A CI/CD pipeline is an automated workflow that takes a software change from source control through building and testing to a release or deployment. A useful starting model is source → build → test → deploy, but real pipelines vary: teams can add checks, run work in parallel, and require approval before production.
What is a CI/CD pipeline?
A CI/CD pipeline is a repeatable route for moving software changes from a repository toward release. It coordinates the work needed to build and verify a change, then makes the tested result available in an environment or for release. The pipeline may be defined and run by a CI/CD platform or another automation system. GitLab’s overview and Jenkins Pipeline documentation describe this general workflow.
CI/CD commonly expands to continuous integration and continuous delivery or continuous deployment. In practice, the term describes automated software workflows; it does not refer to a consumer hardware product.
What are the steps in a CI/CD pipeline?
Source, build, test, and deploy are useful labels for the main flow, not a rule that every pipeline must have exactly four sequential stages. A team’s repository, tools, and release policy determine the actual jobs and order.
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1. Source change and trigger
A code change in the repository commonly triggers a pipeline. A workflow may also start manually or on a schedule. The trigger tells the automation when to begin; it does not determine which later checks or release decisions the project needs. GitLab describes these common trigger patterns.
2. Build
The build step compiles or packages the change into a runnable artifact. If the build fails, the team has an early signal that the change needs investigation before it proceeds to later checks or deployment.
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3. Test and verify
Automated tests and other configured checks look for defects before release. Which checks run depends on the project; the broad purpose is to provide evidence that the change is ready to move forward. GitLab characterizes testing as a safety net, rather than prescribing one universal test set.
4. Deploy or prepare for release
A pipeline can deploy the tested result to a test, staging, or production environment, subject to the team’s policy. Some workflows stop with a release prepared for a person to approve; others automate production deployment after the required jobs succeed.
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How do jobs, stages, and runners work?
In GitLab’s pipeline model, a job defines work to perform, a stage groups jobs into an ordering, and a runner executes a job. Jobs in the same stage may run at the same time if runner capacity is available. Later stages generally wait for earlier stages to succeed; a failed job commonly prevents the pipeline from advancing so the problem can be investigated. See GitLab’s pipeline documentation for this model.
This explains why the simple flow should not be mistaken for one task at a time. A test stage might contain several jobs that run concurrently, while the deploy stage waits for the required earlier work. The exact behavior depends on the platform’s configuration.
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What is the difference between continuous delivery and continuous deployment?
The distinction is what happens at the production-release decision:
- Continuous delivery automates the route to a release that is ready to deploy. A person or team can choose when to approve production deployment.
- Continuous deployment automates the release into production after the configured pipeline requirements pass, without a separate human production approval for each change.
An approval gate should be explicit in the workflow. A pipeline that automatically tests and packages software but waits for a person to initiate production release is continuous delivery, not continuous deployment. GitLab’s overview explains this distinction.
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Where is the pipeline configured?
Pipeline configuration can live in the same source repository as the software, so changes to the workflow can be reviewed and versioned alongside code. Jenkins calls this approach pipeline-as-code and uses a Jenkinsfile. GitLab’s introductory tutorial likewise walks through committing pipeline configuration to a repository. See Jenkins Pipeline and the GitLab first-pipeline tutorial.
What should you look at when choosing a CI/CD implementation?
GitLab and Jenkins illustrate different implementation models, but the cited documentation is not a comprehensive product comparison. For a project, check how the system connects to the source repository, whether execution is hosted or self-managed, how jobs and stages are configured, and whether runner capacity supports the parallel work the pipeline needs. Also verify how it connects to the target environments and whether production release requires an approval gate.
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