CI/CD Pipelines
CI/CD automates the path from a commit to running software. Continuous Integration builds and tests every change so problems surface in minutes, not at release time; Continuous Delivery/Deployment automates promoting that change through environments to production.
The payoff is speed and safety: small, frequent, automatically-verified changes are far less risky than big manual releases. A good pipeline is the backbone of modern software delivery.
TL;DR
- Automate everything: build, test, and deploy on every change.
- Keep CI fast (aim under ~10 minutes) with caching and parallelism.
- Manage secrets through the platform's secret store, never in code.
- Deploy progressively: blue-green, canary, or rolling — with rollback.
Quick Example
A GitHub Actions workflow that runs on every push and PR — checkout, install, test, build:
Core Concepts
CI vs CD
- Continuous Integration — merge frequently; build and test automatically on every commit for fast feedback.
- Continuous Delivery — every change is automatically prepared for release (deploy is a button).
- Continuous Deployment — every passing change deploys to production automatically.
Pipeline stages
Deployment Strategies
Best Practices
- Keep it fast — parallelize test suites, cache dependencies, skip unneeded steps.
- Manage secrets via the CI platform's encrypted store; inject as env vars at deploy time.
- Use a clear branch strategy (e.g.
main→ prod,staging→ staging,feature/*→ CI only). - Make every deploy reversible — automated rollback or a fast forward-fix.
Common Mistakes
Putting secrets in the repo
Slow pipelines nobody trusts
FAQ
What's the difference between continuous delivery and deployment?
Continuous delivery keeps every change releasable and automatically deployed to staging, but a human triggers the production release. Continuous deployment goes one step further — every change that passes the pipeline ships to production automatically, with no manual gate.
How fast should CI be?
As fast as you can make it while still catching real problems — under ~10 minutes is a common target for the core build/test loop. Slow pipelines erode trust and tempt people to bypass them. Parallelism, caching, and splitting slow tests into a separate stage help.
Which deployment strategy should I use?
Rolling updates are a fine default. Use blue-green when you need instant rollback and can afford duplicate environments. Use canary — gradually shifting traffic — when you want to limit blast radius and have monitoring to catch regressions early.
How should I handle secrets in CI?
Store them in the CI platform's encrypted secret store (GitHub Actions secrets, GitLab CI variables) and reference them at runtime. Never commit secrets to the repo, and scope them to the jobs/environments that need them. See Secrets Management.
Related Topics
- GitHub Actions — CI/CD in GitHub
- GitLab CI — GitLab's pipelines
- Deployment Strategies — Blue-green, canary, rolling
- Docker — Building images in pipelines
- Secrets Management — Handling CI credentials