Quickstart: Deploy an Azure Linux Container Host for an AKS cluster using Azure PowerShell

Get started with the Azure Linux Container Host by using Azure PowerShell to deploy an Azure Linux Container Host for an AKS cluster. After installing the prerequisites, you create a resource group, create an AKS cluster, connect to the cluster, and run a sample multi-container application in the cluster.

Prerequisites

Create a resource group

An Azure resource group is a logical group in which Azure resources are deployed and managed. When creating a resource group, you need to specify a location. This location is the storage location of your resource group metadata and where your resources run in Azure if you don't specify another region during resource creation.

The following example creates resource group named testAzureLinuxResourceGroup in the eastus region.

  • Create a resource group using the New-AzResourceGroup cmdlet.

    New-AzResourceGroup -Name testAzureLinuxResourceGroup -Location eastus
    

    The following example output resembles successful creation of the resource group:

    ResourceGroupName : testAzureLinuxResourceGroup
    Location          : eastus
    ProvisioningState : Succeeded
    Tags              :
    ResourceId        : /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/testAzureLinuxResourceGroup
    

    Note

    The above example uses eastus, but Azure Linux Container Host clusters are available in all regions.

Create an Azure Linux Container Host cluster

The following example creates a cluster named testAzureLinuxCluster with one node.

  • Create an AKS cluster using the New-AzAksCluster cmdlet with the -NodeOsSKU flag set to AzureLinux.

    New-AzAksCluster -ResourceGroupName testAzureLinuxResourceGroup -Name testAzureLinuxCluster -NodeOsSKU AzureLinux
    

    After a few minutes, the command completes and returns JSON-formatted information about the cluster.

Connect to the cluster

To manage a Kubernetes cluster, use the Kubernetes command-line client, kubectl. kubectl is already installed if you use Azure Cloud Shell.

  1. Install kubectl locally using the Install-AzAksCliTool cmdlet.

    Install-AzAksCliTool
    
  2. Configure kubectl to connect to your Kubernetes cluster using the Import-AzAksCredential cmdlet. This command downloads credentials and configures the Kubernetes CLI to use them.

    Import-AzAksCredential -ResourceGroupName testAzureLinuxResourceGroup -Name testAzureLinuxCluster
    
  3. Verify the connection to your cluster using the kubectl get command. This command returns a list of the cluster pods.

    kubectl get pods --all-namespaces
    

Deploy the application

To deploy the application, you use a manifest file to create all the objects required to run the AKS Store application. A Kubernetes manifest file defines a cluster's desired state, such as which container images to run. The manifest includes the following Kubernetes deployments and services:

Screenshot of Azure Store sample architecture.

  • Store front: Web application for customers to view products and place orders.
  • Product service: Shows product information.
  • Order service: Places orders.
  • Rabbit MQ: Message queue for an order queue.

Note

We don't recommend running stateful containers, such as Rabbit MQ, without persistent storage for production. These are used here for simplicity, but we recommend using managed services, such as Azure Cosmos DB or Azure Service Bus.

