Automating Docker Image Deployment to Azure Container Registry with GitHub Actions

In modern software development workflows, automation is key to streamlining processes and increasing productivity. One common task is building Docker images and deploying them to container registries for seamless integration and deployment. In this guide, we’ll explore how to automate this process using GitHub Actions, a powerful continuous integration and continuous deployment (CI/CD) platform.

Overview

Our goal is to create a GitHub Actions pipeline that builds a Docker image and pushes it to an Azure Container Registry. This pipeline will be triggered on every push to the repository, ensuring that our Docker image is always up to date with the latest changes in our codebase.

Setting Up the Repository

First, let’s ensure our repository is properly set up. For demonstration purposes, I’ve created a sample repository named dockerimge_cloud_registry, which contains the necessary files for our Docker image and pipeline. You can find the repository at GitHub – littleworks-inc/dockerimge_cloud_registry.

GitHub Actions Pipeline

Our GitHub Actions pipeline is defined in a YAML file named azure-pipeline.yml. Let’s break down the key components of this pipeline:

# azure-pipeline.yml

name: Azure Build and publish a Docker image
on:
  push:
    branches:
      - '*'

env:
    container_registry: devtoolhub
    IMAGE_NAME: azurecli

jobs:
  build:
    name: Azure Build & push docker image
    runs-on: ubuntu-latest

    steps:
      # Checkout the source code
      - name: Checkout
        uses: actions/checkout@v3

      # Debugging output
      - name: Debug
        run: |
          echo "github.ref -> {{ github.ref }}"

      # Lint Dockerfile using Hadolint
      - name: lint Action for Azure
        uses: hadolint/[email protected]
        with:
            dockerfile: azure/Dockerfile
            ignore: DL3018,SC2046,DL4006
            failure-threshold: warning
            no-color : false
            no-fail: true

      # Log in to Azure Container Registry
      - name: Azure Credentials 
        uses: azure/docker-login@v1
        with:
          login-server: ${{ env.container_registry }}.azurecr.io
          username: ${{ secrets.AZURE_CLIENT_ID }}
          password: ${{ secrets.ARM_CLIENT_SECRET }}

      # Build Docker image
      - name: Build Docker image
        run: docker build . --file "azure/Dockerfile" --tag ${{ env.container_registry }}.azurecr.io/${{ env.IMAGE_NAME }}

      # Push Docker image to Azure Container Registry
      - name: Push Docker image
        run: docker push ${{ env.container_registry }}.azurecr.io/${{ env.IMAGE_NAME }}

      # Run Trivy vulnerability scanner
      - name: Run Trivy vulnerability scanner
        id: docker-scan
        uses: aquasecurity/trivy-action@master
        with:
          image-ref: '${{ env.container_registry }}.azurecr.io/${{ env.IMAGE_NAME }}:latest'
          format: 'table'
          exit-code: '0'
          ignore-unfixed: true
          vuln-type: 'os,library'
          severity: 'UNKNOWN,LOW,MEDIUM,HIGH,CRITICAL'

Explanation

Trigger: The pipeline is triggered on every push to any branch.
Environment Variables: Defines variables such as the container registry name and image name.
Secrets: GitHub repository secrets are used to securely store sensitive information such as Azure credentials.
AZURE_CLIENT_ID: Azure client ID for authentication.
ARM_CLIENT_SECRET: Azure client secret for authentication.
Steps: Each step in the pipeline performs a specific task, such as linting the Dockerfile, logging in to Azure Container Registry, building and pushing the Docker image, and scanning it for vulnerabilities using Trivy.

Conclusion

With this GitHub Actions pipeline in place, we’ve automated the process of building and deploying Docker images to Azure Container Registry. This not only saves time but also ensures consistency and reliability in our deployment process. Feel free to customize this pipeline according to your project requirements and scale it as needed.

For the complete pipeline code and more details, visit GitHub – littleworks-inc/dockerimge_cloud_registry.

Stay tuned for more automation tips and tricks!

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