Azure DevOps Multi-Stage Pipelines are a feature that allows you to define complex, multi-stage CI/CD (Continuous Integration/Continuous Deployment) workflows as code using YAML. These pipelines enable you to automate the building, testing, and deployment of your applications through a series of stages and jobs. Here are the key aspects of Azure DevOps Multi-Stage Pipelines:

1. Stages: Multi-Stage Pipelines are organized into stages, which represent different phases of your CI/CD process. Each stage can have one or more jobs. Common stages include “Build,” “Test,” “Dev,” “Staging,” and “Production.”

2. Jobs: A stage consists of one or more jobs. A job represents a collection of steps that run on the same agent. Jobs within a stage can be configured to run concurrently or sequentially.

3. Parallel and Sequential Execution: You can define whether stages and jobs should run in parallel or sequentially. Parallel execution allows multiple stages or jobs to run concurrently, which can speed up the pipeline.

4. Artifacts: Artifacts generated in one stage can be passed to subsequent stages. This allows you to create a smooth flow of code and resources through the pipeline.

5. Environment Variables: You can define environment-specific variables and secrets for each stage, allowing you to customize the behavior of your pipeline at each stage without modifying the code.

6. Deployment Targets: In deployment stages (e.g., “Staging” and “Production”), you specify the target environment where your application or service will be deployed. This can include Azure resources like Azure App Service, Kubernetes clusters, virtual machines, or other platforms.

7. Manual Intervention: Stages can include manual approval gates before proceeding to the next stage. This is useful for ensuring that deployments to critical environments like production are validated by team members.

8. Retries and Conditions: You can configure stages and jobs to retry failed tasks or set conditions that determine whether a stage or job should run based on specific criteria (e.g., trigger on a specific branch).

9. Post-Deployment Actions: After a deployment stage, you can configure post-deployment actions such as running tests, sending notifications, or cleaning up resources.

10. Logging and Monitoring: Azure DevOps provides extensive logging and monitoring capabilities for each stage and job, allowing you to track the progress and status of each step.

11. Customization: Multi-Stage Pipelines are highly customizable. You can define custom conditions, scripts, and steps to tailor each stage and job to your specific needs.

12. Artifact Retention: Azure DevOps allows you to specify how long artifacts generated in a stage should be retained, helping to manage storage costs.

Example Usage: Here’s a simplified example of a multi-stage Azure DevOps YAML pipeline for a .NET application:

In this example, the pipeline has stages for building, testing, and deploying the application to the development environment. Additional stages can be added for staging and production deployments. Each stage is defined in YAML, making it easy to version, maintain, and automate your CI/CD process.