Edit

Share via

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

  • Article

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 an Azure Resource Manager template.
  • Run a sample multi-container application with a group of microservices and web front ends simulating a retail scenario.

An Azure Resource Manager template is a JavaScript Object Notation (JSON) file that defines the infrastructure and configuration for your project. The template uses declarative syntax. You describe your intended deployment without writing the sequence of programming commands to create the deployment.

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

  • If you don't have an Azure subscription, create an Azure free account before you begin.

  • Make sure that the identity you use to create your cluster has the appropriate minimum permissions. For more details on access and identity for AKS, see Access and identity options for Azure Kubernetes Service (AKS).

  • To deploy an ARM template, you need write access on the resources you're deploying and access to all operations on the Microsoft.Resources/deployments resource type. For example, to deploy a virtual machine, you need Microsoft.Compute/virtualMachines/write and Microsoft.Resources/deployments/* permissions. For a list of roles and permissions, see Azure built-in roles.

After you deploy the cluster from the template, you can use either Azure CLI or Azure PowerShell to connect to the cluster and deploy the sample application.

This article requires Azure CLI version 2.0.64 or later. If you're using Azure Cloud Shell, the latest version is already installed there.

Create an SSH key pair

To create an AKS cluster using an ARM template, you provide an SSH public key. If you need this resource, follow the steps in this section. Otherwise, skip to the Review the template section.

To access AKS nodes, you connect using an SSH key pair (public and private). To create an SSH key pair:

  1. Go to https://shell.azure.com to open Cloud Shell in your browser.

  2. Create an SSH key pair using the az sshkey create command or the ssh-keygen command.

    # Create an SSH key pair using Azure CLI
az sshkey create --name "mySSHKey" --resource-group "myResourceGroup"

# or

# Create an SSH key pair using ssh-keygen
ssh-keygen -t rsa -b 4096

  3. To deploy the template, you must provide the public key from the SSH pair. To retrieve the public key, call az sshkey show:

    az sshkey show --name "mySSHKey" --resource-group "myResourceGroup" --query "publicKey"

By default, the SSH key files are created in the ~/.ssh directory. Running the az sshkey create or ssh-keygen command will overwrite any existing SSH key pair with the same name.

For more information about creating SSH keys, see Create and manage SSH keys for authentication in Azure.

Review the template

The template used in this quickstart is from Azure Quickstart Templates.

