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Rename mssqlctl to azdata
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‎docs/big-data-cluster/big-data-cluster-consume-apps.md‎

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## Prerequisites
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- [SQL Server 2019 big data cluster](deployment-guidance.md)
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- [mssqlctl command-line utility](deploy-install-mssqlctl.md)
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- An app deployed using either [`mssqlctl`](big-data-cluster-create-apps.md) or the [App Deploy extension](app-deployment-extension.md)
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- [azdata command-line utility](deploy-install-mssqlctl.md)
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- An app deployed using either [`azdata`](big-data-cluster-create-apps.md) or the [App Deploy extension](app-deployment-extension.md)
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## Capabilities
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After you have deployed an application to your SQL Server 2019 big data cluster (preview), you can access and consume that application using a RESTful web service. This enables integration of that app from other applications or services (for example, a mobile app or website). The following table describes the application deployment commands that you can use with **mssqlctl** to get information about the RESTful web service for your app.
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After you have deployed an application to your SQL Server 2019 big data cluster (preview), you can access and consume that application using a RESTful web service. This enables integration of that app from other applications or services (for example, a mobile app or website). The following table describes the application deployment commands that you can use with **azdata** to get information about the RESTful web service for your app.
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|Command |Description |
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|:---|:---|
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|`mssqlctl app describe` | Describe application. |
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|`azdata app describe` | Describe application. |
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You can get help with the `--help` parameter as in the following example:
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```bash
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mssqlctl app describe --help
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azdata app describe --help
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```
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The following sections describe how to retrieve an endpoint for an application and how to work with the RESTful web service for application integration.
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## Retrieve the endpoint
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The **mssqlctl app describe** command provides detailed information about the app including the end point in your cluster. This is typically used by an app developer to build an app using the swagger client and using the webservice to interact with the app in a RESTful manner.
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The **azdata app describe** command provides detailed information about the app including the end point in your cluster. This is typically used by an app developer to build an app using the swagger client and using the webservice to interact with the app in a RESTful manner.
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Describe your app by running a command similar to the following:
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```bash
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mssqlctl app describe --name addpy --version v1
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azdata app describe --name addpy --version v1
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```
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```json
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## Generate a JWT access token
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In order to access the RESTful web service for the app you have deployed you first have to generate a JWT Access token. Open the following URL in your browser: `https://[IP]:[PORT]/api/docs/swagger.json` using the IP address and port you retrieved running the `describe` command above. You will have to log in with the same credentials you used for `mssqlctl login`.
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In order to access the RESTful web service for the app you have deployed you first have to generate a JWT Access token. Open the following URL in your browser: `https://[IP]:[PORT]/api/docs/swagger.json` using the IP address and port you retrieved running the `describe` command above. You will have to log in with the same credentials you used for `azdata login`.
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Paste the contents of the `swagger.json` into the [Swagger Editor](https://editor.swagger.io) to understand what methods are available:
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## Execute the app using the RESTful web service
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> [!NOTE]
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> If you want, you can open the URL for the `swagger` that was returned when you ran `mssqlctl app describe --name [appname] --version [version]` in your browser, which should be similar to `https://[IP]:[PORT]/api/app/[appname]/[version]/swagger.json`. You will have to log in with the same credentials you used for `mssqlctl login`. The contents of the `swagger.json` you can paste into [Swagger Editor](https://editor.swagger.io). You will see that the web service exposes the `run` method. Also note the Base URL displayed at the top.
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> If you want, you can open the URL for the `swagger` that was returned when you ran `azdata app describe --name [appname] --version [version]` in your browser, which should be similar to `https://[IP]:[PORT]/api/app/[appname]/[version]/swagger.json`. You will have to log in with the same credentials you used for `azdata login`. The contents of the `swagger.json` you can paste into [Swagger Editor](https://editor.swagger.io). You will see that the web service exposes the `run` method. Also note the Base URL displayed at the top.
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You can use your favorite tool to call the `run` method (`https://[IP]:30778/api/app/[appname]/[version]/run`), passing in the parameters in the body of your POST request as json. In this example we will use [Postman](https://www.getpostman.com/). Before making the call, you will need to set the `Authorization` to `Bearer Token` and paste in the token you retrieved earlier. This will set a header on your request. See the screenshot below.
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![Postman Run Body](media/big-data-cluster-consume-apps/postman_run_2.png)
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When you send the request, you will get the same output as you did when you ran the app through `mssqlctl app run`:
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When you send the request, you will get the same output as you did when you ran the app through `azdata app run`:
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![Postman Run Result](media/big-data-cluster-consume-apps/postman_result.png)
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‎docs/big-data-cluster/big-data-cluster-create-apps.md‎

