Automated deployments for Azure Kubernetes Service (AKS)

06/09/2025

Automated Deployments streamline the process of setting up a GitHub Action or Azure DevOps Pipeline, making it easy to create a continuous deployment pipeline for your application to Azure Kubernetes Service (AKS). Once connected, every new commit automatically triggers the pipeline, delivering updates to your application seamlessly. You can either bring your own deployment files for quick pipeline creation or generate Dockerfiles and Kubernetes manifests to containerize and deploy non-containerized applications with minimal effort.

Prerequisites

A GitHub account or an Azure DevOps organization.
An AKS cluster. If you don't have one, you can create one using the steps in Deploy an Azure Kubernetes Service (AKS) cluster.
An Azure Container Registry (ACR). If you don't have one, you can create one using the steps in Integrate Azure Container Registry (ACR) with an Azure Kubernetes Service (AKS) cluster.
An application to deploy.

Connect to source code repository

Create an automated deployment workflow and authorize it to connect to the desired source code repository.

In the Azure portal, navigate to your AKS cluster resource.
From the service menu, under Settings, select Automated deployments > Create.
Under Repository details, enter a name for the workflow, then select GitHub or ADO for your repository location.
Select Authorize access to connect to the desired repository.
Choose the Repository and Branch, and then select Next.

Choose the container image configuration

To get an application ready for Kubernetes, you need to build it into a container image and store it in a container registry. You use a Dockerfile to provide instructions on how to build the container image. If your source code repository doesn't already have a Dockerfile, Automated Deployments can generate one for you. Otherwise, you can use an existing Dockerfile.

Without an existing Dockerfile
With an existing Dockerfile

Use Automated Deployments to generate a Dockerfile for many languages and frameworks such as Go, C#, Node.js, Python, Java, Gradle, Clojure, PHP, Ruby, Erlang, Swift, and Rust. The language support is built on what's available in draft.sh.

Select Auto-containerize (generate Dockerfile) for the container configuration.
Select the location of where to save the generated Dockerfile in the repository.
Select the application environment from the list of supported languages and frameworks.
Enter the application port.
Provide the Dockerfile build context path.
Select an existing Azure Container Registry or create a new one. This registry is used to store the built application image.

If your code repository already has a Dockerfile, you can select it to be used to build the application image.

Select Existing Dockerfile for the container configuration.
Select the Dockerfile from your repository.
Enter the Dockerfile build context to pass the set of files and directories to the build process. These files are used to build the image, and they're included in the final image, unless they're ignored by a .dockerignore file.
Select an existing Azure Container Registry or create a new one. This registry is used to store the built application image.

Choose the Kubernetes manifest configuration

Note

The Generate Manifests option also supports advanced features like Service Connector integration, auto-generated Ingress resources, and more detailed, customizable Kubernetes manifest files.

An application running on Kubernetes consists of many Kubernetes primitive components. These components describe what container image to use, how many replicas to run, if there's a public IP required to expose the application, etc. For more information, see the official [Kubernetes documentation][kubernetes-documentation]. If your source code repository doesn't already have the basic Kubernetes manifests to deploy, Automated Deployments can generate them for you. Otherwise, you can use a set of existing manifests. You can also choose an existing Helm chart.

If your code repository already has a Dockerfile, you can select it to be used to build the application image.

Select Use existing Kubernetes manifest deployment files for the deployment options.
Select the Kubernetes manifest file or folder from your repository.
Select Next.

Use Automated Deployments to generate a set of basic Kubernetes manifest files to have your application up and running. At the moment, Automated Deployments creates a Deployment, a Service, and a ConfigMap.

The generated manifests are designed to apply recommendations of [deployment safeguards][deployment-safeguards], such as:

Automatically generating [liveness, readiness, and startup probes][kubernetes-probes].
Preferring [pod anti-affinity][pod-anti-affinity] and [topology spread constraints][topology-spread-constraints] that spread replicas onto different nodes for improved resiliency.
Enforcing the RuntimeDefault [secure computing profile][seccomp-profile] which establishes an extra layer of protection against common system call vulnerabilities exploited by malicious actors.
Dropping all Linux capabilities and only allowing a limited set following the baseline [Kubernetes Pod Security Standards][kubernetes-pod-security-standards].

Generated Kubernetes manifests also support the addition of an Ingress and Service Connector. These optional integrations will be covered below.

To generate Kubernetes manifests:

Select Generate application deployment files for the deployment options.
Enter the application port. This port is used on the generated Service.
Select the location of where to save the generated Kubernetes manifests in the repository.
(Optional) Edit the Application and configuration or Service values in your manifest file by selecting Change.
1. If you don't want to use the defaults that AKS recommends, you can change various values of the manifest file, such as the:
  - Memory/CPU requests
  - Memory/CPU limits
  - TCP Readiness and Startup Probes
  - Minimum/Maximum scaling replicas for HPA
  - Memory/CPU utilization for HPA
  - Loadbalancer Port/Target Port
Select Next.

(Optional) Add environment variables

Define environment variables for a container in Kubernetes by specifying name-value pairs. Environment variables are important as they help enable easier management of settings, secure handling of sensitive information, and flexibility across environments.

Review configuration and deploy

Review the configuration for the application, and Kubernetes manifests, then select Deploy. A pull request (PR) will be generated against the repository that you selected, so don't navigate away from deployment page.

Review and merge pull request

When the deployment succeeds, select View pull request to view the details of the generated pull request on your code repository.

Review the changes under Files changed and make any desired edits.
Select Merge pull request to merge the changes into your code repository.

Merging the change runs the GitHub Actions workflow that builds your application into a container image, stores it in Azure Container Registry, and deploys it to the cluster.

Check the deployed resources

After the pipeline is completed, you can review the created Kubernetes Service in the Azure portal by selecting Services and ingresses under the Kubernetes resources section of the service menu.

Selecting the External IP should open up a new browser page with the running application.

Delete resources

Once you're done with your cluster, use the following steps to delete it to avoid incurring Azure charges:

In the Azure portal, navigate to Automated deployments
Select ... on the pipeline of your choice.
Select Delete.