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CI/CD Pipeline Examples

These CI/CD examples show how different teams structure build, test, approval, deployment, and monitoring stages. Use them as references when designing or documenting your own delivery workflow.

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CI/CD Pipeline Examples

Real examples

Kubernetes microservice deployment

Who uses it: Platform engineer standardizing service delivery

Trigger: merge to main
Build: compile service and run static checks
Test: unit tests, contract tests, e2e smoke tests
Package: Docker build → image registry
Deploy: Helm/Kustomize to staging, then production
Monitor: Grafana alerts, error budget burn, rollback decision

Why this works: Separating image creation from deployment clarifies which stage produces the artifact and which stage promotes it. That separation is essential for reproducible releases.

Frontend web app pipeline

Who uses it: Frontend team deploying a Next.js or React application

Pull request: lint, type-check, unit tests
Preview deployment for every PR
Merge to main: production build + bundle size check
Deploy to CDN/edge platform
Post-deploy: Lighthouse smoke test and error monitoring

Why this works: Frontend pipelines often need preview environments earlier than backend pipelines. Showing preview deployment as a first-class stage helps product and design teams review changes before merge.

Mobile app release pipeline

Who uses it: Mobile team coordinating store releases

Commit → Build iOS/Android artifacts
Automated tests: unit, UI, screenshot regression
Internal distribution: TestFlight / Play Internal Testing
Manual QA approval gate
Store submission and phased rollout
Crash monitoring and rollback/hotfix branch

Why this works: Mobile releases have external store review and phased rollout constraints. A diagram makes those constraints visible so stakeholders do not treat mobile deployment like a web deploy.

Monorepo CI pipeline

Who uses it: Engineering manager reducing CI time in a large repository

Change detection: identify affected packages
Parallel build and test jobs by package
Shared cache for dependencies and artifacts
Integration tests only for affected service graph
Deploy changed services independently

Why this works: The key decision in a monorepo pipeline is affected-project detection. Visualizing it prevents every change from triggering every job, which keeps CI fast as the repository grows.

Tips for better study mind maps

  • Show the artifact handoff clearly: source code becomes a build artifact, then an image, then a deployment.
  • Mark manual gates explicitly so teams can decide which ones are still necessary.
  • Include monitoring after deployment; a pipeline that ends at deploy misses the operational feedback loop.
  • Use labels on arrows for commands or tools such as npm, Docker, Helm, kubectl, or Terraform.

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Go back to the template, swap in your own topics, and keep the same structure if it fits your class or project.

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Use this CI/CD pipeline template