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

  • บทความ

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

Note

To get started with quickly provisioning an AKS cluster, this article includes steps to deploy a cluster with default settings for evaluation purposes only. Before deploying a production-ready cluster, we recommend that you familiarize yourself with our baseline reference architecture to consider how it aligns with your business requirements.

Before you begin

Note

The Azure Linux node pool is now in general availablility (GA). To learn about the benefits and deployment steps, see the Introduction to the Azure Linux Container Host for AKS.

Login to your Azure account

First, log into your Azure account and authenticate using one of the methods described in the following section.

Terraform only supports authenticating to Azure with the Azure CLI. Authenticating using Azure PowerShell isn't supported. Therefore, while you can use the Azure PowerShell module when doing your Terraform work, you first need to authenticate to Azure.

Implement the Terraform code

Note

The sample code for this article is located in the Azure Terraform GitHub repo. You can view the log file containing the test results from current and previous versions of Terraform.

See more articles and sample code showing how to use Terraform to manage Azure resources

  1. Create a directory you can use to test the sample Terraform code and make it your current directory.

  2. Create a file named providers.tf and insert the following code:

    terraform {
  required_version = ">=1.0"

  required_providers {
    azapi = {
      source  = "azure/azapi"
      version = "~>1.5"
    }
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~>3.0"
    }
    random = {
      source  = "hashicorp/random"
      version = "~>3.0"
    }
    time = {
      source  = "hashicorp/time"
      version = "0.9.1"
    }
  }
}

provider "azurerm" {
  features {}
}

  3. Create a file named ssh.tf and insert the following code:

    resource "random_pet" "ssh_key_name" {
  prefix    = "ssh"
  separator = ""
}

resource "azapi_resource_action" "ssh_public_key_gen" {
  type        = "Microsoft.Compute/sshPublicKeys@2022-11-01"
  resource_id = azapi_resource.ssh_public_key.id
  action      = "generateKeyPair"
  method      = "POST"

  response_export_values = ["publicKey", "privateKey"]
}

resource "azapi_resource" "ssh_public_key" {
  type      = "Microsoft.Compute/sshPublicKeys@2022-11-01"
  name      = random_pet.ssh_key_name.id
  location  = azurerm_resource_group.rg.location
  parent_id = azurerm_resource_group.rg.id
}

output "key_data" {
  value = azapi_resource_action.ssh_public_key_gen.output.publicKey
}

  4. Create a file named main.tf and insert the following code:

    # Generate random resource group name
resource "random_pet" "rg_name" {
  prefix = var.resource_group_name_prefix
}

resource "azurerm_resource_group" "rg" {
  location = var.resource_group_location
  name     = random_pet.rg_name.id
}

resource "random_pet" "azurerm_kubernetes_cluster_name" {
  prefix = "cluster"
}

resource "random_pet" "azurerm_kubernetes_cluster_dns_prefix" {
  prefix = "dns"
}

resource "azurerm_kubernetes_cluster" "k8s" {
  location            = azurerm_resource_group.rg.location
  name                = random_pet.azurerm_kubernetes_cluster_name.id
  resource_group_name = azurerm_resource_group.rg.name
  dns_prefix          = random_pet.azurerm_kubernetes_cluster_dns_prefix.id

  identity {
    type = "SystemAssigned"
  }

  default_node_pool {
    name       = "agentpool"
    vm_size    = "Standard_D2_v2"
    node_count = var.node_count
  }
  linux_profile {
    admin_username = var.username

    ssh_key {
      key_data = azapi_resource_action.ssh_public_key_gen.output.publicKey
    }
  }
  network_profile {
    network_plugin    = "kubenet"
    load_balancer_sku = "standard"
  }
}

  5. Create a file named variables.tf and insert the following code:

    variable "resource_group_location" {
  type        = string
  default     = "eastus"
  description = "Location of the resource group."
}

variable "resource_group_name_prefix" {
  type        = string
  default     = "rg"
  description = "Prefix of the resource group name that's combined with a random ID so name is unique in your Azure subscription."
}

variable "node_count" {
  type        = number
  description = "The initial quantity of nodes for the node pool."
  default     = 3
}

variable "msi_id" {
  type        = string
  description = "The Managed Service Identity ID. Set this value if you're running this example using Managed Identity as the authentication method."
  default     = null
}

variable "username" {
  type        = string
  description = "The admin username for the new cluster."
  default     = "azureadmin"
}

  6. Create a file named outputs.tf and insert the following code:

    output "resource_group_name" {
  value = azurerm_resource_group.rg.name
}

output "kubernetes_cluster_name" {
  value = azurerm_kubernetes_cluster.k8s.name
}

output "client_certificate" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config[0].client_certificate
  sensitive = true
}

output "client_key" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config[0].client_key
  sensitive = true
}

output "cluster_ca_certificate" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config[0].cluster_ca_certificate
  sensitive = true
}

output "cluster_password" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config[0].password
  sensitive = true
}

output "cluster_username" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config[0].username
  sensitive = true
}

output "host" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config[0].host
  sensitive = true
}

output "kube_config" {
  value     = azurerm_kubernetes_cluster.k8s.kube_config_raw
  sensitive = true
}

Initialize Terraform

Run terraform init to initialize the Terraform deployment. This command downloads the Azure provider required to manage your Azure resources.

terraform init -upgrade

Key points:

  • The -upgrade parameter upgrades the necessary provider plugins to the newest version that complies with the configuration's version constraints.

