- CI/CD meaning: continuous integration and continuous delivery
- What continuous integration means in CI/CD
- Continuous delivery vs continuous deployment in CI/CD
- The stages of a CI/CD pipeline
- Popular CI/CD tools
- Benefits of CI/CD for teams and customers
- CI/CD pitfalls and security risks
- Getting started with CI/CD and sharing what you learn
- Frequently asked questions
CI/CD stands for continuous integration and continuous delivery or deployment. Developers merge small code changes often, and an automated pipeline builds and tests each one. With continuous delivery, a person approves the release to live; with continuous deployment, changes that pass the tests go live automatically.
CI/CD is one of those bits of developer shorthand that turns up in job ads, agency proposals and software release notes, usually without an explanation. If you work with developers or run a product team, it helps to know what they mean, because it shapes how quickly and safely changes reach your website or app.
I've written this guide from the explanations published by Red Hat, AWS, GitLab and GitHub, so the definitions match how the industry uses them. You don't need a technical background; I'll keep the jargon to a minimum and explain it where it's unavoidable.
CI/CD meaning: continuous integration and continuous delivery
CI/CD combines continuous integration with continuous delivery or continuous deployment. Red Hat describes it as aiming to streamline and accelerate the software development lifecycle, and GitLab calls it a way of releasing products quickly by automating processes that used to be done by hand.
The idea is simple. Instead of saving up weeks of changes and releasing them in one nerve-racking go, a team makes small changes often, and a chain of automated checks builds, tests and prepares each one for release. That chain is called a CI/CD pipeline.
What continuous integration means in CI/CD
GitHub defines continuous integration as a software practice that requires frequently committing code to a shared repository. Every time a developer merges a change, an automated system builds the code and runs tests on it. Red Hat explains the goal: catching conflicts early, when they're easier to fix.
In practice, that means a developer pushes a change, the CI system runs the tests within minutes and the result shows up next to the change. GitHub says the tests can include linters, security checks, code coverage and functional tests, and when they all pass, the change is ready for a teammate to review or merge.
Continuous delivery vs continuous deployment in CI/CD
The CD part has two meanings, and the difference is one human decision:
| Continuous delivery | Continuous deployment | |
|---|---|---|
| What's automated | Building, testing and preparing every change for release | Everything, including the release to live |
| Release to production | A person approves it, often with one click | Happens automatically when tests pass |
| Main requirement | A reliable automated test process | Very well-designed test automation |
| Suits | Teams that want a final human check | Teams confident in their tests and monitoring |
AWS puts it neatly: with continuous delivery, the final decision to deploy to a live production environment is triggered by the developer. With continuous deployment, Red Hat says changes go to production without manual approval. Which one a team picks depends on its appetite for risk.
The stages of a CI/CD pipeline
Pipelines vary, but GitLab and AWS describe the same broad flow:
- Source. A developer pushes code to a shared repository, and that commit kicks off the pipeline.
- Build. The code's compiled or packaged into something that can be deployed.
- Test. Automated tests run. GitLab lists unit, integration and regression tests, and AWS notes there can be several test stages, including UI, load and API reliability testing.
- Staging. The change goes to a test environment that mirrors the live one, where security and load tests can run.
- Production. The change goes live, either after an approval (delivery) or automatically (deployment).
If anything fails along the way, the pipeline stops and the team fixes the problem before trying again.
Popular CI/CD tools
Plenty of tools can run a pipeline. Here are four well-known names and how each describes itself:
- GitHub Actions: workflows that build and test code in a GitHub repository, triggered by events such as a push. They can run on GitHub-hosted virtual machines or on your own machines.
- GitLab CI/CD: built into GitLab, which calls itself a single application for the entire DevSecOps lifecycle.
- Jenkins: describes itself as an open source automation server, with a large library of community-contributed plugins.
- CircleCI: a platform that helps teams build, test and deploy using automation.
Many pipelines end by deploying to cloud services, and the type of cloud service you use changes what your pipeline has to look after. I've explained those layers in IaaS vs PaaS vs SaaS.
Want AI doing the heavy lifting in your marketing?
I build the systems that handle the boring 80 percent, so you get your week back. Done properly, with the human kept in.
Benefits of CI/CD for teams and customers
- Fewer bugs reach customers, because every change is tested before release.
- Faster releases with less downtime, because manual steps are automated.
- Quicker feedback from users, which helps teams improve the product.
- Smaller, incremental releases that carry less risk and are easier to roll back.
- More developer time for building, and less spent on repetitive testing and debugging.
A pipeline usually covers both halves of an app, the screens people see and the server code behind them. If those terms are new, see my guide to front end vs back end development.
CI/CD pitfalls and security risks
CI/CD isn't magic, and Red Hat is candid about the downsides:
- Upfront effort. Continuous deployment can need a lot of setup work at the start.
- Weak tests mean weak releases. Without a manual gate, everything relies on well-designed test automation.
- Security gaps. Fast delivery without safeguards can expose sensitive data, pull in insecure third-party components or let people reach repositories and build tools they shouldn't. Red Hat recommends security checks throughout the pipeline, an approach often called DevSecOps.
- Growing complexity. Longer pipelines and toolchains mean developers need to understand more of the stack.
A practical takeaway: keep secrets such as access keys out of your code, review who can change pipeline settings and treat a failing test as a stop sign, not an inconvenience.
Getting started with CI/CD and sharing what you learn
If you're new to it, a sensible first step is a simple pipeline that runs your tests on every push, using whichever tool sits alongside your code. Add build, staging and deployment steps once that's reliable. Engineers who've solved a tricky pipeline problem often help others most by writing it up.
Engineers who've built a pipeline worth writing about can look at DevOps blogs that accept contributed articles.
Frequently asked questions
What does CI/CD stand for?
CI stands for continuous integration. CD stands for continuous delivery or continuous deployment, depending on whether a person approves the final release.
Is CI/CD the same as DevOps?
Not quite. DevOps is a wider way of working between development and operations teams. Red Hat notes CI/CD pipelines are often supported by teams working in a DevOps or site reliability engineering approach.
Do small teams need a CI/CD pipeline?
They don't need a complex one, but even a solo developer can benefit from automated tests running on every change. It catches mistakes before they reach customers.
Which CI/CD tool should I start with?
Most people start with the tool that sits alongside their code, such as GitHub Actions for GitHub repositories or GitLab CI/CD for GitLab. Jenkins and CircleCI are other well-known options.
What's a CI/CD pipeline?
It's the connected set of automated steps that takes a code change from the repository through building and testing to release.
