@ Resources: Value: !Ref AppName TimeoutInMinutes: 5 S3Bucket: - Description: Creating Amazon S3 bucket for AWS CodePipeline artifacts + Description: S3 bucket for AWS CodePipeline artifacts Type: AWS::S3::Bucket - DeletionPolicy: Retain Properties: BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}" VersioningConfiguration: Status: Enabled S3ArtifactBucketPolicy: DependsOn: [S3Bucket] - Description: Setting Amazon S3 bucket policy for AWS CodePipeline access + Description: S3 bucket policy for AWS CodePipeline access Type: AWS::S3::BucketPolicy Properties: Bucket: !Ref S3Bucket @@ -84,7 +84,7 @@ Resources: aws:SecureTransport: false ProjectPipeline: DependsOn: [S3Bucket, CodeBuildProject] - Description: Creating a deployment pipeline for your project in AWS CodePipeline + Description: AWS CodePipeline deployment pipeline for project Type: AWS::CodePipeline::Pipeline Properties: Name: !Sub "${AppName}-pipeline" @@ -159,7 +159,7 @@ Resources: Type: S3 Location: !Ref S3Bucket CodeBuildTrustRole: - Description: Creating service role in IAM for AWS CodeBuild + Description: Service role for AWS CodeBuild Type: AWS::IAM::Role Properties: RoleName: !Sub "${AppName}-codebuild-role" @@ -173,26 +173,23 @@ Resources: CodeBuildRolePolicy: Type: AWS::IAM::Policy DependsOn: CodeBuildTrustRole - Description: Setting IAM policy for the service role for AWS CodeBuild + Description: IAM policy for the service role for AWS CodeBuild Properties: PolicyName: CodeBuildRolePolicy PolicyDocument: Statement: - Effect: Allow Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] - Resource: ["*"] + Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" - Effect: Allow - Resource: ["*"] Action: ["s3:*"] + Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" - Effect: Allow - Resource: ["*"] Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] - - Effect: Allow - Resource: ["*"] - Action: ["sns:SendMessage"] + Resource: !Sub "arn:aws:kms:${AWS::Region}:${AWS::AccountId}:alias/aws/s3" Roles: [!Ref CodeBuildTrustRole] CloudFormationTrustRole: - Description: Creating service role in IAM for AWS CloudFormation + Description: Service role for AWS CloudFormation Type: AWS::IAM::Role Properties: RoleName: !Sub "${AppName}-cloudformation-role" @@ -206,40 +203,47 @@ Resources: CloudFormationRolePolicy: Type: AWS::IAM::Policy DependsOn: CloudFormationTrustRole - Description: Setting IAM policy for the service role for AWS CloudFormation + Description: IAM policy for the service role for AWS CloudFormation Deployment Properties: PolicyName: CloudFormationRolePolicy PolicyDocument: Statement: - - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] - Resource: "*" + - Action: ["s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] + Resource: + - !Sub "arn:aws:s3:::${AppName}-*-inputbucket-*" + - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*" + - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*" Effect: Allow - - Action: ["s3:PutObject"] - Resource: ["arn:aws:s3:::codepipeline*"] + - Action: ["s3:GetObject", "s3:GetObjectVersion"] + Resource: + - !Sub "arn:aws:s3:::${AppName}-*-inputbucket-*/*" + - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*/*" + - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*/*" + - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - Action: ["lambda:*"] Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" Effect: Allow - Action: ["lambda:CreateEventSourceMapping", "lambda:DeleteEventSourceMapping", "lambda:GetEventSourceMapping", "lambda:UpdateEventSourceMapping" ] - Resource: "*" + Resource: ["*"] Effect: Allow - Action: ["dynamodb:*"] - Resource: "*" + Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-serverless-stack-SentimentTable-*" Effect: Allow - Action: ["sqs:*"] - Resource: "*" + Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-*" Effect: Allow - Action: ["cloudwatch:*"] - Resource: "*" + Resource: !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:${AppName}-serverless-stack-*" Effect: Allow - Action: ["cloudtrail:*"] - Resource: "*" + Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/${AppName}-serverless-stack-InputBucketTrail*" Effect: Allow - Action: ["events:*"] - Resource: "*" + Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-serverless-stack-FileProcessingRule-*" Effect: Allow - Action: ["sns:*"] - Resource: !Sub "arn:aws:sns:${AWS::Region}:*:*" + Resource: !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-AlarmTopic-*" Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" @@ -248,7 +252,7 @@ Resources: Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - Action: ["iam:PassRole"] - Resource: ["*"] + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - Action: ["cloudformation:CreateChangeSet"] Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" @@ -258,7 +262,7 @@ Resources: Effect: Allow Roles: [!Ref CloudFormationTrustRole] CodePipelineTrustRole: - Description: Creating service role in IAM for AWS CodePipeline + Description: Service role for AWS CodePipeline Type: AWS::IAM::Role Properties: RoleName: !Sub "${AppName}-codepipeline-role" @@ -272,24 +276,25 @@ Resources: CodePipelineRolePolicy: Type: AWS::IAM::Policy DependsOn: CodePipelineTrustRole - Description: Setting IAM policy for the service role for AWS CodePipeline + Description: IAM policy for the service role for AWS CodePipeline Properties: PolicyName: CodePipelineRolePolicy PolicyDocument: Statement: - - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning"] - Resource: "*" - Effect: Allow - - Action: ["s3:PutObject"] - Resource: ["arn:aws:s3:::codepipeline*"] + - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning", "s3:PutObject"] + Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] - Resource: "*" + Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-build" Effect: Allow - - Action: ["cloudwatch:*", "s3:*", "sns:*", "cloudformation:*", "rds:*", "sqs:*", "iam:PassRole"] - Resource: "*" + - Action: ["cloudformation:*"] + Resource: + # - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack" + - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack/*" Effect: Allow - - Action: ["lambda:InvokeFunction", "lambda:ListFunctions"] - Resource: "*" + - Action: ["iam:PassRole"] + Resource: !GetAtt CloudFormationTrustRole.Arn Effect: Allow - Roles: [!Ref CodePipelineTrustRole] \ No newline at end of file + Roles: [!Ref CodePipelineTrustRole] + + From 70a8f9d4c23a6da4f4c44233e656fa87d5e049ef Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 22 Jan 2020 15:12:51 +0000 Subject: [PATCH 054/115] removed commented line --- pipeline/pipeline.yaml | 1 - 1 file changed, 1 deletion(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 3e77c60..9c4e34a 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -289,7 +289,6 @@ Resources: Effect: Allow - Action: ["cloudformation:*"] Resource: - # - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack" - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack/*" Effect: Allow - Action: ["iam:PassRole"] From e73baa0527f2041d1377b952bb9f0c405aee0b86 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 22 Jan 2020 10:24:56 -0500 Subject: [PATCH 055/115] Fix typo --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2ab634c..bae4777 100644 --- a/README.md +++ b/README.md @@ -189,9 +189,9 @@ creates the following resources: - **SentimentDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **SentimentDlq** within a 1 minute period and sends notification to the **AlarmTopic**. -- **ConversionQueueAlarm** - A CloudWatch Alarm that detect when there are too many messages in the **ConversionQueue** and sends notification to the **AlarmTopic**. +- **ConversionQueueAlarm** - A CloudWatch Alarm that detects when there are too many messages in the **ConversionQueue** and sends notification to the **AlarmTopic**. -- **SentimentQueueAlarm** - A CloudWatch Alarm that detect when there are too many messages in the **SentimentQueue** and sends notification to the **AlarmTopic**. +- **SentimentQueueAlarm** - A CloudWatch Alarm that detects when there are too many messages in the **SentimentQueue** and sends notification to the **AlarmTopic**. - **ConversionFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when the error rate for **ConversionFunction** is too high and sends notification to the **AlarmTopic**. From 6a7cd135c15411a76b16084a2fb77df0bec9aa50 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 22 Jan 2020 13:00:02 -0500 Subject: [PATCH 056/115] Update stat for many metrics in dashboard --- template.yml | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/template.yml b/template.yml index 6833dfb..d6b97c7 100644 --- a/template.yml +++ b/template.yml @@ -402,7 +402,7 @@ Resources: - Name: FunctionName Value: !Ref ConversionFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false - Id: m2 @@ -414,7 +414,7 @@ Resources: - Name: FunctionName Value: !Ref ConversionFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false EvaluationPeriods: 1 @@ -441,7 +441,7 @@ Resources: - Name: FunctionName Value: !Ref SentimentFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false - Id: m2 @@ -453,7 +453,7 @@ Resources: - Name: FunctionName Value: !Ref SentimentFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false EvaluationPeriods: 1 @@ -480,7 +480,7 @@ Resources: - Name: FunctionName Value: !Ref ConversionFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false - Id: m2 @@ -492,7 +492,7 @@ Resources: - Name: FunctionName Value: !Ref ConversionFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false EvaluationPeriods: 1 @@ -519,7 +519,7 @@ Resources: - Name: FunctionName Value: !Ref SentimentFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false - Id: m2 @@ -531,7 +531,7 @@ Resources: - Name: FunctionName Value: !Ref SentimentFunction Period: 300 - Stat: Average + Stat: Sum Unit: Count ReturnData: false EvaluationPeriods: 1 @@ -562,7 +562,7 @@ Resources: ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Conversion Function Invocations" } @@ -580,7 +580,7 @@ Resources: [ "AWS/Lambda", "Invocations", "FunctionName", "${ConversionFunction}", { "id": "m2", "visible": false } ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Conversion Function Error Rate" } @@ -598,7 +598,7 @@ Resources: [ "AWS/Lambda", "Invocations", "FunctionName", "${ConversionFunction}", { "id": "m2", "visible": false } ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Conversion Function Throttle Rate" } @@ -619,7 +619,7 @@ Resources: ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Conversion DLQ Length" } @@ -640,7 +640,7 @@ Resources: ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Sentiment Function Invocations" } @@ -658,7 +658,7 @@ Resources: [ "AWS/Lambda", "Invocations", "FunctionName", "${SentimentFunction}", { "id": "m2", "visible": false } ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Sentiment Function Error Rate" } @@ -676,7 +676,7 @@ Resources: [ "AWS/Lambda", "Invocations", "FunctionName", "${SentimentFunction}", { "id": "m2", "visible": false } ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Sentiment Function Throttle Rate" } @@ -697,7 +697,7 @@ Resources: ] ], "period":60, - "stat":"Average", + "stat":"Sum", "region": "${AWS::Region}", "title":"Sentiment DLQ Length" } From 0dd01f6116b9c140b7c286383a354d45c4f2b9c0 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 4 Mar 2020 11:38:19 +0000 Subject: [PATCH 057/115] updated diagram to reflect change to SNS event notification --- img/lambda-refarch-fileprocessing-simple.png | Bin 134504 -> 116953 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/img/lambda-refarch-fileprocessing-simple.png b/img/lambda-refarch-fileprocessing-simple.png index 2c2551ea9605aec81605a3bda1f774da760ffcca..32a36cd4b58625a031e76406a4d119fe1503b24f 100644 GIT binary patch literal 116953 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058/115] Refactor out EventBridge Use S3 Events and SNS in place of CloudTrail and EventBridge --- README.md | 103 ++++++++++++----------- cleanup.sh | 20 +++++ deploy.sh | 51 ++++++++++++ src/conversion/conversion.py | 128 ++++++++++++++-------------- src/sentiment/sentiment.py | 138 +++++++++++++++++-------------- template.yml | 156 ++++++++++++++--------------------- 6 files changed, 327 insertions(+), 269 deletions(-) create mode 100644 cleanup.sh create mode 100644 deploy.sh diff --git a/README.md b/README.md index bae4777..4a0dd95 100644 --- a/README.md +++ b/README.md @@ -12,70 +12,69 @@ In this example application we deliver the notes from an interview in Markdown f ### Event Trigger -Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilise [CloudWatch Events](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) and [CloudTrail](https://aws.amazon.com/cloudtrail/). A CloudWatch Events rule checks for S3 PutObject API calls into our Source Bucket using CloudTrail data. CloudTrail records when PutObject API is called. Our rule translates this record into an event, represented as a JSON object. We also define targets in our rule and deliver our JSON event to 2 seperate [SQS Queues](https://aws.amazon.com/sqs/), representing 2 different worflows. Other target types include AWS Lambda Functions, Kinesis Data Streams, Simple Notification Service, Step Functions state machines, and ECS tasks. Refer to [What is Amazon CloudWatch Events?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/WhatIsCloudWatchEvents.html) for more information about eligible targets. +Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilize [AWS S3 Events](https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html) and [Amazon Simple Notification Service](https://docs.aws.amazon.com/sns/latest/dg/welcome.html). When an object is created in S3, an event is emitted to a SNS topic. We deliver our event to 2 seperate [SQS Queues](https://aws.amazon.com/sqs/), representing 2 different workflows. Refer to [What is Amazon Simple Notification Service?](https://docs.aws.amazon.com/sns/latest/dg/welcome.html) for more information about eligible targets. ### Conversion Workflow We target a SQS queue for this workflow. Sending the JSON event to SQS first rather than directly to Lambda allows for more control of Lambda invocations and better error handling. -The Lambda service polls our queue. When messages are available it will send them to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. +The Lambda service polls our queue on our behalf. When messages are available they will be delivered to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. -If our Conversion Lambda function fails to process the messages, SQS sends the event to a dead-letter queue (DLQ) for inspection and reprocessing. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Conversion DLQ. +If our Conversion Lambda function fails to process the messages, the function sends the event to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Conversion DLQ. -Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function execution environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new html file to the HTML Bucket. +Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function execution environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new HTML file to an output S3 bucket. If our function execution results in an error, we will ### Sentiment Analysis Workflow We are using AWS' AI/ML service [Amazon Comprehend](https://aws.amazon.com/comprehend/) which is a machine learning powered service that makes it easy to find insights and relationships in text. We use the Sentiment Analysis API to understand whether interview responses are positive or negative. -The Sentiment workflow uses the same SQS-to-Lambda Function pattern as the Coversion workflow. Our function downloads the interview file, extracts the content, and sends it to the Comprehend Sentiment Analysis API. This returns a Sentiment and a confidence score which describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. +The Sentiment workflow uses the same SQS-to-Lambda Function pattern as the Coversion workflow. Our function downloads the markdown file, extracts the contents, and sends it to the Comprehend Sentiment Analysis API. This returns a Sentiment and a confidence score which describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. Once we have our sentiment we persist the result to our [DynamoDB](https://aws.amazon.com/dynamodb/) table. -If our Sentiment Lambda function fails to process the messages, SQS sends the event to a dead-letter queue (DLQ) for inspection and reprocessing. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Sentiment DLQ. +If our Sentiment Lambda function fails to process the messages, the function sends the event to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Sentiment DLQ. -## Running the Example - -You can use the provided [AWS SAM template](./template.yml) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *SAM Template Resources* section of this document. +## Deploying the Application +The application is built, packaged, and deployed using the [AWS SAM CLI](https://github.com/awslabs/aws-sam-cli). -### Using SAM to Build and Deploy the Application - -#### Build +You can use the provided [AWS SAM template](./template.yml) to launch a stack that demonstrates the Lambda file processing reference architecture. Details about the resources created by this template are provided in the *SAM Template Resources* section of this document. -The AWS SAM CLI comes with abstractions for a number of Lambda runtimes to build your dependencies, and copies the source code into staging folders so that everything is ready to be packaged and deployed. The *sam build* command builds any dependencies that your application has, and copies your application source code to folders under *.aws-sam/build* to be zipped and uploaded to Lambda. +The sample can be built and deployed by running the script `deploy.sh`. ```bash -sam build --use-container +bash deploy.sh s3_bucketname aws_region email_address_to_receive_alarm_messages + +# eg bash deploy.sh my_s3_bucket us-east-1 user@mydomain.com ``` -#### Package +**Note** -Next, run *sam package*. This command takes your Lambda handler source code and any third-party dependencies, zips everything, and uploads the zip file to your Amazon S3 bucket. That bucket and file location are then noted in the packaged-template.yaml file. You use the generated packaged-template.yaml file to deploy the application in the next step. +The S3 bucket *s3_bucketname* must exist prior to running the *deploy.sh* script. This bucket is used the sam package command to store the deployment package. If you need to create a bucket for this purpose, run the following command to create an Amazon S3 bucket: ```bash -sam package \ - --output-template-file packaged-template.yml \ - --s3-bucket bucketname +aws s3 mb s3://bucketname --region region # Example regions: us-east-1, ap-east-1, eu-central-1, sa-east-1 ``` -**Note** +### What Is Happening in the Script? -For *bucketname* in this command, you need an Amazon S3 bucket that the sam package command can use to store the deployment package. The deployment package is used when you deploy your application in a later step. If you need to create a bucket for this purpose, run the following command to create an Amazon S3 bucket: +The *sam build* command builds your application dependencies and copies the source code to folders under *.aws-sam/build* to be zipped and uploaded to Lambda. ```bash -aws s3 mb s3://bucketname --region region # Example regions: us-east-1, ap-east-1, eu-central-1, sa-east-1 +sam build --use-container ``` -#### Deploy - -This command deploys your application to the AWS Cloud. It's important that this command explicitly includes both of the following: +The *sam package* command takes your Lambda handler source code and any third-party dependencies, zips everything, and uploads the zip file to your Amazon S3 bucket. That bucket and file location are then noted in the packaged-template.yaml file. The generated packaged-template.yaml file is used to deploy the application. - * The AWS Region to deploy to. This Region must match the Region of the Amazon S3 source bucket. +```bash +sam package \ + --output-template-file packaged-template.yml \ + --s3-bucket bucketname +``` - * The CAPABILITY_IAM parameter, because creating new Lambda functions involves creating new IAM roles. +The *sam deploy* command deploys your application to the AWS Cloud. ```bash sam deploy \ @@ -119,12 +118,18 @@ You can also view the CloudWatch logs generated by the Lambda functions. ## Cleaning Up the Example Resources -To remove all resources created by this example, do the following: +To remove all resources created by this example, run the following command: + +```bash +bash cleanup.sh +``` + +### What Is Happening in the Script? -### Delete Objects in the Input and Output Buckets. +Objects are cleared out from the `InputBucket` and `ConversionTargetBucket`. ```bash -for bucket in InputBucket CloudTrailBucket ConversionTargetBucket; do +for bucket in InputBucket ConversionTargetBucket; do echo "Clearing out ${bucket}..." BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) aws s3 rm s3://${BUCKET} --recursive @@ -132,14 +137,14 @@ for bucket in InputBucket CloudTrailBucket ConversionTargetBucket; do done ``` -### Delete the CloudFormation Stack +The CloudFormation stack is deleted. ```bash aws cloudformation delete-stack \ --stack-name lambda-file-refarch ``` -### Delete the CloudWatch Log Groups +The CloudWatch Logs Groups associated with the Lambda functions are deleted. ```bash for log_group in $(aws logs describe-log-groups --log-group-name-prefix '/aws/lambda/lambda-file-refarch-' --query "logGroups[*].logGroupName" --output text); do @@ -157,21 +162,19 @@ creates the following resources: - **InputBucket** - An S3 bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger processing functions. -- **CloudTrailBucket** - An S3 bucket that is used to store CloudTrail data. - -- **InputBucketTrail** - An CloudTrail definition that captures events put into the **CloudTrailBucket**. +- **NotificationTopic** - A SNS topic that receives S3 events from the **InputBucket**. -- **CloudTrailBucketPolicy** - A S3 policy which permits the AWS CloudTrail service to write data to the **CloudTrailBucket**. +- **NotificationTopicPolicy** - A SNS topic policy that allows the **InputBucket** to publish events to the **NotificationTopic**. -- **FileProcessingQueuePolicy** - A SQS policy that allows the **FileProcessingRule** to publish events to the **ConversionQueue** and **SentimentQueue**. +- **NotificationQueuePolicy** - A SQS queue policy that allows the **NotificationTopic** to publish events to the **ConversionQueue** and **SentimentQueue**. -- **FileProcessingRule** - A CloudWatch Events Rule that monitors CloudTrail `PutObject` events to the **InputBucket**. +- **ConversionSubscription** - A SNS subscription that allows the **ConversionQueue** to receive messages from **NotificationTopic**. - **ConversionQueue** - A SQS queue that is used to store events for conversion from Markdown to HTML. - **ConversionDlq** - A SQS queue that is used to capture messages that cannot be processed by the **ConversionFunction**. The *RedrivePolicy* on the **ConversionQueue** is used to manage how traffic makes it to this queue. -- **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. +- **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. Errors in the function will be sent to the **ConversionDlq**. - **ConversionTargetBucket** - A S3 bucket that stores the converted HTML. @@ -179,29 +182,29 @@ creates the following resources: - **SentimentDlq** - A SQS queue that is used to capture messages that cannot be processed by the **SentimentFunction**. The *RedrivePolicy* on the **SentimentQueue** is used to manage how traffic makes it to this queue. -- **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. +- **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. Errors in the function will be sent to the **SentimentDlq**. - **SentimentTable** - A DynamoDB table that stores the input file along with the sentiment. -- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive CloudWatch Alarms. +- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive alarms from the **ConversionDlqAlarm** and **SentimentDlqAlarm**. -- **ConversionDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **ConvesionDlq** within a 1 minute period and sends notification to the **AlarmTopic**. +- **ConversionDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **ConvesionDlq** within a 1 minute period and sends a notification to the **AlarmTopic**. -- **SentimentDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **SentimentDlq** within a 1 minute period and sends notification to the **AlarmTopic**. +- **SentimentDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **SentimentDlq** within a 1 minute period and sends a notification to the **AlarmTopic**. -- **ConversionQueueAlarm** - A CloudWatch Alarm that detects when there are too many messages in the **ConversionQueue** and sends notification to the **AlarmTopic**. +- **ConversionQueueAlarm** - A CloudWatch Alarm that detects when there are 20 or more messages in the **ConversionQueue** within a 1 minute period and sends a notification to the **AlarmTopic**. -- **SentimentQueueAlarm** - A CloudWatch Alarm that detects when there are too many messages in the **SentimentQueue** and sends notification to the **AlarmTopic**. +- **SentimentQueueAlarm** - A CloudWatch Alarm that detects when there are 20 or more messages in the **SentimentQueue** within a 1 minute period and sends a notification to the **AlarmTopic**. -- **ConversionFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when the error rate for **ConversionFunction** is too high and sends notification to the **AlarmTopic**. +- **ConversionFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when there is an error rate of 5% over a 5 minute period for the **ConversionFunction** and sends a notification to the **AlarmTopic**. -- **SentimentFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when the error rate for **SentimentFunction** is too high and sends notification to the **AlarmTopic**. +- **SentimentFunctionErrorRateAlarm** - A CloudWatch Alarm that detects when there is an error rate of 5% over a 5 minute period for the **SentimentFunction** and sends a notification to the **AlarmTopic**. -- **ConversionFunctionThrottleRateAlarm** - A CloudWatch Alarm that detects when the throttle rate for **ConversionFunction** is too high and sends notification to the **AlarmTopic**. +- **ConversionFunctionThrottleRateAlarm** - A CloudWatch Alarm that detects when ther is a throttle rate of 1% over a 5 minute period for the **ConversionFunction** and sends a notification to the **AlarmTopic**. -- **SentimentFunctionThrottleRateAlarm** - A CloudWatch Alarm that detects when the throttle rate for **SentimentFunction** is too high and sends notification to the **AlarmTopic**. +- **SentimentFunctionThrottleRateAlarm** - A CloudWatch Alarm that detects when ther is a throttle rate of 1% over a 5 minute period for the **SentimentFunction** and sends a notification to the **AlarmTopic**. -- **ApplicationDashboard** - A CloudWatch Dashboard that presents Lambda function Invocations, Lambda function error and throttle rates, and visible SQS messages. +- **ApplicationDashboard** - A CloudWatch Dashboard that displays Conversion Function Invocations, Conversion Function Error Rate, Conversion Function Throttle Rate, Conversion DLQ Length, Sentiment Function Invocations, Sentiment Function Error Rate, Sentiment Function Throttle Rate, and Sentiment DLQ Length. ## License diff --git a/cleanup.sh b/cleanup.sh new file mode 100644 index 0000000..ecdf945 --- /dev/null +++ b/cleanup.sh @@ -0,0 +1,20 @@ +#!/bin/bash + + +echo "Clearing out resources of lambda-file-refarch stack..." +echo +echo "Cleaning up S3 buckets..." && for bucket in InputBucket ConversionTargetBucket; do + echo "Clearing out ${bucket}..." + BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) + aws s3 rm s3://${BUCKET} --recursive + echo +done + +echo "Deleting CloudFormation stack..." && aws cloudformation delete-stack \ + --stack-name lambda-file-refarch + +echo "Clearing out CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/lambda/lambda-file-refarch- --query "logGroups[*].logGroupName" --output text); do + echo "Removing log group ${log_group}..." + aws logs delete-log-group --log-group-name ${log_group} + echo +done diff --git a/deploy.sh b/deploy.sh new file mode 100644 index 0000000..8ead219 --- /dev/null +++ b/deploy.sh @@ -0,0 +1,51 @@ +#!