What Is CI/CD? Continuous Integration and Delivery Explained

Picture a team that releases software once a quarter. For weeks before each release, everyone merges their work, the build breaks, testers find dozens of bugs at once and the launch slips. When it finally ships, nobody can tell which of the 400 changes caused the new crash.

CI/CD exists to end that cycle. Instead of big, risky releases, the team ships small changes through an automated path that builds, tests and deploys them the same way every time. This guide explains what CI/CD means, walks one code change from commit to production and shows how to tell if your pipeline is actually helping.

CI/CD in plain English

CI/CD combines 2 or 3 related practices.

Continuous integration (CI). Developers merge their work into the shared main branch often, at least daily according to DORA’s guidance, and every merge triggers an automated build and tests. Problems surface within minutes, while the change is still fresh in the developer’s mind.

Continuous delivery (CD). Every change that passes the pipeline is automatically prepared for release, so the software is always in a deployable state. AWS describes the key difference from the next practice as the presence of a manual approval before production.

Continuous deployment (also CD). Every change that passes all automated checks goes to production automatically, with no human approval step.

If you want the details on that last distinction, our guide to continuous delivery vs continuous deployment covers when each one fits.

Following one code change from commit to production

Here is the path a single change takes in a typical CI/CD setup for a web application.

Developer CI (every push/PR) CD (after merge to main) --------- ------------------ ------------------------ Write code | Commit + push --> [1] Checkout code Open pull | request [2] Build / compile | [3] Unit tests + lint | [4] Security scans | Review + merge ------------------> [5] Build release artifact | [6] Deploy to staging | [7] Integration and end-to-end tests | [8] Approval gate (continuous delivery) | [9] Deploy to production | [10] Monitor, alert, roll back if needed

Step by step

1. Commit and push. A developer finishes a small change, such as fixing a checkout bug, commits it to a short-lived branch and opens a pull request.
2. Checkout and build. The CI server pulls the exact commit and compiles or bundles it in a clean environment, so “works on my machine” problems show up immediately.
3. Fast tests and checks. Unit tests, linting and type checks run. DORA’s guidance suggests keeping this feedback to about 10 minutes, so developers wait for it instead of moving on.
4. Security scans. Dependency scanning, secret detection and static analysis flag known vulnerable libraries or leaked keys before they reach the main branch.
5. Review and merge. A teammate reviews the change. Once tests pass and the review is approved, it merges into main.
6. Build a release artifact. The pipeline builds one versioned package, often a container image, that will be promoted through every environment unchanged.
7. Deploy to staging. The artifact is deployed to an environment that mirrors production.
8. Slower tests. Integration, end-to-end and performance tests run against staging.
9. Approval or automatic release. In continuous delivery, someone approves the release. In continuous deployment, it proceeds automatically.
10. Deploy and monitor. The change rolls out, often gradually, while dashboards and alerts watch error rates. If something goes wrong, the pipeline rolls back to the previous version.

Total time from merge to production can be minutes or hours, depending on the tests and approvals you choose.

Key takeaway: CI/CD is less about tools and more about habits: small changes, merged often, tested automatically and released through the same repeatable path every time.

Why teams adopt CI/CD

The benefits come from small batch size and automation working together:

• Fewer surprises. Small changes are easier to test, review and roll back than a quarter’s worth of work.
• Faster feedback. Developers find out about broken code in minutes, not weeks.
• Lower release risk. Every release follows the same scripted steps, so fewer manual errors creep in.
• Better security hygiene. Automated scans catch vulnerable dependencies and exposed secrets early.
• More time for real work. Engineers spend less time on manual builds, deployments and release-day firefighting.

CI/CD also underpins wider changes in how teams work. AI coding assistants increase the volume of code changes, which makes automated testing even more important; our article on how AI coding assistants are changing software teams explores that shift.

The building blocks of a CI/CD pipeline

Pricing for hosted CI/CD usually depends on build minutes, runner size and users. For example, GitHub’s documentation says standard GitHub-hosted runners are free for public repositories, and its Free plan includes 2,000 minutes a month for private repositories. Check current plan details, because they change.

How to tell if your CI/CD is working

Having a pipeline is not the same as getting the benefits. The DORA research program tracks 5 software delivery metrics that many teams use:

Watch these together. Deploying more often is only good if change fail rate and recovery time stay healthy.

Warning signs

• Pipelines that take so long developers stop waiting for them
• Flaky tests that fail randomly and get ignored
• A broken main branch that stays broken for hours
• Manual steps hidden between automated ones
• Long-lived feature branches that merge once a month

DORA’s guidance is direct on one of these: fixing a broken build should take priority over other work, and if it cannot be fixed quickly, the change should be reverted.

CI/CD and the rest of IT

CI/CD changes how organizations handle change control. Instead of a weekly meeting approving every release, teams can treat well-tested, automated deployments as low-risk standard changes, with the pipeline itself providing the audit trail. Our guide to ITSM explains how change enablement works.

Larger organizations often go a step further and build shared pipeline templates and internal developer platforms so every team gets CI/CD by default. See platform engineering and developer experience for that model.

Where to start

1. Put everything in version control. Application code, test scripts, pipeline configuration and, ideally, infrastructure definitions.
2. Automate the build. One command should build the app from a clean checkout.
3. Add fast tests on every pull request. Start with the tests you have; add more for each bug you fix.
4. Merge small and often. Aim for short-lived branches merged at least daily.
5. Automate deployment to a staging environment after every merge to main.
6. Add a production release step, with a manual approval at first.
7. Measure the DORA metrics and improve the slowest stage.

Ready to set one up? Our step-by-step guide on how to build a CI/CD pipeline includes a sample configuration you can adapt. If you are learning these skills for a career move, see how to become a DevOps engineer.

Conclusion

CI/CD is an automated path from a developer’s commit to running software, built on small changes, frequent merges and tests that run every time. Continuous integration catches problems early, continuous delivery keeps code always ready to ship, and continuous deployment removes the final manual step for teams ready for it. Start small, automate one stage at a time and use delivery metrics to see whether it is working.

Sources

• DORA, Continuous integration capability — merge frequency, 10-minute feedback guidance and fixing broken builds
• DORA, Continuous delivery capability — definition of continuous delivery and how it differs from continuous deployment
• DORA’s software delivery metrics — the 5 delivery metrics
• AWS, What is continuous delivery? — manual approval as the difference between delivery and deployment
• GitHub Docs, GitHub Actions billing — included minutes and free usage for public repositories