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---
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title: Deploy applications using mssqlctl
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title: Deploy applications using azdata
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titleSuffix: SQL Server big data clusters
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description: Deploy a Python or R script as an application on SQL Server 2019 big data cluster (preview).
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author: jeroenterheerdt
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- Support hosting additional application types - SSIS and MLeap (new in CTP 2.3)
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- [VS Code Extension](app-deployment-extension.md) to manage application deployment
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Applications are deployed and managed using `mssqlctl` command-line utility. This article provides examples of how to deploy apps from the command line. To learn how to use this in Visual Studio Code refer to [VS Code Extension](app-deployment-extension.md).
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Applications are deployed and managed using `azdata` command-line utility. This article provides examples of how to deploy apps from the command line. To learn how to use this in Visual Studio Code refer to [VS Code Extension](app-deployment-extension.md).
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The following types of apps are supported:
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- R and Python apps (functions, models and apps)
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## Prerequisites
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- [SQL Server 2019 big data cluster](deployment-guidance.md)
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- [mssqlctl command-line utility](deploy-install-mssqlctl.md)
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- [azdata command-line utility](deploy-install-mssqlctl.md)
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## Capabilities
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In SQL Server 2019 (preview) you can create, delete, describe, initialize, list run and update your application. The following table describes the application deployment commands that you can use with **mssqlctl**.
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In SQL Server 2019 (preview) you can create, delete, describe, initialize, list run and update your application. The following table describes the application deployment commands that you can use with **azdata**.
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|Command |Description |
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|`mssqlctl login` | Sign into a SQL Server big data cluster |
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|`mssqlctl app create` | Create application. |
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|`mssqlctl app delete` | Delete application. |
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|`mssqlctl app describe` | Describe application. |
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|`mssqlctl app init` | Kickstart new application skeleton. |
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|`mssqlctl app list` | List application(s). |
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|`mssqlctl app run` | Run application. |
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|`mssqlctl app update`| Update application. |
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|`azdata login` | Sign into a SQL Server big data cluster |
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|`azdata app create` | Create application. |
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|`azdata app delete` | Delete application. |
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|`azdata app describe` | Describe application. |
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|`azdata app init` | Kickstart new application skeleton. |
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|`azdata app list` | List application(s). |
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|`azdata app run` | Run application. |
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|`azdata app update`| Update application. |
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You can get help with the `--help` parameter as in the following example:
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```bash
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mssqlctl app create --help
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azdata app create --help
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```
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The following sections describe these commands in more detail.
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## Sign in
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Before you deploy or interact with applications, first sign in to your SQL Server big data cluster with the `mssqlctl login` command. Specify the external IP address of the `controller-svc-external` service (for example: `https://ip-address:30080`) along with the user name and password to the cluster.
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Before you deploy or interact with applications, first sign in to your SQL Server big data cluster with the `azdata login` command. Specify the external IP address of the `controller-svc-external` service (for example: `https://ip-address:30080`) along with the user name and password to the cluster.
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```bash
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mssqlctl login --controller-endpoint https://<ip-address-of-controller-svc-external>:30080 --controller-username <user-name>
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azdata login --controller-endpoint https://<ip-address-of-controller-svc-external>:30080 --controller-username <user-name>
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## AKS
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## Create an app
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To create an application, you use `mssqlctl` with the `app create` command. These files reside locally on the machine that you are creating the app from.
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To create an application, you use `azdata` with the `app create` command. These files reside locally on the machine that you are creating the app from.
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Use the following syntax to create a new app in big data cluster:
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```bash
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mssqlctl app create --spec <directory containing spec file>
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azdata app create --spec <directory containing spec file>
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```
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The following command shows an example of what this command might look like:
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```bash
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mssqlctl app create --spec ./addpy
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azdata app create --spec ./addpy
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```
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This assumes that you have your application stored in the `addpy` folder. This folder should also contain a specification file for the application, called `spec.yaml`. Please see [the Application Deployment page](concept-application-deployment.md) for more information on the `spec.yaml` file.
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This will create a folder called hello. You can `cd` into the directory and inspect the generated files in the folder. spec.yaml defines the app, such as name, version and source code. You can edit the spec to change name, version, input and outputs.
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## Next steps