{
  "$schema": "https://schema.management.azure.com/schemas/2019-04-01/deploymentTemplate.json#",
  "contentVersion": "1.0.0.0",
  "metadata": {
    "_generator": {
      "name": "bicep",
      "version": "0.26.170.59819",
      "templateHash": "14823542069333410776"
    }
  },
  "parameters": {
    "clusterName": {
      "type": "string",
      "defaultValue": "aks101cluster",
      "metadata": {
        "description": "The name of the Managed Cluster resource."
      }
    },
    "location": {
      "type": "string",
      "defaultValue": "[resourceGroup().location]",
      "metadata": {
        "description": "The location of the Managed Cluster resource."
      }
    },
    "dnsPrefix": {
      "type": "string",
      "metadata": {
        "description": "Optional DNS prefix to use with hosted Kubernetes API server FQDN."
      }
    },
    "osDiskSizeGB": {
      "type": "int",
      "defaultValue": 0,
      "minValue": 0,
      "maxValue": 1023,
      "metadata": {
        "description": "Disk size (in GB) to provision for each of the agent pool nodes. This value ranges from 0 to 1023. Specifying 0 will apply the default disk size for that agentVMSize."
      }
    },
    "agentCount": {
      "type": "int",
      "defaultValue": 3,
      "minValue": 1,
      "maxValue": 50,
      "metadata": {
        "description": "The number of nodes for the cluster."
      }
    },
    "agentVMSize": {
      "type": "string",
      "defaultValue": "standard_d2s_v3",
      "metadata": {
        "description": "The size of the Virtual Machine."
      }
    },
    "linuxAdminUsername": {
      "type": "string",
      "metadata": {
        "description": "User name for the Linux Virtual Machines."
      }
    },
    "sshRSAPublicKey": {
      "type": "string",
      "metadata": {
        "description": "Configure all linux machines with the SSH RSA public key string. Your key should include three parts, for example 'ssh-rsa AAAAB...snip...UcyupgH azureuser@linuxvm'"
      }
    }
  },
  "resources": [
    {
      "type": "Microsoft.ContainerService/managedClusters",
      "apiVersion": "2024-02-01",
      "name": "[parameters('clusterName')]",
      "location": "[parameters('location')]",
      "identity": {
        "type": "SystemAssigned"
      },
      "properties": {
        "dnsPrefix": "[parameters('dnsPrefix')]",
        "agentPoolProfiles": [
          {
            "name": "agentpool",
            "osDiskSizeGB": "[parameters('osDiskSizeGB')]",
            "count": "[parameters('agentCount')]",
            "vmSize": "[parameters('agentVMSize')]",
            "osType": "Linux",
            "mode": "System"
          }
        ],
        "linuxProfile": {
          "adminUsername": "[parameters('linuxAdminUsername')]",
          "ssh": {
            "publicKeys": [
              {
                "keyData": "[parameters('sshRSAPublicKey')]"
              }
            ]
          }
        }
      }
    }
  ],
  "outputs": {
    "controlPlaneFQDN": {
      "type": "string",
      "value": "[reference(resourceId('Microsoft.ContainerService/managedClusters', parameters('clusterName')), '2024-02-01').fqdn]"
    }
  }
}

The resource type defined in the ARM template is Microsoft.ContainerService/managedClusters.

For more AKS samples, see the AKS quickstart templates site.

Deploy the template

  1. Select Deploy to Azure to sign in and open a template.

    Button to deploy the Resource Manager template to Azure.

  2. On the Basics page, leave the default values for the OS Disk Size GB, Agent Count, Agent VM Size, and OS Type, and configure the following template parameters:

    • Subscription: Select an Azure subscription.
    • Resource group: Select Create new. Enter a unique name for the resource group, such as myResourceGroup, then select OK.
    • Location: Select a location, such as East US.
    • Cluster name: Enter a unique name for the AKS cluster, such as myAKSCluster.
    • DNS prefix: Enter a unique DNS prefix for your cluster, such as myakscluster.
    • Linux Admin Username: Enter a username to connect using SSH, such as azureuser.
    • SSH public key source: Select Use existing public key.
    • Key pair name: Copy and paste the public part of your SSH key pair (by default, the contents of ~/.ssh/id_rsa.pub).

  3. Select Review + Create > Create.

It takes a few minutes to create the AKS cluster. Wait for the cluster to be successfully deployed before you move on to the next step.

Connect to the cluster

To manage a Kubernetes cluster, use the Kubernetes command-line client, kubectl.

If you use Azure Cloud Shell, kubectl is already installed. To install and run kubectl locally, call the az aks install-cli 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 the kubectl get command. This command returns a list of the cluster nodes.

    kubectl get nodes

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

    NAME                                STATUS   ROLES   AGE   VERSION
aks-agentpool-27442051-vmss000000   Ready    agent   10m   v1.27.7
aks-agentpool-27442051-vmss000001   Ready    agent   10m   v1.27.7
aks-agentpool-27442051-vmss000002   Ready    agent   11m   v1.27.7

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. 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

    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.

  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

  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

  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.

    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.

Remove the resource group, container service, and all related resources by calling the az group delete command.

az group delete --name myResourceGroup --yes --no-wait

Note

The AKS cluster was created with a system-assigned managed identity, which is the default identity option used in this quickstart. The platform manages this identity so you don't need to manually remove it.

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.

AKS tutorial