Create a Terraform execution plan

Run terraform plan to create an execution plan.

terraform plan -out main.tfplan

Key points:

  • The terraform plan command creates an execution plan, but doesn't execute it. Instead, it determines what actions are necessary to create the configuration specified in your configuration files. This pattern allows you to verify whether the execution plan matches your expectations before making any changes to actual resources.
  • The optional -out parameter allows you to specify an output file for the plan. Using the -out parameter ensures that the plan you reviewed is exactly what is applied.

Apply a Terraform execution plan

Run terraform apply to apply the execution plan to your cloud infrastructure.

terraform apply main.tfplan

Key points:

  • The example terraform apply command assumes you previously ran terraform plan -out main.tfplan.
  • If you specified a different filename for the -out parameter, use that same filename in the call to terraform apply.
  • If you didn't use the -out parameter, call terraform apply without any parameters.

Verify the results

  1. Get the Azure resource group name using the following command.

    resource_group_name=$(terraform output -raw resource_group_name)

  2. Display the name of your new Kubernetes cluster using the az aks list command.

    az aks list \
  --resource-group $resource_group_name \
  --query "[].{\"K8s cluster name\":name}" \
  --output table

  3. Get the Kubernetes configuration from the Terraform state and store it in a file that kubectl can read using the following command.

    echo "$(terraform output kube_config)" > ./azurek8s

  4. Verify the previous command didn't add an ASCII EOT character using the following command.

    cat ./azurek8s

    Key points:

    • If you see << EOT at the beginning and EOT at the end, remove these characters from the file. Otherwise, you may receive the following error message: error: error loading config file "./azurek8s": yaml: line 2: mapping values are not allowed in this context

  5. Set an environment variable so kubectl can pick up the correct config using the following command.

    export KUBECONFIG=./azurek8s

  6. Verify the health of the cluster using the kubectl get nodes command.

    kubectl get nodes

Key points:

  • When you created the AKS cluster, monitoring was enabled to capture health metrics for both the cluster nodes and pods. These health metrics are available in the Azure portal. For more information on container health monitoring, see Monitor Azure Kubernetes Service health.
  • Several key values classified as output when you applied the Terraform execution plan. For example, the host address, AKS cluster user name, and AKS cluster password are output.

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.

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.

  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

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 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.

Clean up resources

Delete AKS resources

When you no longer need the resources created via Terraform, do the following steps:

  1. Run terraform plan and specify the destroy flag.

    terraform plan -destroy -out main.destroy.tfplan

    Key points:

    • The terraform plan command creates an execution plan, but doesn't execute it. Instead, it determines what actions are necessary to create the configuration specified in your configuration files. This pattern allows you to verify whether the execution plan matches your expectations before making any changes to actual resources.
    • The optional -out parameter allows you to specify an output file for the plan. Using the -out parameter ensures that the plan you reviewed is exactly what is applied.

  2. Run terraform apply to apply the execution plan.

    terraform apply main.destroy.tfplan

Delete service principal

  1. Get the service principal ID using the following command.

    sp=$(terraform output -raw sp)

  2. Delete the service principal using the az ad sp delete command.

    az ad sp delete --id $sp

Clone the Azure Developer CLI template

The Azure Developer CLI allows you to quickly download samples from the Azure-Samples repository. In our quickstart, you download the aks-store-demo application. For more information on the general uses cases, see the azd overview.

  1. Clone the AKS store demo template from the Azure-Samples repository using the azd init command with the --template parameter.

    azd init --template Azure-Samples/aks-store-demo

  2. Enter an environment name for your project that uses only alphanumeric characters and hyphens, such as aks-terraform-1.

    Enter a new environment name: aks-terraform-1

Sign in to your Azure Cloud account

The azd template contains all the code needed to create the services, but you need to sign in to your Azure account in order to host the application on AKS.

  1. Sign in to your account using the azd auth login command.

    azd auth login

  2. Copy the device code that appears in the output and press enter to sign in.

    Start by copying the next code: XXXXXXXXX
Then press enter and continue to log in from your browser...

    Important

    If you're using an out-of-network virtual machine or GitHub Codespace, certain Azure security policies cause conflicts when used to sign in with azd auth login. If you run into an issue here, you can follow the azd auth workaround provided, which involves using a curl request to the localhost URL you were redirected to after running azd auth login.

  3. Authenticate with your credentials on your organization's sign in page.

  4. Confirm that it's you trying to connect from the Azure CLI.

  5. Verify the message "Device code authentication completed. Logged in to Azure." appears in your original terminal.

    Waiting for you to complete authentication in the browser...
Device code authentication completed.
Logged in to Azure.

azd auth workaround

This workaround requires you to have the Azure CLI installed.

