Quickstart: Deploy an Azure Kubernetes Service cluster using the Azure CLI

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

  • Deploy an AKS cluster using the Azure CLI.

  • Run a multi-container application with a web front-end and a Redis instance in the cluster.

  • Monitor the health of the cluster and pods that run your application.

    Voting app deployed in Azure Kubernetes Service

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 free account before you begin.

To learn more about creating a Windows Server node pool, see Create an AKS cluster that supports Windows Server containers.

Prerequisites

  • Use the Bash environment in Azure Cloud Shell.

    Launch Cloud Shell in a new window

  • If you prefer, install the Azure CLI to run CLI reference commands.

    • 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 additional sign-in options, see Sign in with the Azure CLI.

    • When you're prompted, install Azure CLI extensions 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.

  • This article requires version 2.0.64 or greater of the Azure CLI. If using Azure Cloud Shell, the latest version is already installed.
  • The identity you are using 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

Run the commands as administrator if you plan to run the commands in this quickstart locally instead of in Azure Cloud Shell.

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 will be prompted to specify a location. This location is:

  • The storage location of your resource group metadata.
  • Where your resources will run in Azure if you don't specify another region during resource creation.

The following example creates a resource group named myResourceGroup in the eastus location.

Create a resource group using the az group create command.

az group create --name myResourceGroup --location eastus

Output for successfully created resource group:

{
  "id": "/subscriptions/<guid>/resourceGroups/myResourceGroup",
  "location": "eastus",
  "managedBy": null,
  "name": "myResourceGroup",
  "properties": {
    "provisioningState": "Succeeded"
  },
  "tags": null
}

Enable cluster monitoring

Verify Microsoft.OperationsManagement and Microsoft.OperationalInsights are registered on your subscription. To check the registration status:

az provider show -n Microsoft.OperationsManagement -o table
az provider show -n Microsoft.OperationalInsights -o table

If they are not registered, register Microsoft.OperationsManagement and Microsoft.OperationalInsights using:

az provider register --namespace Microsoft.OperationsManagement
az provider register --namespace Microsoft.OperationalInsights

Create AKS cluster

Create an AKS cluster using the az aks create command with the --enable-addons monitoring parameter to enable Azure Monitor for containers. The following example creates a cluster named myAKSCluster with one node:

az aks create --resource-group myResourceGroup --name myAKSCluster --node-count 1 --enable-addons monitoring --generate-ssh-keys

After a few minutes, the command completes and returns JSON-formatted information about the cluster.

Note

When you create an AKS cluster, a second resource group is automatically created 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. kubectl is already installed if you use Azure Cloud Shell.

  1. Install kubectl locally using the az aks install-cli command:

    az aks install-cli
    
  2. Configure kubectl to connect to your Kubernetes cluster using the az aks get-credentials command. The following command:

    • Downloads credentials and configures the Kubernetes CLI to use them.
    • Uses ~/.kube/config, the default location for the Kubernetes configuration file. Specify a different location for your Kubernetes configuration file using --file.
    az aks get-credentials --resource-group myResourceGroup --name myAKSCluster
    
  3. Verify the connection to your cluster using the kubectl get command. This command returns a list of the cluster nodes.

    kubectl get nodes
    

    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   v1.12.8
    

Run the application

A Kubernetes manifest file defines a cluster's desired state, such as which container images to run.

In this quickstart, you will use a manifest to create all objects needed to run the Azure Vote application. This manifest includes two Kubernetes deployments:

  • The sample Azure Vote Python applications.
  • A Redis instance.

Two Kubernetes Services are also created:

  • An internal service for the Redis instance.
  • An external service to access the Azure Vote application from the internet.
  1. Create a file named azure-vote.yaml.

    • If you use the Azure Cloud Shell, this file can be created using code, vi, or nano as if working on a virtual or physical system
  2. Copy in the following YAML definition:

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: azure-vote-back
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: azure-vote-back
      template:
        metadata:
          labels:
            app: azure-vote-back
        spec:
          nodeSelector:
            "kubernetes.io/os": linux
          containers:
          - name: azure-vote-back
            image: mcr.microsoft.com/oss/bitnami/redis:6.0.8
            env:
            - name: ALLOW_EMPTY_PASSWORD
              value: "yes"
            resources:
              requests:
                cpu: 100m
                memory: 128Mi
              limits:
                cpu: 250m
                memory: 256Mi
            ports:
            - containerPort: 6379
              name: redis
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: azure-vote-back
    spec:
      ports:
      - port: 6379
      selector:
        app: azure-vote-back
    ---
    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: azure-vote-front
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: azure-vote-front
      template:
        metadata:
          labels:
            app: azure-vote-front
        spec:
          nodeSelector:
            "kubernetes.io/os": linux
          containers:
          - name: azure-vote-front
            image: mcr.microsoft.com/azuredocs/azure-vote-front:v1
            resources:
              requests:
                cpu: 100m
                memory: 128Mi
              limits:
                cpu: 250m
                memory: 256Mi
            ports:
            - containerPort: 80
            env:
            - name: REDIS
              value: "azure-vote-back"
    ---
    apiVersion: v1
    kind: Service
    metadata:
      name: azure-vote-front
    spec:
      type: LoadBalancer
      ports:
      - port: 80
      selector:
        app: azure-vote-front
    
  3. Deploy the application using the kubectl apply command and specify the name of your YAML manifest:

    kubectl apply -f azure-vote.yaml
    

    Output shows the successfully created deployments and services:

    deployment "azure-vote-back" created
    service "azure-vote-back" created
    deployment "azure-vote-front" created
    service "azure-vote-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.

Monitor progress using the kubectl get service command with the --watch argument.

kubectl get service azure-vote-front --watch

The EXTERNAL-IP output for the azure-vote-front service will initially show as pending.

NAME               TYPE           CLUSTER-IP   EXTERNAL-IP   PORT(S)        AGE
azure-vote-front   LoadBalancer   10.0.37.27   <pending>     80:30572/TCP   6s

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:

azure-vote-front   LoadBalancer   10.0.37.27   52.179.23.131   80:30572/TCP   2m

To see the Azure Vote app in action, open a web browser to the external IP address of your service.

Voting app deployed in Azure Kubernetes Service

View the cluster nodes' and pods' health metrics captured by Azure Monitor for containers in the Azure portal.

Delete the cluster

To avoid Azure charges, clean up your unnecessary resources. Use the az group delete command to remove the resource group, container service, and all related resources.

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

Note

When you delete the cluster, the Azure Active Directory service principal used by the AKS cluster is not removed. For steps on how to remove the service principal, see AKS service principal considerations and deletion.

If you used a managed identity, the identity is managed by the platform and does not require removal.

Get the code

Pre-existing container images were used in this quickstart to create a Kubernetes deployment. The related application code, Dockerfile, and Kubernetes manifest file are available on GitHub.

Next steps

In this quickstart, you deployed a Kubernetes cluster and then deployed a multi-container application to it. Access the Kubernetes web dashboard for your AKS cluster.

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