/bin/bash + +if (( ${#} < 3)); then + echo "USAGE: ${0} s3_package_bucket_name aws_region recipient_email" + exit 1 +fi + +### +# Variables +### +export SAM_TEMPLATE="template.yml" +export PACKAGED_TEMPLATE="packaged-template.yml" +export STACK_NAME="lambda-file-refarch" +export S3_CODE_BUCKET=${1} +export AWS_REGION=${2} +export RECIPIENT_EMAIL=${3} +export SAM_BUILD_ARG=${4} # Possible to pass in --skip-pull-image if docker image is already local +export FILE_TO_UPDATE="src/conversion/conversion.py" + +### +# Functions +### +function sam-runner { + sam build --use-container ${SAM_BUILD_ARG} + sam package --output-template-file ${PACKAGED_TEMPLATE} \ + --s3-bucket ${S3_CODE_BUCKET} # 2> /dev/null + sam deploy \ + --template-file ${PACKAGED_TEMPLATE} \ + --stack-name ${STACK_NAME} \ + --region ${AWS_REGION} \ + --tags Project=lambda-refarch-fileprocessing \ + --parameter-overrides AlarmRecipientEmailAddress=${RECIPIENT_EMAIL} \ + --capabilities CAPABILITY_IAM +} + +### +# Main body +### + +# Need to run two passes of the CF template to mitigate race condition. +# Please refer to https://aws.amazon.com/premiumsupport/knowledge-center/unable-validate-destination-s3/ +# for more detailed information. +sed -i '' '30,33 s/^/#/' ${SAM_TEMPLATE} +echo '' >> ${FILE_TO_UPDATE} +sam-runner +echo +sed -i '' '30,33 s/^#//' ${SAM_TEMPLATE} +echo '' >> ${FILE_TO_UPDATE} +sam-runner +git checkout ${FILE_TO_UPDATE} +echo \ No newline at end of file diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index a4c4f77..efdad17 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -170,7 +170,8 @@ def upload_html(bucket, key, source_file): def handler(event, context): - aws_lambda_logging.setup(level=log_level, aws_request_id=context.aws_request_id) + aws_lambda_logging.setup(level=log_level, + aws_request_id=context.aws_request_id) for record in event['Records']: tmpdir = tempfile.mkdtemp() @@ -179,66 +180,73 @@ def handler(event, context): try: json_body = json.loads(record['body']) - request_params = json_body['detail']['requestParameters'] - bucket_name = request_params['bucketName'] - key_name = request_params['key'] - size = check_s3_object_size(bucket_name, key_name) - - if size >= max_object_size: - error_message = f'Source S3 object s3://{bucket_name}/{key_name} is larger ' - error_message += f'than {max_object_size} (max object bytes)' - log.error(error_message) - raise Exception('Source S3 object too large') - - local_file = os.path.join(tmpdir, key_name) - - download_status = get_s3_object(bucket_name, key_name, local_file) - - if download_status == 'ok': - log.info(f'Success: Download to {local_file} for conversion') - else: - log.error(f'Fail to put object to {local_file}') - raise Exception(f'Fail to put object to {local_file}') - - html = convert_to_html(local_file) - - html_filename = os.path.splitext(key_name)[0] + '.html' - - local_html_file = os.path.join(tmpdir, html_filename) - - with open(local_html_file, 'w') as outfile: - outfile.write(html) - log.info(f'''Success: Converted s3://{bucket_name}/{key_name} - to {local_html_file}''') - outfile.close() - - html_upload = upload_html( - target_bucket, - html_filename, - local_html_file) - - if html_upload == 'ok': - '''If function could put the converted file to the S3 bucket then - remove message from the SQS queue''' - try: - sqs_client.delete_message( - QueueUrl=conversion_queue, - ReceiptHandle=sqs_receipt_handle - ) - except Exception as e: - log.error(f'{str(e)}') - raise Exception(str(e)) - - dst_s3_object = f's3://{target_bucket}/{html_filename}' - success_message = f'Success: Uploaded {local_html_file} to ' - success_message += f'{dst_s3_object}' - log.info(success_message) - else: - error_message = f'Could not upload file to ' - error_message += f'{dst_s3_object}: {str(e)}' - log.error(error_message) - raise Exception(error_message) + for record in json_body['Records']: + bucket_name = record['s3']['bucket']['name'] + key_name = record['s3']['object']['key'] + + size = check_s3_object_size(bucket_name, key_name) + + if size >= max_object_size: + error_message = f'Source S3 object ' + error_message = f's3://{bucket_name}/{key_name} is larger ' + error_message += f'than {max_object_size} ' + error_message += f'(max object bytes)' + log.error(error_message) + raise Exception('Source S3 object too large') + + local_file = os.path.join(tmpdir, key_name) + + download_status = get_s3_object(bucket_name, + key_name, + local_file) + + if download_status == 'ok': + success_message = f'Success: Download to ' + success_message += f'{local_file} for conversion' + log.info(success_message) + else: + log.error(f'Fail to put object to {local_file}') + raise Exception(f'Fail to put object to {local_file}') + + html = convert_to_html(local_file) + + html_filename = os.path.splitext(key_name)[0] + '.html' + + local_html_file = os.path.join(tmpdir, html_filename) + + with open(local_html_file, 'w') as outfile: + outfile.write(html) + log.info(f'''Success: Converted s3://{bucket_name}/{key_name} + to {local_html_file}''') + outfile.close() + + html_upload = upload_html( + target_bucket, + html_filename, + local_html_file) + + if html_upload == 'ok': + '''If function could put the converted file to the S3 bucket then + remove message from the SQS queue''' + try: + sqs_client.delete_message( + QueueUrl=conversion_queue, + ReceiptHandle=sqs_receipt_handle + ) + except Exception as e: + log.error(f'{str(e)}') + raise Exception(str(e)) + + dst_s3_object = f's3://{target_bucket}/{html_filename}' + success_message = f'Success: Uploaded {local_html_file} ' + success_message += f'to {dst_s3_object}' + log.info(success_message) + else: + error_message = f'Could not upload file to ' + error_message += f'{dst_s3_object}: {str(e)}' + log.error(error_message) + raise Exception(error_message) except Exception as e: log.error(f'Could not convert record: {str(e)}') raise Exception(f'Could not convert record: {str(e)}') diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 7d5184b..7974e3c 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -145,7 +145,6 @@ def put_sentiment(s3_object, sentiment): result = f'Error: {str(e)}' log.error(response) - xray_recorder.end_subsegment() return(result) @@ -161,70 +160,81 @@ def handler(event, context): try: json_body = json.loads(record['body']) - request_params = json_body['detail']['requestParameters'] - bucket_name = request_params['bucketName'] - key_name = request_params['key'] - - size = check_s3_object_size(bucket_name, key_name) - - if size >= max_object_size: - error_message = f'Source S3 object ' - error_message += f's3://{bucket_name}/{key_name} is larger ' - error_message += f'than {max_object_size} (max object bytes)' - log.error(error_message) - raise Exception(error_message) - - if size == 'NaN': - exc = f'Could not get size for s3://{bucket_name}/{key_name}' - raise Exception(exc) - - local_file = os.path.join(tmpdir, key_name) - - download_status = get_s3_object(bucket_name, key_name, local_file) - - if download_status == 'ok': - log.info(f'Download to {local_file} for sentiment analysis') - else: - log.error(f'Download failure to {local_file}') - raise Exception(f'Download failure to {local_file}') - md_contents = open(local_file, 'r').read() - - sentiment = comprehend_client.detect_sentiment( - Text=md_contents, - LanguageCode='en' - ) - - overall_sentiment = sentiment['Sentiment'] - sentiment_score = sentiment['SentimentScore'] - - sentiment_message = f'{overall_sentiment} ({sentiment_score})' - log.info(sentiment_message) - - source_s3_object = f's3://{bucket_name}/{key_name}' - - put_sentiment_result = put_sentiment(source_s3_object, sentiment) - - if put_sentiment_result == 'ok': - '''If function could put the sentiment to the DDB table then - remove message from SQS queue.''' - try: - sqs_client.delete_message( - QueueUrl=s_queue, - ReceiptHandle=sqs_receipt_handle - ) - except Exception as e: - err_msg = f'Could not remove message from queue: {str(e)}' - log.error(err_msg) - raise Exception(err_msg) - - sentiment_db_msg = f'Put sentiment to {s_table}' - log.info(sentiment_db_msg) - else: - db_put_error_msg = f'Could not put sentiment to {s_table}: ' - db_put_error_msg += f'{put_sentiment_result}' - log.error(db_put_error_msg) - raise Exception(db_put_error_msg) + for record in json_body['Records']: + bucket_name = record['s3']['bucket']['name'] + key_name = record['s3']['object']['key'] + + size = check_s3_object_size(bucket_name, key_name) + + if size >= max_object_size: + error_message = f'Source S3 object ' + error_message += f's3://{bucket_name}/{key_name} ' + error_message += f'is larger ' + error_message += f'than {max_object_size} ' + error_message += f'(max object bytes)' + log.error(error_message) + raise Exception(error_message) + + if size == 'NaN': + exc = f'Could not get size for ' + exc += f's3://{bucket_name}/{key_name}' + raise Exception(exc) + + local_file = os.path.join(tmpdir, key_name) + + download_status = get_s3_object(bucket_name, + key_name, + local_file) + + if download_status == 'ok': + success_message = f'Download to {local_file} ' + success_message += f'for sentiment analysis' + log.info(success_message) + else: + log.error(f'Download failure to {local_file}') + raise Exception(f'Download failure to {local_file}') + + md_contents = open(local_file, 'r').read() + + sentiment = comprehend_client.detect_sentiment( + Text=md_contents, + LanguageCode='en' + ) + + overall_sentiment = sentiment['Sentiment'] + sentiment_score = sentiment['SentimentScore'] + + sentiment_message = f'{overall_sentiment} ({sentiment_score})' + log.info(sentiment_message) + + source_s3_object = f's3://{bucket_name}/{key_name}' + + put_sentiment_result = put_sentiment(source_s3_object, + sentiment) + + if put_sentiment_result == 'ok': + '''If function could put the sentiment to the DDB table then + remove message from SQS queue.''' + try: + sqs_client.delete_message( + QueueUrl=s_queue, + ReceiptHandle=sqs_receipt_handle + ) + except Exception as e: + err_msg = f'Could not remove message ' + err_msg += f'from queue: {str(e)}' + log.error(err_msg) + raise Exception(err_msg) + + sentiment_db_msg = f'Put sentiment to {s_table}' + log.info(sentiment_db_msg) + else: + db_put_error_msg = f'Could not put sentiment ' + db_put_error_msg += f'to {s_table}: ' + db_put_error_msg += f'{put_sentiment_result}' + log.error(db_put_error_msg) + raise Exception(db_put_error_msg) except Exception as e: log.error(f'Could not get sentiment: {str(e)}') raise Exception(f'Could not get sentiment: {str(e)}') diff --git a/template.yml b/template.yml index d6b97c7..d4932f5 100644 --- a/template.yml +++ b/template.yml @@ -25,112 +25,60 @@ Parameters: Resources: InputBucket: Type: AWS::S3::Bucket - - CloudTrailBucket: - Type: AWS::S3::Bucket - - InputBucketTrail: - DependsOn: CloudTrailBucketPolicy - Type: AWS::CloudTrail::Trail - Properties: - S3BucketName: !Ref CloudTrailBucket - EventSelectors: - - DataResources: - - Type: 'AWS::S3::Object' - Values: - - !Sub |- - arn:aws:s3:::${InputBucket}/ - IncludeManagementEvents: false - ReadWriteType: WriteOnly - IsLogging: true - - CloudTrailBucketPolicy: - Type: AWS::S3::BucketPolicy - DependsOn: CloudTrailBucket - Properties: - Bucket: !Ref CloudTrailBucket - PolicyDocument: - Version: "2012-10-17" - Statement: - - - Sid: "AWSCloudTrailAclCheck" - Effect: "Allow" - Principal: - Service: "cloudtrail.amazonaws.com" - Action: "s3:GetBucketAcl" - Resource: !Sub |- - arn:aws:s3:::${CloudTrailBucket} - - - Sid: "AWSCloudTrailWrite" - Effect: "Allow" - Principal: - Service: "cloudtrail.amazonaws.com" - Action: "s3:PutObject" - Resource: - !Sub |- - arn:aws:s3:::${CloudTrailBucket}/AWSLogs/${AWS::AccountId}/* - Condition: - StringEquals: - s3:x-amz-acl: "bucket-owner-full-control" + Properties: + BucketName: !Sub ${AWS::StackName}-${AWS::AccountId}-input-bucket + NotificationConfiguration: + TopicConfigurations: + - Event: s3:ObjectCreated:* + Topic: !Ref NotificationTopic - FileProcessingQueuePolicy: - # https://forums.aws.amazon.com/message.jspa?messageID=743094 - Type: AWS::SQS::QueuePolicy + NotificationTopic: + Type: AWS::SNS::Topic + + NotificationTopicPolicy: + Type: AWS::SNS::TopicPolicy Properties: - Queues: - - !Ref ConversionQueue - - !Ref SentimentQueue PolicyDocument: Version: '2012-10-17' Statement: - - - Effect: Allow - Principal: - AWS: '*' - Action: - - sqs:SendMessage - Resource: !GetAtt ConversionQueue.Arn + - Effect: Allow + Principal: "*" + Action: SNS:Publish + Resource: !Ref NotificationTopic Condition: + StringEquals: + aws:SourceAccount: !Sub ${AWS::AccountId} ArnEquals: - aws:SourceArn: !GetAtt FileProcessingRule.Arn - - - Effect: Allow - Principal: - AWS: '*' + aws:SourceArn: !Sub "arn:aws:s3:::${InputBucket}" + Topics: + - !Ref NotificationTopic + + NotificationQueuePolicy: + Type: AWS::SQS::QueuePolicy + Properties: + PolicyDocument: + Version: '2012-10-17' + Statement: + - Effect: Allow + Principal: "*" Action: - sqs:SendMessage - Resource: !GetAtt SentimentQueue.Arn + Resource: "*" Condition: - ArnEquals: - aws:SourceArn: !GetAtt FileProcessingRule.Arn + ArnEquals: + aws:SourceArn: !Ref NotificationTopic + Queues: + - !Ref ConversionQueue + - !Ref SentimentQueue - FileProcessingRule: - Type: AWS::Events::Rule - DependsOn: - - ConversionQueue - - SentimentQueue + ConversionSubscription: + Type: AWS::SNS::Subscription Properties: - Description: Rule to capture S3 PutObject events - EventPattern: - source: - - aws.s3 - detail-type: - - AWS API Call via CloudTrail - detail: - eventSource: - - s3.amazonaws.com - eventName: - - PutObject - requestParameters: - bucketName: - - !Ref InputBucket - State: 'ENABLED' - Targets: - - Arn: !GetAtt ConversionQueue.Arn - Id: Convert - - Arn: !GetAtt SentimentQueue.Arn - Id: Sentiment - + TopicArn: !Ref NotificationTopic + Endpoint: !GetAtt ConversionQueue.Arn + Protocol: sqs + RawMessageDelivery: true + ConversionQueue: Type: AWS::SQS::Queue DependsOn: ConversionDlq @@ -202,6 +150,11 @@ Resources: TARGET_BUCKET: !Ref ConversionTargetBucket CONVERSION_QUEUE: !Ref ConversionQueue LOG_LEVEL: !Ref ConversionLogLevel + EventInvokeConfig: + DestinationConfig: + OnFailure: + Type: SQS + Destination: !GetAtt ConversionDlq.Arn Events: ConversionQueueReaderEvent: Type: SQS @@ -212,6 +165,14 @@ Resources: ConversionTargetBucket: Type: AWS::S3::Bucket + SentimentSubscription: + Type: AWS::SNS::Subscription + Properties: + TopicArn: !Ref NotificationTopic + Endpoint: !GetAtt SentimentQueue.Arn + Protocol: sqs + RawMessageDelivery: true + SentimentQueue: Type: AWS::SQS::Queue DependsOn: SentimentDlq @@ -290,6 +251,11 @@ Resources: SENTIMENT_TABLE: !Ref SentimentTable SENTIMENT_QUEUE: !Ref SentimentQueue LOG_LEVEL: !Ref SentimentLogLevel + EventInvokeConfig: + DestinationConfig: + OnFailure: + Type: SQS + Destination: !GetAtt SentimentDlq.Arn Events: SentimentQueueReaderEvent: Type: SQS @@ -347,7 +313,7 @@ Resources: - Name: QueueName Value: !GetAtt SentimentDlq.QueueName - ConverstionQueueAlarm: + ConversionQueueAlarm: Type: AWS::CloudWatch::Alarm Properties: AlarmDescription: Conversion queue has too many messages From ab8b186858d6ad9cab7136d112722d90e21a2640 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 12 Mar 2020 11:34:22 +0000 Subject: [PATCH 059/115] updated pipeline permissions --- pipeline/pipeline.yaml | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 9c4e34a..a31410f 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -243,8 +243,10 @@ Resources: Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-serverless-stack-FileProcessingRule-*" Effect: Allow - Action: ["sns:*"] - Resource: !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-AlarmTopic-*" - Effect: Allow + Resource: + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-AlarmTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-NotificationTopic-*" + Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow From 02d42523820e7203454cc80b02c2d5b691d857fb Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 12 Mar 2020 11:46:35 +0000 Subject: [PATCH 060/115] made app name static --- pipeline/pipeline.yaml | 80 ++++++++++++++++++++---------------------- 1 file changed, 38 insertions(+), 42 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index a31410f..457ce20 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -1,10 +1,6 @@ AWSTemplateFormatVersion: "2010-09-09" Description: "Template for full CI/CD serverless applications." Parameters: - AppName: - Type: String - Default: "lambda-file-refarch" - Description: Name of the application. SAMOutputFile: Type: String Default: "packaged-template.yml" @@ -38,7 +34,7 @@ Resources: Properties: Artifacts: Type: CODEPIPELINE - Description: !Sub "Building stage for ${AppName}." + Description: !Sub "Building stage for lambda-file-refarch." Environment: ComputeType: BUILD_GENERAL1_SMALL PrivilegedMode: True @@ -49,19 +45,19 @@ Resources: Value: !Ref SAMOutputFile Image: !Ref CodeBuildImage Type: LINUX_CONTAINER - Name: !Sub "${AppName}-build" + Name: !Sub "lambda-file-refarch-build" ServiceRole: !GetAtt CodeBuildTrustRole.Arn Source: Type: CODEPIPELINE Tags: - Key: app-name - Value: !Ref AppName + Value: "lambda-file-refarch" TimeoutInMinutes: 5 S3Bucket: Description: S3 bucket for AWS CodePipeline artifacts Type: AWS::S3::Bucket Properties: - BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}" + BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch" VersioningConfiguration: Status: Enabled S3ArtifactBucketPolicy: @@ -87,7 +83,7 @@ Resources: Description: AWS CodePipeline deployment pipeline for project Type: AWS::CodePipeline::Pipeline Properties: - Name: !Sub "${AppName}-pipeline" + Name: !Sub "lambda-file-refarch-pipeline" RoleArn: !GetAtt CodePipelineTrustRole.Arn Stages: - Name: Source @@ -100,7 +96,7 @@ Resources: Owner: ThirdParty Provider: GitHub OutputArtifacts: - - Name: !Sub "${AppName}-SourceArtifact" + - Name: !Sub "lambda-file-refarch-SourceArtifact" Configuration: Repo: !Ref GitHubRepoName Branch: !Ref GitHubRepoBranch @@ -111,22 +107,22 @@ Resources: Actions: - Name: build-from-source InputArtifacts: - - Name: !Sub "${AppName}-SourceArtifact" + - Name: !Sub "lambda-file-refarch-SourceArtifact" ActionTypeId: Category: Build Owner: AWS Version: "1" Provider: CodeBuild OutputArtifacts: - - Name: !Sub "${AppName}-BuildArtifact" + - Name: !Sub "lambda-file-refarch-BuildArtifact" Configuration: - ProjectName: !Sub "${AppName}-build" + ProjectName: !Sub "lambda-file-refarch-build" RunOrder: 1 - Name: Deploy Actions: - Name: create-changeset InputArtifacts: - - Name: !Sub "${AppName}-BuildArtifact" + - Name: !Sub "lambda-file-refarch-BuildArtifact" ActionTypeId: Category: Deploy Owner: AWS @@ -134,12 +130,12 @@ Resources: Provider: CloudFormation OutputArtifacts: [] Configuration: - StackName: !Sub "${AppName}-serverless-stack" + StackName: !Sub "lambda-file-refarch-serverless-stack" ActionMode: CHANGE_SET_REPLACE RoleArn: !GetAtt CloudFormationTrustRole.Arn ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM - TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" + TemplatePath: !Sub "lambda-file-refarch-BuildArtifact::${SAMOutputFile}" ParameterOverrides: !Sub '{"AlarmRecipientEmailAddress": "${AlarmRecipientEmailAddress}"}' RunOrder: 1 - Name: execute-changeset @@ -151,7 +147,7 @@ Resources: Provider: CloudFormation OutputArtifacts: [] Configuration: - StackName: !Sub "${AppName}-serverless-stack" + StackName: !Sub "lambda-file-refarch-serverless-stack" ActionMode: CHANGE_SET_EXECUTE ChangeSetName: pipeline-changeset RunOrder: 2 @@ -162,7 +158,7 @@ Resources: Description: Service role for AWS CodeBuild Type: AWS::IAM::Role Properties: - RoleName: !Sub "${AppName}-codebuild-role" + RoleName: !Sub "lambda-file-refarch-codebuild-role" AssumeRolePolicyDocument: Statement: - Effect: Allow @@ -180,10 +176,10 @@ Resources: Statement: - Effect: Allow Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] - Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" + Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/lambda-file-refarch-build*" - Effect: Allow Action: ["s3:*"] - Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch/*" - Effect: Allow Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] Resource: !Sub "arn:aws:kms:${AWS::Region}:${AWS::AccountId}:alias/aws/s3" @@ -192,7 +188,7 @@ Resources: Description: Service role for AWS CloudFormation Type: AWS::IAM::Role Properties: - RoleName: !Sub "${AppName}-cloudformation-role" + RoleName: !Sub "lambda-file-refarch-cloudformation-role" AssumeRolePolicyDocument: Statement: - Effect: Allow @@ -210,16 +206,16 @@ Resources: Statement: - Action: ["s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] Resource: - - !Sub "arn:aws:s3:::${AppName}-*-inputbucket-*" - - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*" - - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*" + - !Sub "arn:aws:s3:::lambda-file-refarch-*-inputbucket-*" + - !Sub "arn:aws:s3:::lambda-file-refarch-*-cloudtrailbucket-*" + - !Sub "arn:aws:s3:::lambda-file-refarch-*-conversiontargetbucket-*" Effect: Allow - Action: ["s3:GetObject", "s3:GetObjectVersion"] Resource: - - !Sub "arn:aws:s3:::${AppName}-*-inputbucket-*/*" - - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*/*" - - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*/*" - - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + - !Sub "arn:aws:s3:::lambda-file-refarch-*-inputbucket-*/*" + - !Sub "arn:aws:s3:::lambda-file-refarch-*-cloudtrailbucket-*/*" + - !Sub "arn:aws:s3:::lambda-file-refarch-*-conversiontargetbucket-*/*" + - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch/*" Effect: Allow - Action: ["lambda:*"] Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" @@ -228,33 +224,33 @@ Resources: Resource: ["*"] Effect: Allow - Action: ["dynamodb:*"] - Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-serverless-stack-SentimentTable-*" + Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/lambda-file-refarch-serverless-stack-SentimentTable-*" Effect: Allow - Action: ["sqs:*"] - Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-*" + Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:lambda-file-refarch-serverless-stack-*" Effect: Allow - Action: ["cloudwatch:*"] - Resource: !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:${AppName}-serverless-stack-*" + Resource: !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:lambda-file-refarch-serverless-stack-*" Effect: Allow - Action: ["cloudtrail:*"] - Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/${AppName}-serverless-stack-InputBucketTrail*" + Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/lambda-file-refarch-serverless-stack-InputBucketTrail*" Effect: Allow - Action: ["events:*"] - Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-serverless-stack-FileProcessingRule-*" + Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/lambda-file-refarch-serverless-stack-FileProcessingRule-*" Effect: Allow - Action: ["sns:*"] Resource: - - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-AlarmTopic-*" - - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-NotificationTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:lambda-file-refarch-serverless-stack-AlarmTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:lambda-file-refarch-serverless-stack-NotificationTopic-*" Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/lambda-file-refarch-*" Effect: Allow - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy", "iam:DeleteRolePolicy", "iam:getRolePolicy", "iam:PutRolePolicy"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/lambda-file-refarch-*" Effect: Allow - Action: ["iam:PassRole"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/lambda-file-refarch-*" Effect: Allow - Action: ["cloudformation:CreateChangeSet"] Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" @@ -267,7 +263,7 @@ Resources: Description: Service role for AWS CodePipeline Type: AWS::IAM::Role Properties: - RoleName: !Sub "${AppName}-codepipeline-role" + RoleName: !Sub "lambda-file-refarch-codepipeline-role" AssumeRolePolicyDocument: Statement: - Effect: Allow @@ -284,14 +280,14 @@ Resources: PolicyDocument: Statement: - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning", "s3:PutObject"] - Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch/*" Effect: Allow - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] - Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-build" + Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/lambda-file-refarch-build" Effect: Allow - Action: ["cloudformation:*"] Resource: - - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack/*" + - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/lambda-file-refarch-serverless-stack/*" Effect: Allow - Action: ["iam:PassRole"] Resource: !GetAtt CloudFormationTrustRole.Arn From 6a019378a13c3bbe5e818671235f794d3ed8dbfe Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 12 Mar 2020 12:16:22 +0000 Subject: [PATCH 061/115] reverted to appname --- pipeline/pipeline.yaml | 82 ++++++++++++++++++++++-------------------- 1 file changed, 43 insertions(+), 39 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 457ce20..2bba1c5 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -1,9 +1,13 @@ AWSTemplateFormatVersion: "2010-09-09" Description: "Template for full CI/CD serverless applications." Parameters: + AppName: + Type: String + Default: lambda-file-refarch + Description: Name used for application deployment SAMOutputFile: Type: String - Default: "packaged-template.yml" + Default: packaged-template.yml Description: The filename for the output SAM file from the buildspec file CodeBuildImage: Type: String @@ -34,7 +38,7 @@ Resources: Properties: Artifacts: Type: CODEPIPELINE - Description: !Sub "Building stage for lambda-file-refarch." + Description: !Sub "Building stage for ${AppName}." Environment: ComputeType: BUILD_GENERAL1_SMALL PrivilegedMode: True @@ -45,19 +49,19 @@ Resources: Value: !Ref SAMOutputFile Image: !Ref CodeBuildImage Type: LINUX_CONTAINER - Name: !Sub "lambda-file-refarch-build" + Name: !Sub "${AppName}-build" ServiceRole: !GetAtt CodeBuildTrustRole.Arn Source: Type: CODEPIPELINE Tags: - Key: app-name - Value: "lambda-file-refarch" + Value: !Ref AppName TimeoutInMinutes: 5 S3Bucket: Description: S3 bucket for AWS CodePipeline artifacts Type: AWS::S3::Bucket Properties: - BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch" + BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}" VersioningConfiguration: Status: Enabled S3ArtifactBucketPolicy: @@ -83,7 +87,7 @@ Resources: Description: AWS CodePipeline deployment pipeline for project Type: AWS::CodePipeline::Pipeline Properties: - Name: !Sub "lambda-file-refarch-pipeline" + Name: !Sub "${AppName}-pipeline" RoleArn: !GetAtt CodePipelineTrustRole.Arn Stages: - Name: Source @@ -96,7 +100,7 @@ Resources: Owner: ThirdParty Provider: GitHub OutputArtifacts: - - Name: !Sub "lambda-file-refarch-SourceArtifact" + - Name: !Sub "${AppName}-SourceArtifact" Configuration: Repo: !Ref GitHubRepoName Branch: !Ref GitHubRepoBranch @@ -107,22 +111,22 @@ Resources: Actions: - Name: build-from-source InputArtifacts: - - Name: !Sub "lambda-file-refarch-SourceArtifact" + - Name: !Sub "${AppName}-SourceArtifact" ActionTypeId: Category: Build Owner: AWS Version: "1" Provider: CodeBuild OutputArtifacts: - - Name: !Sub "lambda-file-refarch-BuildArtifact" + - Name: !Sub "${AppName}-BuildArtifact" Configuration: - ProjectName: !Sub "lambda-file-refarch-build" + ProjectName: !Sub "${AppName}-build" RunOrder: 1 - Name: Deploy Actions: - Name: create-changeset InputArtifacts: - - Name: !Sub "lambda-file-refarch-BuildArtifact" + - Name: !Sub "${AppName}-BuildArtifact" ActionTypeId: Category: Deploy Owner: AWS @@ -130,12 +134,12 @@ Resources: Provider: CloudFormation OutputArtifacts: [] Configuration: - StackName: !Sub "lambda-file-refarch-serverless-stack" + StackName: !Sub "${AppName}-serverless-stack" ActionMode: CHANGE_SET_REPLACE RoleArn: !GetAtt CloudFormationTrustRole.Arn ChangeSetName: pipeline-changeset Capabilities: CAPABILITY_NAMED_IAM - TemplatePath: !Sub "lambda-file-refarch-BuildArtifact::${SAMOutputFile}" + TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" ParameterOverrides: !Sub '{"AlarmRecipientEmailAddress": "${AlarmRecipientEmailAddress}"}' RunOrder: 1 - Name: execute-changeset @@ -147,7 +151,7 @@ Resources: Provider: CloudFormation OutputArtifacts: [] Configuration: - StackName: !Sub "lambda-file-refarch-serverless-stack" + StackName: !Sub "${AppName}-serverless-stack" ActionMode: CHANGE_SET_EXECUTE ChangeSetName: pipeline-changeset RunOrder: 2 @@ -158,7 +162,7 @@ Resources: Description: Service role for AWS CodeBuild Type: AWS::IAM::Role Properties: - RoleName: !Sub "lambda-file-refarch-codebuild-role" + RoleName: !Sub "${AppName}-codebuild-role" AssumeRolePolicyDocument: Statement: - Effect: Allow @@ -176,10 +180,10 @@ Resources: Statement: - Effect: Allow Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] - Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/lambda-file-refarch-build*" + Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" - Effect: Allow Action: ["s3:*"] - Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch/*" + Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" - Effect: Allow Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] Resource: !Sub "arn:aws:kms:${AWS::Region}:${AWS::AccountId}:alias/aws/s3" @@ -188,7 +192,7 @@ Resources: Description: Service role for AWS CloudFormation Type: AWS::IAM::Role Properties: - RoleName: !Sub "lambda-file-refarch-cloudformation-role" + RoleName: !Sub "${AppName}-cloudformation-role" AssumeRolePolicyDocument: Statement: - Effect: Allow @@ -206,16 +210,16 @@ Resources: Statement: - Action: ["s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] Resource: - - !Sub "arn:aws:s3:::lambda-file-refarch-*-inputbucket-*" - - !Sub "arn:aws:s3:::lambda-file-refarch-*-cloudtrailbucket-*" - - !Sub "arn:aws:s3:::lambda-file-refarch-*-conversiontargetbucket-*" + - !Sub "arn:aws:s3:::*-*-inputbucket" + - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*" + - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*" Effect: Allow - Action: ["s3:GetObject", "s3:GetObjectVersion"] Resource: - - !Sub "arn:aws:s3:::lambda-file-refarch-*-inputbucket-*/*" - - !Sub "arn:aws:s3:::lambda-file-refarch-*-cloudtrailbucket-*/*" - - !Sub "arn:aws:s3:::lambda-file-refarch-*-conversiontargetbucket-*/*" - - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch/*" + - !Sub "arn:aws:s3:::${AppName}-*-inputbucket/*" + - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*/*" + - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*/*" + - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - Action: ["lambda:*"] Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" @@ -224,33 +228,33 @@ Resources: Resource: ["*"] Effect: Allow - Action: ["dynamodb:*"] - Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/lambda-file-refarch-serverless-stack-SentimentTable-*" + Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-serverless-stack-SentimentTable-*" Effect: Allow - Action: ["sqs:*"] - Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:lambda-file-refarch-serverless-stack-*" + Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-*" Effect: Allow - Action: ["cloudwatch:*"] - Resource: !