367 lines
18 KiB
Markdown
367 lines
18 KiB
Markdown
---
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stage: Verify
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group: Pipeline Authoring
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info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments
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type: index, howto
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---
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# Migrating from Jenkins **(FREE)**
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A lot of GitLab users have successfully migrated to GitLab CI/CD from Jenkins.
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We've collected several resources here that you might find informative if you're just getting started.
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Think of this page as a "GitLab CI/CD for Jenkins Users" guide.
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The following list of recommended steps was created after observing organizations
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that were able to quickly complete this migration:
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1. Start by reading the GitLab CI/CD [Quick Start Guide](../quick_start/index.md) and [important product differences](#important-product-differences).
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1. Learn the importance of [managing the organizational transition](#manage-organizational-transition).
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1. [Add runners](../runners/index.md) to your GitLab instance.
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1. Educate and enable your developers to independently perform the following steps in their projects:
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1. Review the [Quick Start Guide](../quick_start/index.md) and [Pipeline Configuration Reference](../yaml/index.md).
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1. Use the [Jenkins Wrapper](#jenkinsfile-wrapper) to temporarily maintain fragile Jenkins jobs.
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1. Migrate the build and CI jobs and configure them to show results directly in your merge requests. They can use [Auto DevOps](../../topics/autodevops/index.md) as a starting point, and [customize](../../topics/autodevops/customize.md) or [decompose](../../topics/autodevops/customize.md#use-individual-components-of-auto-devops) the configuration as needed.
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1. Add [Review Apps](../review_apps/index.md).
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1. Migrate the deployment jobs using [cloud deployment templates](../cloud_deployment/index.md), adding [environments](../environments/index.md), and [deploy boards](../../user/project/deploy_boards.md).
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1. Work to unwrap any jobs still running with the use of the Jenkins wrapper.
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1. Take stock of any common CI/CD job definitions then create and share [templates](#templates) for them.
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1. Check the [pipeline efficiency documentation](../pipelines/pipeline_efficiency.md)
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to learn how to make your GitLab CI/CD pipelines faster and more efficient.
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Watch the [Migrating from Jenkins to GitLab](https://www.youtube.com/watch?v=RlEVGOpYF5Y) video for examples of how to:
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- Convert a Jenkins pipeline into a GitLab CI/CD pipeline.
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- Use Auto DevOps to test your code automatically.
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Otherwise, read on for important information that helps you get the ball rolling. Welcome
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to GitLab!
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If you have questions that are not answered here, the [GitLab community forum](https://forum.gitlab.com/)
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can be a great resource.
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## Manage organizational transition
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An important part of transitioning from Jenkins to GitLab is the cultural and organizational
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changes that come with the move, and successfully managing them. A few
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things we have found that help this are:
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- Setting and communicating a clear vision of what your migration goals are helps
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your users understand why the effort is worth it. The value is clear when
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the work is done, but people need to be aware while it's in progress too.
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- Sponsorship and alignment from the relevant leadership team helps with the point above.
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- Spending time educating your users on what's different and sharing this document
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with them helps ensure you are successful.
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- Finding ways to sequence or delay parts of the migration can help a lot, but you
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don't want to leave things in a non-migrated (or partially-migrated) state for too
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long. To gain all the benefits of GitLab, moving your existing Jenkins setup over
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as-is, including any current problems, isn't enough. You need to take advantage
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of the improvements that GitLab offers, and this requires (eventually) updating
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your implementation as part of the transition.
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## JenkinsFile Wrapper
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We are building a [JenkinsFile Wrapper](https://gitlab.com/gitlab-org/jfr-container-builder/) which
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you can use to run a complete Jenkins instance inside of a GitLab job, including plugins. This can help ease the process
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of transition, by letting you delay the migration of less urgent pipelines for a period of time.
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If you are interested in helping GitLab test the wrapper, join our [public testing issue](https://gitlab.com/gitlab-org/gitlab/-/issues/215675) for instructions and to provide your feedback.
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NOTE:
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If you have a paid GitLab subscription, the JenkinsFile Wrapper is not packaged with GitLab and falls outside of the scope of support. For more information, see the [Statement of Support](https://about.gitlab.com/support/statement-of-support/).
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## Important product differences
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Some high level differences between the products worth mentioning are:
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- With GitLab you don't need a root `pipeline` keyword to wrap everything.
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- The way pipelines are triggered and [trigger other pipelines](../yaml/index.md#trigger)
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is different than Jenkins. GitLab pipelines can be triggered:
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- on push
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- on [schedule](../pipelines/schedules.md)
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- from the [GitLab UI](../pipelines/index.md#run-a-pipeline-manually)
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- by [API call](../triggers/index.md)
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- by [webhook](../triggers/index.md#use-a-webhook)
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- by [ChatOps](../chatops/index.md)
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- You can control which jobs run in which cases, depending on how they are triggered,
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with the [`rules` syntax](../yaml/index.md#rules).
