CI/CD pipeline setup is one of those things that seems intimidating until you actually do it. Whether you are automating a single app or building a delivery flow for dozens of services, good pipeline design saves hours and reduces firefights. This article breaks down continuous integration and continuous delivery pipeline setup into practical steps, tool choices, and real-world tips so you can ship safer and faster.
Why CI/CD pipeline setup matters
Teams adopting DevOps want faster feedback and fewer manual steps. A well-built CI/CD pipeline gives you exactly that: consistent builds, automated tests, and reliable deployments. From what I’ve seen, teams that invest in pipeline automation recover from failures faster and deploy more often.
Core concepts: CI vs CD
Short version: continuous integration focuses on merging changes and running tests. Continuous delivery (and continuous deployment) automates the path from a green build to production.
Key stages in a typical pipeline
- Source control (branching strategy)
- Build and compile
- Automated unit and integration tests
- Static analysis and linting
- Containerization or artifact publishing
- Staging deploy and acceptance tests
- Production promotion and monitoring
Getting started: a step-by-step CI/CD pipeline setup
I’ll layout a basic 7-step setup that works for many teams. Adapt as you grow.
1. Choose source control and branching
Pick Git-based hosting (GitHub, GitLab, Bitbucket). Use a branching model you can enforce with pull requests and protected branches. I usually recommend trunk-based or small-feature branches with short lifetimes.
2. Pick a CI/CD engine
Popular choices: Jenkins, GitHub Actions, GitLab CI, CircleCI. If you want cloud-native simplicity, GitHub Actions or GitLab CI are great. If you need heavy customization, Jenkins still wins.
3. Build automation
Keep builds deterministic. Cache dependencies where possible. Use containers (Docker) to ensure the same environment locally and in CI.
4. Automated tests and quality gates
Run unit tests on every push. Run integration and e2e tests on PRs and merges to protected branches. Add linting and code coverage checks as blocking gates.
5. Artifact management and containerization
Publish artifacts to a registry or package repo. For containerized apps, push images to Docker Hub or a private registry. Tag images with build numbers and commit ids.
6. Deployment stages
Create separate pipelines or jobs for staging and production. Use feature flags or canary releases for safer rollouts. Automate rollbacks based on health checks.
7. Monitoring and feedback loop
Integrate observability: logs, metrics, and alerts. Feed failures back to developers through the pipeline so fixes are fast.
Tool comparison table
| Tool | Strength | Best for | Notes |
|---|---|---|---|
| Jenkins | Highly customizable | Complex, on-prem setups | Large plugin ecosystem; needs maintenance |
| GitHub Actions | Integrated with GitHub | Cloud-native, simple workflows | Great for open-source and GitHub-centric teams |
| GitLab CI | All-in-one platform | End-to-end pipelines with visibility | Good for monorepos and integrated artifact registry |
Best practices and common pitfalls
- Keep pipelines fast. Slow pipelines kill adoption. Parallelize where possible.
- Make pipelines declarative. Store pipeline configs in code so they’re versioned.
- Use secrets management. Do not hardcode credentials.
- Start small. Automate the most valuable steps first, then expand.
- Avoid long-running mutable environments; prefer ephemeral test environments.
Real-world example: small microservice pipeline
Imagine a Node.js service. I’d use GitHub, GitHub Actions for CI, Docker to build an image, push to a registry, deploy to Kubernetes. Pipeline jobs: install, test, build image, scan image, push image, deploy to staging, run smoke tests, promote to production with manual approval.
Security and compliance
Scan dependencies and container images. Run SAST for critical repos. Use role-based access for pipeline triggers and protect production branches with approvals.
Scaling pipelines across teams
When multiple teams share infrastructure, centralize shared steps in reusable pipeline templates or actions. Document standards and add templates for common service types.
Cost and maintenance considerations
CI minutes and runner maintenance cost money. Optimize by using self-hosted runners for heavy builds, and cache aggressively. Track flaky tests and address them quickly.
Quick checklist before you ship
- Protected branches and PR reviews
- Automated unit and integration tests
- Artifact or image registry with immutable tags
- Staging deploy and smoke tests
- Monitoring and rollback plan
Final thoughts
CI/CD pipeline setup is not a one-time project. It evolves as your codebase grows. Start with a reliable, small pipeline and iterate. With the right tools and discipline, you’ll reduce manual toil and increase deploy confidence.