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:lambda-file-refarch-serverless-stack-*" + Resource: !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:${AppName}-serverless-stack-*" Effect: Allow - Action: ["cloudtrail:*"] - Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/lambda-file-refarch-serverless-stack-InputBucketTrail*" + Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/${AppName}-serverless-stack-InputBucketTrail*" Effect: Allow - Action: ["events:*"] - Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/lambda-file-refarch-serverless-stack-FileProcessingRule-*" + Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-serverless-stack-FileProcessingRule-*" Effect: Allow - Action: ["sns:*"] Resource: - - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:lambda-file-refarch-serverless-stack-AlarmTopic-*" - - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:lambda-file-refarch-serverless-stack-NotificationTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-AlarmTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-NotificationTopic-*" Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/lambda-file-refarch-*" + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy", "iam:DeleteRolePolicy", "iam:getRolePolicy", "iam:PutRolePolicy"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/lambda-file-refarch-*" + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - Action: ["iam:PassRole"] - Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/lambda-file-refarch-*" + Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - Action: ["cloudformation:CreateChangeSet"] Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" @@ -263,7 +267,7 @@ Resources: Description: Service role for AWS CodePipeline Type: AWS::IAM::Role Properties: - RoleName: !Sub "lambda-file-refarch-codepipeline-role" + RoleName: !Sub "${AppName}-codepipeline-role" AssumeRolePolicyDocument: Statement: - Effect: Allow @@ -280,14 +284,14 @@ Resources: PolicyDocument: Statement: - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning", "s3:PutObject"] - Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-lambda-file-refarch/*" + Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] - Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/lambda-file-refarch-build" + Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-build" Effect: Allow - Action: ["cloudformation:*"] Resource: - - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/lambda-file-refarch-serverless-stack/*" + - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack/*" Effect: Allow - Action: ["iam:PassRole"] Resource: !GetAtt CloudFormationTrustRole.Arn From 3ce4c070e49cf6a86ed9e1e851ad886839aa43b4 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 12 Mar 2020 13:37:46 +0000 Subject: [PATCH 062/115] added missing permissions --- pipeline/pipeline.yaml | 27 ++++++++++++++++----------- 1 file changed, 16 insertions(+), 11 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 2bba1c5..554d613 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -134,7 +134,7 @@ Resources: Provider: CloudFormation OutputArtifacts: [] Configuration: - StackName: !Sub "${AppName}-serverless-stack" + StackName: !Sub "${AppName}" ActionMode: CHANGE_SET_REPLACE RoleArn: !GetAtt CloudFormationTrustRole.Arn ChangeSetName: pipeline-changeset @@ -151,7 +151,7 @@ Resources: Provider: CloudFormation OutputArtifacts: [] Configuration: - StackName: !Sub "${AppName}-serverless-stack" + StackName: !Sub "${AppName}" ActionMode: CHANGE_SET_EXECUTE ChangeSetName: pipeline-changeset RunOrder: 2 @@ -208,7 +208,7 @@ Resources: PolicyName: CloudFormationRolePolicy PolicyDocument: Statement: - - Action: ["s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] + - Action: ["s3:PutBucketNotification", "s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] Resource: - !Sub "arn:aws:s3:::*-*-inputbucket" - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*" @@ -224,28 +224,33 @@ Resources: - Action: ["lambda:*"] Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" Effect: Allow + - Action: ["lambda:PutFunctionEventInvokeConfig"] + Resource: ["*"] + Effect: Allow - Action: ["lambda:CreateEventSourceMapping", "lambda:DeleteEventSourceMapping", "lambda:GetEventSourceMapping", "lambda:UpdateEventSourceMapping" ] Resource: ["*"] Effect: Allow - Action: ["dynamodb:*"] - Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-serverless-stack-SentimentTable-*" + Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-SentimentTable-*" Effect: Allow - Action: ["sqs:*"] - Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-*" + Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${AppName}-*" Effect: Allow - Action: ["cloudwatch:*"] - Resource: !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:${AppName}-serverless-stack-*" + Resource: + - !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:${AppName}-*" + - !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:dashboard/${AppName}" Effect: Allow - Action: ["cloudtrail:*"] - Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/${AppName}-serverless-stack-InputBucketTrail*" + Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/${AppName}-InputBucketTrail*" Effect: Allow - Action: ["events:*"] - Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-serverless-stack-FileProcessingRule-*" + Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-FileProcessingRule-*" Effect: Allow - Action: ["sns:*"] Resource: - - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-AlarmTopic-*" - - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-serverless-stack-NotificationTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-AlarmTopic-*" + - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-NotificationTopic-*" Effect: Allow - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" @@ -291,7 +296,7 @@ Resources: Effect: Allow - Action: ["cloudformation:*"] Resource: - - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}-serverless-stack/*" + - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}/*" Effect: Allow - Action: ["iam:PassRole"] Resource: !GetAtt CloudFormationTrustRole.Arn From 0bdc3ca93c268c9ce9d40c432261f4e822d36d1a Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 12 Mar 2020 16:16:34 +0000 Subject: [PATCH 063/115] tidied up naming and permissions --- pipeline/pipeline.yaml | 81 ++++++++++++++++++++++++++++-------------- 1 file changed, 55 insertions(+), 26 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 554d613..31b5b44 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -179,13 +179,19 @@ Resources: PolicyDocument: Statement: - Effect: Allow - Action: ["logs:CreateLogGroup", "logs:CreateLogStream", "logs:PutLogEvents"] + Action: + - logs:CreateLogGroup + - logs:CreateLogStream + - logs:PutLogEvents Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" - Effect: Allow Action: ["s3:*"] Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" - Effect: Allow - Action: ["kms:GenerateDataKey*", "kms:Encrypt", "kms:Decrypt"] + Action: + - kms:GenerateDataKey* + - kms:Encrypt + - kms:Decrypt Resource: !Sub "arn:aws:kms:${AWS::Region}:${AWS::AccountId}:alias/aws/s3" Roles: [!Ref CodeBuildTrustRole] CloudFormationTrustRole: @@ -208,65 +214,88 @@ Resources: PolicyName: CloudFormationRolePolicy PolicyDocument: Statement: - - Action: ["s3:PutBucketNotification", "s3:GetBucketVersioning", "s3:CreateBucket", "s3:DeleteBucket", "s3:GetBucketPolicy", "s3:DeleteBucketPolicy", "s3:PutBucketPolicy"] + - Action: + - s3:PutBucketNotification + - s3:GetBucketVersioning + - s3:CreateBucket + - s3:DeleteBucket + - s3:GetBucketPolicy + - s3:DeleteBucketPolicy + - s3:PutBucketPolicy Resource: - !Sub "arn:aws:s3:::*-*-inputbucket" - - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*" - - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*" + - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*" Effect: Allow - - Action: ["s3:GetObject", "s3:GetObjectVersion"] + + - Action: + - s3:GetObject + - s3:GetObjectVersion Resource: - - !Sub "arn:aws:s3:::${AppName}-*-inputbucket/*" - - !Sub "arn:aws:s3:::${AppName}-*-cloudtrailbucket-*/*" - - !Sub "arn:aws:s3:::${AppName}-*-conversiontargetbucket-*/*" - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow + - Action: ["lambda:*"] Resource: !Sub "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:*" Effect: Allow - - Action: ["lambda:PutFunctionEventInvokeConfig"] - Resource: ["*"] - Effect: Allow - - Action: ["lambda:CreateEventSourceMapping", "lambda:DeleteEventSourceMapping", "lambda:GetEventSourceMapping", "lambda:UpdateEventSourceMapping" ] + + - Action: + - lambda:CreateEventSourceMapping + - lambda:DeleteEventSourceMapping + - lambda:GetEventSourceMapping + - lambda:UpdateEventSourceMapping + - lambda:PutFunctionEventInvokeConfig + - lambda:DeleteFunctionEventInvokeConfig + - lambda:UpdateFunctionEventInvokeConfig Resource: ["*"] Effect: Allow + - Action: ["dynamodb:*"] Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-SentimentTable-*" Effect: Allow + - Action: ["sqs:*"] Resource: !Sub "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${AppName}-*" Effect: Allow + - Action: ["cloudwatch:*"] Resource: - !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:alarm:${AppName}-*" - - !Sub "arn:aws:cloudwatch:${AWS::Region}:${AWS::AccountId}:dashboard/${AppName}" - Effect: Allow - - Action: ["cloudtrail:*"] - Resource: !Sub "arn:aws:cloudtrail:${AWS::Region}:${AWS::AccountId}:trail/${AppName}-InputBucketTrail*" - Effect: Allow - - Action: ["events:*"] - Resource: !Sub "arn:aws:events:${AWS::Region}:${AWS::AccountId}:rule/${AppName}-FileProcessingRule-*" + - !Sub "arn:aws:cloudwatch::${AWS::AccountId}:dashboard/${AppName}" Effect: Allow + - Action: ["sns:*"] Resource: - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-AlarmTopic-*" - !Sub "arn:aws:sns:${AWS::Region}:${AWS::AccountId}:${AppName}-NotificationTopic-*" Effect: Allow - - Action: ["iam:GetRole", "iam:CreateRole", "iam:DeleteRole", "iam:TagRole"] + + - Action: + - iam:GetRole + - iam:CreateRole + - iam:DeleteRole + - iam:TagRole Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - - Action: ["iam:AttachRolePolicy", "iam:DetachRolePolicy", "iam:DeleteRolePolicy", "iam:getRolePolicy", "iam:PutRolePolicy"] + + - Action: + - iam:AttachRolePolicy + - iam:DetachRolePolicy + - iam:DeleteRolePolicy + - iam:getRolePolicy + - iam:PutRolePolicy Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow + - Action: ["iam:PassRole"] Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow + - Action: ["cloudformation:CreateChangeSet"] - Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" - Effect: Allow - - Action: ["cloudformation:CreateChangeSet"] - Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Include" + Resource: + - !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" + - !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Include" Effect: Allow + Roles: [!Ref CloudFormationTrustRole] CodePipelineTrustRole: Description: Service role for AWS CodePipeline From 615e93591769327a18fcd05f13b1df322ccab588 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 13 Mar 2020 11:21:38 +0000 Subject: [PATCH 064/115] added pipeline documentation --- PIPELINE-README.md | 74 ++++++++++++++++++ ...refarch-fileprocessing-simple-pipeline.png | Bin 0 -> 95074 bytes pipeline/pipeline.yaml | 22 ++++-- 3 files changed, 90 insertions(+), 6 deletions(-) create mode 100644 PIPELINE-README.md create mode 100644 img/lambda-refarch-fileprocessing-simple-pipeline.png diff --git a/PIPELINE-README.md b/PIPELINE-README.md new file mode 100644 index 0000000..21a284d --- /dev/null +++ b/PIPELINE-README.md @@ -0,0 +1,74 @@ +# Serverless Reference Architecture: Real-time File Processing Deployment Pipeline + +The Real-time File Processing reference pipeline architecture is an example of using basic CI/CD pipeline using the AWS fully managed continuous delivery service [CodePipeline](https://aws.amazon.com/codepipeline/) in order to deploy a Serverless application. Our pipeline consists of source, build and deployment stages. +We use exactly the same method as in the manual deployment however we utilise [CodeBuild](https://aws.amazon.com/codebuild/) to build and package our application and the native CodePipeline CloudFormation support to deploy our package. + +## CI/CD Pipeline Diagram + +![Reference Architecture - Real-time File Processing CI/CD Pipeline](img/lambda-refarch-fileprocessing-simple-pipeline.png) + +## Pipeline Components + +### CloudFormation Template + +pipeline/pipeline.yml is a CloudFormation template that will deploy all the required pipeline components. Once the stack has deployed the Pipeline will automatically execute and deploy the Serverless Application. See getting started for information on how to deploy the template. + +#### Deployed Resources + +* Pipeline S3 bucket, used to store pipeline artefacts that are passed between stages. +* CodePipeline +* CodeBuild Project +* Roles for CodePipeline, CodeBuild and the CloudFormation Deployment + +### Source + +For this application we are hosting our source code in GitHub. Other [Source Integrations](https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action-type.html#integrations-source) are available however this template focuses on GitHub. Whenever an update is pushed to the GitHub branch being +monitored our pipeline will being executing. The source stage will connect to GitHub using the credentials provided and download the branch into our pipelines artefact bucket for use in the other stages. + +### Build + +In order to run our SAM build and SAM package commands we are using the fully managed continuous integration service [CodeBuild](https://aws.amazon.com/codebuild/) CodeBuild allows us to perform a sequence of commands that we define in the [BuildSpec.yml](https://docs.aws.amazon.com/codebuild/latest/userguide/build-spec-ref.html) +file that will execute inside the [build environment](https://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref.html) we define using a docker container. For this project we are using the Amazon Linux 2 version 1.0 container with Python 3.7. + +Within the buildspec.yml we are: + +* Updating SAM to the latest version +* Running SAM build as per the manual deployment +* Running SAM Package again as per the manual deployment steps +* Instructing CodeBuild to pass the output template back to the Pipeline for use in the deployment stage. + +### Deploy + +To deploy our application stack we are not using SAM Deploy, instead we are opting to use CodePipelines native support for CloudFormation. The Pipeline has a role it use with appropriate permissions to deploy the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) +and [approval actions](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-action-add.html) to demonstrate a manual approval workflow. The first deployment will not require approval however subsequent updates will. + +Additional resources will be deployed as per the main architecture documentation. + +## Getting started + +To get started you just need to deploy the pipeline CloudFormation stack using the template found in this repository under pipeline/pipeline.yaml in order for this to be successful you will need to provide some additional information. + + GitHub Repository information. + + GitHubRepoName: The name of the GitHub repository hosting your source code. + + GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. + + GitHubRepoOwner: the GitHub repository owner. e.g. awslabs + + GitHubToken: GitHub OAuthToken with access to be able to clone the repository. You can find more information in the [GitHub Documentation](https://github.com/settings/tokens) + + +### Deploying the template + +You can deploy the template using either the [AWS Console](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-create-stack.html) or the [AWS CLI](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-cli-creating-stack.html) + +## Clean-up + +In order to remove all resources created by this example you will first need to make sure the 3 S3 buckets are empty. + +* Pipeline artefact bucket +* Application input bucket +* Application conversion bucket + +Once that is complete you can remove both the Application Stack and the Pipeline Stack. diff --git a/img/lambda-refarch-fileprocessing-simple-pipeline.png b/img/lambda-refarch-fileprocessing-simple-pipeline.png new file mode 100644 index 0000000000000000000000000000000000000000..1237df86113430dd29a8f1691bd16bf26c647ada GIT binary patch literal 95074 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--- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -286,11 +286,13 @@ Resources: Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - - Action: ["iam:PassRole"] + - Action: + - iam:PassRole Resource: !Sub "arn:aws:iam::${AWS::AccountId}:role/${AppName}-*" Effect: Allow - - Action: ["cloudformation:CreateChangeSet"] + - Action: + - cloudformation:CreateChangeSet Resource: - !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Serverless-2016-10-31" - !Sub "arn:aws:cloudformation:${AWS::Region}:aws:transform/Include" @@ -317,17 +319,25 @@ Resources: PolicyName: CodePipelineRolePolicy PolicyDocument: Statement: - - Action: ["s3:GetObject", "s3:GetObjectVersion", "s3:GetBucketVersioning", "s3:PutObject"] + - Action: + - s3:GetObject + - s3:GetObjectVersion + - s3:GetBucketVersioning + - s3:PutObject Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - - Action: ["codebuild:StartBuild", "codebuild:BatchGetBuilds"] + - Action: + - codebuild:StartBuild + - codebuild:BatchGetBuilds Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-build" Effect: Allow - - Action: ["cloudformation:*"] + - Action: + - cloudformation:* Resource: - !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}/*" Effect: Allow - - Action: ["iam:PassRole"] + - Action: + - iam:PassRole Resource: !GetAtt CloudFormationTrustRole.Arn Effect: Allow Roles: [!Ref CodePipelineTrustRole] From 250646c8c8be7e5b4fd058d1bf95302078d977cd Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 13 Mar 2020 11:22:53 +0000 Subject: [PATCH 065/115] added pipeline documentation --- PIPELINE-README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/PIPELINE-README.md b/PIPELINE-README.md index 21a284d..0fd231c 100644 --- a/PIPELINE-README.md +++ b/PIPELINE-README.md @@ -48,8 +48,6 @@ Additional resources will be deployed as per the main architecture documentation To get started you just need to deploy the pipeline CloudFormation stack using the template found in this repository under pipeline/pipeline.yaml in order for this to be successful you will need to provide some additional information. - GitHub Repository information. - GitHubRepoName: The name of the GitHub repository hosting your source code. GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. @@ -58,6 +56,7 @@ To get started you just need to deploy the pipeline CloudFormation stack using t GitHubToken: GitHub OAuthToken with access to be able to clone the repository. You can find more information in the [GitHub Documentation](https://github.com/settings/tokens) + AlarmRecipientEmailAddress: You will need to provide an email address that can be used for configuring notifications ### Deploying the template From bd956360023a12198510ac135e8447f8b4683a2c Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 13 Mar 2020 11:24:08 +0000 Subject: [PATCH 066/115] updated buildspec to upgrade SAM --- buildspec.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/buildspec.yml b/buildspec.yml index 31438eb..40d62d5 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -4,6 +4,8 @@ phases: install: runtime-versions: python: 3.7 + commands: + - pip install --upgrade aws-sam-cli build: commands: - sam build --use-container @@ -13,3 +15,4 @@ phases: artifacts: files: - $SAM_OUTPUT_TEMPLATE + \ No newline at end of file From f7cda10817ea55605de7db6c05b8da5172cb94fe Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 13 Mar 2020 17:20:18 +0000 Subject: [PATCH 067/115] typos and wording corrections --- PIPELINE-README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/PIPELINE-README.md b/PIPELINE-README.md index 0fd231c..e076441 100644 --- a/PIPELINE-README.md +++ b/PIPELINE-README.md @@ -23,7 +23,7 @@ pipeline/pipeline.yml is a CloudFormation template that will deploy all the requ ### Source For this application we are hosting our source code in GitHub. Other [Source Integrations](https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action-type.html#integrations-source) are available however this template focuses on GitHub. Whenever an update is pushed to the GitHub branch being -monitored our pipeline will being executing. The source stage will connect to GitHub using the credentials provided and download the branch into our pipelines artefact bucket for use in the other stages. +monitored our pipeline will begin executing. The source stage will connect to GitHub using the credentials provided and clone the branch into our pipeline artefact bucket for use in the other stages. ### Build @@ -39,7 +39,7 @@ Within the buildspec.yml we are: ### Deploy -To deploy our application stack we are not using SAM Deploy, instead we are opting to use CodePipelines native support for CloudFormation. The Pipeline has a role it use with appropriate permissions to deploy the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) +To deploy our application stack we are not using SAM Deploy, instead we are opting to use CodePipelines native support for CloudFormation. The pipeline has a role it use with appropriate permissions to deploy the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) and [approval actions](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-action-add.html) to demonstrate a manual approval workflow. The first deployment will not require approval however subsequent updates will. Additional resources will be deployed as per the main architecture documentation. From 13bf463d0742801958a9d16b1492101b24ed9b6d Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 13 Mar 2020 18:46:29 +0000 Subject: [PATCH 068/115] new line correction --- PIPELINE-README.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/PIPELINE-README.md b/PIPELINE-README.md index e076441..98a229d 100644 --- a/PIPELINE-README.md +++ b/PIPELINE-README.md @@ -27,7 +27,7 @@ monitored our pipeline will begin executing. The source stage will connect to Gi ### Build -In order to run our SAM build and SAM package commands we are using the fully managed continuous integration service [CodeBuild](https://aws.amazon.com/codebuild/) CodeBuild allows us to perform a sequence of commands that we define in the [BuildSpec.yml](https://docs.aws.amazon.com/codebuild/latest/userguide/build-spec-ref.html) +In order to run our SAM build and SAM package commands we are using [CodeBuild](https://aws.amazon.com/codebuild/), a fully managed continuous integration service . Codebuild allows us to perform a sequence of commands that we define in the [BuildSpec.yml](https://docs.aws.amazon.com/codebuild/latest/userguide/build-spec-ref.html) file that will execute inside the [build environment](https://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref.html) we define using a docker container. For this project we are using the Amazon Linux 2 version 1.0 container with Python 3.7. Within the buildspec.yml we are: @@ -39,8 +39,7 @@ Within the buildspec.yml we are: ### Deploy -To deploy our application stack we are not using SAM Deploy, instead we are opting to use CodePipelines native support for CloudFormation. The pipeline has a role it use with appropriate permissions to deploy the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) -and [approval actions](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-action-add.html) to demonstrate a manual approval workflow. The first deployment will not require approval however subsequent updates will. +To deploy our application stack we are not using SAM Deploy, instead we are opting to use the CodePipeline native support for CloudFormation. The pipeline has a role it use with appropriate permissions to deploy the template created by the SAM package step which will create a stack containing the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) and [approval actions](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-action-add.html) to demonstrate a manual approval workflow. The first deployment will not require approval however subsequent updates will. Additional resources will be deployed as per the main architecture documentation. From fd9a6ba2f3c812f760b3735aa4798acdb907647a Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 16 Mar 2020 18:07:25 +0000 Subject: [PATCH 069/115] add well architected notes draft --- WELL-ARCHITECTED.md | 198 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 198 insertions(+) create mode 100644 WELL-ARCHITECTED.md diff --git a/WELL-ARCHITECTED.md b/WELL-ARCHITECTED.md new file mode 100644 index 0000000..14602de --- /dev/null +++ b/WELL-ARCHITECTED.md @@ -0,0 +1,198 @@ +## Operational Excellence + +#### OPS 1. How do you evaluate your Serverless application’s health? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Understand, analyze and alert on metrics provided out of the box +* [x] **[Best]** Use application, business, and operations metrics +* [x] **[Good]** Use distributed tracing and code is instrumented with additional context +* [ ] **[Good]** Use structured and centralized logging +