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- GitLab [pipeline scheduling concepts](../pipelines/schedules.md) are also different from Jenkins.
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- You can reuse pipeline configurations using the [`include` keyword](../yaml/index.md#include)
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and [templates](#templates). Your templates can be kept in a central repository (with different
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permissions), and then any project can use them. This central project could also
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contain scripts or other reusable code.
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- You can also use the [`extends` keyword](../yaml/index.md#extends) to reuse configuration
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in a single pipeline configuration.
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- All jobs in a single stage always run in parallel, and all stages run in sequence.
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Certain jobs might break this sequencing as needed with our [directed acyclic graph](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/47063)
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feature.
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- The [`parallel`](../yaml/index.md#parallel) keyword can automatically parallelize tasks,
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like tests that support parallelization.
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- Usually all jobs in a single stage run in parallel, and all stages run in sequence.
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Different [pipeline architectures](../pipelines/pipeline_architectures.md) allow you to change this behavior.
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- The new [`rules` syntax](../yaml/index.md#rules) is the recommended method of
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controlling when different jobs run. It is more powerful than the `only/except` syntax.
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- One important difference is that jobs run independently of each other and have a
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fresh environment in each job. Passing artifacts between jobs is controlled using the
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[`artifacts`](../yaml/index.md#artifacts) and [`dependencies`](../yaml/index.md#dependencies)
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keywords. When finished, use the planned [Workspaces](https://gitlab.com/gitlab-org/gitlab/-/issues/29265)
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feature to persist a common workspace between serial jobs.
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- The `.gitlab-ci.yml` file is checked in to the root of your repository, much like a Jenkinsfile, but
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is in the YAML format (see [complete reference](../yaml/index.md)) instead of a Groovy DSL. It's most
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analogous to the declarative Jenkinsfile format.
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- Manual approvals or gates can be set up as [`when:manual` jobs](../jobs/job_control.md#create-a-job-that-must-be-run-manually). These can
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also leverage [`protected environments`](../jobs/job_control.md#run-a-job-after-a-delay)
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to control who is able to approve them.
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- GitLab comes with a [container registry](../../user/packages/container_registry/index.md), so you can use
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container images to set up your build environment. For example, set up one pipeline that builds your build environment
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itself and publish that to the container registry. Then, have your pipelines use this instead of each building their
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own environment, which is slower and may be less consistent. We have extensive documentation on [how to use the Container Registry](../../user/packages/container_registry/index.md).
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- A central utilities repository can be a great place to put assorted scheduled jobs
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or other manual jobs that function like utilities. Jenkins installations tend to
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have a few of these.
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## Agents vs. runners
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Both Jenkins agents and GitLab runners are the hosts that run jobs. To convert the
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Jenkins agent, uninstall it and then [install and register the runner](../runners/index.md).
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Runners do not require much overhead, so you can size them similarly to the Jenkins
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agents you were using.
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Some important differences in the way runners work in comparison to agents are:
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- Runners can be set up as [shared across an instance, be added at the group level, or set up at the project level](../runners/runners_scope.md).
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They self-select jobs from the scopes you've defined automatically.
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- You can also [use tags](../runners/configure_runners.md#use-tags-to-control-which-jobs-a-runner-can-run) for finer control, and
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associate runners with specific jobs. For example, you can use a tag for jobs that
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require dedicated, more powerful, or specific hardware.
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- GitLab has [autoscaling for runners](https://docs.gitlab.com/runner/configuration/autoscale.html).
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Use autoscaling to provision runners only when needed and scale down when not needed,
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similar to ephemeral agents in Jenkins.
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If you are using `gitlab.com`, you can take advantage of our [shared runner fleet](../runners/index.md)
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to run jobs without provisioning your own runners. We are investigating making them
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[available for self-managed instances](https://gitlab.com/groups/gitlab-org/-/epics/835)
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as well.
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## Groovy vs. YAML
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Jenkins Pipelines are based on [Groovy](https://groovy-lang.org/), so the pipeline specification is written as code.
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GitLab works a bit differently, using the more highly structured [YAML](https://yaml.org/) format.
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The scripting elements are in `script` blocks separate from the pipeline specification itself.
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Using YAML is a strength of GitLab, in that it helps keep the learning curve much simpler to get up and running.
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It also avoids some of the problem of unconstrained complexity which can make your Jenkinsfile hard to understand
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and manage.
