Quickstart: Deploy an Azure Kubernetes Service (AKS) cluster
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 2.0.27 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 creating a resource group you are asked to specify a location, this is where your resources will live in Azure.
The following example creates a resource group named myResourceGroup in the eastus location.
az group create --name myResourceGroup --location eastus
Output:
{
"id": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/myResourceGroup",
"location": "eastus",
"managedBy": null,
"name": "myResourceGroup",
"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.
az aks create --resource-group myResourceGroup --name myAKSCluster --node-count 1 --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 myResourceGroup --name myAKSCluster
To verify the connection to your cluster, use the kubectl get command to return a list of the cluster nodes. Note that this can take a few minutes 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 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/v1beta1
kind: Deployment
metadata:
name: azure-vote-back
spec:
replicas: 1
template:
metadata:
labels:
app: azure-vote-back
spec:
containers:
- name: azure-vote-back
image: redis
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/v1beta1
kind: Deployment
metadata:
name: azure-vote-front
spec:
replicas: 1
template:
metadata:
labels:
app: azure-vote-front
spec:
containers:
- name: azure-vote-front
image: microsoft/azure-vote-front:v1
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.
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 myResourceGroup --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.