Bridging the Gap: Integrating Azure DevOps with GitHub for Automated Testing

Maintaining robust unit tests is crucial for ensuring code quality. This article explores integrating Azure DevOps with your GitHub repository to establish an automated testing pipeline. We'll create a pipeline that triggers upon code changes in GitHub, runs unit tests, and enforces successful test execution before allowing deployments.

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1. Building the Bridge: Connecting Azure DevOps and GitHub

• Navigate to your Azure DevOps project and access the "Project settings" by clicking on the gear icon in the top right corner.
• Under "Service connections," click on "Create connection."

Connecting to GitHub:

• Search for "GitHub" and choose "GitHub" (generic).
• Provide a descriptive name for the connection (e.g., "GitHubConnection").
• Click "Authorize" to grant Azure DevOps access to your GitHub account.
• Choose the desired level of access (typically "Full control" for pipeline execution).
• Click "Save" to establish the connection between Azure DevOps and your GitHub account.

2. Creating the Pipeline: Defining the Testing Workflow

• Navigate to "Pipelines" within your project and click "Create pipeline."
• Choose "Starter pipeline" and select "GitHub" as the repository source.

Connecting Your GitHub Repository:

• Authorize Azure DevOps to access your GitHub repositories.
• Select the repository containing your codebase.
• Optionally, choose a specific branch to monitor for changes (e.g., "main" for production deployments).

Understanding the Pipeline Stages:

The default starter pipeline provides a "Get sources" stage that retrieves code from the repository. We'll modify this stage and add additional ones for testing.

3. Configuring the Pipeline Tasks: Running Unit Tests

Modifying the "Get sources" stage:

• Click on the "Get sources" stage and navigate to the "Tasks" tab.
• Under "Version spec," choose "Branch" and specify the branch you want to monitor for changes (e.g., "main").

Adding the Test Stage:

• Click the "+" icon next to the "Get sources" stage and choose a task relevant to your chosen unit testing framework.
• Common options include:
  • xUnit: Search for "dotnet test" and configure it to execute your xUnit test project(s).
  • MSTest: Search for "vstest" and configure it to target your MSTest test assemblies.

Task Configuration:

Configure the chosen task based on your specific test project locations and execution requirements. Ensure the task points to the necessary test files within your codebase.

Conditional Deployment:

• Navigate to the pipeline editor and click on the ellipsis (...) next to the "Get sources" stage.
• Choose "Add a stage condition."
• Under "Condition type," select "Always run."
• Under "Conditional execution," choose "Run this stage only if the condition succeeds."

Linking Stages with Test Results:

• Configure the condition to reference the outcome of your unit testing task. For example, for an xUnit task, you can use the condition "succeeded()." This ensures the deployment stage only runs if all unit tests pass.

Adding the Deployment Stage (Optional):

• If you already have a deployment pipeline set up in Azure DevOps, you don't need to create a new one here. You can link this testing pipeline to your existing deployment pipeline.
• If you want to include deployment within this pipeline, follow the steps outlined in similar articles to configure an additional stage for deployment to your chosen environment (e.g., Azure App Service).

4. Continuous Testing in Action: Automated Quality Checks

With the pipeline configured, the following workflow emerges upon a code push to the specified branch in your GitHub repository:

1. The push triggers the Azure DevOps pipeline execution.
2. The pipeline retrieves the code from your GitHub repository.
3. The testing stage executes your unit tests.
4. If all tests pass, the conditional stage allows deployment to proceed (if a deployment stage is included).
5. If any tests fail, the pipeline execution halts, and the deployment is blocked, preventing potentially broken code from reaching production.

This integration establishes automated unit testing within your development workflow, promoting code quality and ensuring deployments only occur with passing test results.

Additional Considerations:

• You can configure pipeline notifications to alert developers of test results (success or failure) upon code pushes.
• Explore advanced testing strategies like code coverage analysis to gain further insights into the effectiveness of your unit test suite.

By leveraging Azure DevOps and GitHub integration, you create a robust automated testing pipeline, safeguarding the quality and stability of your code throughout the development lifecycle.