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.

Before you begin

This quickstart 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 a trial 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).

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 settings:

   • Under Project details:
     • Subscription: Select the Azure subscription you want to use for this AKS cluster.
     • Resource group: Select Create new, enter a resource group name, such as myResourceGroup, and then select Ok. 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:

     • Cluster preset configuration: Select 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.

     • Kubernetes cluster name: Enter a cluster name, such as myAKSCluster.

     • Region: Select a region, such as China North 3.

     • Availability zones: Select None.

     • AKS pricing tier: Select Free.

     • Leave the default values for the remaining settings, and select Next.

       

5. On the Node pools tab, configure the following settings:

   • Select Add node pool and enter a Node pool name, such as nplinux.

   • Mode: Select User.

   • OS SKU: Select Ubuntu Linux.

   • Availability zones: Select None.

   • Leave the Enable Azure Spot instances checkbox unchecked.

   • Node size: Select Choose a size. On the Select a VM size page, select D2s_v3, and then select Select.

   • Leave the default values for the remaining settings, and select Add.

     

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

   It takes a few minutes to create the AKS cluster. When your deployment is complete, navigate to your resource by selecting Go to resource, or by browsing to the AKS cluster resource group and selecting the AKS resource.

Connect to the cluster

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

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.

1. In the local 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.

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 sure 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.

   

Delete the cluster

If you don't plan on going through the AKS tutorial series, 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.

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