+ +* [ ] None of these + + +##### Notes + +The example uses structured logging output to Cloudwatch. For our example we only deploy to a single account so we don't require the use of cross account centralised logging. + +We have alarms configured with notifications should processing fail. + +We do not have a defined KPI within the application. We could however use a metric such as number of records processed within a given time frame and alert if this is outside of the defined thresholds. + +#### OPS 2. How do you approach application lifecycle management? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Use infrastructure as code and stages isolated in separate environments +* [x] **[Good]** Prototype new features using temporary environments +* [ ] **[Good]** Use a rollout deployment mechanism +* [ ] **[Good]** Use configuration management +* [ ] **[Good]** Review the function runtime deprecation policy +* [ ] **[Best]** Use CI/CD including automated testing across separate accounts +
+ +* [ ] None of these + + +##### Notes + +Our example utilizes infrastructure as code and includes a simple pipeline that will build and deploy within an individual account and to an individual environment. However the nature of this example means it can be deployed many times it's possible. You can for example deploy a staging pipeline that would watch a development branch and deploy and changes to the Staging application stack. You could also deploy a production pipeline stack that watches the master branch and merges here will trigger a production release. + +For this example a rollout mechanism would involve adopting either a Blue / Green deployment strategy with you controlling which input bucket a particular user hits . Alternatively for application business logic only changes these could be tested by having a notification invoke an alternate version of a lambda under specific conditions. + +### Security + +#### SEC 1: How do you control access to your Serverless API? + +* [x] Question does not apply to this workload +
+ +* [ ] **[Required]** Use appropriate endpoint type and mechanisms to secure access to your API +* [ ] **[Good]** Use authentication and authorization mechanisms +* [ ] **[Best]** Scope access based on identity’s metadata +
+ +* [ ] None of these + + +##### Notes + +#### SEC 2: How do you manage your Serverless application’s security boundaries? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Evaluate and define resource policies +* [x] **[Good]** Control network traffic at all layers +* [x] **[Best]** Smaller functions require fewer permissions +* [x] **[Required]** Use temporary credentials between resources and components +
+ +* [ ] None of these + + +##### Notes + +We use IAM policy to ensure that resources can only be called by other resources that should be calling them. + +The pipeline will assume a role with only the permissions it requires to deploy the application. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. + +This application does not use private networking. + +We have individual functions for each different piece of business logic. + +#### SEC 3: How do you implement Application Security in your workload?*** + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Review security awareness documents frequently +* [x] **[Required]** Store secrets that are used in your code securely +* [ ] **[Good]** Implement runtime protection to help prevent against malicious code execution +* [ ] **[Best]** Automatically review workload’s code dependencies/libraries +* [x] **[Best]** Validate inbound events +
+ +* [ ] None of these + + +##### Notes + +This application doesn't have any stored secrets. The GitHub token is required by CodeBuild, this is passed as a string for CloudFormation, it is not however visible within the CloudFormation console. This could be improved by manually creating a secrets manager entry for the token and replacing the CloudFormation parameter for the token with the secrets manager value by utilising Dynamic References. +https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/dynamic-references.html + +For reviewing dependencies and libraries we could integrate an automatic check into the pipeline. There are many tools and providers which can check code. Currently this is manual using PEP8 and Bandit manual checks. + +We only check for particular events and check to make sure the object is valid. + + +### Reliability + +#### REL 1. How do you regulate inbound request rates? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Use throttling to control inbound request rates +* [ ] **[Good]** Use, analyze and enforce API quotas +* [X] **[Best]** Use mechanisms to protect non-scalable resources +
+ +* [ ] None of these + + +##### Notes + +We are using SQS queues in front of our Lambda functions, this helps us throttle the rate at which our application processes requests. + +We don't have API's to set quotas for. + +Our downstream resources are S3 and DynamoDB on-demand which are more than capable of scaling to match our volumes. + +#### REL 2. How do you build resiliency into your Serverless application? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Manage transaction, partial, and intermittent failures +* [ ] **[Required]** Manage duplicate and unwanted events +* [ ] **[Good]** Orchestrate long-running transactions +* [x] **[Best]** Consider scaling patterns at burst rates +
+ +* [ ] None of these + +We use SQS queues and DLQ's to ensure any processing failure results in a notification. + +Our example does not deal with duplicate events or files. Any duplicate will overwrite the previous, this could be improved inserting another layer of business logic that first checks the inbound file and renames with a UUID, it could additionally check to see if the file hash has already been processed. + +The processing time of our transactions is fast and we can handle multiple files in a single invocation. Under heavy load of inbound files the SQS queue handles the work being distributed to lambda up to 1000 concurrent batches. + + +##### Notes + +#### PERF 1. How do you optimize your Serverless application’s performance? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Measure, evaluate, and select optimum capacity units +* [x] **[Good]** Measure and optimize function startup time +* [ ] **[Good]** Take advantage of concurrency via async and stream-based function invocations +* [x] **[Good]** Optimize access patterns and apply caching where applicable +* [x] **[Best]** Integrate with managed services directly over functions when possible +
+ +* [ ] None of these + + +##### Notes + +We have looked at how our function performs with different batch sizes and memory configurations to find what we believe is optimal for cost/performance . + +For our example there is no real advantage to async. If concurrency was an issue it would be possible to chain the business logic, rather than perform it in parallel. + +Data is pulled from S3 and held locally and cached for the execution, however currently there is only a single task performed per invocation so there is no benefit. Caching outside of the function would offer no benefit over S3. + +In our Sentiment function we are utilising comprehend which a managed service. + +#### COST 1. How do you optimize your Serverless application’s costs? + +* [ ] Question does not apply to this workload +
+ +* [x] **[Required]** Minimize external calls and function code initialization +* [x] **[Required]** Optimize logging output and its retention +* [x] **[Good]** Optimize function configuration to reduce cost +* [x] **[Best]** Use cost-aware usage patterns in code +
+ +* [ ] None of these + +##### Notes + +We have configurable logging levels and bench marked our function for optimal cost/performance. From 800fd28c6d18d68262a3bce9548317d5e9157340 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 17 Mar 2020 11:20:23 +0000 Subject: [PATCH 070/115] Updated readme with suggestions and added section on using multiple pipelines for dev/prod --- PIPELINE-README.md => pipeline/README.md | 35 ++++++++++++++++++------ 1 file changed, 27 insertions(+), 8 deletions(-) rename PIPELINE-README.md => pipeline/README.md (64%) diff --git a/PIPELINE-README.md b/pipeline/README.md similarity index 64% rename from PIPELINE-README.md rename to pipeline/README.md index 98a229d..ff49f46 100644 --- a/PIPELINE-README.md +++ b/pipeline/README.md @@ -47,19 +47,38 @@ Additional resources will be deployed as per the main architecture documentation To get started you just need to deploy the pipeline CloudFormation stack using the template found in this repository under pipeline/pipeline.yaml in order for this to be successful you will need to provide some additional information. - GitHubRepoName: The name of the GitHub repository hosting your source code. - - GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. + * GitHubToken: GitHub OAuthToken with access to be able to clone the repository. You can find more information in the [GitHub Documentation](https://github.com/settings/tokens) + * AlarmRecipientEmailAddress: You will need to provide an email address that can be used for configuring notifications + +Optionally, if you are deploying from your own repository you will need to also provide: + + * GitHubRepoName: The name of the GitHub repository hosting your source code. By default it points to the AWSLabs repo. + * GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. + * GitHubRepoOwner: the GitHub repository owner. e.g. awslabs - GitHubRepoOwner: the GitHub repository owner. e.g. awslabs +### Deploying the template - GitHubToken: GitHub OAuthToken with access to be able to clone the repository. You can find more information in the [GitHub Documentation](https://github.com/settings/tokens) +You can deploy the template using either the [AWS Console](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-create-stack.html) or the [AWS CLI](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-cli-creating-stack.html) - AlarmRecipientEmailAddress: You will need to provide an email address that can be used for configuring notifications +[TODO] Insert quick link to create CFN stack +##### Example CLI Deployment -### Deploying the template +> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" + +### Deploying twice for a Development and Production example. + +You can actually deploy the pipeline twice to give two seperate envionments. Allowing you to create a simple dev to production workflow. + +Deploy the first stack using a stack name of "lambda-file-refarch-pipeline-dev" update the **AppName** parameter to be environment specific. e.g. "lambda-file-refarch-dev" and make sure to update the branch to the development one. + +Example CLI Deployment for development pipeline + +> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-dev" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="develop" + +Once that has deployed and the application stack has also succesfully deployed you can provision the production pipeline stack. + +> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-prod" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="master" -You can deploy the template using either the [AWS Console](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-create-stack.html) or the [AWS CLI](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-cli-creating-stack.html) ## Clean-up From 200fbbe991d8b129e4d3e4b5e7019930d5c2e485 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 17 Mar 2020 11:22:42 +0000 Subject: [PATCH 071/115] corrected stack names --- pipeline/README.md | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/pipeline/README.md b/pipeline/README.md index ff49f46..1e41015 100644 --- a/pipeline/README.md +++ b/pipeline/README.md @@ -67,17 +67,19 @@ You can deploy the template using either the [AWS Console](https://docs.aws.amaz ### Deploying twice for a Development and Production example. -You can actually deploy the pipeline twice to give two seperate envionments. Allowing you to create a simple dev to production workflow. +You can actually deploy the pipeline twice to give two separate environments. Allowing you to create a simple dev to production workflow. + +This will allow you to build your application in your development branch and any changes will automatically be picked up and deployed by the pipeline. Once you have tested and are happy the changes can be merged to master and they will be automatically built and deployed to production. Deploy the first stack using a stack name of "lambda-file-refarch-pipeline-dev" update the **AppName** parameter to be environment specific. e.g. "lambda-file-refarch-dev" and make sure to update the branch to the development one. Example CLI Deployment for development pipeline -> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-dev" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="develop" +> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-dev" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-dev" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="develop" -Once that has deployed and the application stack has also succesfully deployed you can provision the production pipeline stack. +Once that has deployed and the application stack has also successfully deployed you can provision the production pipeline stack. -> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-prod" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="master" +> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-prod" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-prod" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="master" ## Clean-up @@ -88,4 +90,5 @@ In order to remove all resources created by this example you will first need to * Application input bucket * Application conversion bucket -Once that is complete you can remove both the Application Stack and the Pipeline Stack. +Once that is complete you can remove both the Application Stack and the Pipeline Stack. +Note that the pipeline stack should not be removed until the application stack has successfully deleted as it is deployed using a role present in the pipeline stack. This role is used to also delete the stack. From 9444527f1b874a54ce53071963ebff53721c6f8d Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 17 Mar 2020 11:28:57 +0000 Subject: [PATCH 072/115] Changed some spacing --- pipeline/README.md | 35 +++++++++++++++++++++++++++++++++-- 1 file changed, 33 insertions(+), 2 deletions(-) diff --git a/pipeline/README.md b/pipeline/README.md index 1e41015..7f7ffac 100644 --- a/pipeline/README.md +++ b/pipeline/README.md @@ -5,28 +5,38 @@ We use exactly the same method as in the manual deployment however we utilise [C ## CI/CD Pipeline Diagram + ![Reference Architecture - Real-time File Processing CI/CD Pipeline](img/lambda-refarch-fileprocessing-simple-pipeline.png) + ## Pipeline Components + ### CloudFormation Template + pipeline/pipeline.yml is a CloudFormation template that will deploy all the required pipeline components. Once the stack has deployed the Pipeline will automatically execute and deploy the Serverless Application. See getting started for information on how to deploy the template. + #### Deployed Resources + * Pipeline S3 bucket, used to store pipeline artefacts that are passed between stages. * CodePipeline * CodeBuild Project * Roles for CodePipeline, CodeBuild and the CloudFormation Deployment + ### Source + For this application we are hosting our source code in GitHub. Other [Source Integrations](https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action-type.html#integrations-source) are available however this template focuses on GitHub. Whenever an update is pushed to the GitHub branch being monitored our pipeline will begin executing. The source stage will connect to GitHub using the credentials provided and clone the branch into our pipeline artefact bucket for use in the other stages. + ### Build + In order to run our SAM build and SAM package commands we are using [CodeBuild](https://aws.amazon.com/codebuild/), a fully managed continuous integration service . Codebuild allows us to perform a sequence of commands that we define in the [BuildSpec.yml](https://docs.aws.amazon.com/codebuild/latest/userguide/build-spec-ref.html) file that will execute inside the [build environment](https://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref.html) we define using a docker container. For this project we are using the Amazon Linux 2 version 1.0 container with Python 3.7. @@ -36,15 +46,21 @@ Within the buildspec.yml we are: * Running SAM build as per the manual deployment * Running SAM Package again as per the manual deployment steps * Instructing CodeBuild to pass the output template back to the Pipeline for use in the deployment stage. +
+ ### Deploy + To deploy our application stack we are not using SAM Deploy, instead we are opting to use the CodePipeline native support for CloudFormation. The pipeline has a role it use with appropriate permissions to deploy the template created by the SAM package step which will create a stack containing the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) and [approval actions](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-action-add.html) to demonstrate a manual approval workflow. The first deployment will not require approval however subsequent updates will. Additional resources will be deployed as per the main architecture documentation. +
+ ## Getting started + To get started you just need to deploy the pipeline CloudFormation stack using the template found in this repository under pipeline/pipeline.yaml in order for this to be successful you will need to provide some additional information. * GitHubToken: GitHub OAuthToken with access to be able to clone the repository. You can find more information in the [GitHub Documentation](https://github.com/settings/tokens) @@ -55,31 +71,46 @@ Optionally, if you are deploying from your own repository you will need to also * GitHubRepoName: The name of the GitHub repository hosting your source code. By default it points to the AWSLabs repo. * GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. * GitHubRepoOwner: the GitHub repository owner. e.g. awslabs +
+ ### Deploying the template + You can deploy the template using either the [AWS Console](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-create-stack.html) or the [AWS CLI](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-cli-creating-stack.html) -[TODO] Insert quick link to create CFN stack +**[TODO]** Insert quick link to create CFN stack +
+ + ##### Example CLI Deployment + > aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" +
+ ### Deploying twice for a Development and Production example. + You can actually deploy the pipeline twice to give two separate environments. Allowing you to create a simple dev to production workflow. This will allow you to build your application in your development branch and any changes will automatically be picked up and deployed by the pipeline. Once you have tested and are happy the changes can be merged to master and they will be automatically built and deployed to production. Deploy the first stack using a stack name of "lambda-file-refarch-pipeline-dev" update the **AppName** parameter to be environment specific. e.g. "lambda-file-refarch-dev" and make sure to update the branch to the development one. +
+ +##### Example CLI Deployment for development pipeline -Example CLI Deployment for development pipeline > aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-dev" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-dev" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="develop" +
Once that has deployed and the application stack has also successfully deployed you can provision the production pipeline stack. +
> aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-prod" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-prod" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="master" +
## Clean-up From 3efee78a962539db8951411635586770f4781198 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 17 Mar 2020 11:34:15 +0000 Subject: [PATCH 073/115] Renamed some resources to allow for 2 or more Deployments --- pipeline/pipeline.yaml | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index d68db0e..830949b 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -15,6 +15,7 @@ Parameters: Description: Image used for CodeBuild project. GitHubRepoName: Type: String + Default: "lambda-refarch-fileprocessing" Description: The GitHub repo name GitHubRepoBranch: Type: String @@ -22,6 +23,7 @@ Parameters: Default: master GitHubRepoOwner: Type: String + Default: "awslabs" Description: GitHub Repository Owner. GitHubToken: NoEcho: true @@ -61,7 +63,7 @@ Resources: Description: S3 bucket for AWS CodePipeline artifacts Type: AWS::S3::Bucket Properties: - BucketName: !Sub "serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}" + BucketName: !Sub "pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}" VersioningConfiguration: Status: Enabled S3ArtifactBucketPolicy: @@ -186,7 +188,7 @@ Resources: Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" - Effect: Allow Action: ["s3:*"] - Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + Resource: !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" - Effect: Allow Action: - kms:GenerateDataKey* @@ -231,7 +233,7 @@ Resources: - s3:GetObject - s3:GetObjectVersion Resource: - - !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + - !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - Action: ["lambda:*"] @@ -324,7 +326,7 @@ Resources: - s3:GetObjectVersion - s3:GetBucketVersioning - s3:PutObject - Resource: !Sub "arn:aws:s3:::serverless-app-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + Resource: !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" Effect: Allow - Action: - codebuild:StartBuild From 7d8f6dc7a89395566d7c58e0a10fbff0771a56cd Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 17 Mar 2020 16:16:45 +0000 Subject: [PATCH 074/115] added cleanup script --- pipeline/cleanup.sh | 71 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 71 insertions(+) create mode 100644 pipeline/cleanup.sh diff --git a/pipeline/cleanup.sh b/pipeline/cleanup.sh new file mode 100644 index 0000000..4969903 --- /dev/null +++ b/pipeline/cleanup.sh @@ -0,0 +1,71 @@ +#!/bin/bash + + +echo "Clearing out resources of lambda-file-refarch and Pipeline stacks..." +echo +echo "Cleaning up Application S3 buckets..." && for bucket in InputBucket ConversionTargetBucket; do + echo "Clearing out ${bucket}..." + BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) + aws s3 rm s3://${BUCKET} --recursive + echo +done + +echo "Cleaning up Pipeline S3 buckets..." +BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch-pipeline --logical-resource-id "PipelineBucket" --query "StackResourceDetail.PhysicalResourceId" --output text) + +echo + +echo "Removing all VERSIONS from ${BUCKET}" + +VERSIONS=`aws s3api list-object-VERSIONS --bucket $BUCKET |jq '.VERSIONS'` +MARKERS=`aws s3api list-object-VERSIONS --bucket $BUCKET |jq '.DeleteMARKERS'` +let COUNT=`echo $VERSIONS |jq 'length'`-1 + +if [ $COUNT -gt -1 ]; then + echo "removing files from bucket" + for i in $(seq 0 $COUNT); do + KEY=`echo $VERSIONS | jq .[$i].KEY |sed -e 's/\"//g'` + VERSIONID=`echo $VERSIONS | jq .[$i].VERSIONID |sed -e 's/\"//g'` + CMD="aws s3api delete-object --bucket $BUCKET --KEY $KEY --version-id $VERSIONID" + echo $CMD + $CMD + done +fi + +let COUNT=`echo $MARKERS |jq 'length'`-1 + +if [ $COUNT -gt -1 ]; then + echo "removing delete MARKERS" + + for i in $(seq 0 $COUNT); do + KEY=`echo $MARKERS | jq .[$i].KEY |sed -e 's/\"//g'` + VERSIONID=`echo $MARKERS | jq .[$i].VERSIONID |sed -e 's/\"//g'` + CMD="aws s3api delete-object --bucket $BUCKET --KEY $KEY --version-id $VERSIONID" + echo $CMD + $CMD + done +fi + +echo "Deleting lambda-file-refarch CloudFormation stack..." && aws cloudformation delete-stack \ + --stack-name lambda-file-refarch + +echo "Waiting for stack deletion..." && aws cloudformation wait stack-delete-complete \ + --stack-name lambda-file-refarch + +echo "Deleting lambda-file-refarch-pipeline CloudFormation stack..." && aws cloudformation delete-stack \ + --stack-name lambda-file-refarch-pipeline + +echo "Waiting for stack deletion..." && aws cloudformation wait stack-delete-complete \ + --stack-name lambda-file-refarch-pipeline + +echo "Clearing out Application CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/lambda/lambda-file-refarch- --query "logGroups[*].logGroupName" --output text); do + echo "Removing log group ${log_group}..." + aws logs delete-log-group --log-group-name ${log_group} + echo +done + +echo "Clearing out CodeBuild CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/codebuild/lambda-file-refarch- --query "logGroups[*].logGroupName" --output text); do + echo "Removing log group ${log_group}..." + aws logs delete-log-group --log-group-name ${log_group} + echo +done \ No newline at end of file From f27c1542da4294f6be5f914e7a3f8ecb4080afe3 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 18 Mar 2020 09:39:38 +0000 Subject: [PATCH 075/115] added -app to isolate from main application and improved cleanup and added to the readme.md --- pipeline/README.md | 20 ++++++++++---------- pipeline/cleanup.sh | 39 ++++++++++++++++++++------------------- pipeline/pipeline.yaml | 18 +++++++++--------- 3 files changed, 39 insertions(+), 38 deletions(-) diff --git a/pipeline/README.md b/pipeline/README.md index 7f7ffac..071a6c4 100644 --- a/pipeline/README.md +++ b/pipeline/README.md @@ -46,7 +46,7 @@ Within the buildspec.yml we are: * Running SAM build as per the manual deployment * Running SAM Package again as per the manual deployment steps * Instructing CodeBuild to pass the output template back to the Pipeline for use in the deployment stage. -
+ ### Deploy @@ -55,13 +55,13 @@ Within the buildspec.yml we are: To deploy our application stack we are not using SAM Deploy, instead we are opting to use the CodePipeline native support for CloudFormation. The pipeline has a role it use with appropriate permissions to deploy the template created by the SAM package step which will create a stack containing the resources defined in our SAM Template. We are using [change sets](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-updating-stacks-changesets.html) and [approval actions](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-action-add.html) to demonstrate a manual approval workflow. The first deployment will not require approval however subsequent updates will. Additional resources will be deployed as per the main architecture documentation. -
+ ## Getting started -To get started you just need to deploy the pipeline CloudFormation stack using the template found in this repository under pipeline/pipeline.yaml in order for this to be successful you will need to provide some additional information. +To get started using the template found in this repository under pipeline/pipeline.yaml. You will need to provide additional information to deploy the stack. * GitHubToken: GitHub OAuthToken with access to be able to clone the repository. You can find more information in the [GitHub Documentation](https://github.com/settings/tokens) * AlarmRecipientEmailAddress: You will need to provide an email address that can be used for configuring notifications @@ -71,7 +71,7 @@ Optionally, if you are deploying from your own repository you will need to also * GitHubRepoName: The name of the GitHub repository hosting your source code. By default it points to the AWSLabs repo. * GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. * GitHubRepoOwner: the GitHub repository owner. e.g. awslabs -
+ ### Deploying the template @@ -80,14 +80,14 @@ Optionally, if you are deploying from your own repository you will need to also You can deploy the template using either the [AWS Console](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-console-create-stack.html) or the [AWS CLI](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/using-cfn-cli-creating-stack.html) **[TODO]** Insert quick link to create CFN stack -
+ ##### Example CLI Deployment > aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" -
