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Azure Kubernetes Service (AKS) is a managed Kubernetes service that lets you quickly deploy and manage clusters. In this quickstart, you learn how to:
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.
This quickstart assumes a basic understanding of Kubernetes concepts. For more information, see Kubernetes core concepts for Azure Kubernetes Service (AKS).
Use the Bash environment in Azure Cloud Shell. For more information, see Get started with Azure Cloud Shell.
If you prefer to run CLI reference commands locally, install the Azure CLI. If you're running on Windows or macOS, consider running Azure CLI in a Docker container. For more information, see How to run the Azure CLI in a Docker container.
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 other sign-in options, see Authenticate to Azure using Azure CLI.
When you're prompted, install the Azure CLI extension on first use. For more information about extensions, see Use and manage 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.
Define the following environment variables for use throughout this quickstart:
export RANDOM_ID="$(openssl rand -hex 3)"
export MY_RESOURCE_GROUP_NAME="myAKSResourceGroup$RANDOM_ID"
export REGION="westeurope"
export MY_AKS_CLUSTER_NAME="myAKSCluster$RANDOM_ID"
export MY_DNS_LABEL="mydnslabel$RANDOM_ID"
An Azure resource group is a logical group in which Azure resources are deployed and managed. When you create a resource group, you're prompted to specify a location. This location is the storage location of your resource group metadata and where your resources run in Azure if you don't specify another region during resource creation.
Create a resource group using the az group create command.
az group create --name $MY_RESOURCE_GROUP_NAME --location $REGION
Results:
{
"id": "/subscriptions/xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx/resourceGroups/myAKSResourceGroupxxxxxx",
"location": "eastus",
"managedBy": null,
"name": "testResourceGroup",
"properties": {
"provisioningState": "Succeeded"
},
"tags": null,
"type": "Microsoft.Resources/resourceGroups"
}
Create an AKS cluster using the az aks create command. The following example creates a cluster with one node and enables a system-assigned managed identity.
az aks create \
--resource-group $MY_RESOURCE_GROUP_NAME \
--name $MY_AKS_CLUSTER_NAME \
--node-count 1 \
--generate-ssh-keys
Note
When you create a new cluster, AKS automatically creates a second resource group to store the AKS resources. For more information, see Why are two resource groups created with AKS?
To manage a Kubernetes cluster, use the Kubernetes command-line client, kubectl. kubectl is already installed if you use Azure Cloud Shell. To install kubectl locally, use the az aks install-cli command.
Configure kubectl to connect to your Kubernetes cluster using the az aks get-credentials command. This command downloads credentials and configures the Kubernetes CLI to use them.
az aks get-credentials --resource-group $MY_RESOURCE_GROUP_NAME --name $MY_AKS_CLUSTER_NAME
Verify the connection to your cluster using the kubectl get command. This command returns a list of the cluster nodes.
kubectl get nodes
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:
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.
Create a file named aks-store-quickstart.yaml and copy in the following manifest:
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: rabbitmq
spec:
serviceName: rabbitmq
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
startupProbe:
httpGet:
path: /health
port: 3000
failureThreshold: 5
initialDelaySeconds: 20
periodSeconds: 10
readinessProbe:
httpGet:
path: /health
port: 3000
failureThreshold: 3
initialDelaySeconds: 3
periodSeconds: 5
livenessProbe:
httpGet:
path: /health
port: 3000
failureThreshold: 5
initialDelaySeconds: 3
periodSeconds: 3
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
env:
- name: AI_SERVICE_URL
value: "http://ai-service:5001/"
resources:
requests:
cpu: 1m
memory: 1Mi
limits:
cpu: 2m
memory: 20Mi
readinessProbe:
httpGet:
path: /health
port: 3002
failureThreshold: 3
initialDelaySeconds: 3
periodSeconds: 5
livenessProbe:
httpGet:
path: /health
port: 3002
failureThreshold: 5
initialDelaySeconds: 3
periodSeconds: 3
---
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
startupProbe:
httpGet:
path: /health
port: 8080
failureThreshold: 3
initialDelaySeconds: 5
periodSeconds: 5
readinessProbe:
httpGet:
path: /health
port: 8080
failureThreshold: 3
initialDelaySeconds: 3
periodSeconds: 3
livenessProbe:
httpGet:
path: /health
port: 8080
failureThreshold: 5
initialDelaySeconds: 3
periodSeconds: 3
---
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.
Deploy the application using the kubectl apply command and specify the name of your YAML manifest.
kubectl apply -f aks-store-quickstart.yaml
You can validate that the application is running by visiting the public IP address or the application URL.
Get the application URL using the following commands:
runtime="5 minutes"
endtime=$(date -ud "$runtime" +%s)
while [[ $(date -u +%s) -le $endtime ]]
do
STATUS=$(kubectl get pods -l app=store-front -o 'jsonpath={..status.conditions[?(@.type=="Ready")].status}')
echo $STATUS
if [ "$STATUS" == 'True' ]
then
export IP_ADDRESS=$(kubectl get service store-front --output 'jsonpath={..status.loadBalancer.ingress[0].ip}')
echo "Service IP Address: $IP_ADDRESS"
break
else
sleep 10
fi
done
curl $IP_ADDRESS
Results:
<!doctype html>
<html lang="">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width,initial-scale=1">
<link rel="icon" href="/favicon.ico">
<title>store-front</title>
<script defer="defer" src="/js/chunk-vendors.df69ae47.js"></script>
<script defer="defer" src="/js/app.7e8cfbb2.js"></script>
<link href="/css/app.a5dc49f6.css" rel="stylesheet">
</head>
<body>
<div id="app"></div>
</body>
</html>
echo "You can now visit your web server at $IP_ADDRESS"
If you don't plan on going through the AKS tutorial, clean up unnecessary resources to avoid Azure charges. You can remove the resource group, container service, and all related resources using the az group delete command.
Note
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.
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.
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