Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster with Flatcar Container Linux for AKS (preview) using Azure CLI

Azure Kubernetes Service (AKS) is a managed Kubernetes service that lets you quickly deploy and manage clusters. In this quickstart, you learn how to:

Create an AKS cluster using Flatcar Container Linux for AKS (preview).
Deploy an AKS cluster using the Azure CLI.
Run a sample multi-container application with a group of microservices and web front ends that simulate a retail scenario.

Note

This article includes steps to deploy a cluster with default settings for evaluation purposes only.

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 trial subscription, create an Azure trial subscription before you begin.

If you prefer to run CLI reference commands locally, install the Azure CLI. If you're running on Windows or macOS, consider running Azure CLI in a Docker container. For more information, see How to run the Azure CLI in a Docker container.
- If you're using a local installation, sign in to the Azure CLI by using the az login command. To finish the authentication process, follow the steps displayed in your terminal. For other sign-in options, see Sign in with the Azure CLI.
- When you're prompted, install the Azure CLI extension on first use. For more information about extensions, see Use extensions with the Azure CLI.
- Run az version to find the version and dependent libraries that are installed. To upgrade to the latest version, run az upgrade.

Make sure that the identity you're using to create your cluster has the appropriate minimum permissions. For more information 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 set command. For more information, see How to manage Azure subscriptions – Azure CLI.

Register resource providers

You might need to register resource providers in your Azure subscription. For example, Microsoft.ContainerService is required.

Check the registration status using the az provider show command.

az provider show --namespace Microsoft.ContainerService --query registrationState

If necessary, register the resource provider using the az provider register command.

az provider register --namespace Microsoft.ContainerService

Install `aks-preview` extension

Important

AKS preview features are available on a self-service, opt-in basis. Previews are provided "as is" and "as available," and they're excluded from the service-level agreements and limited warranty. AKS previews are partially covered by customer support on a best-effort basis. As such, these features aren't meant for production use. For more information, see the following support articles:

Install the aks-preview Azure CLI extension using the az extension add command.
```
az extension add --name aks-preview
```
Update to the latest version of the extension using the az extension update command. Flatcar Container Linux requires a minimum of 18.0.0b42.
```
az extension update --name aks-preview
```

Register `AKSFlatcarPreview` feature flag

az feature register --namespace "Microsoft.ContainerService" --name "AKSFlatcarPreview"

Verify the registration status using the az feature show command. It takes a few minutes for the status to show Registered.
```
az feature show --namespace Microsoft.ContainerService --name AKSFlatcarPreview
```
When the status reflects Registered, refresh the registration of the Microsoft.ContainerService resource provider using the az provider register command.
```
az provider register --namespace Microsoft.ContainerService
```

Define environment variables

Define the following environment variables for use throughout this quickstart:

export RANDOM_ID="$(openssl rand -hex 3)"
export MY_RESOURCE_GROUP_NAME="myAKSResourceGroup$RANDOM_ID"
export REGION="chinanorth3"
export MY_AKS_CLUSTER_NAME="myAKSCluster$RANDOM_ID"

The RANDOM_ID variable's value is a six-character alphanumeric value appended to the resource group and cluster name so that the names are unique. Use the echo command to view variable values like echo $RANDOM_ID.

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.

Create a resource group using the az group create command.

az group create \
  --name $MY_RESOURCE_GROUP_NAME \
  --location $REGION

Example output:

{
  "id": "/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/myAKSResourceGroup<randomIDValue>",
  "location": "chinanorth3",
  "managedBy": null,
  "name": "myAKSResourceGroup<randomIDValue>",
  "properties": {
    "provisioningState": "Succeeded"
  },
  "tags": null,
  "type": "Microsoft.Resources/resourceGroups"
}

Create an AKS cluster

Create an AKS cluster using the az aks create command. The following example creates a cluster with one node and enables a system-assigned managed identity:

az aks create \
  --resource-group $MY_RESOURCE_GROUP_NAME \
  --name $MY_AKS_CLUSTER_NAME \
  --os-sku flatcar \
  --node-count 1 \
  --generate-ssh-keys

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. To install kubectl locally, use the az aks install-cli command.

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 $MY_RESOURCE_GROUP_NAME \
  --name $MY_AKS_CLUSTER_NAME
```
Verify the connection to your cluster using the kubectl get command. This command returns a list of the cluster nodes.
```
kubectl get nodes
```

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.
RabbitMQ: Message queue for an order queue.

Note

We don't recommend running stateful containers, such as RabbitMQ, without persistent storage for production. We use it here for simplicity, but we recommend using managed services, such as Azure Cosmos DB or Azure Service Bus.

Create a file named aks-store-quickstart.yaml and copy in the following manifest.

apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: rabbitmq
spec:
  serviceName: rabbitmq
  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
        startupProbe:
          httpGet:
            path: /health
            port: 3000
          failureThreshold: 5
          initialDelaySeconds: 20
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /health
            port: 3000
          failureThreshold: 3
          initialDelaySeconds: 3
          periodSeconds: 5
        livenessProbe:
          httpGet:
            path: /health
            port: 3000
          failureThreshold: 5
          initialDelaySeconds: 3
          periodSeconds: 3
      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
        env:
        - name: AI_SERVICE_URL
          value: "http://ai-service:5001/"
        resources:
          requests:
            cpu: 1m
            memory: 1Mi
          limits:
            cpu: 2m
            memory: 20Mi
        readinessProbe:
          httpGet:
            path: /health
            port: 3002
          failureThreshold: 3
          initialDelaySeconds: 3
          periodSeconds: 5
        livenessProbe:
          httpGet:
            path: /health
            port: 3002
          failureThreshold: 5
          initialDelaySeconds: 3
          periodSeconds: 3
---
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
        startupProbe:
          httpGet:
            path: /health
            port: 8080
          failureThreshold: 3
          initialDelaySeconds: 5
          periodSeconds: 5
        readinessProbe:
          httpGet:
            path: /health
            port: 8080
          failureThreshold: 3
          initialDelaySeconds: 3
          periodSeconds: 3
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          failureThreshold: 5
          initialDelaySeconds: 3
          periodSeconds: 3
---
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 Cli by selecting the Upload/Download files button and selecting the file from your local file system.

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 sure all pods are Running before proceeding.
```
kubectl get pods
```
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 AKS tutorial, clean up unnecessary resources to avoid Azure billing charges.

Remove the resource group, container service, and all related resources using the az group delete command.
```
az group delete --name $MY_RESOURCE_GROUP_NAME
```
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.

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

AKS tutorial

Last updated on 2025-11-27

Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster with Flatcar Container Linux for AKS (preview) using Azure CLI

Before you begin

Register resource providers

Install aks-preview extension

Register AKSFlatcarPreview feature flag

Define environment variables

Create a resource group

Create an AKS cluster

Connect to the cluster

Deploy the application

Test the application

Delete the cluster

Next steps

Additional resources

Install `aks-preview` extension

Register `AKSFlatcarPreview` feature flag