+ ### Deploying twice for a Development and Production example. @@ -98,19 +98,17 @@ You can actually deploy the pipeline twice to give two separate environments. Al This will allow you to build your application in your development branch and any changes will automatically be picked up and deployed by the pipeline. Once you have tested and are happy the changes can be merged to master and they will be automatically built and deployed to production. Deploy the first stack using a stack name of "lambda-file-refarch-pipeline-dev" update the **AppName** parameter to be environment specific. e.g. "lambda-file-refarch-dev" and make sure to update the branch to the development one. -
##### Example CLI Deployment for development pipeline > aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-dev" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-dev" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="develop" -
+ Once that has deployed and the application stack has also successfully deployed you can provision the production pipeline stack. -
+ > aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-prod" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-prod" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="master" -
## Clean-up @@ -123,3 +121,5 @@ In order to remove all resources created by this example you will first need to Once that is complete you can remove both the Application Stack and the Pipeline Stack. Note that the pipeline stack should not be removed until the application stack has successfully deleted as it is deployed using a role present in the pipeline stack. This role is used to also delete the stack. + +Additionally there will be some codebuild logs and loggroups left over in CloudWatch, these can be deleted. \ No newline at end of file diff --git a/pipeline/cleanup.sh b/pipeline/cleanup.sh index 4969903..05e2155 100644 --- a/pipeline/cleanup.sh +++ b/pipeline/cleanup.sh @@ -1,11 +1,12 @@ #!/bin/bash +command -v jq >/dev/null 2>&1 || { echo >&2 "jq is required but it's not installed. Aborting."; exit 1; } echo "Clearing out resources of lambda-file-refarch and Pipeline stacks..." echo echo "Cleaning up Application S3 buckets..." && for bucket in InputBucket ConversionTargetBucket; do echo "Clearing out ${bucket}..." - BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) + BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch-app --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) aws s3 rm s3://${BUCKET} --recursive echo done @@ -15,19 +16,19 @@ BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-ref echo -echo "Removing all VERSIONS from ${BUCKET}" +echo "Removing all versions from ${BUCKET}" -VERSIONS=`aws s3api list-object-VERSIONS --bucket $BUCKET |jq '.VERSIONS'` -MARKERS=`aws s3api list-object-VERSIONS --bucket $BUCKET |jq '.DeleteMARKERS'` -let COUNT=`echo $VERSIONS |jq 'length'`-1 +VERSIONS=`aws s3api list-object-versions --bucket $BUCKET | jq '.Versions'` +MARKERS=`aws s3api list-object-versions --bucket $BUCKET | jq '.DeleteMarkers'` +let COUNT=`echo $VERSIONS | jq 'length'`-1 if [ $COUNT -gt -1 ]; then echo "removing files from bucket" for i in $(seq 0 $COUNT); do - KEY=`echo $VERSIONS | jq .[$i].KEY |sed -e 's/\"//g'` - VERSIONID=`echo $VERSIONS | jq .[$i].VERSIONID |sed -e 's/\"//g'` - CMD="aws s3api delete-object --bucket $BUCKET --KEY $KEY --version-id $VERSIONID" - echo $CMD + KEY=`echo $VERSIONS | jq .[$i].Key | sed -e 's/\"//g'` + VERSIONID=`echo $VERSIONS | jq .[$i].VersionId | sed -e 's/\"//g'` + CMD="aws s3api delete-object --bucket $BUCKET --key $KEY --version-id $VERSIONID" + echo ${CMD} $CMD done fi @@ -35,22 +36,22 @@ fi let COUNT=`echo $MARKERS |jq 'length'`-1 if [ $COUNT -gt -1 ]; then - echo "removing delete MARKERS" + echo "removing delete markers" for i in $(seq 0 $COUNT); do - KEY=`echo $MARKERS | jq .[$i].KEY |sed -e 's/\"//g'` - VERSIONID=`echo $MARKERS | jq .[$i].VERSIONID |sed -e 's/\"//g'` - CMD="aws s3api delete-object --bucket $BUCKET --KEY $KEY --version-id $VERSIONID" - echo $CMD + KEY=`echo $MARKERS | jq .[$i].Key | sed -e 's/\"//g'` + VERSIONID=`echo $MARKERS | jq .[$i].VersionId | sed -e 's/\"//g'` + CMD="aws s3api delete-object --bucket $BUCKET --key $KEY --version-id $VERSIONID" + echo ${CMD} $CMD done fi -echo "Deleting lambda-file-refarch CloudFormation stack..." && aws cloudformation delete-stack \ - --stack-name lambda-file-refarch +echo "Deleting lambda-file-refarch-app CloudFormation stack..." && aws cloudformation delete-stack \ + --stack-name lambda-file-refarch-app echo "Waiting for stack deletion..." && aws cloudformation wait stack-delete-complete \ - --stack-name lambda-file-refarch + --stack-name lambda-file-refarch-app echo "Deleting lambda-file-refarch-pipeline CloudFormation stack..." && aws cloudformation delete-stack \ --stack-name lambda-file-refarch-pipeline @@ -58,13 +59,13 @@ echo "Deleting lambda-file-refarch-pipeline CloudFormation stack..." && aws clou echo "Waiting for stack deletion..." && aws cloudformation wait stack-delete-complete \ --stack-name lambda-file-refarch-pipeline -echo "Clearing out Application CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/lambda/lambda-file-refarch- --query "logGroups[*].logGroupName" --output text); do +echo "Clearing out Application CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/lambda/lambda-file-refarch-app- --query "logGroups[*].logGroupName" --output text); do echo "Removing log group ${log_group}..." aws logs delete-log-group --log-group-name ${log_group} echo done -echo "Clearing out CodeBuild CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/codebuild/lambda-file-refarch- --query "logGroups[*].logGroupName" --output text); do +echo "Clearing out CodeBuild CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix /aws/codebuild/lambda-file-refarch-app-build --query "logGroups[*].logGroupName" --output text); do echo "Removing log group ${log_group}..." aws logs delete-log-group --log-group-name ${log_group} echo diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 830949b..49e8347 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -3,7 +3,7 @@ Description: "Template for full CI/CD serverless applications." Parameters: AppName: Type: String - Default: lambda-file-refarch + Default: lambda-file-refarch-app Description: Name used for application deployment SAMOutputFile: Type: String @@ -34,7 +34,7 @@ Parameters: Description: Email address for any alerts. Resources: CodeBuildProject: - DependsOn: [S3Bucket] + DependsOn: [PipelineBucket] Description: AWS CodeBuild project Type: AWS::CodeBuild::Project Properties: @@ -46,7 +46,7 @@ Resources: PrivilegedMode: True EnvironmentVariables: - Name: ARTIFACT_BUCKET - Value: !Ref S3Bucket + Value: !Ref PipelineBucket - Name: SAM_OUTPUT_TEMPLATE Value: !Ref SAMOutputFile Image: !Ref CodeBuildImage @@ -59,7 +59,7 @@ Resources: - Key: app-name Value: !Ref AppName TimeoutInMinutes: 5 - S3Bucket: + PipelineBucket: Description: S3 bucket for AWS CodePipeline artifacts Type: AWS::S3::Bucket Properties: @@ -67,11 +67,11 @@ Resources: VersioningConfiguration: Status: Enabled S3ArtifactBucketPolicy: - DependsOn: [S3Bucket] + DependsOn: [PipelineBucket] Description: S3 bucket policy for AWS CodePipeline access Type: AWS::S3::BucketPolicy Properties: - Bucket: !Ref S3Bucket + Bucket: !Ref PipelineBucket PolicyDocument: Version: "2012-10-17" Id: SSEAndSSLPolicy @@ -80,12 +80,12 @@ Resources: Effect: Deny Principal: "*" Action: s3:* - Resource: !Sub "arn:aws:s3:::${S3Bucket}/*" + Resource: !Sub "arn:aws:s3:::${PipelineBucket}/*" Condition: Bool: aws:SecureTransport: false ProjectPipeline: - DependsOn: [S3Bucket, CodeBuildProject] + DependsOn: [PipelineBucket, CodeBuildProject] Description: AWS CodePipeline deployment pipeline for project Type: AWS::CodePipeline::Pipeline Properties: @@ -159,7 +159,7 @@ Resources: RunOrder: 2 ArtifactStore: Type: S3 - Location: !Ref S3Bucket + Location: !Ref PipelineBucket CodeBuildTrustRole: Description: Service role for AWS CodeBuild Type: AWS::IAM::Role From 0e8bf92fc33e278c3a4d93b281297239b4be954a Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 18 Mar 2020 09:42:28 +0000 Subject: [PATCH 076/115] updated Readme JQ requirements --- pipeline/README.md | 12 +++++++++++- 1 file changed, 11 insertions(+), 1 deletion(-) diff --git a/pipeline/README.md b/pipeline/README.md index 071a6c4..08bb15a 100644 --- a/pipeline/README.md +++ b/pipeline/README.md @@ -122,4 +122,14 @@ In order to remove all resources created by this example you will first need to Once that is complete you can remove both the Application Stack and the Pipeline Stack. Note that the pipeline stack should not be removed until the application stack has successfully deleted as it is deployed using a role present in the pipeline stack. This role is used to also delete the stack. -Additionally there will be some codebuild logs and loggroups left over in CloudWatch, these can be deleted. \ No newline at end of file +Additionally there will be some Codebuild logs and Log Groups left over in CloudWatch, these can be deleted. + +Alternatively you can use the script /pipeline/cleanup.sh + +Things to note: + +* Script will remove only stacks deployed as described in the examples. + +* Both the application and the pipeline stacks will be removed. + +* JQ needs to be installed in order to empty the pipeline bucket as versioning is enabled. The command to delete versions and markers requires it. \ No newline at end of file From 8bec4dcc6854d24171d7fb0fcf7d09023a9bf248 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 09:17:42 +0000 Subject: [PATCH 077/115] fixed some typos --- WELL-ARCHITECTED.md | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/WELL-ARCHITECTED.md b/WELL-ARCHITECTED.md index 14602de..71d2228 100644 --- a/WELL-ARCHITECTED.md +++ b/WELL-ARCHITECTED.md @@ -61,15 +61,17 @@ For this example a rollout mechanism would involve adopting either a Blue / Gree ##### Notes +This solution doesn't include an API frontend so the question doesn't apply. + #### SEC 2: How do you manage your Serverless application’s security boundaries? * [ ] Question does not apply to this workload
-* [x] **[Required]** Evaluate and define resource policies -* [x] **[Good]** Control network traffic at all layers -* [x] **[Best]** Smaller functions require fewer permissions -* [x] **[Required]** Use temporary credentials between resources and components +* [x] **[Required]** Evaluate and define resource policies +* [x] **[Good]** Control network traffic at all layers +* [x] **[Best]** Smaller functions require fewer permissions +* [x] **[Required]** Use temporary credentials between resources and components
* [ ] None of these @@ -102,7 +104,7 @@ We have individual functions for each different piece of business logic. ##### Notes -This application doesn't have any stored secrets. The GitHub token is required by CodeBuild, this is passed as a string for CloudFormation, it is not however visible within the CloudFormation console. This could be improved by manually creating a secrets manager entry for the token and replacing the CloudFormation parameter for the token with the secrets manager value by utilising Dynamic References. +This application doesn't have any stored secrets. The GitHub token is required by CodePipeline, this is passed as a string for CloudFormation, it is not however visible within the CloudFormation console. This could be improved by manually creating a secrets manager entry for the token and replacing the CloudFormation parameter for the token with the secrets manager value by utilising Dynamic References. https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/dynamic-references.html For reviewing dependencies and libraries we could integrate an automatic check into the pipeline. There are many tools and providers which can check code. Currently this is manual using PEP8 and Bandit manual checks. From 53c5823443483d87d98bf4cf3653046cfa9de995 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 10:15:03 +0000 Subject: [PATCH 078/115] PR comment corrections --- buildspec.yml | 1 - pipeline/README.md | 19 ++++++++++++++----- pipeline/pipeline.yaml | 2 +- 3 files changed, 15 insertions(+), 7 deletions(-) diff --git a/buildspec.yml b/buildspec.yml index 40d62d5..a89995b 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -15,4 +15,3 @@ phases: artifacts: files: - $SAM_OUTPUT_TEMPLATE - \ No newline at end of file diff --git a/pipeline/README.md b/pipeline/README.md index 08bb15a..d3dd346 100644 --- a/pipeline/README.md +++ b/pipeline/README.md @@ -6,7 +6,7 @@ We use exactly the same method as in the manual deployment however we utilise [C ## CI/CD Pipeline Diagram -![Reference Architecture - Real-time File Processing CI/CD Pipeline](img/lambda-refarch-fileprocessing-simple-pipeline.png) +![Reference Architecture - Real-time File Processing CI/CD Pipeline](../img/lambda-refarch-fileprocessing-simple-pipeline.png) ## Pipeline Components @@ -15,7 +15,7 @@ We use exactly the same method as in the manual deployment however we utilise [C ### CloudFormation Template -pipeline/pipeline.yml is a CloudFormation template that will deploy all the required pipeline components. Once the stack has deployed the Pipeline will automatically execute and deploy the Serverless Application. See getting started for information on how to deploy the template. +pipeline.yml is a CloudFormation template that will deploy all the required pipeline components. Once the stack has deployed the Pipeline will automatically execute and deploy the Serverless Application. See getting started for information on how to deploy the template. #### Deployed Resources @@ -31,13 +31,13 @@ pipeline/pipeline.yml is a CloudFormation template that will deploy all the requ For this application we are hosting our source code in GitHub. Other [Source Integrations](https://docs.aws.amazon.com/codepipeline/latest/userguide/integrations-action-type.html#integrations-source) are available however this template focuses on GitHub. Whenever an update is pushed to the GitHub branch being -monitored our pipeline will begin executing. The source stage will connect to GitHub using the credentials provided and clone the branch into our pipeline artefact bucket for use in the other stages. +monitored (default: master) our pipeline will begin executing. The source stage will connect to GitHub using the credentials provided and clone the branch into our pipeline artefact bucket for use in the other stages. ### Build -In order to run our SAM build and SAM package commands we are using [CodeBuild](https://aws.amazon.com/codebuild/), a fully managed continuous integration service . Codebuild allows us to perform a sequence of commands that we define in the [BuildSpec.yml](https://docs.aws.amazon.com/codebuild/latest/userguide/build-spec-ref.html) +In order to run our SAM build and SAM package commands we are using [CodeBuild](https://aws.amazon.com/codebuild/), a fully managed continuous integration service. Codebuild allows us to perform a sequence of commands that we define in the [buildSpec.yml](https://docs.aws.amazon.com/codebuild/latest/userguide/build-spec-ref.html) file that will execute inside the [build environment](https://docs.aws.amazon.com/codebuild/latest/userguide/build-env-ref.html) we define using a docker container. For this project we are using the Amazon Linux 2 version 1.0 container with Python 3.7. Within the buildspec.yml we are: @@ -70,7 +70,7 @@ Optionally, if you are deploying from your own repository you will need to also * GitHubRepoName: The name of the GitHub repository hosting your source code. By default it points to the AWSLabs repo. * GitHubRepoBranch: The GitHub repo branch code pipeline should watch for changes on. This defaults to master, but any branch can be used. - * GitHubRepoOwner: the GitHub repository owner. e.g. awslabs + * GitHubRepoOwner: the GitHub repository owner. e.g. aws-samples @@ -111,6 +111,15 @@ Once that has deployed and the application stack has also successfully deployed > aws cloudformation deploy --template-file pipeline/pipeline.yaml --stack-name "lambda-file-refarch-pipeline-prod" --capabilities "CAPABILITY_IAM" "CAPABILITY_NAMED_IAM" --parameter-overrides AppName="lambda-file-refarch-prod" GitHubToken="**{replace with your GitHub Token}**" AlarmRecipientEmailAddress="**{replace with your admin email}**" GitHubRepoBranch="master" +##### Approval Actions + +For any additional source code updates after the pipeline has been deployed and executed successfully you will be required to approve or reject the change-set execution. There will be an email sent to the admin email address, which will include a link to the approval request. + +Alternatively you can do this via the console or cli [Approve or Reject an Approval Action in CodePipeline](https://docs.aws.amazon.com/codepipeline/latest/userguide/approvals-approve-or-reject.html) + + + + ## Clean-up In order to remove all resources created by this example you will first need to make sure the 3 S3 buckets are empty. diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 49e8347..70c6bf6 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -23,7 +23,7 @@ Parameters: Default: master GitHubRepoOwner: Type: String - Default: "awslabs" + Default: "aws-samples" Description: GitHub Repository Owner. GitHubToken: NoEcho: true From 62309751d84a35d100dd3818f98733669c7170c2 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 10:42:35 +0000 Subject: [PATCH 079/115] added approval notification --- pipeline/pipeline.yaml | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 70c6bf6..62f2c2d 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -66,6 +66,12 @@ Resources: BucketName: !Sub "pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}" VersioningConfiguration: Status: Enabled + PipelineNotificationTopic: + Type: AWS::SNS::Topic + Properties: + Subscription: + - Protocol: email + Endpoint: !Ref AlarmRecipientEmailAddress S3ArtifactBucketPolicy: DependsOn: [PipelineBucket] Description: S3 bucket policy for AWS CodePipeline access @@ -144,6 +150,16 @@ Resources: TemplatePath: !Sub "${AppName}-BuildArtifact::${SAMOutputFile}" ParameterOverrides: !Sub '{"AlarmRecipientEmailAddress": "${AlarmRecipientEmailAddress}"}' RunOrder: 1 + - Name: approve-changeset + InputArtifacts: [] + ActionTypeId: + Category: Approval + Owner: AWS + Provider: Manual + Version: '1' + Configuration: + NotificationArn: !Ref PipelineNotificationTopic + RunOrder: 2 - Name: execute-changeset InputArtifacts: [] ActionTypeId: @@ -156,7 +172,7 @@ Resources: StackName: !Sub "${AppName}" ActionMode: CHANGE_SET_EXECUTE ChangeSetName: pipeline-changeset - RunOrder: 2 + RunOrder: 3 ArtifactStore: Type: S3 Location: !Ref PipelineBucket From f6ece51a759d4128d680794302ab9c5bdb8dbf4a Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 10:59:36 +0000 Subject: [PATCH 080/115] added permissions --- pipeline/pipeline.yaml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 62f2c2d..0372712 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -358,6 +358,10 @@ Resources: - iam:PassRole Resource: !GetAtt CloudFormationTrustRole.Arn Effect: Allow + - Action: + - sns:Publish + Resource: !Ref PipelineNotificationTopic + Effect: Allow Roles: [!Ref CodePipelineTrustRole] From 8e97eb75286d5f8685d06afe550dc6554052d3bd Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 11:27:25 +0000 Subject: [PATCH 081/115] added failure notification --- pipeline/pipeline.yaml | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 0372712..401eac1 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -176,6 +176,26 @@ Resources: ArtifactStore: Type: S3 Location: !Ref PipelineBucket + PipelineEventRule: + Type: "AWS::Events::Rule" + Properties: + Description: "CodePipelineEventRule" + EventPattern: + source: + - aws.codepipeline + detail-type: + - CodePipeline Pipeline Execution State Change + detail: + state: + - FAILED + State: "ENABLED" + Targets: + - Arn: !Ref PipelineNotificationTopic + Id: "PipelineTopic" + InputTransformer: + InputTemplate: !Sub '"The ${AppName} Pipeline has failed. Go to https://console.aws.amazon.com/codepipeline/home/view/ for more information"' + InputPathsMap: + pipeline: "$.detail.pipeline" CodeBuildTrustRole: Description: Service role for AWS CodeBuild Type: AWS::IAM::Role From 5a5174be0f3a2ee4e3386c9fff523252d46d9b61 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 11:44:53 +0000 Subject: [PATCH 082/115] added failure notification --- pipeline/pipeline.yaml | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 401eac1..e3d7ac2 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -181,13 +181,13 @@ Resources: Properties: Description: "CodePipelineEventRule" EventPattern: - source: - - aws.codepipeline - detail-type: - - CodePipeline Pipeline Execution State Change + source: + - aws.codepipeline + detail-type: + - CodePipeline Pipeline Execution State Change detail: - state: - - FAILED + state: + - FAILED State: "ENABLED" Targets: - Arn: !Ref PipelineNotificationTopic From 0ee96cfb609150f2a703901ec5b68eb0e8bc0047 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Tue, 24 Mar 2020 12:09:56 +0000 Subject: [PATCH 083/115] added failure notification --- pipeline/pipeline.yaml | 26 ++++++++++++++++++++++---- 1 file changed, 22 insertions(+), 4 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index e3d7ac2..34a84ec 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -72,6 +72,21 @@ Resources: Subscription: - Protocol: email Endpoint: !Ref AlarmRecipientEmailAddress + PipelineSNSTopicPolicy: + Type: AWS::SNS::TopicPolicy + Properties: + PolicyDocument: + Id: PipelineTopicPolicy + Version: '2012-10-17' + Statement: + - Effect: Allow + Principal: + Service: + - events.amazonaws.com + Action: sns:Publish + Resource: !Ref PipelineNotificationTopic + Topics: + - !Ref PipelineNotificationTopic S3ArtifactBucketPolicy: DependsOn: [PipelineBucket] Description: S3 bucket policy for AWS CodePipeline access @@ -179,23 +194,26 @@ Resources: PipelineEventRule: Type: "AWS::Events::Rule" Properties: - Description: "CodePipelineEventRule" + Description: "Trigger notifications based on pipeline state change to Failure" EventPattern: source: - - aws.codepipeline + - "aws.codepipeline" detail-type: - CodePipeline Pipeline Execution State Change detail: state: - - FAILED + - "FAILED" State: "ENABLED" Targets: - Arn: !Ref PipelineNotificationTopic Id: "PipelineTopic" InputTransformer: - InputTemplate: !Sub '"The ${AppName} Pipeline has failed. Go to https://console.aws.amazon.com/codepipeline/home/view/ for more information"' + InputTemplate: !Sub '"The ${AppName} Pipeline in has at

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089/115] Remove redrive policy from SQS, update ref architecture diagram It is better to standardize on function EventInvokeConfig forerror destinations. --- README.md | 10 +++++----- img/lambda-refarch-fileprocessing-simple.png | Bin 96293 -> 96248 bytes template.yml | 6 ------ 3 files changed, 5 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 47b5ba4..44f5a7d 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ The Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses [AWS Lambda](https://aws.amazon.com/lambda). This architecture is ideal for workloads that need more than one data derivative of an object. -In this example application we deliver the notes from an interview in Markdown format to S3. CloudWatch Events is used to trigger multiple processing flows - one to convert and persist Markdown files to HTML and another to detect and persist sentiment. +In this example application, we deliver notes from an interview in Markdown format to S3. S3 Events are used to trigger multiple processing flows - one to convert and persist Markdown files to HTML and another to detect and persist sentiment. ## Architectural Diagram @@ -12,7 +12,7 @@ In this example application we deliver the notes from an interview in Markdown f ### Event Trigger -Unlike batch processing, in this architecture we process each individual file as it arrives. To achive this we utilize [AWS S3 Events](https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html) and [Amazon Simple Notification Service](https://docs.aws.amazon.com/sns/latest/dg/welcome.html). When an object is created in S3, an event is emitted to a SNS topic. We deliver our event to 2 seperate [SQS Queues](https://aws.amazon.com/sqs/), representing 2 different workflows. Refer to [What is Amazon Simple Notification Service?](https://docs.aws.amazon.com/sns/latest/dg/welcome.html) for more information about eligible targets. +In this architecture, individual files are processed as they arrive. To achive this, we utilize [AWS S3 Events](https://docs.aws.amazon.com/AmazonS3/latest/dev/NotificationHowTo.html) and [Amazon Simple Notification Service](https://docs.aws.amazon.com/sns/latest/dg/welcome.html). When an object is created in S3, an event is emitted to a SNS topic. We deliver our event to 2 seperate [SQS Queues](https://aws.amazon.com/sqs/), representing 2 different workflows. Refer to [What is Amazon Simple Notification Service?](https://docs.aws.amazon.com/sns/latest/dg/welcome.html) for more information about eligible targets. ### Conversion Workflow @@ -186,7 +186,7 @@ creates the following resources: - **ConversionQueue** - A SQS queue that is used to store events for conversion from Markdown to HTML. -- **ConversionDlq** - A SQS queue that is used to capture messages that cannot be processed by the **ConversionFunction**. The *RedrivePolicy* on the **ConversionQueue** is used to manage how traffic makes it to this queue. +- **ConversionDlq** - A SQS queue that is used to capture messages that cannot be processed by the **ConversionFunction**. - **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. Errors in the function will be sent to the **ConversionDlq**. @@ -196,13 +196,13 @@ creates the following resources: - **SentimentQueue** - A SQS queue that is used to store events for sentiment analysis processing. -- **SentimentDlq** - A SQS queue that is used to capture messages that cannot be processed by the **SentimentFunction**. The *RedrivePolicy* on the **SentimentQueue** is used to manage how traffic makes it to this queue. +- **SentimentDlq** - A SQS queue that is used to capture messages that cannot be processed by the **SentimentFunction**. - **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. Errors in the function will be sent to the **SentimentDlq**. - **SentimentTable** - A DynamoDB table that stores the input file along with the sentiment. -- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive alarms from the **ConversionDlqAlarm** and **SentimentDlqAlarm**. +- **AlarmTopic** - A SNS topic that has an email as a subscriber. This topic is used to receive alarms from the **ConversionDlqAlarm**, **SentimentDlqAlarm**, **ConversionQueueAlarm**, **SentimentQueueAlarm**, **ConversionFunctionErrorRateAlarm**, **SentimentFunctionErrorRateAlarm**, **ConversionFunctionThrottleRateAlarm**, and **SentimentFunctionThrottleRateAlarm**. - **ConversionDlqAlarm** - A CloudWatch Alarm that detects when there there are any messages sent to the **ConvesionDlq** within a 1 minute period and sends a notification to the **AlarmTopic**. diff --git a/img/lambda-refarch-fileprocessing-simple.png b/img/lambda-refarch-fileprocessing-simple.png index ac158a3c44904cde3b1bcea028a08b7a734ee3e8..890f2202d5769a43f465c4faaf676b7ae4d9a6f4 100644 GIT binary patch literal 96248 zcmb5Vcl^`j`ab@~fvA8WxIjhlC^*S#lA?l5lXN%TO)A4Sqbp5E+BAu>L;)vy+yg~D zZUvmEfQrcRs7F9iK@o5tWja8R`FnzX#`pF5egF8rU$jY+Cr_Sn-`92B_w#UlEb8lb z+>qmXdV2Z={B)wH=cu7QJx3nVr#HAV>e7{`_4JJPw;8@&GnKL`_nd=z|2#VffogTB ztdwQx9F#r>K@bRmE`qR&AUFj<=b#=G2Vao;VuEnxz->^zRM*>omd!UB7fa=Qv6Zjs 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+190,6 @@ Resources: DependsOn: SentimentDlq Properties: VisibilityTimeout: 60 - RedrivePolicy: - deadLetterTargetArn: !GetAtt SentimentDlq.Arn - maxReceiveCount: 5 SentimentDlq: Type: AWS::SQS::Queue From 7f3560bbd04a91ec028d7799d1444881c3b075cb Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Thu, 2 Apr 2020 11:45:24 -0400 Subject: [PATCH 090/115] Update to reflect better ARN + change of error handling --- README.md | 12 ++--- deploy.sh | 51 ------------------- img/lambda-refarch-fileprocessing-simple.png | Bin 96248 -> 116953 bytes template.yml | 18 +++---- 4 files changed, 13 insertions(+), 68 deletions(-) delete mode 100644 deploy.sh diff --git a/README.md b/README.md index 44f5a7d..c03d9f7 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ We target a SQS queue for this workflow. Sending the JSON event to SQS first rat The Lambda service polls our queue on our behalf. When messages are available they will be delivered to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. -If our Conversion Lambda function fails to process the messages, the function sends the event to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Conversion DLQ. +If our Conversion Lambda function cannot remove the messages from the Conversion queue, they are sent to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Conversion DLQ. Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function execution environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new HTML file to an output S3 bucket. If our function execution results in an error, we will @@ -32,7 +32,7 @@ The Sentiment workflow uses the same SQS-to-Lambda Function pattern as the Cover Once we have our sentiment we persist the result to our [DynamoDB](https://aws.amazon.com/dynamodb/) table. -If our Sentiment Lambda function fails to process the messages, the function sends the event to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Sentiment DLQ. +If our Sentiment Lambda function cannot remove the messages from the Sentiment SQS queue, they are sent to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Sentiment DLQ. ## Building and Deploying the Application with the AWS Serverless Application Model (AWS SAM) @@ -186,9 +186,9 @@ creates the following resources: - **ConversionQueue** - A SQS queue that is used to store events for conversion from Markdown to HTML. -- **ConversionDlq** - A SQS queue that is used to capture messages that cannot be processed by the **ConversionFunction**. +- **ConversionDlq** - A SQS queue that is used to capture messages that cannot be processed by the **ConversionFunction**. The *RedrivePolicy* on the **ConversionQueue** is used to manage how traffic makes it to this queue. -- **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. Errors in the function will be sent to the **ConversionDlq**. +- **ConversionFunction** - A Lambda function that takes the input file, converts it to HTML, and stores the resulting file to **ConversionTargetBucket**. - **ConversionTargetBucket** - A S3 bucket that stores the converted HTML. @@ -196,9 +196,9 @@ creates the following resources: - **SentimentQueue** - A SQS queue that is used to store events for sentiment analysis processing. -- **SentimentDlq** - A SQS queue that is used to capture messages that cannot be processed by the **SentimentFunction**. +- **SentimentDlq** - A SQS queue that is used to capture messages that cannot be processed by the **SentimentFunction**. The *RedrivePolicy* on the **SentimentQueue** is used to manage how traffic makes it to this queue. -- **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. Errors in the function will be sent to the **SentimentDlq**. +- **SentimentFunction** - A Lambda function that takes the input file, performs sentiment analysis, and stores the output to the **SentimentTable**. - **SentimentTable** - A DynamoDB table that stores the input file along with the sentiment. diff --git a/deploy.sh b/deploy.sh deleted file mode 100644 index 8ead219..0000000 --- a/deploy.sh +++ /dev/null @@ -1,51 +0,0 @@ -#!/bin/bash - -if (( ${#} < 3)); then - echo "USAGE: ${0} s3_package_bucket_name aws_region recipient_email" - exit 1 -fi - -### -# Variables -### -export SAM_TEMPLATE="template.yml" -export PACKAGED_TEMPLATE="packaged-template.yml" -export STACK_NAME="lambda-file-refarch" -export S3_CODE_BUCKET=${1} -export AWS_REGION=${2} -export RECIPIENT_EMAIL=${3} -export SAM_BUILD_ARG=${4} # Possible to pass in --skip-pull-image if docker image is already local -export FILE_TO_UPDATE="src/conversion/conversion.py" - -### -# Functions -### -function sam-runner { - sam build --use-container ${SAM_BUILD_ARG} - sam package --output-template-file ${PACKAGED_TEMPLATE} \ - --s3-bucket ${S3_CODE_BUCKET} # 2> /dev/null - sam deploy \ - --template-file ${PACKAGED_TEMPLATE} \ - --stack-name ${STACK_NAME} \ - --region ${AWS_REGION} \ - --tags Project=lambda-refarch-fileprocessing \ - --parameter-overrides AlarmRecipientEmailAddress=${RECIPIENT_EMAIL} \ - --capabilities CAPABILITY_IAM -} - -### -# Main body -### - -# Need to run two passes of the CF template to mitigate race condition. -# Please refer to https://aws.amazon.com/premiumsupport/knowledge-center/unable-validate-destination-s3/ -# for more detailed information. -sed -i '' '30,33 s/^/#/' ${SAM_TEMPLATE} -echo '' >> ${FILE_TO_UPDATE} -sam-runner -echo -sed -i '' '30,33 s/^#//' ${SAM_TEMPLATE} -echo '' >> ${FILE_TO_UPDATE} -sam-runner -git checkout ${FILE_TO_UPDATE} -echo \ No newline at end of file diff --git a/img/lambda-refarch-fileprocessing-simple.png b/img/lambda-refarch-fileprocessing-simple.png 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Remove test messages sent from s3 to queues during stack creation --- src/notification/notification.py | 16 ++++++++++++++-- template.yml | 13 +++++++++++-- 2 files changed, 25 insertions(+), 4 deletions(-) diff --git a/src/notification/notification.py b/src/notification/notification.py index 8012b2e..23f62bb 100644 --- a/src/notification/notification.py +++ b/src/notification/notification.py @@ -4,10 +4,12 @@ import cfnresponse s3Client = boto3.client('s3') +sqsClient = boto3.client('sqs') + logger = logging.getLogger() logger.setLevel(logging.DEBUG) -def addBucketNotification(bucket_name, notification_id, sns_arn): +def addBucketNotification(bucket_name, notification_id, sns_arn, sqs_urls): notificationResponse = s3Client.put_bucket_notification_configuration( Bucket=bucket_name, NotificationConfiguration={ @@ -22,13 +24,23 @@ def addBucketNotification(bucket_name, notification_id, sns_arn): ] } ) + + # Purge the SQS Queues once notification configuration has been set. + # This will avoid the issue of s3:Test messages being consumed by + # the Conversion and Sentiment Lambda functions. + for sqs_url in sqs_urls: + logger.info(f'Clearing queue {sqs_url}') + purgeResponse = sqsClient.purge_queue(QueueUrl=sqs_url) + logger.info(f'PurgeQueue response: {json.dumps(purgeResponse)}') + return notificationResponse def create(properties, physical_id): bucket_name = properties['S3Bucket'] notification_id = properties['NotificationId'] sns_arn = properties['SnsArn'] - response = addBucketNotification(bucket_name, notification_id, sns_arn) + sqs_urls = properties['SqsUrls'] + response = addBucketNotification(bucket_name, notification_id, sns_arn, sqs_urls) logger.info(f'AddBucketNotification response: {json.dumps(response)}') return cfnresponse.SUCCESS, physical_id diff --git a/template.yml b/template.yml index cc871db..f0bc5f4 100644 --- a/template.yml +++ b/template.yml @@ -38,14 +38,15 @@ Resources: Version: '2012-10-17' Statement: - Effect: Allow - Principal: "*" + Principal: + Service: "s3.amazonaws.com" Action: SNS:Publish Resource: !Ref NotificationTopic Condition: StringEquals: aws:SourceAccount: !Sub ${AWS::AccountId} ArnEquals: - aws:SourceArn: !Sub "arn:aws:s3:::${AWS::StackName}-${AWS::AccountId}-inputbucket" + aws:SourceArn: !Sub "arn:aws:s3:::${AWS::StackName}-${AWS::AccountId}-input-bucket" Topics: - !Ref NotificationTopic @@ -75,6 +76,13 @@ Resources: CodeUri: ./src/notification/ Timeout: 60 Policies: + - Version: '2012-10-17' + Statement: + - Effect: Allow + Action: sqs:PurgeQueue + Resource: + - !GetAtt ConversionQueue.Arn + - !GetAtt SentimentQueue.Arn - Version: '2012-10-17' Statement: - Effect: Allow @@ -90,6 +98,7 @@ Resources: S3Bucket: !Ref InputBucket SnsArn: !Ref NotificationTopic NotificationId: S3ObjectCreatedEvent + SqsUrls: [ !Ref ConversionQueue, !Ref SentimentQueue ] ConversionSubscription: Type: AWS::SNS::Subscription From 53937ccf1930130a22ec1323e60d20e1f3c69cb3 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Wed, 13 May 2020 23:11:15 -0400 Subject: [PATCH 092/115] updatddashboard --- template.yml | 158 +++++++++++++++++++++++++++++++++++++++++++++------ 1 file changed, 140 insertions(+), 18 deletions(-) diff --git a/template.yml b/template.yml index f0bc5f4..2a8dc31 100644 --- a/template.yml +++ b/template.yml @@ -549,7 +549,7 @@ Resources: }, { "type":"metric", - "x":0, + "x":12, "y":0, "width":12, "height":6, @@ -568,25 +568,64 @@ Resources: { "type":"metric", "x":0, - "y":0, + "y":6, "width":12, "height":6, "properties":{ "metrics":[ - [ "AWS/Lambda", "Throttles", "FunctionName", "${ConversionFunction}", { "id": "m1", "visible": false } ], - [ { "expression": "100*(m1/m2)", "label": "Throttle Rate", "id": "e1", "region": "${AWS::Region}" } ], - [ "AWS/Lambda", "Invocations", "FunctionName", "${ConversionFunction}", { "id": "m2", "visible": false } ] + [ "AWS/Lambda", "ConcurrentExecutions", "FunctionName", "${ConversionFunction}", { "stat": "Average" } ], + [ "...", { "stat": "Maximum" } ], + [ "...", { "stat": "Minimum", "label": "ConcurrentExecutions (minimum)" } ], + [ "...", { "stat": "p90", "label": "ConcurrentExecutions (p90)"} ], + [ "...", { "stat": "p95", "label": "ConcurrentExecutions (p95)"} ], + [ "...", { "stat": "p99", "label": "ConcurrentExecutions (p99)" } ] + ], + "period":60, + "stat":"Maximum", + "region": "${AWS::Region}", + "title":"Conversion Function Concurrent Executions" + } + }, + { + "type":"metric", + "x":12, + "y":6, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ "AWS/Lambda", "Duration", "FunctionName", "${ConversionFunction}", { "label": "Duration (Avg)", "stat": "Average" } ], + [ "...", { "label": "Duration (Max)" } ], + [ "...", { "stat": "p99", "label": "Duration (p99)" } ] ], "period":60, "stat":"Sum", "region": "${AWS::Region}", - "title":"Conversion Function Throttle Rate" + "title": "Conversion Function Duration" } }, { "type":"metric", - "x":0, - "y":0, + "x": 0, + "y": 18, + "width": 12, + "height": 6, + "properties":{ + "view": "timeSeries", + "stacked": false, + "title": "Conversion Function Throttles", + "metrics":[ + [ "AWS/Lambda", "Throttles", "FunctionName", "${ConversionFunction}" ] + ], + "period":60, + "stat":"Sum", + "region": "${AWS::Region}" + } + }, + { + "type":"metric", + "x":12, + "y":18, "width":12, "height":6, "properties":{ @@ -607,7 +646,7 @@ Resources: { "type":"metric", "x":0, - "y":0, + "y":24, "width":12, "height":6, "properties":{ @@ -627,8 +666,8 @@ Resources: }, { "type":"metric", - "x":0, - "y":0, + "x":12, + "y":24, "width":12, "height":6, "properties":{ @@ -646,25 +685,64 @@ Resources: { "type":"metric", "x":0, - "y":0, + "y":36, "width":12, "height":6, "properties":{ "metrics":[ - [ "AWS/Lambda", "Throttles", "FunctionName", "${SentimentFunction}", { "id": "m1", "visible": false } ], - [ { "expression": "100*(m1/m2)", "label": "Throttle Rate", "id": "e1", "region": "${AWS::Region}" } ], - [ "AWS/Lambda", "Invocations", "FunctionName", "${SentimentFunction}", { "id": "m2", "visible": false } ] + [ "AWS/Lambda", "ConcurrentExecutions", "FunctionName", "${SentimentFunction}", { "stat": "Average" } ], + [ "...", { "stat": "Maximum" } ], + [ "...", { "stat": "Minimum", "label": "ConcurrentExecutions (minimum)" } ], + [ "...", { "stat": "p90", "label": "ConcurrentExecutions (p90)"} ], + [ "...", { "stat": "p95", "label": "ConcurrentExecutions (p95)"} ], + [ "...", { "stat": "p99", "label": "ConcurrentExecutions (p99)" } ] + ], + "period":60, + "stat":"Maximum", + "region": "${AWS::Region}", + "title":"Sentiment Function Concurrent Executions" + } + }, + { + "type":"metric", + "x":12, + "y":36, + "width":12, + "height":6, + "properties":{ + "metrics":[ + [ "AWS/Lambda", "Duration", "FunctionName", "${SentimentFunction}", { "label": "Duration (Avg)", "stat": "Average" } ], + [ "...", { "label": "Duration (Max)" } ], + [ "...", { "stat": "p99", "label": "Duration (p99)" } ] ], "period":60, "stat":"Sum", "region": "${AWS::Region}", - "title":"Sentiment Function Throttle Rate" + "title": "Sentiment Function Duration" } }, { "type":"metric", - "x":0, - "y":0, + "x": 0, + "y": 42, + "width": 12, + "height": 6, + "properties":{ + "view": "timeSeries", + "stacked": false, + "title": "Sentiment Function Throttles", + "metrics":[ + [ "AWS/Lambda", "Throttles", "FunctionName", "${SentimentFunction}" ] + ], + "period":60, + "stat":"Sum", + "region": "${AWS::Region}" + } + }, + { + "type":"metric", + "x":12, + "y":42, "width":12, "height":6, "properties":{ @@ -681,6 +759,50 @@ Resources: "region": "${AWS::Region}", "title":"Sentiment DLQ Length" } + }, + { + "type": "text", + "x": 0, + "y": 48, + "width": 24, + "height": 1, + "properties": { + "markdown": "\n# Alarms" + } + }, + { + "type": "metric", + "x": 0, + "y": 49, + "width": 12, + "height": 6, + "properties": { + "title": "ConversionDlq Alarm", + "annotations": { + "alarms": [ + "${ConversionDlqAlarm.Arn}" + ] + }, + "view": "timeSeries", + "stacked": false + } + }, + { + "type": "metric", + "x": 12, + "y": 49, + "width": 12, + "height": 6, + "properties": { + "title": "SentimentDlq Alarm", + "annotations": { + "alarms": [ + "${SentimentDlqAlarm.Arn}" + ] + }, + "view": "timeSeries", + "stacked": false + } } ] }' From fac4d179fddc04debf535dad32e3a6404ff093f1 Mon Sep 17 00:00:00 2001 From: Brian McNamara Date: Fri, 15 May 2020 07:54:58 -0400 Subject: [PATCH 093/115] Update boto3 clients and resources to use aws region --- src/conversion/conversion.py | 6 ++++-- src/notification/notification.py | 17 +++++++++++------ src/sentiment/sentiment.py | 10 ++++++---- 3 files changed, 21 insertions(+), 12 deletions(-) diff --git a/src/conversion/conversion.py b/src/conversion/conversion.py index efdad17..a605a1a 100644 --- a/src/conversion/conversion.py +++ b/src/conversion/conversion.py @@ -16,15 +16,17 @@ max_object_size = 104857600 # 100MB = 104857600 bytes +aws_region = os.environ['AWS_REGION'] + conversion_queue = os.getenv('CONVERSION_QUEUE') target_bucket = os.getenv('TARGET_BUCKET') log_level = os.getenv('LOG_LEVEL') -s3_resource = boto3.resource('s3') +s3_resource = boto3.resource('s3', region_name=aws_region) -sqs_client = boto3.client('sqs') +sqs_client = boto3.client('sqs', region_name=aws_region) log = logging.getLogger() diff --git a/src/notification/notification.py b/src/notification/notification.py index 23f62bb..716ffaf 100644 --- a/src/notification/notification.py +++ b/src/notification/notification.py @@ -1,16 +1,21 @@ -import boto3 -import logging import json +import logging +import os + +import boto3 import cfnresponse -s3Client = boto3.client('s3') -sqsClient = boto3.client('sqs') + +aws_region = os.environ['AWS_REGION'] + +s3_client = boto3.client('s3', region_name=aws_region) +sqs_client = boto3.client('sqs', region_name=aws_region) logger = logging.getLogger() logger.setLevel(logging.DEBUG) def addBucketNotification(bucket_name, notification_id, sns_arn, sqs_urls): - notificationResponse = s3Client.put_bucket_notification_configuration( + notificationResponse = s3_client.put_bucket_notification_configuration( Bucket=bucket_name, NotificationConfiguration={ 'TopicConfigurations': [ @@ -30,7 +35,7 @@ def addBucketNotification(bucket_name, notification_id, sns_arn, sqs_urls): # the Conversion and Sentiment Lambda functions. for sqs_url in sqs_urls: logger.info(f'Clearing queue {sqs_url}') - purgeResponse = sqsClient.purge_queue(QueueUrl=sqs_url) + purgeResponse = sqs_client.purge_queue(QueueUrl=sqs_url) logger.info(f'PurgeQueue response: {json.dumps(purgeResponse)}') return notificationResponse diff --git a/src/sentiment/sentiment.py b/src/sentiment/sentiment.py index 7974e3c..3b587cd 100644 --- a/src/sentiment/sentiment.py +++ b/src/sentiment/sentiment.py @@ -16,19 +16,21 @@ max_object_size = 104857600 # 100MB = 104857600 bytes +aws_region = os.environ['AWS_REGION'] + s_table = os.getenv('SENTIMENT_TABLE') s_queue = os.getenv('SENTIMENT_QUEUE') log_level = os.getenv('LOG_LEVEL') -comprehend_client = boto3.client('comprehend') +comprehend_client = boto3.client('comprehend', region_name=aws_region) -s3_resource = boto3.resource('s3') +s3_resource = boto3.resource('s3', region_name=aws_region) -dynamodb_resource = boto3.resource('dynamodb') +dynamodb_resource = boto3.resource('dynamodb', region_name=aws_region) table = dynamodb_resource.Table(s_table) -sqs_client = boto3.client('sqs') +sqs_client = boto3.client('sqs', region_name=aws_region) log = logging.getLogger() From 1f56948f4495e0ce826558ce39035165493d7c9f Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 15 May 2020 15:25:06 +0100 Subject: [PATCH 094/115] Added end to end testing stage --- buildspec-test.yml | 12 +++++++ pipeline/pipeline.yaml | 54 +++++++++++++++++++++++++++++++ tests.sh | 42 ++++++++++++++++++++++++ sample-1.md => tests/sample-01.md | 0 sample-2.md => tests/sample-02.md | 0 tests/sample-03.md | 15 +++++++++ tests/sample-04.md | 15 +++++++++ tests/sample-05.md | 15 +++++++++ tests/sample-06.md | 15 +++++++++ tests/sample-07.md | 15 +++++++++ tests/sample-08.md | 15 +++++++++ tests/sample-09.md | 15 +++++++++ tests/sample-10.md | 15 +++++++++ tests/sample-11.md | 15 +++++++++ tests/sample-12.md | 15 +++++++++ tests/sample-13.md | 15 +++++++++ tests/sample-14.md | 15 +++++++++ tests/sample-15.md | 15 +++++++++ tests/sample-16.md | 15 +++++++++ tests/sample-17.md | 15 +++++++++ tests/sample-18.md | 15 +++++++++ tests/sample-19.md | 15 +++++++++ tests/sample-20.md | 15 +++++++++ tests/sample-21.md | 15 +++++++++ tests/sample-22.md | 15 +++++++++ tests/sample-23.md | 15 +++++++++ tests/sample-24.md | 15 +++++++++ 27 files changed, 438 insertions(+) create mode 100644 buildspec-test.yml create mode 100644 tests.sh rename sample-1.md => tests/sample-01.md (100%) rename sample-2.md => tests/sample-02.md (100%) create mode 100644 tests/sample-03.md create mode 100644 tests/sample-04.md create mode 100644 tests/sample-05.md create mode 100644 tests/sample-06.md create mode 100644 tests/sample-07.md create mode 100644 tests/sample-08.md create mode 100644 tests/sample-09.md create mode 100644 tests/sample-10.md create mode 100644 tests/sample-11.md create mode 100644 tests/sample-12.md create mode 100644 tests/sample-13.md create mode 100644 tests/sample-14.md create mode 100644 tests/sample-15.md create mode 100644 tests/sample-16.md create mode 100644 tests/sample-17.md create mode 100644 tests/sample-18.md create mode 100644 tests/sample-19.md create mode 100644 tests/sample-20.md create mode 100644 tests/sample-21.md create mode 100644 tests/sample-22.md create mode 100644 tests/sample-23.md create mode 100644 tests/sample-24.md diff --git a/buildspec-test.yml b/buildspec-test.yml new file mode 100644 index 0000000..f8d0464 --- /dev/null +++ b/buildspec-test.yml @@ -0,0 +1,12 @@ +version: 0.2 + +phases: + install: + runtime-versions: + python: 3.7 + commands: + - pip install --upgrade awscli + build: + commands: + - chmod +x tests.sh + - ./tests.sh $OUTPUT_STACK_NAME diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index 14dad62..bd1ad8f 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -59,6 +59,31 @@ Resources: - Key: app-name Value: !Ref AppName TimeoutInMinutes: 5 + CodeBuildTestProject: + DependsOn: [PipelineBucket] + Description: AWS CodeBuild project + Type: AWS::CodeBuild::Project + Properties: + Artifacts: + Type: CODEPIPELINE + Description: !Sub "Testing stage for ${AppName}." + Environment: + ComputeType: BUILD_GENERAL1_SMALL + PrivilegedMode: True + EnvironmentVariables: + - Name: OUTPUT_STACK_NAME + Value: !Sub "${AppName}" + Image: !Ref CodeBuildImage + Type: LINUX_CONTAINER + Name: !Sub "${AppName}-test" + ServiceRole: !GetAtt CodeBuildTrustRole.Arn + Source: + Type: CODEPIPELINE + BuildSpec: "buildspec-test.yml" + Tags: + - Key: app-name + Value: !Ref AppName + TimeoutInMinutes: 5 PipelineBucket: Description: S3 bucket for AWS CodePipeline artifacts Type: AWS::S3::Bucket @@ -196,6 +221,19 @@ Resources: ActionMode: CHANGE_SET_EXECUTE ChangeSetName: pipeline-changeset RunOrder: 3 + - Name: Test + Actions: + - Name: end-to-end + InputArtifacts: + - Name: !Sub "${AppName}-SourceArtifact" + ActionTypeId: + Category: Build + Owner: AWS + Version: "1" + Provider: CodeBuild + Configuration: + ProjectName: !Sub "${AppName}-test" + RunOrder: 1 ArtifactStore: Type: S3 Location: !Ref PipelineBucket @@ -251,6 +289,22 @@ Resources: - Effect: Allow Action: ["s3:*"] Resource: !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + - Effect: Allow + Action: ["s3:*"] + Resource: !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + - Effect: Allow + Action: + - dynamodb:GetItem + - dynamodb:DeleteItem + Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table-${AppName}-SentimentTable-*" + - Effect: Allow + Action: + - s3:PutObject + - s3:GetObect + - s3:DeleteObject + Resource: + - !Sub "arn:aws:s3:::*-*-inputbucket" + - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*" - Effect: Allow Action: - kms:GenerateDataKey* diff --git a/tests.sh b/tests.sh new file mode 100644 index 0000000..5975d31 --- /dev/null +++ b/tests.sh @@ -0,0 +1,42 @@ +#!/bin/bash + + +## Get Stack Resources + +BUCKET_IN=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id 'InputBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) +BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id 'ConversionTargetBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) +DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id 'SentimentTable' --query "StackResourceDetail.PhysicalResourceId" --output text) + +echo "Input Bucket: $BUCKET_IN" +echo "Ouput Bucket: $BUCKET_OUT" +echo "Dynamo Table: $BUCKET_IN" + +## Get Samples + +TEST_FILES=(~/tests/*.md) + +## Upload test samples + +for f in "${arr[@]}"; do + echo "Test file found: $f" +done + + + +# echo "Clearing out resources of lambda-file-refarch stack..." +# echo +# echo "Cleaning up S3 buckets..." && for bucket in InputBucket ConversionTargetBucket; do +# echo "Clearing out ${bucket}..." +# BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) +# aws s3 rm s3://${BUCKET} --recursive +# echo +# done + +# echo "Deleting CloudFormation stack..." && aws cloudformation delete-stack \ +# --stack-name lambda-file-refarch + +# echo "Clearing out CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix '/aws/lambda/lambda-file-refarch-' --query "logGroups[*].logGroupName" --output text); do +# echo "Removing log group ${log_group}..." +# aws logs delete-log-group --log-group-name ${log_group} +# echo +# done diff --git a/sample-1.md b/tests/sample-01.md similarity index 100% rename from sample-1.md rename to tests/sample-01.md diff --git a/sample-2.md b/tests/sample-02.md similarity index 100% rename from sample-2.md rename to tests/sample-02.md diff --git a/tests/sample-03.md b/tests/sample-03.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-03.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-04.md b/tests/sample-04.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-04.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-05.md b/tests/sample-05.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-05.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-06.md b/tests/sample-06.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-06.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-07.md b/tests/sample-07.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-07.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-08.md b/tests/sample-08.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-08.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-09.md b/tests/sample-09.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-09.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-10.md b/tests/sample-10.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-10.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-11.md b/tests/sample-11.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-11.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-12.md b/tests/sample-12.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-12.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-13.md b/tests/sample-13.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-13.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-14.md b/tests/sample-14.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-14.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-15.md b/tests/sample-15.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-15.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-16.md b/tests/sample-16.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-16.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-17.md b/tests/sample-17.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-17.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-18.md b/tests/sample-18.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-18.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-19.md b/tests/sample-19.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-19.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-20.md b/tests/sample-20.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-20.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-21.md b/tests/sample-21.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-21.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-22.md b/tests/sample-22.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-22.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-23.md b/tests/sample-23.md new file mode 100644 index 0000000..aea9cb6 --- /dev/null +++ b/tests/sample-23.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with hated the new thing. They used words like 'terrible', 'awful', and 'boring' to describe the new thing. + +## Interview 2 + +The person I spoke with was really not impressed. They used words like 'confusing', 'complex', and 'terrible' to describe the new thing. + +# Summary + +In short, the two people interviewed were not very happy with the new thing. \ No newline at end of file diff --git a/tests/sample-24.md b/tests/sample-24.md new file mode 100644 index 0000000..740534b --- /dev/null +++ b/tests/sample-24.md @@ -0,0 +1,15 @@ +# Introduction + +This is a report that captures important information regarding an interview. + +## Interview 1 + +The person I spoke with was elated. They used words like 'fantastic', 'impressive', and 'ground breaking' to describe the new thing. + +## Interview 2 + +The person I spoke with was really pleased. They used words like 'wow', 'great', and 'cool' to describe the new thing. + +# Summary + +In short, the two people interviewed were very happy with the new thing. \ No newline at end of file From 29e728e140e6c163b9b7578def8595a8e42b3e78 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 15 May 2020 15:25:51 +0100 Subject: [PATCH 095/115] added pycharm --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 5cbe22e..a0bbe76 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ packaged-template.yml .aws-sam +.idea __pycache__ \ No newline at end of file From a97d1e63ba23aed34bbcf92bc66adfea8d0e1b5d Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 18 May 2020 14:51:50 +0100 Subject: [PATCH 096/115] Added permissions and test failure code. --- buildspec-test.yml | 4 ++++ buildspec.yml | 2 ++ pipeline/pipeline.yaml | 11 +++++++++-- 3 files changed, 15 insertions(+), 2 deletions(-) diff --git a/buildspec-test.yml b/buildspec-test.yml index f8d0464..8c21fcd 100644 --- a/buildspec-test.yml +++ b/buildspec-test.yml @@ -10,3 +10,7 @@ phases: commands: - chmod +x tests.sh - ./tests.sh $OUTPUT_STACK_NAME + post_build: + commands: + - bash -c "if [ /"$CODEBUILD_BUILD_SUCCEEDING/" == /"0/" ]; then exit 1; fi" + - echo Test stage successfully completed on `date` diff --git a/buildspec.yml b/buildspec.yml index a89995b..208e225 100644 --- a/buildspec.yml +++ b/buildspec.yml @@ -12,6 +12,8 @@ phases: post_build: commands: - sam package --output-template-file $SAM_OUTPUT_TEMPLATE --s3-bucket $ARTIFACT_BUCKET + - bash -c "if [ /"$CODEBUILD_BUILD_SUCCEEDING/" == /"0/" ]; then exit 1; fi" + - echo Build stage successfully completed on `date` artifacts: files: - $SAM_OUTPUT_TEMPLATE diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index bd1ad8f..e870ef0 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -285,13 +285,18 @@ Resources: - logs:CreateLogGroup - logs:CreateLogStream - logs:PutLogEvents - Resource: !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" + Resource: + - !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-build*" + - !Sub "arn:aws:logs:${AWS::Region}:${AWS::AccountId}:log-group:/aws/codebuild/${AppName}-test*" - Effect: Allow Action: ["s3:*"] Resource: !