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

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.

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 account, create a 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.

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.

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.

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.

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

Remove-AzResourceGroup -Name myResourceGroup

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.