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

Article
10/26/2023

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 CLI.
Run a sample multi-container application with a group of microservices and web front ends simulating a retail scenario.

Note

This sample application is just for demo purposes and doesn't represent all the best practices for Kubernetes applications.

Before you begin

This quickstart assumes a basic understanding of Kubernetes concepts. For more information, see Kubernetes core concepts for Azure Kubernetes Service (AKS).
You need an Azure account with an active subscription. If you don't have one, create an account for free.
To learn more about creating a Windows Server node pool, see Create an AKS cluster that supports Windows Server containers.
This article requires Azure CLI version 2.0.64 or later. If you're using Azure Cloud Shell, the latest version is already installed.
Make sure 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).
If you have multiple Azure subscriptions, select the appropriate subscription ID in which the resources should be billed using the az account command.
Verify you have the Microsoft.OperationsManagement and Microsoft.OperationalInsights providers registered on your subscription. These Azure resource providers are required to support Container insights. Check the registration status using the following commands:
```
az provider show -n Microsoft.OperationsManagement -o table
az provider show -n Microsoft.OperationalInsights -o table
```
If they're not registered, register them using the following commands:
```
az provider register --namespace Microsoft.OperationsManagement
az provider register --namespace Microsoft.OperationalInsights
```

Note

If you plan to run the commands locally instead of in Azure Cloud Shell, make sure you run the commands with administrative privileges.

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 a resource group

An Azure resource group is a logical group in which Azure resources are deployed and managed. When you create a resource group, you're prompted 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 a resource group named myResourceGroup in the eastus location.

Create a resource group using the az group create command.

az group create --name myResourceGroup --location eastus

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

{
  "id": "/subscriptions/<guid>/resourceGroups/myResourceGroup",
  "location": "eastus",
  "managedBy": null,
  "name": "myResourceGroup",
  "properties": {
    "provisioningState": "Succeeded"
  },
  "tags": null
}

Create an AKS cluster

The following example creates a cluster named myAKSCluster with one node and enables a system-assigned managed identity.

Create an AKS cluster using the az aks create command with the --enable-addons monitoring and --enable-msi-auth-for-monitoring parameters to enable Azure Monitor Container insights with managed identity authentication (preview).
```
az aks create -g myResourceGroup -n myAKSCluster --enable-managed-identity --node-count 1 --enable-addons monitoring --enable-msi-auth-for-monitoring  --generate-ssh-keys
```
After a few minutes, the command completes and returns JSON-formatted information about the cluster.

Note

When you create a new cluster, AKS automatically creates a second resource group to store the AKS resources. For more information, see Why are two resource groups created with AKS?

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.

Install kubectl locally using the az aks install-cli command.
```
az aks install-cli
```
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
```
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 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   v1.12.8
```

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:

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.

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.

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.

Check the status of the deployed pods using the kubectl get pods command. Make all pods are Running before proceeding.
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
```
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 going through the following tutorials, clean up unnecessary resources to avoid Azure charges.

Remove the resource group, container service, and all related resources using 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 deployed a simple multi-container application to it.

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

AKS tutorial

This quickstart is for introductory purposes. For guidance on creating full solutions with AKS for production, see AKS solution guidance.

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

Before you begin

Create a resource group

Create an AKS cluster

Connect to the cluster

Deploy the application

Test the application

Delete the cluster

Next steps

Feedback

Additional resources

Additional resources