CI builds and tests every commit automatically; CD deploys tested builds to staging and production the same way every time. Set one up by putting everything in version control, adding automated builds and tests, adding security checks, automating deployment with rollback, and monitoring. Measure it with the DORA metrics.
CI and CD, defined
GitHub's documentation describes continuous integration as a practice of committing code frequently to a shared repository, where changes are built and tested automatically, which catches errors early and cuts debugging time.
It describes continuous deployment as using automation to publish and deploy software updates, with the code built and tested before it is deployed. Continuous delivery is the same idea with a human approval before production; continuous deployment releases automatically once all checks pass.
The stages of a pipeline
Most pipelines follow the same shape:
- Commit: a developer pushes a change; the pipeline starts.
- Build: the code is compiled or packaged, the same way every time.
- Test: fast component and integration tests run; a failure stops the pipeline.
- Security checks: dependencies and configuration are scanned.
- Deploy to staging: the build goes to a production-like environment.
- Further tests: regression, end-to-end and smoke tests against staging.
- Deploy to production: automatically or after approval, with a rollback ready.
- Monitor: errors and performance are watched after release.
How to set one up
Set it up in this order:
- Version control: code, configuration and deployment scripts in one repository, with branch protection and reviews.
- A pipeline tool: most code hosts and cloud platforms include one; choose what your team can maintain.
- Automated build: one command builds the application from a clean checkout.
- Automated tests: start with fast tests on every commit; add the regression suite before production. ISTQB defines regression testing as testing after modification.
- Secrets: stored in the tool's secret store, never in the repository.
- Environments: staging that matches production as closely as practical.
- Deployment and rollback: scripted deployment, and a tested way to return to the previous version.
- Monitoring: alerts on errors after each release.
Security in the pipeline
A pipeline is also a route into production, so protect it. Scan dependencies on every build for known vulnerabilities, limit who can change the pipeline and approve production releases, and keep secrets out of logs. The OWASP Top 10 2025 lists software supply chain failures as A03, a risk the pipeline both creates and can check.
Measuring the pipeline
The DORA metrics (guide last updated January 2026) fit a pipeline closely: change lead time (commit to production), deployment frequency, change fail rate, failed deployment recovery time and deployment rework rate. A good pipeline shortens lead time and recovery time while keeping the fail rate down.
Common pipeline mistakes
The faults we see most:
- Slow pipelines that developers bypass. Keep commit checks to minutes.
- Flaky tests that fail at random, so failures get ignored.
- Staging unlike production, so problems appear only after release.
- No rollback, so every failed release becomes an emergency fix.
- Secrets in the repository or printed in logs.
Conclusion
A CI/CD pipeline builds and tests every commit (continuous integration) and deploys tested builds the same way every time (continuous delivery or deployment). Set one up from version control, automated builds and tests, security checks, staging, scripted deployment with rollback and monitoring, and measure it with the DORA metrics.
PromotEdge International is an international strategy, technology, marketing and design company, and our delivery team is in India. Our DevOps team sets up CI/CD pipelines with tests, security checks and rollback, in your own cloud accounts, on the tools your team uses.
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