Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster using the Bicep Kubernetes extension (preview)

Artikel
06.08.2024

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 Bicep Kubernetes extension (preview).
Run a sample multi-container application with a group of microservices and web front ends simulating a retail scenario.

Vigtigt

The Bicep Kubernetes extension is currently in preview. You can enable the feature from the Bicep configuration file by adding:

JSON

{
 "experimentalFeaturesEnabled": {
   "extensibility": true,
 }
}

Bemærk

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

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 an Azure free 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).

Bicep is a domain-specific language (DSL) that uses declarative syntax to deploy Azure resources. It provides concise syntax, reliable type safety, and support for code reuse. Bicep offers the best authoring experience for your infrastructure-as-code solutions in Azure.

To set up your environment for Bicep development, see Install Bicep tools. After completing the steps, you have Visual Studio Code and the Bicep extension. You also have either the latest Azure CLI version or the latest Azure PowerShell module.
To create an AKS cluster using a Bicep file, you provide an SSH public key. If you need this resource, see the following section. Otherwise, skip to Review the Bicep file.
To deploy a Bicep file, you need write access on the resources you deploy and access to all operations on the Microsoft.Resources/deployments resource type. For example, to deploy a virtual machine, you need Microsoft.Compute/virtualMachines/write and Microsoft.Resources/deployments/* permissions. For a list of roles and permissions, see Azure built-in roles.

Create an SSH key pair

Go to https://shell.azure.com to open Cloud Shell in your browser.

Create an SSH key pair using the az sshkey create Azure CLI command or the ssh-keygen command.

Azure CLI

# Create an SSH key pair using Azure CLI
az sshkey create --name "mySSHKey" --resource-group "myResourceGroup"

# Create an SSH key pair using ssh-keygen
ssh-keygen -t rsa -b 4096

For more information about creating SSH keys, see Create and manage SSH keys for authentication in Azure.

Review the Bicep file

The Bicep file used to create an AKS cluster is from Azure Quickstart Templates. For more AKS samples, see AKS quickstart templates.

Bicep

@description('The name of the Managed Cluster resource.')
param clusterName string = 'aks101cluster'

@description('The location of the Managed Cluster resource.')
param location string = resourceGroup().location

@description('Optional DNS prefix to use with hosted Kubernetes API server FQDN.')
param dnsPrefix string

@description('Disk size (in GB) to provision for each of the agent pool nodes. This value ranges from 0 to 1023. Specifying 0 will apply the default disk size for that agentVMSize.')
@minValue(0)
@maxValue(1023)
param osDiskSizeGB int = 0

@description('The number of nodes for the cluster.')
@minValue(1)
@maxValue(50)
param agentCount int = 3

@description('The size of the Virtual Machine.')
param agentVMSize string = 'standard_d2s_v3'

@description('User name for the Linux Virtual Machines.')
param linuxAdminUsername string

@description('Configure all linux machines with the SSH RSA public key string. Your key should include three parts, for example \'ssh-rsa AAAAB...snip...UcyupgH azureuser@linuxvm\'')
param sshRSAPublicKey string

resource aks 'Microsoft.ContainerService/managedClusters@2024-02-01' = {
  name: clusterName
  location: location
  identity: {
    type: 'SystemAssigned'
  }
  properties: {
    dnsPrefix: dnsPrefix
    agentPoolProfiles: [
      {
        name: 'agentpool'
        osDiskSizeGB: osDiskSizeGB
        count: agentCount
        vmSize: agentVMSize
        osType: 'Linux'
        mode: 'System'
      }
    ]
    linuxProfile: {
      adminUsername: linuxAdminUsername
      ssh: {
        publicKeys: [
          {
            keyData: sshRSAPublicKey
          }
        ]
      }
    }
  }
}

output controlPlaneFQDN string = aks.properties.fqdn

The resource defined in the Bicep file is Microsoft.ContainerService/managedClusters.

Save a copy of the file as main.bicep to your local computer.

Add the application definition

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.

Bemærk

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 in the same folder as main.bicep and copy in the following manifest:

YAML

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.

Open main.bicep in Visual Studio Code.
Press Ctrl+Shift+P to open Command Palette.
Search for bicep, and then select Bicep: Import Kubernetes Manifest.
Select aks-store-quickstart.yaml from the prompt. This process creates an aks-store-quickstart.bicep file in the same folder.

Open main.bicep and add the following Bicep at the end of the file to reference the newly created aks-store-quickstart.bicep module:

Bicep

module kubernetes './aks-store-quickstart.bicep' = {
  name: 'buildbicep-deploy'
  params: {
    kubeConfig: aks.listClusterAdminCredential().kubeconfigs[0].value
  }
}

Save both main.bicep and aks-store-quickstart.bicep.

Create an Azure resource group using the az group create command.

Azure CLI
```
az group create --name myResourceGroup --location eastus
```

Deploy the Bicep file using the az deployment group create command.

Azure CLI

az deployment group create --resource-group myResourceGroup --template-file main.bicep --parameters clusterName=<cluster-name> dnsPrefix=<dns-previs> linuxAdminUsername=<linux-admin-username> sshRSAPublicKey='<ssh-key>'

Create an Azure resource group using the New-AzResourceGroup cmdlet.

Azure PowerShell
```
New-AzResourceGroup -Name myResourceGroup -Location eastus
```

Deploy the Bicep file using the New-AzResourceGroupDeployment cmdlet.

Azure PowerShell

New-AzResourceGroupDeployment -ResourceGroupName myResourceGroup -TemplateFile ./main.bicep -clusterName=<cluster-name> -dnsPrefix=<dns-prefix> -linuxAdminUsername=<linux-admin-username> -sshRSAPublicKey="<ssh-key>"

Provide the following values in the commands:

Cluster name: Enter a unique name for the AKS cluster, such as myAKSCluster.
DNS prefix: Enter a unique DNS prefix for your cluster, such as myakscluster.
Linux Admin Username: Enter a username to connect using SSH, such as azureuser.
SSH RSA Public Key: Copy and paste the public part of your SSH key pair (by default, the contents of ~/.ssh/id_rsa.pub).

It takes a few minutes to create the AKS cluster. Wait for the cluster successfully deploy before you move on to the next step.

Validate the Bicep deployment

Sign in to the Azure portal.
On the Azure portal menu or from the Home page, navigate to your AKS cluster.
Under Kubernetes resources, select Services and ingresses.
Find the store-front service and copy the value for External IP.
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 charges.

Azure CLI
Azure PowerShell

Remove the resource group, container service, and all related resources using the az group delete command.

Azure CLI

az group delete --name myResourceGroup --yes --no-wait

Remove the resource group, container service, and all related resources using the Remove-AzResourceGroup cmdlet.

Azure PowerShell

Remove-AzResourceGroup -Name myResourceGroup

Bemærk

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. 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.

AKS tutorial

Del via

Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster using the Bicep Kubernetes extension (preview)

Before you begin

Create an SSH key pair

Review the Bicep file

Add the application definition

Deploy the Bicep file

Validate the Bicep deployment

Delete the cluster

Next steps

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