  1. Open a terminal window and log in with the Azure CLI using the az login command with the --scope parameter set to https://graph.microsoft.com/.default.

    az login --scope https://graph.microsoft.com/.default

    You should be redirected to an authentication page in a new tab to create a browser access token, as shown in the following example:

    https://login.microsoftonline.com/organizations/oauth2/v2.0/authorize?clientid=<your_client_id>.

  2. Copy the localhost URL of the webpage you received after attempting to sign in with azd auth login.

  3. In a new terminal window, use the following curl request to log in. Make sure you replace the <localhost> placeholder with the localhost URL you copied in the previous step.

    curl <localhost>

    A successful login outputs an HTML webpage, as shown in the following example:

    <!DOCTYPE html>
<html>
<head>
    <meta charset="utf-8" />
    <meta http-equiv="refresh" content="60;url=https://docs.microsoft.com/cli/azure/">
    <title>Login successfully</title>
    <style>
        body {
            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
        }

        code {
            font-family: Consolas, 'Liberation Mono', Menlo, Courier, monospace;
            display: inline-block;
            background-color: rgb(242, 242, 242);
            padding: 12px 16px;
            margin: 8px 0px;
        }
    </style>
</head>
<body>
    <h3>You have logged into Microsoft Azure!</h3>
    <p>You can close this window, or we will redirect you to the <a href="https://docs.microsoft.com/cli/azure/">Azure CLI documentation</a> in 1 minute.</p>
    <h3>Announcements</h3>
    <p>[Windows only] Azure CLI is collecting feedback on using the <a href="https://learn.microsoft.com/windows/uwp/security/web-account-manager">Web Account Manager</a> (WAM) broker for the login experience.</p>
    <p>You may opt-in to use WAM by running the following commands:</p>
    <code>
        az config set core.allow_broker=true<br>
        az account clear<br>
        az login
    </code>
</body>
</html>

  4. Close the current terminal and open the original terminal. You should see a JSON list of your subscriptions.

  5. Copy the id field of the subscription you want to use.

  6. Set your subscription using the az account set command.

    az account set --subscription <subscription_id>

Create and deploy resources for your cluster

To deploy the application, you use the azd up command to create all the objects required to run the AKS Store application.

  • An azure.yaml file defines a cluster's desired state, such as which container images to fetch and includes the following Kubernetes deployments and services:

Diagram that shows the 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.

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 Cosmos DB or Azure Service Bus.

Deploy application resources

The azd template for this quickstart creates a new resource group with an AKS cluster and an Azure Key Vault. The key vault stores client secrets and runs the services in the pets namespace.

  1. Create all the application resources using the azd up command.

    azd up

    azd up runs all the hooks inside of the azd-hooks folder to preregister, provision, and deploy the application services.

    Customize hooks to add custom code into the azd workflow stages. For more information, see the azd hooks reference.

  2. Select an Azure subscription for your billing usage.

    ? Select an Azure Subscription to use:  [Use arrows to move, type to filter]
> 1. My Azure Subscription (xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx)

  3. Select a region to deploy your application to.

    Select an Azure location to use:  [Use arrows to move, type to filter]
  1.  (South America) Brazil Southeast (brazilsoutheast)
  2.  (US) Central US (centralus)
  3.  (US) East US (eastus)
> 43. (US) East US 2 (eastus2)
  4.  (US) East US STG (eastusstg)
  5.  (US) North Central US (northcentralus)
  6.  (US) South Central US (southcentralus)

    azd automatically runs the preprovision and postprovision hooks to create the resources for your application. This process can take a few minutes to complete. Once complete, you should see an output similar to the following example:

    SUCCESS: Your workflow to provision and deploy to Azure completed in 9 minutes 40 seconds.

Generate Terraform plans

Within your Azure Developer template, the /infra/terraform folder contains all the code used to generate the Terraform plan.

Terraform deploys and runs commands using terraform apply as part of azd's provisioning step. Once complete, you should see an output similar to the following example:

Plan: 5 to add, 0 to change, 0 to destroy.
...
Saved the plan to: /workspaces/aks-store-demo/.azure/aks-terraform-azd/infra/terraform/main.tfplan

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. Set your namespace as the demo namespace pets using the kubectl set-context command.

    kubectl config set-context --current --namespace=pets

  2. Check the status of the deployed pods using the kubectl get pods command. Make sure all pods are Running before proceeding.

    kubectl get pods

  3. Check for a public IP address for the store-front application and 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

  4. 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 sample 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

  5. 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

Once you're finished with the quickstart, clean up unnecessary resources to avoid Azure charges.

  1. Delete all the resources created in the quickstart using the azd down command.

    azd down

  2. Confirm your decision to remove all used resources from your subscription by typing y and pressing Enter.

    ? Total resources to delete: 14, are you sure you want to continue? (y/N)

  3. Allow purge to reuse the quickstart variables if applicable by typing y and pressing Enter.

    [Warning]: These resources have soft delete enabled allowing them to be recovered for a period or time after deletion. During this period, their names can't be reused. In the future, you can use the argument --purge to skip this confirmation.

Troubleshoot Terraform on Azure

Troubleshoot common problems when using Terraform on Azure.

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.

Learn more about using AKS.