AZ-400 Practice Question: Design and implement build and release pipelines
Which TWO of the following are true about multi-stage pipelines in Azure Pipelines?
⚠ Common exam trap
It's easy for candidates to assume stages must be sequential or share the same agent, but Azure Pipelines explicitly supports parallel execution and independent agent allocation per stage.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Stages can run in parallel if dependencies allow.
Azure Pipelines allows stages to run in parallel when their dependencies are configured appropriately. By default, stages run sequentially, but you can use the 'dependsOn' keyword to define dependencies, and if a stage has no dependencies on another, it can execute concurrently. This enables faster pipeline execution by running independent stages simultaneously.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Stages can run in parallel if dependencies allow.
Why this is correct
Stages in a multi-stage pipeline can execute in parallel when they have no dependencies on one another. You explicitly declare this by using `dependsOn: none` on the stage; otherwise, stages default to sequential execution based on implicit dependencies.
- ✗
Each stage can contain only one job.
Why it's wrong here
This statement is false because a single stage can contain one or more jobs. Defining multiple jobs inside a stage allows them to run in parallel (if no dependencies exist) or sequentially, each potentially on different agent pools or with different execution requirements.
- ✗
Each stage must run on the same agent.
Why it's wrong here
This is incorrect: each stage does not have to use the same agent. You can specify different agent pools (or even different compute targets like Microsoft-hosted vs self-hosted) per job within a stage, and stages themselves can use entirely different infrastructure based on their job definitions.
- ✗
Stages cannot have conditions.
Why it's wrong here
Stages absolutely can have conditions. For example, you can set a stage condition like `condition: succeeded()` to run only if all previous stages succeeded, or use custom expressions based on variables, parameters, or build artifacts to control whether a stage executes.
- ✓
They are defined in a single YAML file.
Why this is correct
Multi-stage pipelines are defined in a single YAML file (typically azure-pipelines.yml), using the `stages` keyword to structure the entire workflow from build through deployment. Because the definition is code, it lives in version control, allowing the pipeline to be reviewed, branched, and promoted exactly like application source code. This contrasts with older classic build/release definitions that were stored separately in the Azure DevOps service and could not be versioned as part of the repo.
Go deeper
Related to this question
Learn chapter
Introduction to DevOps and Azure DevOps
Key term
Pipeline
A pipeline is an automated series of steps that takes code from development to production, ensuring quality and speed.
Key term
Azure Pipelines
Azure Pipelines is a cloud-based CI/CD service from Microsoft that automatically builds, tests, and deploys code to any platform or cloud.
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