AZ-400 Designing and Implementing Microsoft DevOps Solutions Exam

Select a deployment automation solution, including GitHub Actions and Azure Pipelines

Automating builds and releases is essential for modern software teams. Deployment automation uses pipelines to compile code, run tests, and deploy applications. GitHub Actions and Azure Pipelines are two popular choices that help teams implement continuous integration and continuous delivery.

GitHub Actions is tightly integrated with GitHub repositories. It offers a marketplace of prebuilt workflows and the option to run on hosted runners or self-hosted runners. This makes it easy to build, test, and deploy code changes without leaving the GitHub interface.

Azure Pipelines works across GitHub, Azure Repos, and other Git services. It provides advanced features like parallel jobs, gated approvals, and multi-platform support. When choosing between these tools, consider factors such as cost, security, and team familiarity.

Key factors to evaluate include:

• Cost: Compare usage-based charges for hosted runners.
• Tool selection: Review available extensions and tasks.
• Integration: Check compatibility with your version control and cloud platforms.

Design and implement a GitHub runner or Azure DevOps agent infrastructure, including cost, tool selection, licenses, connectivity, and maintainability

A runner or agent is the compute environment where your pipeline jobs execute. Self-hosted runners and self-hosted agents let you control the hardware, OS, and software dependencies. This can reduce costs and meet specific compliance needs.

When planning your infrastructure, assess the following:

• Cost: Upfront hardware versus per-job hosted fees
• Tool selection: Required SDKs, build tools, and testing frameworks
• Licenses: Operating system and third-party software costs
• Connectivity: Network access to repositories and deployment targets

Regular maintenance ensures that runners stay updated and secure. Automate OS patches, toolchain updates, and health checks. Implement monitoring to verify runner availability and job success rates.

Design and implement integration between GitHub repositories and Azure Pipelines

Integrating GitHub with Azure Pipelines streamlines your CI/CD workflow. A service connection links your GitHub repository to Azure DevOps, enabling Azure Pipelines to fetch code and report status.

To set up integration:

1. Create a GitHub service connection in Azure DevOps.
2. Grant permissions for Azure Pipelines to access required repositories.
3. Configure branch policies to enforce code review and build validation.

This integration supports pull request and commit-based triggers. It also provides detailed build reports directly in GitHub, making it easy for developers to see results and address failures.

Develop and implement pipeline trigger rules

Pipeline triggers decide when a run should start. Trigger rules can be based on commits, pull requests, schedules, or manual interventions. Properly configured triggers help avoid unnecessary jobs and speed up feedback loops.

Common trigger types include:

• CI triggers: Launch builds on every commit to specified branches.
• PR triggers: Build and test code before merging a pull request.
• Scheduled triggers: Run jobs at fixed intervals, such as nightly tests.
• Path filters: Only trigger when changes occur in certain files or folders.

Define triggers in YAML or via the Azure DevOps UI. Use underlines to highlight important branches and critical paths. Testing trigger rules in a sandbox helps ensure expected behavior before applying to production pipelines.

Develop pipelines by using YAML

Using YAML for pipelines brings infrastructure as code practices to CI/CD. YAML files live alongside your code, making pipeline changes reviewable and versionable. This approach ensures consistency and reusability across projects.

Key YAML concepts include:

• Stages: Group related jobs, such as build, test, and deploy.
• Jobs: Specify the tasks to run on an agent or runner.
• Steps: Define individual commands or tasks within a job.
• Templates: Reuse common pipeline fragments across multiple YAML files.
• Variables: Store values for reuse, with support for variable groups.

Indentation and schema validation are crucial to avoid errors. Keep YAML files clear by using descriptive names, comments, and separating complex logic into templates. This makes pipelines easier to maintain and update as requirements evolve.

Conclusion

In the Design and implement pipelines section, we explored how to choose between GitHub Actions and Azure Pipelines based on cost, integration, and feature needs. We covered setting up and maintaining self-hosted runners or agents, ensuring the right tools, licenses, and connectivity. Integration between GitHub and Azure Pipelines was shown to streamline workflows with service connections and branch policies. We then examined how pipeline trigger rules can be fine-tuned using CI, PR, scheduled, and path-based triggers. Finally, we highlighted the benefits of defining pipelines in YAML, using templates, stages, and variables to achieve infrastructure as code. These practices build a robust and maintainable pipeline strategy for Azure DevOps solutions.