‎docs/big-data-cluster/cluster-troubleshooting-commands.md‎

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| **appproxy-svc-external** | Support application deployment scenarios. |
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> [!TIP]
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> This is a way of viewing the services with **kubectl**, but it is also possible to use `mssqlctl bdc endpoint list` command to view these endpoints. For more information, see [Get big data cluster endpoints](deployment-guidance.md#endpoints).
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> This is a way of viewing the services with **kubectl**, but it is also possible to use `azdata bdc endpoint list` command to view these endpoints. For more information, see [Get big data cluster endpoints](deployment-guidance.md#endpoints).
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‎docs/big-data-cluster/concept-application-deployment.md‎

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## How to work with Application Deployment
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- [Command line interface `azdata`](big-data-cluster-create-apps.md)
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It is also possible for an application to be executed using a RESTful web service. For more information, see [Consume applications on big data clusters](big-data-cluster-consume-apps.md).
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- [Deploy applications using mssqlctl](big-data-cluster-create-apps.md)
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- [Deploy applications using azdata](big-data-cluster-create-apps.md)
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‎docs/big-data-cluster/concept-controller.md‎

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## Deploying the controller service
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The controller is deployed and hosted in the same Kubernetes namespace where the customer wants to build out a big data cluster. This service is installed by a Kubernetes administrator during cluster bootstrap, using the **mssqlctl** command-line utility. For more information, see [Get started with SQL Server big data clusters](deploy-get-started.md).
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The controller is deployed and hosted in the same Kubernetes namespace where the customer wants to build out a big data cluster. This service is installed by a Kubernetes administrator during cluster bootstrap, using the **azdata** command-line utility. For more information, see [Get started with SQL Server big data clusters](deploy-get-started.md).
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The buildout workflow will layout on top of Kubernetes a fully functional SQL Server big data cluster that includes all the components described in the [Overview](big-data-cluster-overview.md) article. The bootstrap workflow first creates the controller service, and once this is deployed, the controller service will coordinate the installation and configuration of rest of the services part of master, compute, data, and storage pools.
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## Managing the cluster through the controller service
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You can manage the cluster through the controller service using either **mssqlctl** commands. If you deploy additional Kubernetes objects like pods into the same namespace, they are not managed or monitored by the controller service. You can also use **kubectl** commands to manage the cluster at the Kubernetes level. For more information, see [Monitoring and troubleshoot SQL Server big data clusters](cluster-troubleshooting-commands.md).
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You can manage the cluster through the controller service using either **azdata** commands. If you deploy additional Kubernetes objects like pods into the same namespace, they are not managed or monitored by the controller service. You can also use **kubectl** commands to manage the cluster at the Kubernetes level. For more information, see [Monitoring and troubleshoot SQL Server big data clusters](cluster-troubleshooting-commands.md).
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The controller and the Kubernetes objects (stateful sets, pods, secrets, etc.) created for a big data cluster reside in a dedicated Kubernetes namespace. The controller service will be granted permission by the Kubernetes cluster administrator to manage all resources within that namespace. The RBAC policy for this scenario is configured automatically as part of initial cluster deployment using **mssqlctl**.
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The controller and the Kubernetes objects (stateful sets, pods, secrets, etc.) created for a big data cluster reside in a dedicated Kubernetes namespace. The controller service will be granted permission by the Kubernetes cluster administrator to manage all resources within that namespace. The RBAC policy for this scenario is configured automatically as part of initial cluster deployment using **azdata**.
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### mssqlctl
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### azdata
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**mssqlctl** is a command-line utility written in Python that enables cluster administrators to bootstrap and manage big data clusters via the REST APIs exposed by the controller service.
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**azdata** is a command-line utility written in Python that enables cluster administrators to bootstrap and manage big data clusters via the REST APIs exposed by the controller service.
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## Controller service security
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