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

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 portal.
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.
If you're unfamiliar with the Azure Cloud Shell, review Overview of Azure Cloud Shell.
To learn more about creating a Windows Server node pool, see Create an AKS cluster that supports Windows Server containers.
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).

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

Sign in to the Azure portal.
On the Azure portal menu or from the Home page, select Create a resource.
In the Categories section, select Containers > Azure Kubernetes Service (AKS).
On the Basics page, configure the following options:
- 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.
- Cluster details:
  - Ensure that the Preset configuration is Standard ($$). For more details on preset configurations, see Cluster configuration presets in the Azure portal.
  - Enter a Kubernetes cluster name, such as myAKSCluster.
  - Select a Region for the AKS cluster, and leave the default value selected for Kubernetes version.
- Primary node pool:
  - Leave the default values selected.
Note

You can change the preset configuration when creating your cluster by selecting Learn more and compare presets and choosing a different option.
Select Next: Node pools when complete.
On the Node pools page, leave the default options and then select Next: Access.
On the Access page, configure the following options:
- The default value for Resource identity is System-assigned managed identity. Managed identities provide an identity for applications to use when connecting to resources that support Microsoft Entra authentication. For more details about managed identities, see What are managed identities for Azure resources?.
- The Kubernetes role-based access control (RBAC) option is the default value to provide more fine-grained control over access to the Kubernetes resources deployed in your AKS cluster.
Select Next: Networking when complete.
Keep the default Networking options, which uses the kubenet networking plug-in, and then select Next: Integrations.
Keep the default Integrations options and then select Next: Advanced.
Keep the default Advanced options and then select Next: Tags.
On the tags page, leave the default option and then select Next: Review + create.
When you navigate to the Review + create tab, Azure runs validation on the settings that you have chosen. If validation passes, you can proceed to create the AKS cluster by selecting Create. If validation fails, then it indicates which settings need to be modified.
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.

Open Cloud Shell using the >_ button on the top of the Azure portal.
Note

To perform these operations in a local shell installation:
1. Verify Azure CLI or Azure PowerShell is installed.
2. Connect to Azure via the az login or Connect-AzAccount command.

Azure CLI
Azure PowerShell

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 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
```

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 myResourceGroup -Name myAKSCluster
```
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:

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.

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

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.

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.

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

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

Before you begin

Create an AKS cluster

Connect to the cluster

Deploy the application

Test the application

Delete the cluster

Next steps

Feedback

Additional resources

Additional resources