GitHub Actions vs GitLab CI vs Jenkins for Small Teams

For a team of five, the CI choice is less about features, which are all adequate, than about who keeps it running. Each of the three has a model that suits a situation, and the wrong choice shows up as maintenance work a year later. The comparison here is general and dated: features and prices change, so check current terms before committing. It builds on portable CI scripts.

At a glance

                    GitHub Actions     GitLab CI           Jenkins
Hosting             SaaS (+ runners)   SaaS or self-host   self-host only
Config              workflow YAML      .gitlab-ci.yml      Jenkinsfile (Groovy)
Setup effort        minutes            minutes             hours to days
Maintenance         low                low (SaaS)          high
Reusable pieces     marketplace        templates/includes  plugins
Self-hosted runner  yes                yes                 yes (agents)
Best fit            GitHub repos       GitLab repos        custom, legacy, air-gapped

The table shows relative effort, not measured numbers. The last row is the most important: the best CI is usually the one attached to the host of your repositories, since pull request checks, permissions and secrets are already connected.

GitHub Actions

Workflows are YAML files under .github/workflows/, triggered by repository events. The marketplace has an action for nearly everything, which speeds the start and creates dependencies you should pin. The free tier for public repositories is generous; private repositories have a monthly allowance of minutes and then pay per minute, which is cheaper on Linux than macOS or Windows. Details are in shell scripts in Actions. Weaknesses: workflow YAML gets verbose, local runs need a tool such as act, and security needs care with third-party actions and pull_request_target.

GitLab CI

A single .gitlab-ci.yml defines stages and jobs, with strong built-in features: environments, a container registry, review apps, merge request pipelines and caching. It can be fully self-hosted, which suits organisations that cannot send code out. The YAML supports includes and templates for reuse. The learning curve is in rules: and the many ways pipelines are created. See building a GitLab CI pipeline. Runners are separate programs you register, so a self-hosted runner is routine.

Jenkins

Jenkins is the veteran: highly customisable, thousands of plugins and no dependence on any repository host. That freedom is the cost. Someone has to patch the controller, update plugins (a frequent source of security advisories and breakage), manage agents, back up the configuration and keep the Java version current. Pipelines in Groovy are powerful and easy to over-complicate. It earns its place when you need an air-gapped installation, an unusual integration, or when it is already running and works. See shell in Jenkins pipelines.

A decision rule

Pick by constraints in this order. If code must stay on your infrastructure, choose GitLab self-hosted or Jenkins. Otherwise use the CI of your repository host. If you need macOS or GPU builds, look at runner availability and cost, then compare hosted and self-hosted runners. If the team has no one to maintain servers, avoid Jenkins. Whatever you pick, keep scripts portable so the decision stays reversible.

Beyond the feature table

Feature lists converge, and what separates the tools is the shape of the work around them. GitHub Actions treats a workflow as a reaction to repository events, so anything that starts from a pull request, issue or release is natural, and anything that is a long-lived orchestration across many repositories takes effort. GitLab CI models a pipeline as stages and jobs attached to a project, with environments and releases as built-in concepts, which suits teams that want one product for planning, code and deployment. Jenkins models jobs on a server, with pipelines as code layered on top, which gives total freedom and total responsibility.

Think about the failure mode that costs you most. With a hosted platform, the risk is an outage or a policy change outside your control, mitigated by keeping pipeline logic in portable scripts. With Jenkins, the risk is an unpatched server and a pile of plugins nobody understands, mitigated by treating the controller as a production service with backups, upgrades and an owner. Choose the risk you are better equipped to manage.

Security and supply chain

Each platform has had its own incidents, and the lessons transfer. Third-party actions and plugins run with your permissions, so pin them and review changes. Secrets exposed to forked pull requests are the classic hole, and each platform has a setting that controls it, which you should check explicitly instead of trusting the default. Tokens used by the pipeline should be scoped to the minimum, and short-lived credentials by OIDC federation beat stored cloud keys on all three platforms. Whatever the tool, write down who can edit the pipeline file, since whoever can edit it can run code with its secrets.

Cost and lock-in

Hosted minutes cost little for small teams and grow with parallel jobs, larger runners and storage for artifacts and caches. Run a month of real usage, read the bill and project it for twice the volume before committing. Lock-in lives in proprietary syntax and in the marketplace pieces you depend on. Keep the logic in scripts and task runners and the platform file thin, and a migration becomes a week of rewriting triggers rather than a quarter of rewriting builds. Teams that have done one migration tend to protect themselves this way from then on.

A practical way to decide

Run a short trial. Port the two most representative pipelines to the candidate, one fast check and one release flow, and measure the time to set up, the time to run, the number of surprises and the time a new teammate needs to understand it. Ask the people who will maintain it which one they would rather be paged about. The answer tends to match the one with the fewest moving parts they have to own, which is usually the platform attached to the repository host.

Operating cost over time

The first month tells you little, and the third year tells you everything. A hosted platform has a small constant overhead: reading release notes, renewing tokens, updating pinned actions. A self-hosted GitLab or Jenkins controller adds upgrades with schema migrations, plugin compatibility checks, disk growth in artifact storage and the occasional weekend recovery. Estimate the hours per month honestly, multiply by the cost of the person doing it and compare with the subscription. For many small teams the subscription is the cheaper line, even though the invoice looks bigger than a server bill.

Plan an exit as well. Export your pipeline definitions, keep scripts portable and note which features you rely on that exist only on one platform. Reading this list once a year costs an hour and gives a realistic view of how hard leaving would be, which in turn keeps the platform's vendor honest about prices and the team honest about convenience.

The same job on each platform

# GitHub Actions: .github/workflows/ci.yml
on: [pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: make test

# GitLab CI: .gitlab-ci.yml
test:
  image: debian:13-slim
  script:
    - make test

Both files do the same thing: check out the code and run one named task. Jenkins expresses it as a Jenkinsfile with a stage that calls sh 'make test'. The platform-specific part is a handful of lines, and the logic stays in the Makefile, which is the portability argument made earlier in this post in its smallest form.

Where this does not apply

Other options exist, such as CircleCI, Buildkite, Woodpecker, Drone and Forgejo Actions, each with a niche. A very small project with a few tests may only need a pre-push hook and a nightly cron job. Prices, free minutes and features change often, so check the pricing pages. See the GitHub Actions documentation, the GitLab CI documentation and the Jenkins documentation.