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" - Effect: Allow Action: ["s3:*"] Resource: !Sub "arn:aws:s3:::pipeline-${AWS::AccountId}-${AWS::Region}-${AppName}/*" + - Effect: Allow + Action: ["cloudformation:DescribeStackResource"] + Resource: !Sub "arn:aws:cloudformation:${AWS::Region}:${AWS::AccountId}:stack/${AppName}/*" - Effect: Allow Action: - dynamodb:GetItem @@ -447,7 +452,9 @@ Resources: - Action: - codebuild:StartBuild - codebuild:BatchGetBuilds - Resource: !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-build" + Resource: + - !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-build" + - !Sub "arn:aws:codebuild:${AWS::Region}:${AWS::AccountId}:project/${AppName}-test" Effect: Allow - Action: - cloudformation:* From eeec833f1ce9fa1cc696438422db6376a36c16ad Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 18 May 2020 15:28:57 +0100 Subject: [PATCH 097/115] updated test script --- tests.sh | 171 ++++++++++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 149 insertions(+), 22 deletions(-) diff --git a/tests.sh b/tests.sh index 5975d31..ef44c9b 100644 --- a/tests.sh +++ b/tests.sh @@ -1,42 +1,169 @@ #!/bin/bash +set -e + +if [ -z $1 ]; then + echo "Stack name not passed, exiting" + exit 1 +fi + +STACK=$1 +echo "$STACK" + + +function clean { + + ## Cleanup DB + + + for f in "${TEST_FILES[@]}"; do + + FILE_NAME=$(cut -d "/" -f2- <<< "$f") + + echo "Removing item from DB : $FILE_NAME" + + aws dynamodb delete-item --table-name $DYNAMO_TABLE \ + --key "{\"id\": {\"S\": \"s3://$BUCKET_IN/$FILE_NAME\"}}" + + + if [ $? -ne 0 ]; then + echo -e "Remove item failed" ; exit 1 + fi + + done + + ## Cleanup Output + + + for f in "${TEST_FILES[@]}"; do + + FILE_NAME=$(cut -d "/" -f2- <<< "$f") + + echo "Removing from output : ${FILE_NAME/md/html}" + + aws s3 rm s3://"$BUCKET_OUT"/"${FILE_NAME/md/html}" + + if [[ $? -ne 0 ]]; then + echo -e "File not processed" ; exit 1 + fi + + done + + ## Cleanup Input + + + for f in "${TEST_FILES[@]}"; do + + FILE_NAME=$(cut -d "/" -f2- <<< "$f") + + echo "Removing from input: $FILE_NAME" + + aws s3 rm s3://"$BUCKET_IN"/"$FILE_NAME" + + if [[ $? -ne 0 ]]; then + echo -e "File not processed" ; exit 1 + fi + + + done + + +} + ## Get Stack Resources -BUCKET_IN=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id 'InputBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) -BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id 'ConversionTargetBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) -DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id 'SentimentTable' --query "StackResourceDetail.PhysicalResourceId" --output text) +BUCKET_IN=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'InputBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) +BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'ConversionTargetBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) +DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'SentimentTable' --query "StackResourceDetail.PhysicalResourceId" --output text) echo "Input Bucket: $BUCKET_IN" echo "Ouput Bucket: $BUCKET_OUT" -echo "Dynamo Table: $BUCKET_IN" +echo "Dynamo Table: $DYNAMO_TABLE" ## Get Samples -TEST_FILES=(~/tests/*.md) +TEST_FILES=(tests/sample-*.md) ## Upload test samples -for f in "${arr[@]}"; do - echo "Test file found: $f" +for f in "${TEST_FILES[@]}"; do + + FILE_NAME=$(cut -d "/" -f2- <<< "$f") + + echo "Upload sample : $FILE_NAME" + + aws s3 cp $f s3://"$BUCKET_IN"/"$FILE_NAME" + + if [ $? -ne 0 ]; then + echo -e "Upload Failed" ; exit 1 + fi + +done + + +# Give Lambda a chance to execute or wait for last file to get to output. + +END=$((SECONDS+30)) + +echo "Wating for execution" + +while [ $SECONDS -lt $END ] + +do + + FILE_NAME=$(cut -d "/" -f2- <<< ${TEST_FILES[-1]}) + + EXISTS=$(aws s3api head-object --bucket $BUCKET_OUT --key ${FILE_NAME/md/html}) || NOT_EXIST=true + + if [[ $EXISTS ]]; then + echo "File exists, continuing" + break + fi + + echo "File doesn't exist yet... Waiting for timeout." + sleep 1 + +done + + +# Check for files in output bucket + +for f in "${TEST_FILES[@]}"; do + + FILE_NAME=$(cut -d "/" -f2- <<< "$f") + + echo "Checking for Output : ${FILE_NAME/md/html}" + + EXISTS=(aws s3api head-object --bucket $BUCKET_OUT --key ${FILE_NAME/md/html}) || $NOT_EXIST=true + + if [[ -z $EXISTS ]]; then + echo -e "File ${FILE_NAME/md/html} not processed" ; exit 1 + fi + + echo "${FILE_NAME/md/html} found" + done +# Check DynamoDB for Sentiment + +for f in "${TEST_FILES[@]}"; do + FILE_NAME=$(cut -d "/" -f2- <<< "$f") -# echo "Clearing out resources of lambda-file-refarch stack..." -# echo -# echo "Cleaning up S3 buckets..." && for bucket in InputBucket ConversionTargetBucket; do -# echo "Clearing out ${bucket}..." -# BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id ${bucket} --query "StackResourceDetail.PhysicalResourceId" --output text) -# aws s3 rm s3://${BUCKET} --recursive -# echo -# done + echo "Checking for Sentiment : $FILE_NAME" -# echo "Deleting CloudFormation stack..." && aws cloudformation delete-stack \ -# --stack-name lambda-file-refarch + SENTIMENT=$(aws dynamodb get-item --table-name $DYNAMO_TABLE \ + --projection-expression "overall_sentiment" \ + --key "{\"id\": {\"S\": \"s3://$BUCKET_IN/$FILE_NAME\"}}") + + if [[ -z $SENTIMENT ]]; then + echo -e "No Sentiment" ; exit 1 + fi + + echo $SENTIMENT + +done -# echo "Clearing out CloudWatch Log Groups..." && for log_group in $(aws logs describe-log-groups --log-group-name-prefix '/aws/lambda/lambda-file-refarch-' --query "logGroups[*].logGroupName" --output text); do -# echo "Removing log group ${log_group}..." -# aws logs delete-log-group --log-group-name ${log_group} -# echo -# done +# Call Clean Up +clean From fed0588993bf2d2d54df9f9aec92161b1777e164 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 18 May 2020 16:50:13 +0100 Subject: [PATCH 098/115] updated test script --- 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b/pipeline/README.md @@ -23,7 +23,7 @@ pipeline.yml is a CloudFormation template that will deploy all the required pipe * Pipeline S3 bucket, used to store pipeline artefacts that are passed between stages. * CodePipeline -* CodeBuild Project +* CodeBuild Build and Test Projects * Roles for CodePipeline, CodeBuild and the CloudFormation Deployment * SNS Topic for Pipeline notifications * CloudWatch Event for Pipeline Failures @@ -59,6 +59,12 @@ To deploy our application stack we are not using SAM Deploy, CodePipeline doesn' You will need to approve the deployment before the pipeline execution actually deploys any resources. Once approved, additional resources will be deployed as per the main architecture documentation. +### Test + +The test stage will execute a bash script to perform an end to end test of the application. It uploads 24 sample files from the tests directory and checks for outputs and sentiment DB entries. + +If it cannot locate either the output files or DB entries the pipeline will fail. Once the tests successfully complete the script removes the test resources. + ## Getting started diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index e870ef0..d68709d 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -301,15 +301,15 @@ Resources: Action: - dynamodb:GetItem - dynamodb:DeleteItem - Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table-${AppName}-SentimentTable-*" + Resource: !Sub "arn:aws:dynamodb:${AWS::Region}:${AWS::AccountId}:table/${AppName}-SentimentTable-*" - Effect: Allow Action: - s3:PutObject - - s3:GetObect + - s3:GetObject - s3:DeleteObject Resource: - - !Sub "arn:aws:s3:::*-*-inputbucket" - - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*" + - !Sub "arn:aws:s3:::${AppName}-${AWS::AccountId}-inputbucket/*" + - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*/*" - Effect: Allow Action: - kms:GenerateDataKey* diff --git a/tests.sh b/tests.sh index ef44c9b..32a9b14 100644 --- a/tests.sh +++ b/tests.sh @@ -73,9 +73,20 @@ function clean { ## Get Stack Resources -BUCKET_IN=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'InputBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) -BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'ConversionTargetBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) -DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'SentimentTable' --query "StackResourceDetail.PhysicalResourceId" --output text) +BUCKET_IN=$(aws cloudformation describe-stack-resource \ +--stack-name "$STACK" --logical-resource-id 'InputBucket' \ +--query "StackResourceDetail.PhysicalResourceId" \ +--output text) || echo -e "Couldn't get stack details" ; exit 1 + +BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name "$STACK" \ +--logical-resource-id 'ConversionTargetBucket' \ +--query "StackResourceDetail.PhysicalResourceId" \ +--output text) || echo -e "Couldn't get stack details" ; exit 1 + +DYNAMO_TABLE=$(aws cloudformation describe-stack-resource \ +--stack-name "$STACK" --logical-resource-id 'SentimentTable' \ +--query "StackResourceDetail.PhysicalResourceId" \ +--output text) || echo -e "Couldn't get stack details" ; exit 1 echo "Input Bucket: $BUCKET_IN" echo "Ouput Bucket: $BUCKET_OUT" From 9d95ad234185974106029aec52ce4ca27e664b63 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 27 May 2020 11:37:45 +0100 Subject: [PATCH 099/115] Improved formatting to make it more readable --- WELL-ARCHITECTED.md | 122 ++++++++++++++++++++++++-------------------- 1 file changed, 66 insertions(+), 56 deletions(-) diff --git a/WELL-ARCHITECTED.md b/WELL-ARCHITECTED.md index 71d2228..d390126 100644 --- a/WELL-ARCHITECTED.md +++ b/WELL-ARCHITECTED.md @@ -3,29 +3,27 @@ #### OPS 1. How do you evaluate your Serverless application’s health? * [ ] Question does not apply to this workload -
* [x] **[Required]** Understand, analyze and alert on metrics provided out of the box * [x] **[Best]** Use application, business, and operations metrics * [x] **[Good]** Use distributed tracing and code is instrumented with additional context -* [ ] **[Good]** Use structured and centralized logging -
- +* [ ] **[Good]** Use structured and centralized logging * [ ] None of these - + ##### Notes -The example uses structured logging output to Cloudwatch. For our example we only deploy to a single account so we don't require the use of cross account centralised logging. - -We have alarms configured with notifications should processing fail. +>* The example uses structured logging output to Cloudwatch. For our example we only deploy to a single account so we don't require the use of cross account centralised logging. +> +>* We have alarms configured with notifications should processing fail. +> +>* We do not have a defined KPI within the application. We could however use a metric such as number of records processed within a given time frame and alert if this is outside of the defined thresholds. -We do not have a defined KPI within the application. We could however use a metric such as number of records processed within a given time frame and alert if this is outside of the defined thresholds. +--- #### OPS 2. How do you approach application lifecycle management? * [ ] Question does not apply to this workload -
* [x] **[Required]** Use infrastructure as code and stages isolated in separate environments * [x] **[Good]** Prototype new features using temporary environments @@ -33,168 +31,180 @@ We do not have a defined KPI within the application. We could however use a metr * [ ] **[Good]** Use configuration management * [ ] **[Good]** Review the function runtime deprecation policy * [ ] **[Best]** Use CI/CD including automated testing across separate accounts -
* [ ] None of these ##### Notes -Our example utilizes infrastructure as code and includes a simple pipeline that will build and deploy within an individual account and to an individual environment. However the nature of this example means it can be deployed many times it's possible. You can for example deploy a staging pipeline that would watch a development branch and deploy and changes to the Staging application stack. You could also deploy a production pipeline stack that watches the master branch and merges here will trigger a production release. +>* Our example utilizes infrastructure as code and includes a simple pipeline that will build and deploy within an individual account and to an individual environment. However the nature of this example means it can be deployed many times it's possible. You can for example deploy a staging pipeline that would watch a development branch and deploy and changes to the Staging application stack. You could also deploy a production pipeline stack that watches the master branch and merges here will trigger a production release. +> +>* For this example a rollout mechanism would involve adopting either a Blue / Green deployment strategy with you controlling which input bucket a particular user hits . Alternatively for application business logic only changes these could be tested by having a notification invoke an alternate version of a lambda under specific conditions. -For this example a rollout mechanism would involve adopting either a Blue / Green deployment strategy with you controlling which input bucket a particular user hits . Alternatively for application business logic only changes these could be tested by having a notification invoke an alternate version of a lambda under specific conditions. +--- -### Security +## Security #### SEC 1: How do you control access to your Serverless API? * [x] Question does not apply to this workload -
+ * [ ] **[Required]** Use appropriate endpoint type and mechanisms to secure access to your API * [ ] **[Good]** Use authentication and authorization mechanisms * [ ] **[Best]** Scope access based on identity’s metadata -
+ * [ ] None of these ##### Notes -This solution doesn't include an API frontend so the question doesn't apply. +>This solution doesn't include an API frontend so the question doesn't apply. + +--- #### SEC 2: How do you manage your Serverless application’s security boundaries? * [ ] Question does not apply to this workload -
+ * [x] **[Required]** Evaluate and define resource policies * [x] **[Good]** Control network traffic at all layers * [x] **[Best]** Smaller functions require fewer permissions * [x] **[Required]** Use temporary credentials between resources and components -
* [ ] None of these ##### Notes -We use IAM policy to ensure that resources can only be called by other resources that should be calling them. - -The pipeline will assume a role with only the permissions it requires to deploy the application. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. - -This application does not use private networking. +> * We use IAM policy to ensure that resources can only be called by other resources that should be calling them. +> +> * The pipeline will assume a role with only the permissions it requires to deploy the application. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. +> +> * This application does not use private networking. +> +> * We have individual functions for each different piece of business logic. -We have individual functions for each different piece of business logic. +--- #### SEC 3: How do you implement Application Security in your workload?*** * [ ] Question does not apply to this workload -
+ * [x] **[Required]** Review security awareness documents frequently * [x] **[Required]** Store secrets that are used in your code securely * [ ] **[Good]** Implement runtime protection to help prevent against malicious code execution * [ ] **[Best]** Automatically review workload’s code dependencies/libraries * [x] **[Best]** Validate inbound events -
+ * [ ] None of these ##### Notes -This application doesn't have any stored secrets. The GitHub token is required by CodePipeline, this is passed as a string for CloudFormation, it is not however visible within the CloudFormation console. This could be improved by manually creating a secrets manager entry for the token and replacing the CloudFormation parameter for the token with the secrets manager value by utilising Dynamic References. -https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/dynamic-references.html +> * This application doesn't have any stored secrets. The GitHub token is required by CodePipeline, this is passed as a string for CloudFormation, it is not however visible within the CloudFormation console. This could be improved by manually creating a secrets manager entry for the token and replacing the CloudFormation parameter for the token with the secrets manager value by utilising Dynamic References. +>https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/dynamic-references.html +> +> * For reviewing dependencies and libraries we could integrate an automatic check into the pipeline. There are many tools and providers which can check code. Currently this is manual using PEP8 and Bandit manual checks. +> +> * We only check for particular events and check to make sure the object is valid. -For reviewing dependencies and libraries we could integrate an automatic check into the pipeline. There are many tools and providers which can check code. Currently this is manual using PEP8 and Bandit manual checks. +--- -We only check for particular events and check to make sure the object is valid. - - -### Reliability +## Reliability #### REL 1. How do you regulate inbound request rates? * [ ] Question does not apply to this workload -
+ * [x] **[Required]** Use throttling to control inbound request rates * [ ] **[Good]** Use, analyze and enforce API quotas * [X] **[Best]** Use mechanisms to protect non-scalable resources -
+ * [ ] None of these ##### Notes -We are using SQS queues in front of our Lambda functions, this helps us throttle the rate at which our application processes requests. - -We don't have API's to set quotas for. +> * We are using SQS queues in front of our Lambda functions, this helps us throttle the rate at which our application processes requests. +> +> * We don't have API's to set quotas for. +> +> * Our downstream resources are S3 and DynamoDB on-demand which are more than capable of scaling to match our volumes. -Our downstream resources are S3 and DynamoDB on-demand which are more than capable of scaling to match our volumes. +--- #### REL 2. How do you build resiliency into your Serverless application? * [ ] Question does not apply to this workload -
+ * [x] **[Required]** Manage transaction, partial, and intermittent failures * [ ] **[Required]** Manage duplicate and unwanted events * [ ] **[Good]** Orchestrate long-running transactions * [x] **[Best]** Consider scaling patterns at burst rates -
+ * [ ] None of these -We use SQS queues and DLQ's to ensure any processing failure results in a notification. +##### Notes -Our example does not deal with duplicate events or files. Any duplicate will overwrite the previous, this could be improved inserting another layer of business logic that first checks the inbound file and renames with a UUID, it could additionally check to see if the file hash has already been processed. +> * We use SQS queues and DLQ's to ensure any processing failure results in a notification. +> +> * Our example does not deal with duplicate events or files. Any duplicate will overwrite the previous, this could be improved inserting another layer of business logic that first checks the inbound file and renames with a UUID, it could additionally check to see if the file hash has already been processed. +> +> * The processing time of our transactions is fast and we can handle multiple files in a single invocation. Under heavy load of inbound files the SQS queue handles the work being distributed to lambda up to 1000 concurrent batches. -The processing time of our transactions is fast and we can handle multiple files in a single invocation. Under heavy load of inbound files the SQS queue handles the work being distributed to lambda up to 1000 concurrent batches. +--- -##### Notes +## Performance Efficiency #### PERF 1. How do you optimize your Serverless application’s performance? * [ ] Question does not apply to this workload -
+ * [x] **[Required]** Measure, evaluate, and select optimum capacity units * [x] **[Good]** Measure and optimize function startup time * [ ] **[Good]** Take advantage of concurrency via async and stream-based function invocations * [x] **[Good]** Optimize access patterns and apply caching where applicable * [x] **[Best]** Integrate with managed services directly over functions when possible -
* [ ] None of these ##### Notes -We have looked at how our function performs with different batch sizes and memory configurations to find what we believe is optimal for cost/performance . - -For our example there is no real advantage to async. If concurrency was an issue it would be possible to chain the business logic, rather than perform it in parallel. +> * We have looked at how our function performs with different batch sizes and memory configurations to find what we believe is optimal for cost/performance . +> +> * For our example there is no real advantage to async. If concurrency was an issue it would be possible to chain the business logic, rather than perform it in parallel. +> +> * Data is pulled from S3 and held locally and cached for the execution, however currently there is only a single task performed per invocation so there is no benefit. Caching outside of the function would offer no benefit over S3. +> +> * In our Sentiment function we are utilising comprehend which a managed service. -Data is pulled from S3 and held locally and cached for the execution, however currently there is only a single task performed per invocation so there is no benefit. Caching outside of the function would offer no benefit over S3. +--- -In our Sentiment function we are utilising comprehend which a managed service. +## Cost Optimization #### COST 1. How do you optimize your Serverless application’s costs? * [ ] Question does not apply to this workload -
* [x] **[Required]** Minimize external calls and function code initialization * [x] **[Required]** Optimize logging output and its retention * [x] **[Good]** Optimize function configuration to reduce cost * [x] **[Best]** Use cost-aware usage patterns in code -
* [ ] None of these ##### Notes -We have configurable logging levels and bench marked our function for optimal cost/performance. +>We have configurable logging levels and bench marked our function for optimal cost/performance. From b92623a0004c9276f18717bbba7811ee896190ac Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 1 Jul 2020 17:13:37 +0100 Subject: [PATCH 100/115] Added code notes for extension replacement and updated README.md to reflect new sample test files. --- .gitignore | 1 + README.md | 6 +++--- tests.sh | 2 ++ 3 files changed, 6 insertions(+), 3 deletions(-) diff --git a/.gitignore b/.gitignore index a0bbe76..bbd3428 100644 --- a/.gitignore +++ b/.gitignore @@ -1,4 +1,5 @@ packaged-template.yml .aws-sam .idea +.history __pycache__ \ No newline at end of file diff --git a/README.md b/README.md index bae4777..f310c7f 100644 --- a/README.md +++ b/README.md @@ -91,14 +91,14 @@ You will receive an email asking you to confirm subscription to the `lambda-file ## Testing the Example -After you have created the stack using the CloudFormation template, you can test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use the sample-1.md and sample-2.md files in the repository as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. +After you have created the stack using the CloudFormation template, you can manually test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use the any of the sample-xx.md files in the repository /tests directory as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. ```bash INPUT_BUCKET=$(aws cloudformation describe-stack-resource --stack-name lambda-file-refarch --logical-resource-id InputBucket --query "StackResourceDetail.PhysicalResourceId" --output text) -aws s3 cp ./sample-1.md s3://${INPUT_BUCKET}/sample-1.md -aws s3 cp ./sample-2.md s3://${INPUT_BUCKET}/sample-2.md +aws s3 cp ./tests/sample-01.md s3://${INPUT_BUCKET}/sample-01.md +aws s3 cp ./tests/sample-02.md s3://${INPUT_BUCKET}/sample-02.md ``` Once the input files has been uploaded to the input bucket, a series of events are put into motion. diff --git a/tests.sh b/tests.sh index 32a9b14..30bac90 100644 --- a/tests.sh +++ b/tests.sh @@ -37,6 +37,8 @@ function clean { for f in "${TEST_FILES[@]}"; do + ## We know our output files will have a html extention so we need to substitute md for html when working with the output. + FILE_NAME=$(cut -d "/" -f2- <<< "$f") echo "Removing from output : ${FILE_NAME/md/html}" From 4ec1b6b3153b579f4fff574ea10e4e6ba11d9ab3 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Wed, 1 Jul 2020 17:26:57 +0100 Subject: [PATCH 101/115] Added notes for event duplication and rephrased SEC2 for application as a whole rather than pipeline. --- WELL-ARCHITECTED.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/WELL-ARCHITECTED.md b/WELL-ARCHITECTED.md index d390126..02c88f1 100644 --- a/WELL-ARCHITECTED.md +++ b/WELL-ARCHITECTED.md @@ -81,7 +81,7 @@ > * We use IAM policy to ensure that resources can only be called by other resources that should be calling them. > -> * The pipeline will assume a role with only the permissions it requires to deploy the application. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. +> * All application components will assume a role with only the permissions it requires in order to perform it's function. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. > > * This application does not use private networking. > @@ -146,7 +146,7 @@ * [x] **[Required]** Manage transaction, partial, and intermittent failures -* [ ] **[Required]** Manage duplicate and unwanted events +* [x] **[Required]** Manage duplicate and unwanted events * [ ] **[Good]** Orchestrate long-running transactions * [x] **[Best]** Consider scaling patterns at burst rates @@ -157,7 +157,9 @@ > * We use SQS queues and DLQ's to ensure any processing failure results in a notification. > -> * Our example does not deal with duplicate events or files. Any duplicate will overwrite the previous, this could be improved inserting another layer of business logic that first checks the inbound file and renames with a UUID, it could additionally check to see if the file hash has already been processed. +> * The Dynamo key and converted S3 object for each analysis is tied to the input object being analyzed. Pushing the same document will result in the same artifact. +> +> * Our example does not deal with duplicate files. Any duplicate will overwrite the previous, this could be improved inserting another layer of business logic that first checks the inbound file and renames with a UUID, it could additionally check to see if the file hash has already been processed. > > * The processing time of our transactions is fast and we can handle multiple files in a single invocation. Under heavy load of inbound files the SQS queue handles the work being distributed to lambda up to 1000 concurrent batches. From f640e11838fc44c5ecf079de8e71bb7507326343 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 2 Jul 2020 12:20:23 +0100 Subject: [PATCH 102/115] Corrected a sentence which made no sense, and the spelling error. --- WELL-ARCHITECTED.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/WELL-ARCHITECTED.md b/WELL-ARCHITECTED.md index 02c88f1..94b6035 100644 --- a/WELL-ARCHITECTED.md +++ b/WELL-ARCHITECTED.md @@ -37,7 +37,7 @@ ##### Notes ->* Our example utilizes infrastructure as code and includes a simple pipeline that will build and deploy within an individual account and to an individual environment. However the nature of this example means it can be deployed many times it's possible. You can for example deploy a staging pipeline that would watch a development branch and deploy and changes to the Staging application stack. You could also deploy a production pipeline stack that watches the master branch and merges here will trigger a production release. +>* Our example utilizes infrastructure as code and includes a simple pipeline that will build and deploy within an individual account and to an individual environment. However the nature of this example means it can be deployed multiple times with different configurations. You can for example deploy a staging pipeline that would watch a development branch and deploy and changes to the Staging application stack. You could also deploy a production pipeline stack that watches the master branch and merges here will trigger a production release. > >* For this example a rollout mechanism would involve adopting either a Blue / Green deployment strategy with you controlling which input bucket a particular user hits . Alternatively for application business logic only changes these could be tested by having a notification invoke an alternate version of a lambda under specific conditions. @@ -81,7 +81,7 @@ > * We use IAM policy to ensure that resources can only be called by other resources that should be calling them. > -> * All application components will assume a role with only the permissions it requires in order to perform it's function. