GitLab CI
A GitLab CI pipeline starts with a single file, .gitlab-ci.yml, sitting at the root of the repository. That file declares a set of stages, build, test, and deploy are typical ones, and the jobs that run within each. By default, GitLab runs jobs in the same stage in parallel and starts the next stage after the current one succeeds, although the needs keyword can allow jobs to run earlier.
The actual work happens on runners, machines GitLab dispatches jobs to. GitLab.com provides shared runners that most teams use out of the box, and a team can also register and host its own runners for specific hardware, private network access, or cost control at higher volume. Artifacts and caching let a pipeline pass files and dependencies between stages, and across runs, without rebuilding everything from scratch on every single pipeline.
What sets GitLab CI apart is how tightly it's woven into the rest of GitLab. Merge requests, issue tracking, the container registry, and pipeline results all live in the same place, and GitLab tracks environments and deployments natively rather than as a bolted-on feature. That native environment tracking pairs naturally with a GitOps-style deployment model, where the state of a deployment matters as much as the fact that a pipeline ran successfully.
How a pipeline is put together
- Defined in a single
.gitlab-ci.ymlfile at the root of the repository, describing stages and the jobs within each. - Stages run in order, build then test then deploy, for example, while jobs inside a single stage run in parallel by default.
- Runners, GitLab-hosted shared runners or self-hosted ones a team registers, provide the machine each job actually executes on.
- Artifacts and caching pass files and dependencies between stages and across pipeline runs, without rebuilding everything each time.
- Environments track where a deployment actually went, staging or production, directly inside GitLab's own interface.
What teams build with it
- Continuous integration, running linters, unit tests, and end-to-end suites automatically on every merge request.
- Continuous deployment, pushing a build to a defined environment once checks pass, often with a manual approval step for production.
- GitOps-style delivery, since GitLab's environment and deployment tracking pair naturally with a reconciliation-based deployment model.
- Scheduled pipelines, like a nightly regression run, triggered on a cron schedule rather than a code change.
Benefits and challenges
| Benefit | Challenge |
|---|---|
| Lives inside GitLab already, tightly integrated with merge requests, issues, and the container registry, no separate CI system to stand up. | Self-hosted GitLab and heavier runner infrastructure take real setup and upkeep if a team isn't using GitLab's own shared runners. |
| A single YAML file at the root of the repo makes the whole pipeline easy to find and version alongside the code it builds. | Complex pipelines with many stages and conditional rules can get genuinely hard to read in one file, however well it's organized. |
| Built-in environments and deployment tracking give strong native support for GitOps-style workflows. | Shared runner minutes are metered on GitLab's hosted plans, and heavy pipelines can add up in cost at scale. |
Frequently asked questions
How is GitLab CI different from GitHub Actions?
Both define a pipeline in YAML and trigger it off repository events, but they live inside different platforms. GitHub Actions integrates with GitHub's ecosystem and Marketplace of reusable actions. GitLab CI integrates with GitLab's own merge requests, issue tracking, and container registry, and is generally considered to have deeper built-in support for tracking deployments and environments.
Do I need to self-host GitLab to use GitLab CI?
No. GitLab.com offers hosted shared runners similar to how GitHub offers hosted runners for Actions, with a free tier of minutes and paid tiers beyond that. Self-hosting GitLab, and optionally your own runners, is an option for teams that want more control, not a requirement to use GitLab CI at all.
What is a runner in GitLab CI?
A runner is the actual machine, GitLab-hosted or self-hosted, that executes a pipeline's jobs. GitLab's shared runners work for most teams out of the box, while a self-hosted runner is usually chosen for specific hardware needs, network access to internal systems, or cost control at higher volume.
How Klarent helps
Klarent's AI-generated tests run as a job inside a GitLab CI pipeline like any other stage, and self-healing execution keeps them passing through interface changes instead of turning every merge request into a maintenance chore.