Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster

• 09/24/2018
• 5 minutes to read
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In this quickstart, an AKS cluster is deployed using the Azure CLI. A multi-container application consisting of web front end and a Redis instance is then run on the cluster. Once completed, the application is accessible over the internet.

This quickstart assumes a basic understanding of Kubernetes concepts, for detailed information on Kubernetes see the Kubernetes documentation.

Open Azure Cloud Shell

Azure Cloud Shell is a free, interactive shell that you can use to run the steps in this article. Common Azure tools are preinstalled and configured in Cloud Shell for you to use with your account. Just select the Copy button to copy the code, paste it in Cloud Shell, and then press Enter to run it. There are a few ways to open Cloud Shell:

Select Try It in the upper-right corner of a code block.
Open Cloud Shell in your browser.
Select the Cloud Shell button on the menu in the upper-right corner of the Azure portal.

If you choose to install and use the CLI locally, this quickstart requires that you are running the Azure CLI version 2.0.46 or later. Run az --version to find the version. If you need to install or upgrade, see Install Azure CLI.

Create a resource group

Create a resource group with the az group create command. An Azure resource group is a logical group in which Azure resources are deployed and managed. When you create a resource group, you are asked to specify a location. This location is where your resources run in Azure.

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

az group create --name myAKSCluster --location eastus

Output:

{
  "id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myAKSCluster",
  "location": "eastus",
  "managedBy": null,
  "name": "myAKSCluster",
  "properties": {
    "provisioningState": "Succeeded"
  },
  "tags": null
}

Create AKS cluster

Use the az aks create command to create an AKS cluster. The following example creates a cluster named myAKSCluster with one node. Azure Monitor for containers is also enabled using the --enable-addons monitoring parameter. For more information on enabling the container health monitoring solution, see Monitor Azure Kubernetes Service health.

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

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

Connect to the cluster

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

If you're using Azure Cloud Shell, kubectl is already installed. If you want to install it locally, use the az aks install-cli command.

az aks install-cli

To configure kubectl to connect to your Kubernetes cluster, use the az aks get-credentials command. This step downloads credentials and configures the Kubernetes CLI to use them.

az aks get-credentials --resource-group myAKSCluster --name myAKSCluster

To verify the connection to your cluster, use the kubectl get command to return a list of the cluster nodes. It can take a few minutes for the nodes to appear.

kubectl get nodes

Output:

NAME                          STATUS    ROLES     AGE       VERSION
k8s-myAKSCluster-36346190-0   Ready     agent     2m        v1.7.7

Run the application

A Kubernetes manifest file defines a desired state for the cluster, including what container images should be running. For this example, a manifest is used to create all objects needed to run the Azure Vote application. This manifest includes two Kubernetes deployments, one for the Azure Vote Python applications, and the other for a Redis instance. Also, two Kubernetes Services are created, an internal service for the Redis instance, and an external service for accessing the Azure Vote application from the internet.

Create a file named azure-vote.yaml and copy into it the following YAML code. If you are working in Azure Cloud Shell, this file can be created using vi or Nano as if working on a virtual or physical system.

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:
      containers:
      - name: azure-vote-back
        image: redis
        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:
      containers:
      - name: azure-vote-front
        image: microsoft/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

Use the kubectl apply command to run the application.

kubectl apply -f azure-vote.yaml

Output:

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

Test the application

As the application is run, a Kubernetes service is created that exposes the application front end to the internet. This process can take a few minutes to complete.

To monitor progress, use the kubectl get service command with the --watch argument.

kubectl get service azure-vote-front --watch

Initially the EXTERNAL-IP for the azure-vote-front service appears 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 has changed from pending to an IP address, use CTRL-C to stop the kubectl watch process.

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

Now browse to the external IP address to see the Azure Vote App.

Monitor health and logs

When the AKS cluster was created, 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.

To see current status, uptime, and resource usage for the Azure Vote pods, complete the following steps:

1. Open a web browser to the Azure portal https://portal.azure.com.
2. Select your resource group, such as myResourceGroup, then select your AKS cluster, such as myAKSCluster.
3. Under Monitoring on the left-hand side, choose Insights (preview)
4. Across the top, choose to + Add Filter
5. Select Namespace as the property, then choose <All but kube-system>
6. Choose to view the Containers.

The azure-vote-back and azure-vote-front containers are displayed, as shown in the following example:

To see logs for the azure-vote-front pod, select the View container logs link on the right-hand side of the containers list. These logs include the stdout and stderr streams from the container.

Delete cluster

When the cluster is no longer needed, use the az group delete command to remove the resource group, container service, and all related resources.

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

Get the code

In this quickstart, pre-created container images have been used to create a Kubernetes deployment. The related application code, Dockerfile, and Kubernetes manifest file are available on GitHub.

https://github.com/Azure-Samples/azure-voting-app-redis

Next steps

In this quickstart, you deployed a Kubernetes cluster and deployed a multi-container application to it.

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