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. +> * All application components will assume a role with only the permissions it requires in order to perform its function. This will either be only being able to perform a specific action on multiple resources or any action on a particular resource. > > * This application does not use private networking. > From b109c8dd039e32f4194463352fba0fa4c20faf96 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 2 Jul 2020 20:39:03 +0100 Subject: [PATCH 103/115] Update pollicy for input bucket name change --- pipeline/pipeline.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index d68709d..b746b4c 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -308,7 +308,7 @@ Resources: - s3:GetObject - s3:DeleteObject Resource: - - !Sub "arn:aws:s3:::${AppName}-${AWS::AccountId}-inputbucket/*" + - !Sub "arn:aws:s3:::${AppName}-${AWS::AccountId}-input-bucket/*" - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*/*" - Effect: Allow Action: @@ -346,7 +346,7 @@ Resources: - s3:DeleteBucketPolicy - s3:PutBucketPolicy Resource: - - !Sub "arn:aws:s3:::*-*-inputbucket" + - !Sub "arn:aws:s3:::*-*-input-bucket" - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*" Effect: Allow From 19f38bd29e623056dc2cde3eda4ce9dd08a9e967 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 2 Jul 2020 21:02:29 +0100 Subject: [PATCH 104/115] Update pollicy for input bucket name change --- pipeline/pipeline.yaml | 4 ++-- template.yml | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/pipeline/pipeline.yaml b/pipeline/pipeline.yaml index b746b4c..d68709d 100644 --- a/pipeline/pipeline.yaml +++ b/pipeline/pipeline.yaml @@ -308,7 +308,7 @@ Resources: - s3:GetObject - s3:DeleteObject Resource: - - !Sub "arn:aws:s3:::${AppName}-${AWS::AccountId}-input-bucket/*" + - !Sub "arn:aws:s3:::${AppName}-${AWS::AccountId}-inputbucket/*" - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*/*" - Effect: Allow Action: @@ -346,7 +346,7 @@ Resources: - s3:DeleteBucketPolicy - s3:PutBucketPolicy Resource: - - !Sub "arn:aws:s3:::*-*-input-bucket" + - !Sub "arn:aws:s3:::*-*-inputbucket" - !Sub "arn:aws:s3:::${AppName}-conversiontargetbucket-*" Effect: Allow diff --git a/template.yml b/template.yml index 2a8dc31..fc6acd0 100644 --- a/template.yml +++ b/template.yml @@ -26,7 +26,7 @@ Resources: InputBucket: Type: AWS::S3::Bucket Properties: - BucketName: !Sub ${AWS::StackName}-${AWS::AccountId}-input-bucket + BucketName: !Sub ${AWS::StackName}-${AWS::AccountId}-inputbucket NotificationTopic: Type: AWS::SNS::Topic From c73072b1f091fdcc5b15aa7bd4b305d11994ca08 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Thu, 2 Jul 2020 21:36:26 +0100 Subject: [PATCH 105/115] Update topic policy due to S3 change --- template.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/template.yml b/template.yml index fc6acd0..2d23789 100644 --- a/template.yml +++ b/template.yml @@ -46,7 +46,7 @@ Resources: StringEquals: aws:SourceAccount: !Sub ${AWS::AccountId} ArnEquals: - aws:SourceArn: !Sub "arn:aws:s3:::${AWS::StackName}-${AWS::AccountId}-input-bucket" + aws:SourceArn: !Sub "arn:aws:s3:::${AWS::StackName}-${AWS::AccountId}-inputbucket" Topics: - !Ref NotificationTopic From 4e14faf876d9ce8d7d378e5e9c9d396178e58f11 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 3 Jul 2020 09:47:47 +0100 Subject: [PATCH 106/115] Reverted script to previous version. --- tests.sh | 21 +++++---------------- 1 file changed, 5 insertions(+), 16 deletions(-) diff --git a/tests.sh b/tests.sh index 30bac90..05557a4 100644 --- a/tests.sh +++ b/tests.sh @@ -37,8 +37,6 @@ function clean { for f in "${TEST_FILES[@]}"; do - ## We know our output files will have a html extention so we need to substitute md for html when working with the output. - FILE_NAME=$(cut -d "/" -f2- <<< "$f") echo "Removing from output : ${FILE_NAME/md/html}" @@ -75,20 +73,9 @@ function clean { ## Get Stack Resources -BUCKET_IN=$(aws cloudformation describe-stack-resource \ ---stack-name "$STACK" --logical-resource-id 'InputBucket' \ ---query "StackResourceDetail.PhysicalResourceId" \ ---output text) || echo -e "Couldn't get stack details" ; exit 1 - -BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name "$STACK" \ ---logical-resource-id 'ConversionTargetBucket' \ ---query "StackResourceDetail.PhysicalResourceId" \ ---output text) || echo -e "Couldn't get stack details" ; exit 1 - -DYNAMO_TABLE=$(aws cloudformation describe-stack-resource \ ---stack-name "$STACK" --logical-resource-id 'SentimentTable' \ ---query "StackResourceDetail.PhysicalResourceId" \ ---output text) || echo -e "Couldn't get stack details" ; exit 1 +BUCKET_IN=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'InputBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) +BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'ConversionTargetBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) +DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'SentimentTable' --query "StackResourceDetail.PhysicalResourceId" --output text) echo "Input Bucket: $BUCKET_IN" echo "Ouput Bucket: $BUCKET_OUT" @@ -144,6 +131,8 @@ done for f in "${TEST_FILES[@]}"; do + # We know our output files will have a html extention so we need to substitute md for html when working with the output. + FILE_NAME=$(cut -d "/" -f2- <<< "$f") echo "Checking for Output : ${FILE_NAME/md/html}" From 34b678f5b44f2a60ed8dab62a8f232e0a81b30d9 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 3 Jul 2020 10:28:12 +0100 Subject: [PATCH 107/115] Removed error handling as after testing the script exits correctly on these errors with a meaningful message back from the CLI. --- tests.sh | 29 +++++++++++++++++++++-------- 1 file changed, 21 insertions(+), 8 deletions(-) diff --git a/tests.sh b/tests.sh index 05557a4..edc55d8 100644 --- a/tests.sh +++ b/tests.sh @@ -73,13 +73,28 @@ function clean { ## Get Stack Resources -BUCKET_IN=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'InputBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) -BUCKET_OUT=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'ConversionTargetBucket' --query "StackResourceDetail.PhysicalResourceId" --output text) -DYNAMO_TABLE=$(aws cloudformation describe-stack-resource --stack-name "$STACK" --logical-resource-id 'SentimentTable' --query "StackResourceDetail.PhysicalResourceId" --output text) +BUCKET_IN=$(aws cloudformation describe-stack-resource \ +--stack-name "$STACK" --logical-resource-id 'InputBucket' \ +--query "StackResourceDetail.PhysicalResourceId" \ +--output text) -echo "Input Bucket: $BUCKET_IN" -echo "Ouput Bucket: $BUCKET_OUT" -echo "Dynamo Table: $DYNAMO_TABLE" + +BUCKET_OUT=$(aws cloudformation describe-stack-resource \ +--stack-name "$STACK" \ +--logical-resource-id 'ConversionTargetBucket' \ +--query "StackResourceDetail.PhysicalResourceId" \ +--output text) + + +DYNAMO_TABLE=$(aws cloudformation describe-stack-resource \ +--stack-name "$STACK" --logical-resource-id 'SentimentTable' \ +--query "StackResourceDetail.PhysicalResourceId" \ +--output text) + + +echo "Found Input Bucket: $BUCKET_IN" +echo "Found Ouput Bucket: $BUCKET_OUT" +echo "Found DynamoDB Table: $DYNAMO_TABLE" ## Get Samples @@ -131,8 +146,6 @@ done for f in "${TEST_FILES[@]}"; do - # We know our output files will have a html extention so we need to substitute md for html when working with the output. - FILE_NAME=$(cut -d "/" -f2- <<< "$f") echo "Checking for Output : ${FILE_NAME/md/html}" From dd89103af15fc385b5fa4109b6c7d10565e97996 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Fri, 3 Jul 2020 11:07:03 +0100 Subject: [PATCH 108/115] Added note around using the test script instead of manually testing and an "Extra credit" test example that demonstrates X-ray integration. --- README.md | 34 +++++++++++++++++- ...farch-fileprocessing-x-ray-error-trace.png | Bin 0 -> 150904 bytes 2 files changed, 33 insertions(+), 1 deletion(-) create mode 100644 img/lambda-refarch-fileprocessing-x-ray-error-trace.png diff --git a/README.md b/README.md index dc27dc6..036c12a 100644 --- a/README.md +++ b/README.md @@ -100,7 +100,13 @@ You will receive an email asking you to confirm subscription to the `lambda-file ## Testing the Example -After you have created the stack using the CloudFormation template, you can manually test the system by uploading a Markdown file to the InputBucket that was created in the stack. You can use the any of the sample-xx.md files in the repository /tests directory as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. +After you have created the stack using the CloudFormation template, you can manually test the system by uploading a Markdown file to the InputBucket that was created in the stack. +Alternatively you test it by utilising the pipeline tests.sh script, however the test script removes the resources it creates, so if you wish to explore the solution and see the output files +and DynamoDB tables manually uploading is the better option. + +### Manually testing: + + You can use the any of the sample-xx.md files in the repository /tests directory as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. @@ -126,6 +132,32 @@ aws dynamodb scan --table-name ${DYNAMO_TABLE} --query "Items[*]" You can also view the CloudWatch logs generated by the Lambda functions. + +### Using the test script + +The pipeline end to end test script can be manually executed, you will need to ensure you have adequate permissions to perform the test script actions. + +* Describing stack resources +* Uploading and deleting files from the S3 input bucket +* Deleting files from the S3 output bucket +* Reading and deleting entries from the DynamoDB table + +```bash +./tests.sh lambda-file-refarch +``` + +### Extra credit testing + +Try uploading (or adding to ./tests if you are using the script) an oversized (>100MB) or invalid file type to the input bucket. +You can check in X-ray to explore how you can trace these kind of errors within the solution. + +```bash + fallocate -l 110M ./tests/sample-oversize.md +``` + +![X-Ray Error Tracing - Real-time File Processing](img/lambda-refarch-fileprocessing-x-ray-error-trace.png) + + ## Cleaning Up the Example Resources To remove all resources created by this example, run the following command: diff --git a/img/lambda-refarch-fileprocessing-x-ray-error-trace.png b/img/lambda-refarch-fileprocessing-x-ray-error-trace.png new file mode 100644 index 0000000000000000000000000000000000000000..f552c1fd12c6674ac22d3faf3a4e664557f09cd7 GIT binary patch literal 150904 zcmbrlWmr^U*9JNWNJ)qS(jh1flF}_Dg22$BDBay5ozgAcIdsEFNq4tMcjpjiqwv1( z`SJZY*V)$v%nY;lQ|nplzVEf30J#t1=%@s!AP@*$QbJT71bQq20>PgkKL$P-Mu=+% z{=iwwiwlE_`-wJyHwgMdGD09wX(-y&XGGvViiL!#H3)>!diMj@VV?UH_>kO2OvOgT zO82vkp}85EqM@lSh=rMjnVXrDo0*mD4Kp`87dI=XfL!=A2z2WpDJrDsptU`R;-Yv` zdwamd)_v`Tclqd)ebv7Iz22)xpJkVUBVLC7Bp!Q7 zpp*YD%lvj9G(2Qr(El#MStHAXKVmId4wT5L z4_c!o@;mp){Ans7nRaqDg$fPQ#H%~#eXgsg<|r9q_CqDr-HskV`?((@ttx&5RM2{u 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z#q_6fF18(A^RFI=AOSm^B++5-8^8_Fa94JJtd=>mHPHfM=yQmf*Yw$IP5e`^D*i$L zaJJ|2qFGcp_y@^FWuMmGq+Ff7eBSDU~hmIEBVsduI1M%Fm+kHsp= zVd3fyjSdPXZ(O{8n)bz4c;5Vg*H7(47M=1o6cAoazodR+?uv|1icY&1 zsKlwES`6wyrCg1qKZ=f?9q5t44VQGAh{HyMJaT}_=$a-Dh*I8Hv%|Z->Eg%t1UYmh zHYXK4RteUz#;`udX;`ScVN78RiuTbJMOl8f@AH8z*}*vmdx=gJM>^GF8!abCAQ*w( zqXCT%dSd`b9!CClEeqajXrfXZiktXgJTrxEH;yE_^f&fO0i(1I+n^(>mTr$ca Date: Fri, 3 Jul 2020 11:12:49 +0100 Subject: [PATCH 109/115] Added some more notes. --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 036c12a..3c50ca4 100644 --- a/README.md +++ b/README.md @@ -146,6 +146,11 @@ The pipeline end to end test script can be manually executed, you will need to e ./tests.sh lambda-file-refarch ``` +Whilst the script is executing you will see all the stages output to the command line. The samples are uploaded, +the script will then wait for files to appear in the output bucket before checking they have all been processed and the +matching html file exists in the output bucket. It will also check that the sentiment for each of the files has been +recorded in the DynamoDB table. Once complete the script will remove all the files created and the entries from the DynamoDB table. + ### Extra credit testing Try uploading (or adding to ./tests if you are using the script) an oversized (>100MB) or invalid file type to the input bucket. From 054425b13927a8d3547e39a9f7f69ebb007820e0 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 6 Jul 2020 14:15:42 +0100 Subject: [PATCH 110/115] Changed file extension conversion code to work with MacOS and corrected spelling. --- tests.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests.sh b/tests.sh index edc55d8..3fd8c8a 100644 --- a/tests.sh +++ b/tests.sh @@ -121,13 +121,13 @@ done END=$((SECONDS+30)) -echo "Wating for execution" +echo "Waiting for execution" while [ $SECONDS -lt $END ] do - FILE_NAME=$(cut -d "/" -f2- <<< ${TEST_FILES[-1]}) + FILE_NAME=$(cut -d "/" -f2- <<< ${TEST_FILES[*]: -1}}) EXISTS=$(aws s3api head-object --bucket $BUCKET_OUT --key ${FILE_NAME/md/html}) || NOT_EXIST=true From 4b8c00360f8b6f01dedf59a8af2f05a3e0419801 Mon Sep 17 00:00:00 2001 From: jrrudge Date: Mon, 6 Jul 2020 14:29:04 +0100 Subject: [PATCH 111/115] Rogue curly brace removed. --- tests.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests.sh b/tests.sh index 3fd8c8a..367502b 100644 --- a/tests.sh +++ b/tests.sh @@ -127,7 +127,7 @@ while [ $SECONDS -lt $END ] do - FILE_NAME=$(cut -d "/" -f2- <<< ${TEST_FILES[*]: -1}}) + FILE_NAME=$(cut -d "/" -f2- <<< ${TEST_FILES[*]: -1}) EXISTS=$(aws s3api head-object --bucket $BUCKET_OUT --key ${FILE_NAME/md/html}) || NOT_EXIST=true From 411c7b780670d924ef65b343131664c886d0d147 Mon Sep 17 00:00:00 2001 From: Brian Mcnamara Date: Sun, 2 Aug 2020 22:22:21 -0400 Subject: [PATCH 112/115] Feedback update --- .gitignore | 4 +- README.md | 95 +++++++++--------- ...ambda-refarch-fileprocessing-dashboard.png | Bin 0 -> 146502 bytes src/conversion/conversion.py | 84 +++++++--------- src/conversion/requirements.txt | 5 +- src/sentiment/requirements.txt | 5 +- src/sentiment/sentiment.py | 70 ++++++------- template.yml | 13 ++- 8 files changed, 128 insertions(+), 148 deletions(-) create mode 100644 img/lambda-refarch-fileprocessing-dashboard.png diff --git a/.gitignore b/.gitignore index bbd3428..c4597ae 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,5 @@ -packaged-template.yml +samconfig.toml .aws-sam .idea .history -__pycache__ \ No newline at end of file +__pycache__ diff --git a/README.md b/README.md index 3c50ca4..fe5779e 100644 --- a/README.md +++ b/README.md @@ -16,28 +16,23 @@ In this architecture, individual files are processed as they arrive. To achive t ### Conversion Workflow -We target a SQS queue for this workflow. Sending the JSON event to SQS first rather than directly to Lambda allows for more control of Lambda invocations and better error handling. +Our function will take Markdown files stored in our **InputBucket**, convert them to HTML, and store them in our **OutputBucket**. The **ConversionQueue** SQS queue captures the S3 Event JSON payload, allowing for more control of our **ConversionFunction** and better error handling. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. -The Lambda service polls our queue on our behalf. When messages are available they will be delivered to our function. Lambda can automatically scale with the number of messages on the queue. Refer to [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html) for more details. - -If our Conversion Lambda function cannot remove the messages from the Conversion queue, they are sent to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Conversion DLQ. - -Our function business logic uses this information to retrieve the file from S3 using the [Python AWS SDK (boto3)](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html?id=docs_gateway) and store it in a temporary location within the function execution environment. The path of the file is then passed to a python function which reads the file contents and converts it to HTML using the Python [Markdown Library](https://pypi.org/project/Markdown/). We then generate the filename for the new HTML file and write it to our temporary location. Finally we upload the new HTML file to an output S3 bucket. If our function execution results in an error, we will +If our **ConversionFunction** cannot remove the messages from the **ConversionQueue**, they are sent to **ConversionDlq**, a dead-letter queue (DLQ), for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the **ConversionDlq**. ### Sentiment Analysis Workflow -We are using AWS' AI/ML service [Amazon Comprehend](https://aws.amazon.com/comprehend/) which is a machine learning powered service that makes it easy to find insights and relationships in text. We use the Sentiment Analysis API to understand whether interview responses are positive or negative. +Our function will take Markdown files stored in our **InputBucket**, detect the overall sentiment for each file, and store the result in our **SentimentTable**. -The Sentiment workflow uses the same SQS-to-Lambda Function pattern as the Coversion workflow. Our function downloads the markdown file, extracts the contents, and sends it to the Comprehend Sentiment Analysis API. This returns a Sentiment and a confidence score which describes the level of confidence that Amazon Comprehend has in the accuracy of its detection of sentiments. +We are using [Amazon Comprehend](https://aws.amazon.com/comprehend/) to detect overall interview sentiment. Amazon Comprehend is a machine learning powered service that makes it easy to find insights and relationships in text. We use the Sentiment Analysis API to understand whether interview responses are positive or negative. -Once we have our sentiment we persist the result to our [DynamoDB](https://aws.amazon.com/dynamodb/) table. - -If our Sentiment Lambda function cannot remove the messages from the Sentiment SQS queue, they are sent to a dead-letter queue (DLQ) for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the Sentiment DLQ. +The Sentiment workflow uses the same SQS-to-Lambda Function pattern as the Coversion workflow. +If our **SentimentFunction** cannot remove the messages from the **SentimentQueue**, they are sent to **SentimentDlq**, a dead-letter queue (DLQ), for inspection. A CloudWatch Alarm is configured to send notification to an email address when there are any messages in the **SentimentDlq**. ## Building and Deploying the Application with the AWS Serverless Application Model (AWS SAM) -This application is deployed using the AWS Serverless Application Model (AWS SAM). AWS SAM is an open-source framework that enables you to build serverless applications on AWS. It provides you with a template specification to define your serverless application, and a command line interface (CLI) tool. +This application is deployed using the [AWS Serverless Application Model (AWS SAM)](https://aws.amazon.com/serverless/sam/). AWS SAM is an open-source framework that enables you to build serverless applications on AWS. It provides you with a template specification to define your serverless application, and a command line interface (CLI) tool. ### Pre-requisites @@ -47,66 +42,56 @@ This application is deployed using the AWS Serverless Application Model (AWS SAM * [Docker](https://docs.docker.com/install/) -### Build +### Clone the Repository -The AWS SAM CLI comes with abstractions for a number of Lambda runtimes to build your dependencies, and copies the source code into staging folders so that everything is ready to be packaged and deployed. The *sam build* command builds any dependencies that your application has, and copies your application source code to folders under *.aws-sam/build* to be zipped and uploaded to Lambda. +#### Clone with SSH ```bash -sam build --use-container +git clone git@github.com:mcnamarabrian/lambda-refarch-fileprocessing.git ``` -**Note** - -Be sure to use v0.41.0 of the AWS SAM CLI or newer. Failure to use the proper version of the AWS SAM CLI will result in a `InvalidDocumentException` exception. The `EventInvokeConfig` property is not recognized in earlier versions of the AWS SAM CLI. To confirm your version of AWS SAM, run the command `sam --version`. - -### Package - -Next, run *sam package*. This command takes your Lambda handler source code and any third-party dependencies, zips everything, and uploads the zip file to your Amazon S3 bucket. That bucket and file location are then noted in the packaged-template.yaml file. You use the generated packaged-template.yaml file to deploy the application in the next step. +#### Clone with HTTPS ```bash -sam package \ - --output-template-file packaged-template.yml \ - --s3-bucket bucketname +git clone https://github.com/mcnamarabrian/lambda-refarch-fileprocessing.git ``` -**Note** +### Build -For *bucketname* in this command, you need an Amazon S3 bucket that the sam package command can use to store the deployment package. The deployment package is used when you deploy your application in a later step. If you need to create a bucket for this purpose, run the following command to create an Amazon S3 bucket: +The AWS SAM CLI comes with abstractions for a number of Lambda runtimes to build your dependencies, and copies the source code into staging folders so that everything is ready to be packaged and deployed. The *sam build* command builds any dependencies that your application has, and copies your application source code to folders under *.aws-sam/build* to be zipped and uploaded to Lambda. ```bash -aws s3 mb s3://bucketname --region region # Example regions: us-east-1, ap-east-1, eu-central-1, sa-east-1 +sam build --use-container ``` -### Deploy +**Note** -This command deploys your application to the AWS Cloud. It's important that this command explicitly includes both of the following: +Be sure to use v0.41.0 of the AWS SAM CLI or newer. Failure to use the proper version of the AWS SAM CLI will result in a `InvalidDocumentException` exception. The `EventInvokeConfig` property is not recognized in earlier versions of the AWS SAM CLI. To confirm your version of AWS SAM, run the command `sam --version`. - * The AWS Region to deploy to. This Region must match the Region of the Amazon S3 source bucket. +### Deploy - * The CAPABILITY_IAM parameter, because creating new Lambda functions involves creating new IAM roles. +For the first deployment, please run the following command and save the generated configuration file *samconfig.toml*. Please use **lambda-file-refarch** for the stack name. ```bash -sam deploy \ - --template-file packaged-template.yml \ - --stack-name lambda-file-refarch \ - --region region \ - --tags Project=lambda-refarch-fileprocessing \ - --parameter-overrides AlarmRecipientEmailAddress= \ - --capabilities CAPABILITY_IAM +sam deploy --guided ``` -You will receive an email asking you to confirm subscription to the `lambda-file-refarch-AlarmTopic` SNS topic that will receive alerts should either the `ConversionDlq` SQS queue or `SentimentDlq` SQS queue receive messages. +You will be prompted to enter data for *ConversionLogLevel* and *SentimentLogLevel*. The default value for each is *INFO* but you can also enter *DEBUG*. You will also be prompted for *AlarmRecipientEmailAddress*. +Subsequent deployments can use the simplified `sam deploy`. The command will use the generated configuration file *samconfig.toml*. + +You will receive an email asking you to confirm subscription to the `lambda-file-refarch-AlarmTopic` SNS topic that will receive alerts should either the `ConversionDlq` SQS queue or `SentimentDlq` SQS queue receive messages. ## Testing the Example After you have created the stack using the CloudFormation template, you can manually test the system by uploading a Markdown file to the InputBucket that was created in the stack. + Alternatively you test it by utilising the pipeline tests.sh script, however the test script removes the resources it creates, so if you wish to explore the solution and see the output files and DynamoDB tables manually uploading is the better option. -### Manually testing: +### Manually testing - You can use the any of the sample-xx.md files in the repository /tests directory as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. + You can use the any of the sample-xx.md files in the repository /**tests** directory as example files. After the files have been uploaded, you can see the resulting HTML file in the output bucket of your stack. You can also view the CloudWatch logs for each of the functions in order to see the details of their execution. You can use the following commands to copy a sample file from the provided S3 bucket into the input bucket of your stack. @@ -143,26 +128,37 @@ The pipeline end to end test script can be manually executed, you will need to e * Reading and deleting entries from the DynamoDB table ```bash -./tests.sh lambda-file-refarch +bash ./tests.sh lambda-file-refarch ``` -Whilst the script is executing you will see all the stages output to the command line. The samples are uploaded, -the script will then wait for files to appear in the output bucket before checking they have all been processed and the -matching html file exists in the output bucket. It will also check that the sentiment for each of the files has been -recorded in the DynamoDB table. Once complete the script will remove all the files created and the entries from the DynamoDB table. +While the script is executing you will see all the stages output to the command line. The samples are uploaded to the **InputBucket**, the script will then wait for files to appear in the **OutputBucket** before checking they have all been processed and the matching html file exists in the **OutputBucket**. It will also check that the sentiment for each of the files has been recorded in the **SentimentTable**. Once complete the script will remove all the files created and the entries from the **SentimentTable**. ### Extra credit testing Try uploading (or adding to ./tests if you are using the script) an oversized (>100MB) or invalid file type to the input bucket. You can check in X-ray to explore how you can trace these kind of errors within the solution. +* Linux command + ```bash - fallocate -l 110M ./tests/sample-oversize.md +fallocate -l 110M ./tests/sample-oversize.md +``` + +* Mac OS X command + +```bash +mkfile 110m ./tests/sample-oversize.md ``` ![X-Ray Error Tracing - Real-time File Processing](img/lambda-refarch-fileprocessing-x-ray-error-trace.png) +## Viewing the CloudWatch dashboard + +A dashboard is created as a part of the stack creation process. Metrics are published for the conversion and sentiment analysis processes. In addition, the alarms and alarm states are published. + +![CloudWatch Dashboard - Real-time File Processing](img/lambda-refarch-fileprocessing-dashboard.png) + ## Cleaning Up the Example Resources To remove all resources created by this example, run the following command: @@ -204,10 +200,11 @@ done ## SAM Template Resources ### Resources + [The provided template](https://s3.amazonaws.com/awslambda-reference-architectures/file-processing/packaged-template.yml) creates the following resources: -- **InputBucket** - An S3 bucket that holds the raw Markdown files. Uploading a file to this bucket will trigger processing functions. +- **InputBucket** - A S3 bucket that holds the raw Markdown files. 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fe5779e..39f3b14 100644 --- a/README.md +++ b/README.md @@ -47,13 +47,13 @@ This application is deployed using the [AWS Serverless Application Model (AWS SA #### Clone with SSH ```bash -git clone git@github.com:mcnamarabrian/lambda-refarch-fileprocessing.git +git clone git@github.com:aws-samples/lambda-refarch-fileprocessing.git ``` #### Clone with HTTPS ```bash -git clone https://github.com/mcnamarabrian/lambda-refarch-fileprocessing.git +git clone https://github.com/aws-samples/lambda-refarch-fileprocessing.git ``` ### Build