🚀 CI/CD Pipeline for Sample Application using Azure DevOps

Overview

This project demonstrates the setup of a Continuous Integration and Continuous Deployment (CI/CD) pipeline using Azure DevOps for a sample application. This pipeline automates the build, testing, and deployment stages, and deploys to either Azure App Service or Azure Kubernetes Service (AKS).

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Key Steps

🔧 Step 1: Build Pipeline Configuration

• Configure the CI pipeline in Azure DevOps to build the application, run unit tests, and create artifacts.

🚀 Step 2: Release Pipeline Configuration

• Set up the CD pipeline to deploy artifacts to Azure App Service or Azure Kubernetes Service based on chosen environment.

☁️ Step 3: Azure App Service or AKS Deployment

• Demonstrate the steps to deploy to either Azure App Service (for web applications) or AKS (for containerized applications).

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Getting Started

Prerequisites

• Azure DevOps account
• Azure subscription with permission to deploy to Azure resources
• Git repository containing the sample application code
• Basic knowledge of YAML for pipeline configuration

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Step-by-Step Guide

Step 1: Set Up CI Pipeline in Azure DevOps

1. Create a New Project in Azure DevOps:

   • Go to Azure DevOps, create a new project, and link it to your Git repository.

2. Define CI Pipeline (YAML):

   • Create a YAML file (azure-pipelines.yml) in the root directory of your repository for the CI configuration.
   • Below is a sample CI configuration:

     trigger:
       branches:
         include:
           - main
     
     pool:
       vmImage: 'ubuntu-latest'
     
     steps:
       - task: UseDotNet@2
         inputs:
           packageType: 'sdk'
           version: '6.x'
     
       - script: dotnet build
         displayName: 'Build Solution'
     
       - script: dotnet test --collect:"XPlat Code Coverage"
         displayName: 'Run Unit Tests'
     
       - task: PublishBuildArtifacts@1
         inputs:
           PathtoPublish: '$(Build.ArtifactStagingDirectory)'
           ArtifactName: 'drop'

3. Run the CI Pipeline:

   • Commit and push the azure-pipelines.yml file to trigger the build process, which will run the defined steps, including building and testing the application.

Step 2: Set Up CD Pipeline in Azure DevOps

1. Create a Release Pipeline:

   • In Azure DevOps, go to Pipelines > Releases and create a new release pipeline.
   • Choose the artifact generated by the CI pipeline as the source.

2. Define Stages for Deployment:

   • Azure App Service: Add an Azure App Service Deploy task to deploy the web application.
   • Azure Kubernetes Service (AKS): Add a Kubectl apply task to deploy containers to AKS.

3. Sample YAML for AKS Deployment:

   - stage: Deploy
     jobs:
       - deployment: DeployToAKS
         environment: 'aks'
         pool:
           vmImage: 'ubuntu-latest'
         steps:
           - task: Kubernetes@1
             inputs:
               connectionType: 'Azure Resource Manager'
               azureSubscription: '<Azure Subscription>'
               azureResourceGroup: '<Resource Group>'
               kubernetesCluster: '<AKS Cluster Name>'
               namespace: default
               command: apply
               arguments: '-f k8s/deployment.yaml'
   

4. Configure Release Triggers:

• Set up Continuous Deployment Trigger in the Release pipeline to automatically deploy artifacts from the build pipeline.

Deployment Options

Option 1: Deploy to Azure App Service

• Use the Azure App Service Deploy task in the release pipeline to deploy a web application to Azure App Service.

Option 2: Deploy to Azure Kubernetes Service (AKS)

• For containerized applications, configure the pipeline to deploy to AKS by applying the Kubernetes configuration files (e.g., deployment.yaml, service.yaml).

Summary of the Pipeline Workflow

1. Code Commit : Push code to the repository.

2. CI Pipeline : Triggers on each commit, building the application, running tests, and publishing artifacts.

3. CD Pipeline : Deploys the latest build to the chosen Azure service (App Service or AKS) automatically.

Contributing : Feel free to submit issues or pull requests to suggest improvements or additional features.

License : This project is licensed under the MIT License.