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Continuous Integration vs Continuous Delivery: What's the Difference?
CI proves every commit integrates and passes tests. Continuous delivery keeps it releasable. Different practices, different failure modes.
Quick answer
- Continuous integration is the practice of merging every developer’s work into a shared branch at least daily and proving each merge with an automated build and test run.
- Continuous delivery extends that so every passing build is deployable to production on demand, with the release decision left to a human.
- The practical difference is what happens after the pipeline goes green: CI stops, delivery produces a release candidate that can ship at any time.
- Most teams that say they do CI/CD actually practise continuous integration and manual deployment — which is a valid stopping point, not a failure.
- Neither requires a specific vendor; CI is a behaviour, and the pipeline is only the evidence that the behaviour happened.
What is the difference between continuous integration and continuous delivery?
Continuous integration is about integration risk. Every commit is merged into a shared branch quickly and verified by an automated build and test run, so conflicts and breakages surface in hours rather than at the end of a release cycle. The output of CI is a commit that is known to work with everyone else’s commits.
Continuous delivery is about release risk. It takes that verified commit and keeps it in a state where it could be deployed to production at any moment, which requires the same build to be packaged, deployed to a production-like environment, and tested there. The output of CD is a release candidate, not a release.
| Question | Continuous integration | Continuous delivery |
|--------------------------------|----------------------------------|----------------------------------------|
| What problem does it solve? | Merge conflicts and breakage | Releases that are scary and slow |
| How often does it run? | Every push / pull request | Every passing build |
| What is the output? | A verified commit | A deployable release candidate |
| Who decides to ship? | Nobody — merging is the action | A human, by pressing deploy |
| Typical failure | Long-lived branches, no tests | Manual steps that drift from the build |Where does continuous deployment fit?
Continuous deployment removes the human decision: every commit that passes the full pipeline goes to production automatically. That is a third practice, and it is the one most often confused with continuous delivery because both are abbreviated CD.
Continuous deployment is only safe when the pipeline can detect a bad release and reverse it without a person. Feature flags, automated rollback, and real production monitoring are prerequisites, not nice-to-haves. Teams that adopt it without them are not deploying continuously; they are releasing without a gate.
Do you need CI before you can do continuous delivery?
Yes. Delivery without integration is just an automated deploy of unverified code. The order of adoption is therefore fixed: get every commit building and testing on a shared branch first, then make the artifact deployable, then automate deployment if the risk profile allows it.
What you do not need is a particular tool, or a pipeline for every repository. A single workflow that runs tests on pull requests and a scripted deploy is enough to practise CI and the first half of delivery.
Which one should a small team adopt first?
Adopt continuous integration first, because it is cheap and its benefit appears immediately: broken code stops accumulating. A single workflow that installs from the lockfile, runs tests, and blocks the merge captures most of the value.
Add continuous delivery when deploying has become the risky part — when releases happen rarely, when they require a checklist, or when nobody is confident that main is deployable. The signal is not team size; it is how long it has been since the last production deploy that nobody dreaded.
Where this bites vibecoders
AI-generated projects usually arrive with a deploy button already wired to the host — push to main and it ships — and no test stage at all. That looks like continuous deployment and is actually continuous deployment of unverified code. The fix is not to remove the automatic deploy; it is to add the integration step in front of it, so the button only fires on code that passed something.
Where AI coding assistants get this wrong
- Calling an auto-deploy on push CI/CD when no tests run before the deploy.
- Assuming continuous delivery means deploying to production automatically.
- Adding a pipeline for deployment only, with no build or test stage.
- Long-lived branches that make integration a weekly event instead of a daily one.
- Treating a green build as proof the release is deployable, with no staging run.
- Confusing continuous delivery with continuous deployment in job descriptions and team agreements.
Checklist
- Confirm every push to the shared branch triggers a build and test run.
- Block merges when that run fails.
- Package the tested commit as an artifact rather than rebuilding later.
- Decide explicitly whether a human approves production deploys.
- Write the decision down, because CI/CD means different things to different teams.
- Measure how often main is deployable before claiming delivery.
FAQ
Is CI/CD one thing or two?
Two practices that are usually automated together. CI merges and verifies frequently; CD keeps the verified result deployable. The slash in CI/CD hides the fact that a team can do the first without the second, and many healthy teams do exactly that.
What does the D in CI/CD stand for?
It depends on who is speaking. Continuous delivery keeps releases on demand and human-approved; continuous deployment ships every passing commit automatically. When someone says CD, ask which one they mean, because the operational requirements are very different.
Can you have continuous delivery without automated tests?
Technically you can automate packaging and deployment without tests, but what you have is automated release of unverified code. Delivery is defined by confidence that the artifact is releasable, and without tests that confidence is an assumption rather than a measurement.
How often should integration happen?
At least once a day per developer, and ideally on every completed small change. The threshold that matters is branch lifetime: a branch that lives a week has already deferred the conflicts it was supposed to reveal, regardless of how often the pipeline runs.
Related topics
- What Is CI/CD?
- What Is Continuous Delivery?
- Continuous Delivery vs Continuous Deployment: Which Do You Need?
- What Are the Stages of a CI/CD Pipeline?
- What Is Trunk-Based Development?
- How to Set Up GitOps on a Single-Node k3s Cluster