  1. Create a file named aks-store-quickstart.yaml and copy in the following manifest:

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: rabbitmq
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: rabbitmq
      template:
        metadata:
          labels:
            app: rabbitmq
        spec:
          nodeSelector:
            "kubernetes.io/os": linux
          containers:
          - name: rabbitmq
            image: mcr.microsoft.com/mirror/docker/library/rabbitmq:3.10-management-alpine
            ports:
            - containerPort: 5672
              name: rabbitmq-amqp
            - containerPort: 15672
              name: rabbitmq-http
            env:
            - name: RABBITMQ_DEFAULT_USER
              value: "username"
            - name: RABBITMQ_DEFAULT_PASS
              value: "password"
            resources:
              requests:
                cpu: 10m
                memory: 128Mi
              limits:
                cpu: 250m
                memory: 256Mi
            volumeMounts:
            - name: rabbitmq-enabled-plugins
              mountPath: /etc/rabbitmq/enabled_plugins
              subPath: enabled_plugins
          volumes:
          - name: rabbitmq-enabled-plugins
            configMap:
              name: rabbitmq-enabled-plugins
              items:
              - key: rabbitmq_enabled_plugins
                path: enabled_plugins
    ---
    apiVersion: v1
    data:
      rabbitmq_enabled_plugins: |
        [rabbitmq_management,rabbitmq_prometheus,rabbitmq_amqp1_0].
    kind: ConfigMap
    metadata:
      name: rabbitmq-enabled-plugins
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: rabbitmq
    spec:
      selector:
        app: rabbitmq
      ports:
        - name: rabbitmq-amqp
          port: 5672
          targetPort: 5672
        - name: rabbitmq-http
          port: 15672
          targetPort: 15672
      type: ClusterIP
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: order-service
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: order-service
      template:
        metadata:
          labels:
            app: order-service
        spec:
          nodeSelector:
            "kubernetes.io/os": linux
          containers:
          - name: order-service
            image: ghcr.io/azure-samples/aks-store-demo/order-service:latest
            ports:
            - containerPort: 3000
            env:
            - name: ORDER_QUEUE_HOSTNAME
              value: "rabbitmq"
            - name: ORDER_QUEUE_PORT
              value: "5672"
            - name: ORDER_QUEUE_USERNAME
              value: "username"
            - name: ORDER_QUEUE_PASSWORD
              value: "password"
            - name: ORDER_QUEUE_NAME
              value: "orders"
            - name: FASTIFY_ADDRESS
              value: "0.0.0.0"
            resources:
              requests:
                cpu: 1m
                memory: 50Mi
              limits:
                cpu: 75m
                memory: 128Mi
          initContainers:
          - name: wait-for-rabbitmq
            image: busybox
            command: ['sh', '-c', 'until nc -zv rabbitmq 5672; do echo waiting for rabbitmq; sleep 2; done;']
            resources:
              requests:
                cpu: 1m
                memory: 50Mi
              limits:
                cpu: 75m
                memory: 128Mi
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: order-service
    spec:
      type: ClusterIP
      ports:
      - name: http
        port: 3000
        targetPort: 3000
      selector:
        app: order-service
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: product-service
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: product-service
      template:
        metadata:
          labels:
            app: product-service
        spec:
          nodeSelector:
            "kubernetes.io/os": linux
          containers:
          - name: product-service
            image: ghcr.io/azure-samples/aks-store-demo/product-service:latest
            ports:
            - containerPort: 3002
            resources:
              requests:
                cpu: 1m
                memory: 1Mi
              limits:
                cpu: 1m
                memory: 7Mi
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: product-service
    spec:
      type: ClusterIP
      ports:
      - name: http
        port: 3002
        targetPort: 3002
      selector:
        app: product-service
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: store-front
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: store-front
      template:
        metadata:
          labels:
            app: store-front
        spec:
          nodeSelector:
            "kubernetes.io/os": linux
          containers:
          - name: store-front
            image: ghcr.io/azure-samples/aks-store-demo/store-front:latest
            ports:
            - containerPort: 8080
              name: store-front
            env:
            - name: VUE_APP_ORDER_SERVICE_URL
              value: "http://order-service:3000/"
            - name: VUE_APP_PRODUCT_SERVICE_URL
              value: "http://product-service:3002/"
            resources:
              requests:
                cpu: 1m
                memory: 200Mi
              limits:
                cpu: 1000m
                memory: 512Mi
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: store-front
    spec:
      ports:
      - port: 80
        targetPort: 8080
      selector:
        app: store-front
      type: LoadBalancer
    

    If you create and save the YAML file locally, then you can upload the manifest file to your default directory in CloudShell by selecting the Upload/Download files button and selecting the file from your local file system.

  2. Deploy the application using the kubectl apply command and specify the name of your YAML manifest.

    kubectl apply -f aks-store-quickstart.yaml
    

    The following example output shows the deployments and services:

    deployment.apps/rabbitmq created
    service/rabbitmq created
    deployment.apps/order-service created
    service/order-service created
    deployment.apps/product-service created
    service/product-service created
    deployment.apps/store-front created
    service/store-front created
    

Test the application

When the application runs, a Kubernetes service exposes the application front end to the internet. This process can take a few minutes to complete.

  1. Check the status of the deployed pods using the kubectl get pods command. Make sure all pods are Running before proceeding.

    kubectl get pods
    
  2. Check for a public IP address for the store-front application. Monitor progress using the kubectl get service command with the --watch argument.

    kubectl get service store-front --watch
    

    The EXTERNAL-IP output for the store-front service initially shows as pending:

    NAME          TYPE           CLUSTER-IP    EXTERNAL-IP   PORT(S)        AGE
    store-front   LoadBalancer   10.0.100.10   <pending>     80:30025/TCP   4h4m
    
  3. Once the EXTERNAL-IP address changes from pending to an actual public IP address, use CTRL-C to stop the kubectl watch process.

    The following example output shows a valid public IP address assigned to the service:

    NAME          TYPE           CLUSTER-IP    EXTERNAL-IP    PORT(S)        AGE
    store-front   LoadBalancer   10.0.100.10   20.62.159.19   80:30025/TCP   4h5m
    
  4. Open a web browser to the external IP address of your service to see the Azure Store app in action.

Delete the cluster

If you don't plan on continuing through the following tutorials, remove the created resources to avoid incurring Azure charges.

  • Remove the resource group and all related resources using the RemoveAzResourceGroup cmdlet.

    Remove-AzResourceGroup -Name testAzureLinuxResourceGroup
    

Next steps

In this quickstart, you deployed an Azure Linux Container Host AKS cluster. To learn more about the Azure Linux Container Host and walk through a complete cluster deployment and management example, continue to the Azure Linux Container Host tutorial.