Cloud DevOps Pipelines (AWS CodePipeline, Azure Pipelines) Questions and Answers for Viva

Answer-1: A DevOps pipeline is an automated process that helps in continuous integration, delivery, and deployment of software.

Answer-2: AWS CodePipeline is a fully managed continuous delivery service that helps automate release pipelines for fast and reliable application and infrastructure updates.

Answer-3: Azure Pipelines is a cloud service that supports continuous integration and continuous delivery (CI/CD) for building, testing, and deploying code projects.

Answer-4: Source, build, test, deploy, and release.

Answer-5: It integrates seamlessly with services like CodeCommit, CodeBuild, CodeDeploy, Lambda, and CloudFormation.

Answer-6: Yes, it supports multiple languages such as Java, .NET, Node.js, Python, and platforms like Linux, Windows, and macOS.

Answer-7: CI is the practice of automatically integrating code changes from multiple contributors into a shared repository several times a day.

Answer-8: CD is the practice of automatically deploying every code change to a testing or production environment after the build stage.

Answer-9: It automates the build, test, and deploy phases so changes can be delivered to production automatically.

Answer-10: Artifacts are the files or packages produced by the build process that are used in subsequent stages like testing or deployment.

Answer-11: Pipelines can be defined using the AWS Management Console, CLI, SDKs, or CloudFormation templates.

Answer-12: Azure Pipelines allows running multiple jobs in parallel to speed up build and deployment processes.

Answer-13: CodeBuild compiles source code, runs tests, and produces artifacts for deployment.

Answer-14: Azure Pipelines includes built-in tasks to deploy containers to Kubernetes clusters using Helm charts or kubectl commands.

Answer-15: CodePipeline orchestrates the entire release process, while CodeDeploy specifically handles deployment of applications to instances.

Answer-16: Yes, it supports integration with Jenkins, GitHub, GitLab, and other tools using webhooks and custom actions.

Answer-17: By using service connections, role-based access control, and secure variable storage.

Answer-18: It is a manual approval step requiring human intervention before the pipeline continues.

Answer-19: YAML pipelines are pipelines defined as code using YAML syntax, allowing versioning and easier maintenance.

Answer-20: You can configure pipelines with automated rollback actions or manual intervention for failures.

Answer-21: Triggers automatically start pipelines on events such as code commits, pull requests, or schedule.

Answer-22: Through the AWS Management Console, CloudWatch metrics, and event notifications.

Answer-23: A stage is a logical unit of work in a pipeline, such as build, test, or deploy.

Answer-24: It allows defining multiple deployment stages with approvals, gates, and environment configurations.

Answer-25: Tracking and managing different versions of build artifacts to ensure consistent deployments.

Answer-26: Yes, Azure Pipelines supports hybrid deployment targets.

Answer-27: Lambda can be used for custom actions or to automate tasks within the pipeline.

Answer-28: Using Azure Key Vault integration or pipeline secret variables.

Answer-29: A build agent is a machine or container that runs the pipeline jobs.

Answer-30: By configuring deployment actions with strategies like blue/green, canary, or rolling updates.

Answer-31: IaC enables automated, repeatable, and version-controlled infrastructure provisioning.

Answer-32: It integrates with various testing frameworks and allows automated test execution during the pipeline.

Answer-33: Manual or automated gates that control deployment to specific environments.

Answer-34: Yes, it can deploy AWS Lambda functions and serverless applications using CloudFormation.

Answer-35: Hosted agents are managed by Microsoft, while self-hosted agents run on your own infrastructure.

Answer-36: By reviewing logs, notifications, and triggering rollback or retry mechanisms.

Answer-37: Variables that store values used during the pipeline execution, which can be secret or non-secret.

Answer-38: By parallelizing actions and optimizing build and test processes.

Answer-39: It pulls source code from repositories to start the pipeline execution.

Answer-40: Through service connections that allow pipelines to trigger on GitHub repository changes.

Answer-41: Yes, multiple pipeline executions can run concurrently for different branches or releases.

Answer-42: It supports building, testing, and deploying Docker containers.

Answer-43: To pause the pipeline and wait for human approval before continuing.

Answer-44: By redeploying previous artifact versions or using deployment strategies that support rollback.

Answer-45: AWS CloudWatch, AWS CloudTrail, and third-party monitoring services.

Answer-46: Continuous delivery prepares code for release, while continuous deployment automatically releases every change to production.

Answer-47: By using YAML pipeline templates and branch-specific triggers.

Answer-48: It is priced based on the number of active pipelines per month.

Answer-49: Yes, it integrates tightly with Azure Repos, Boards, Artifacts, and Test Plans.

Answer-50: By enabling logging, version control, access controls, and audit trails.