[GitHub] [airflow] ianstanton commented on a change in pull request #13209: Add support for worker persistence with KEDA v2.0.0 in helm chart

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ianstanton commented on a change in pull request #13209:
URL: https://github.com/apache/airflow/pull/13209#discussion_r586936226



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File path: chart/README.md
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@@ -323,22 +323,30 @@ helm install --name my-release \
 
 KEDA stands for Kubernetes Event Driven Autoscaling. [KEDA](https://github.com/kedacore/keda) is a custom controller that allows users to create custom bindings
 to the Kubernetes [Horizontal Pod Autoscaler](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/).
-We've built a scaler that allows users to create scalers based on postgreSQL queries and shared it with the community. This enables us to scale the number of airflow workers deployed on Kubernetes by this chart depending on the number of task that are `queued` or `running`.
+
+The autoscaler will adjust the number of active celery workers based on the number of tasks in `queued` or `running` state.
+
+KEDA may be used with the `CeleryExecutor` and `CeleryKubernetesExecutor` executors.
+
+### Install KEDA
+
+First install into the cluster under namespace `keda`.
 
 ```bash
 helm repo add kedacore https://kedacore.github.io/charts
 
 helm repo update
 
-helm install \
-    --set image.keda=docker.io/kedacore/keda:1.2.0 \
-    --set image.metricsAdapter=docker.io/kedacore/keda-metrics-adapter:1.2.0 \
-    --namespace keda --name keda kedacore/keda
+kubectl create namespace keda
+
+helm install keda kedacore/keda \
+    --namespace keda \
+    --version "v2.0.0"
 ```
 
-Once KEDA is installed (which should be pretty quick since there is only one pod). You can try out KEDA autoscaling
-on this chart by setting `workers.keda.enabled=true` your helm command or in the `values.yaml`.
-(Note: KEDA does not support StatefulSets so you need to set `worker.persistence.enabled` to `false`)
+### Enable KEDA for airflow
+
+Enable for the airflow instance by setting `workers.keda.enabled=true` your helm command or in the `values.yaml`.

Review comment:
       ```suggestion
   Enable for the airflow instance by setting `workers.keda.enabled=true` in your helm command or in the `values.yaml`.
   ```




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