Deploying Containerized Application with Azure Kubernetes Service (AKS)
Azure Kubernetes Service (AKS) allows you to deploy, manage, and scale containerized applications using Kubernetes. Follow these steps to deploy a containerized application to AKS.
Prerequisites
Before you begin, make sure you have the following:
- An Azure account with the necessary permissions to create an AKS cluster.
- Azure CLI installed on your local machine.
- Docker installed on your local machine to build and push the container image.
Step 1: Create an AKS Cluster
Use Azure CLI to create an AKS cluster. Replace <resource-group> and <cluster-name> with your preferred values.
az group create --name <resource-group> --location <location>
az aks create --resource-group <resource-group> --name <cluster-name> --node-count 2 --enable-addons monitoring --generate-ssh-keys
Step 2: Connect to the AKS Cluster
Once the cluster is created, run the following command to configure kubectl to connect to the AKS cluster.
az aks get-credentials --resource-group <resource-group> --name <cluster-name>
Step 3: Build and Push the Container Image
Navigate to your application’s directory and build the Docker image.
docker build -t <image-name> .
Then, push the image to Azure Container Registry (ACR).
Step 4: Deploy the Application to AKS
Create a Kubernetes deployment and a service to expose the application.
kubectl create deployment <deployment-name> --image=<image-name>
kubectl expose deployment <deployment-name> --type=LoadBalancer --port=80
Step 5: Access the Application
Retrieve the public IP address of the Load Balancer to access the deployed application.
kubectl get service <deployment-name>
That’s it! Your containerized application is now deployed and running on Azure Kubernetes Service.
Conclusion
In this guide, we went through the process of deploying a containerized application to Azure Kubernetes Service using Azure CLI and Kubernetes commands. AKS provides a scalable and managed Kubernetes service, making it an ideal choice for running containerized workloads in the cloud.
For more advanced management and customization options, refer to the official Azure Kubernetes Service documentation.