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adchia merged 2 commits into from
Sep 2, 2022
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chore: Add more references to kubernetes for SEO for k8s #3170

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chore: Add more references to kubernetes for SEO for k8s
adchia Sep 2, 2022
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chore: Add more references to kubernetes for SEO for k8s
adchia Sep 2, 2022
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2 changes: 1 addition & 1 deletion docs/SUMMARY.md
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Expand Up @@ -49,7 +49,7 @@
* [Read features from the online store](how-to-guides/feast-snowflake-gcp-aws/read-features-from-the-online-store.md)
* [Scaling Feast](how-to-guides/scaling-feast.md)
* [Structuring Feature Repos](how-to-guides/structuring-repos.md)
* [Running Feast in production](how-to-guides/running-feast-in-production.md)
* [Running Feast in production (e.g. on Kubernetes)](how-to-guides/running-feast-in-production.md)
* [Upgrading for Feast 0.20+](how-to-guides/automated-feast-upgrade.md)
* [Customizing Feast](how-to-guides/customizing-feast/README.md)
* [Adding a custom batch materialization engine](how-to-guides/customizing-feast/creating-a-custom-materialization-engine.md)
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6 changes: 3 additions & 3 deletions docs/how-to-guides/running-feast-in-production.md
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# Running Feast in production
# Running Feast in production (e.g. on Kubernetes)

## Overview

After learning about Feast concepts and playing with Feast locally, you're now ready to use Feast in production. This guide aims to help with the transition from a sandbox project to production-grade deployment in the cloud or on-premise.
After learning about Feast concepts and playing with Feast locally, you're now ready to use Feast in production. This guide aims to help with the transition from a sandbox project to production-grade deployment in the cloud or on-premise (e.g. on Kubernetes).

A typical production architecture looks like:

Expand Down Expand Up @@ -58,7 +58,7 @@ This approach may not scale to large amounts of data, which users of Feast may b
In this case, we recommend using one of the more [scalable materialization engines](./scaling-feast.md#scaling-materialization), such as the [Bytewax Materialization Engine](../reference/batch-materialization/bytewax.md), or the [Snowflake Materialization Engine](../reference/batch-materialization/snowflake.md).
Users may also need to [write a custom materialization engine](../how-to-guides/customizing-feast/creating-a-custom-materialization-engine.md) to work on their existing infrastructure.

The Bytewax materialization engine can run materialization on existing kubernetes cluster. An example configuration of this in a `feature_store.yaml` is as follows:
The Bytewax materialization engine can run materialization on an existing Kubernetes cluster. An example configuration of this in a `feature_store.yaml` is as follows:

```yaml
batch_engine:
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2 changes: 1 addition & 1 deletion infra/charts/feast-feature-server/README.md
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Expand Up @@ -11,7 +11,7 @@ helm repo add feast-charts https://feast-helm-charts.storage.googleapis.com
helm repo update
```

Install Feast
Install Feast Feature Server on Kubernetes

A base64 encoded version of the `feature_store.yaml` file is needed. Helm install example:
```
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2 changes: 1 addition & 1 deletion infra/charts/feast-feature-server/README.md.gotmpl
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Expand Up @@ -11,7 +11,7 @@ helm repo add feast-charts https://feast-helm-charts.storage.googleapis.com
helm repo update
```

Install Feast
Install Feast Feature Server on Kubernetes

A base64 encoded version of the `feature_store.yaml` file is needed. Helm install example:
```
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