Azure Kubernetes Service (AKS) cluster and Azure Functions with KEDA

This example lives in the pulumi/examples repository. Check out just this directory to use it:

$ git clone --filter=blob:none --sparse https://github.com/pulumi/examples pulumi-examples
$ git -C pulumi-examples sparse-checkout set classic-azure-ts-aks-keda
$ cd pulumi-examples/classic-azure-ts-aks-keda

This example demonstrates creating an Azure Kubernetes Service (AKS) Cluster, and deploying an Azure Function App with Kubernetes-based Event Driven Autoscaling (KEDA) into it, all in one Pulumi program. Please see https://docs.microsoft.com/en-us/azure/aks/ for more information about AKS and https://docs.microsoft.com/en-us/azure/azure-functions/functions-kubernetes-keda for more information about KEDA.

Prerequisites#

1. Install Pulumi
2. Configure Azure credentials
3. Install Node.js

This example deploys a Helm Chart from the Kedacore Helm chart repository. Add and update the repository before deploying.

If you are using Helm v2:

helm init --client-only
helm repo add kedacore https://kedacore.github.io/charts
helm repo update

If you are using Helm v3:

helm repo add kedacore https://kedacore.github.io/charts
helm repo update

Deploying the example#

1. Create a new stack, which is an isolated deployment target for this example:

   pulumi stack init

2. Set the Azure region to deploy to:

   pulumi config set azure:location <value>
   pulumi config set azure:subscriptionId <YOUR_SUBSCRIPTION_ID>

3. Install dependencies:

   npm install

4. Deploy everything with the pulumi up command. This provisions all the Azure resources necessary, including an Active Directory service principal, AKS cluster, and then deploys the Apache Helm Chart, and an Azure Function managed by KEDA, all in a single gesture:

   Note: Due to an issue in Azure Terraform Provider, the creation of an Azure Service Principal, which is needed to create the Kubernetes cluster (see cluster.ts), is delayed and may not be available when the cluster is created. If you get a “Service Principal not found” error, as a work around, you should be able to run pulumi up again, at which time the Service Principal replication should have been completed. See this issue and this doc for further details.

   pulumi up

5. After a couple minutes, your cluster and Azure Function app will be ready. Four output variables will be printed, reflecting your cluster name (clusterName), Kubernetes config (kubeConfig), Storage Account name (storageAccountName), and storage queue name (queueName).

   Using these output variables, you may configure your kubectl client using the kubeConfig configuration:

   pulumi stack output kubeconfig --show-secrets > kubeconfig.yaml
   KUBECONFIG=./kubeconfig.yaml kubectl get deployment

   NAME           READY     UP-TO-DATE     AVAILABLE    AGE
   keda-edge      1/1       1              1            9m
   queue-handler  0/0       0              0            2m

   Now, go ahead an enqueue a new message to the storage queue. You may use a tool like Microsoft Azure Storage Explorer to navigate to the queue and add a new message.

   Wait for a minute and then query the deployments again:

   KUBECONFIG=./kubeconfig.yaml kubectl get deployment

   NAME           READY     UP-TO-DATE     AVAILABLE    AGE
   keda-edge      1/1       1              1            14m
   queue-handler  1/1       1              1            7m

   Note that the queue-handler deployment got 1 instance ready. Looking at the pods:

   KUBECONFIG=./kubeconfig.yaml kubectl get pod

   NAME                          READY   STATUS    RESTARTS   AGE
   keda-edge-97664558c-q2mkd     1/1     Running   0          15m
   queue-handler-c496dcfc-mb6tx  1/1     Running   0          2m3s

   There’s now a pod processing queue messages. The message should be gone from the storage queue at this point. Query the logs of the pod:

   KUBECONFIG=./kubeconfig.yaml kubectl logs queue-handler-c496dcfc-mb6tx

   ...
   C# Queue trigger function processed: Test Message
   Executed 'queue' (Succeeded, Id=ecd9433a-c6b7-468e-b6c6-6e7909bafce7)
   ...

6. At this point, you have a running cluster. Feel free to modify your program, and run pulumi up to redeploy changes. The Pulumi CLI automatically detects what has changed and makes the minimal edits necessary to accomplish these changes. This could be altering the existing chart, adding new Azure or Kubernetes resources, or anything, really.

Cleaning up#

Once you are done, destroy all of the resources and the stack:

pulumi destroy
pulumi stack rm