Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster using Azure portal

Azure Kubernetes Service (AKS) is a managed Kubernetes service that lets you quickly deploy and manage clusters. In this quickstart, you:

  • Deploy an AKS cluster using the Azure portal.
  • Run a sample multi-container application with a group of microservices and web front ends simulating a retail scenario.

Note

To get started with quickly provisioning an AKS cluster, this article includes steps to deploy a cluster with default settings for evaluation purposes only. Before deploying a production-ready cluster, we recommend that you familiarize yourself with our baseline reference architecture to consider how it aligns with your business requirements.

Before you begin

This quickstart assumes a basic understanding of Kubernetes concepts. For more information, see Kubernetes core concepts for Azure Kubernetes Service (AKS).

Note

The Azure Linux node pool is now generally available (GA). To learn about the benefits and deployment steps, see the Introduction to the Azure Linux Container Host for AKS.

Create an AKS cluster

  1. Sign in to the Azure portal.

  2. On the Azure portal home page, select Create a resource.

  3. In the Categories section, select Containers > Azure Kubernetes Service (AKS).

  4. On the Basics tab, configure the following options:

    • Under Project details:
      • Select an Azure Subscription.
      • Create an Azure Resource group, such as myResourceGroup. While you can select an existing resource group, for testing or evaluation purposes, we recommend creating a resource group to temporarily host these resources and avoid impacting your production or development workloads.
    • Under Cluster details:
      • Set the Cluster preset configuration to Dev/Test. For more details on preset configurations, see Cluster configuration presets in the Azure portal.

        Note

        You can change the preset configuration when creating your cluster by selecting Compare presets and choosing a different option. Screenshot of Create AKS cluster - portal preset options.

      • Enter a Kubernetes cluster name, such as myAKSCluster.

      • Select a Region for the AKS cluster.

      • Set the Availability zones setting to None.

      • Set the AKS pricing tier to Free.

      • Leave the default value selected for Kubernetes version.

      • Leave the Automatic upgrade setting set to the recommended value, which is Enabled with patch.

      • Leave the Authentication and authorization setting set to Local accounts with Kubernetes RBAC.

        Screenshot showing how to configure an AKS cluster in Azure portal.

  5. Select Next. On the Node pools tab, add a new node pool:

    • Select Add node pool.

    • Enter a Node pool name, such as nplinux.

    • For Mode, select User.

    • For OS SKU, select Ubuntu Linux.

    • Set the Availability zones setting to None.

    • Leave the Enable Azure Spot instances checkbox unchecked.

    • For Node size, select Choose a size. On the Select a VM size page, select D2s_v3, then choose the Select button.

    • Leave the Scale method setting set to Autoscale.

    • Leave the Minimum node count and Maximum node count fields set to their default settings.

      Screenshot showing how to create a node pool running Ubuntu Linux.

  6. Leave all settings on the other tabs set to their defaults.

  7. Select Review + create to run validation on the cluster configuration. After validation completes, select Create to create the AKS cluster.

It takes a few minutes to create the AKS cluster. When your deployment is complete, navigate to your resource by either:

  • Selecting Go to resource, or
  • Browsing to the AKS cluster resource group and selecting the AKS resource. In this example you browse for myResourceGroup and select the resource myAKSCluster.

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. If you're unfamiliar with the Cloud Shell, review Overview of Azure Cloud Shell.

If you're using Cloud Shell, open it with the >_ button on the top of the Azure portal. If you're using PowerShell locally, connect to Azure via the Connect-AzAccount command. If you're using Azure CLI locally, connect to Azure via the az login command.

  1. Configure kubectl to connect to your Kubernetes cluster using the az aks get-credentials command. This command downloads credentials and configures the Kubernetes CLI to use them.

    az aks get-credentials --resource-group myResourceGroup --name myAKSCluster
    
  2. Verify the connection to your cluster using kubectl get to return a list of the cluster nodes.

    kubectl get nodes
    

    The following example output shows the single node created in the previous steps. Make sure the node status is Ready.

    NAME                                STATUS   ROLES   AGE     VERSION
    aks-nodepool1-31718369-0   Ready    agent   6m44s   v1.15.10
    

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 CosmosDB or Azure Service Bus.

  1. In the Cloud Shell, open an editor and create a file named aks-store-quickstart.yaml.

  2. Paste the following manifest into the editor:

    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
    

    For a breakdown of YAML manifest files, see Deployments and YAML manifests.

    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.

  3. 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 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
    

    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
    
  3. Open a web browser to the external IP address of your service to see the Azure Store app in action.

    Screenshot of AKS Store sample application.

Delete the cluster

If you don't plan on going through the AKS tutorial, clean up unnecessary resources to avoid Azure charges.

  1. In the Azure portal, navigate to your AKS cluster resource group.

  2. Select Delete resource group.

  3. Enter the name of the resource group to delete, and then select Delete > Delete.

    Note

    The AKS cluster was created with a system-assigned managed identity. This identity is managed by the platform and doesn't require removal.

Next steps

In this quickstart, you deployed a Kubernetes cluster and then deployed a simple multi-container application to it. This sample application is for demo purposes only and doesn't represent all the best practices for Kubernetes applications. For guidance on creating full solutions with AKS for production, see AKS solution guidance.

To learn more about AKS and walk through a complete code-to-deployment example, continue to the Kubernetes cluster tutorial.