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We do of course still value DRY (don't repeat yourself) principles. We want to ensure that
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behaviors of your jobs can be codified once and applied as needed. You can use the `extends` syntax to
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[reuse configuration in your jobs](../yaml/index.md#extends), and `include` can
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be used to [reuse pipeline configurations](../yaml/index.md#include) in pipelines
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in different projects:
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```yaml
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.in-docker:
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tags:
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- docker
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image: alpine
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rspec:
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extends:
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- .in-docker
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script:
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- rake rspec
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```
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## Artifact publishing
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Artifacts may work a bit differently than you've used them with Jenkins. In GitLab, any job can define
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a set of artifacts to be saved by using the `artifacts` keyword. This can be configured to point to a file
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or set of files that can then be persisted from job to job. Read more on our detailed
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[artifacts documentation](../jobs/job_artifacts.md):
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```yaml
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pdf:
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script: xelatex mycv.tex
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artifacts:
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paths:
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- ./mycv.pdf
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- ./output/
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expire_in: 1 week
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```
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Additionally, we have package management features like built-in container and package registries that you
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can leverage. You can see the complete list of packaging features in the
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[Packages and registries](../../user/packages/index.md) documentation.
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## Integrated features
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You may have used plugins to get things like code quality, unit tests, and security scanning working in Jenkins.
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GitLab takes advantage of our connected ecosystem to automatically pull these kinds of results into
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your merge requests, pipeline details pages, and other locations. You may find that you actually don't
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need to configure anything to have these appear.
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Our [CI/CD feature index](../index.md#features) has the full list of bundled features and links to the documentation for each.
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Refer to this index if these features aren't working as expected, or if you'd like to see what's available.
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### Templates
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For advanced CI/CD teams, project templates can enable the reuse of pipeline configurations,
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as well as encourage inner sourcing.
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In self-managed GitLab instances, you can build an [Instance Template Repository](../../user/admin_area/settings/instance_template_repository.md).
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Development teams across the whole organization can select templates from a dropdown list.
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A group maintainer or a group owner is able to set a group to use as the source for the
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[custom project templates](../../user/admin_area/custom_project_templates.md). This can
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be used by all projects in the group. An instance administrator can set a group as
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the source for [instance project templates](../../user/group/custom_project_templates.md),
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which can be used by projects in that instance.
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## Convert a declarative Jenkinsfile
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A declarative Jenkinsfile contains "Sections" and "Directives" which are used to control the behavior of your
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pipelines. Equivalents for all of these exist in GitLab, which we've documented below.
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This section is based on the [Jenkinsfile syntax documentation](https://www.jenkins.io/doc/book/pipeline/syntax/)
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and is meant to be a mapping of concepts there to concepts in GitLab.
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### Sections
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#### `agent`
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The agent section is used to define how a pipeline executes. For GitLab, we use [runners](../runners/index.md)
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to provide this capability. You can configure your own runners in Kubernetes or on any host. You can also take advantage
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of our shared runner fleet (the shared runner fleet is only available for GitLab.com users).
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We also support using [tags](../runners/configure_runners.md#use-tags-to-control-which-jobs-a-runner-can-run) to direct different jobs
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to different runners (execution agents).
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The `agent` section also allows you to define which Docker images should be used for execution, for which we use
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the [`image`](../yaml/index.md#image) keyword. The `image` can be set on a single job or at the top level, in which
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case it applies to all jobs in the pipeline:
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```yaml
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my_job:
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image: alpine
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```
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#### `post`
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The `post` section defines the actions that should be performed at the end of the pipeline. GitLab also supports
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this through the use of stages. You can define your stages as follows, and any jobs assigned to the `before_pipeline`
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or `after_pipeline` stages run as expected. You can call these stages anything you like:
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```yaml
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stages:
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- before_pipeline
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- build
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- test
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- deploy
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- after_pipeline
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```
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Setting a step to be performed before and after any job can be done via the
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[`before_script`](../yaml/index.md#before_script) and [`after_script`](../yaml/index.md#after_script) keywords:
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```yaml
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default:
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before_script:
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- echo "I run before any jobs starts in the entire pipeline, and can be responsible for setting up the environment."
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```
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#### `stages`
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GitLab CI/CD also lets you define stages, but is a little bit more free-form to configure. The GitLab [`stages` keyword](../yaml/index.md#stages)
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is a top level setting that enumerates the list of stages. You are not required to nest individual jobs underneath
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the `stages` section. Any job defined in the `.gitlab-ci.yml` can be made a part of any stage through use of the
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[`stage` keyword](../yaml/index.md#stage).
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Unless otherwise specified, every pipeline is instantiated with a `build`, `test`, and `deploy` stage
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which are run in that order. Jobs that have no `stage` defined are placed by default in the `test` stage.
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Of course, each job that refers to a stage must refer to a stage that exists in the pipeline configuration.
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```yaml
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stages:
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- build
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- test
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- deploy
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my_job:
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stage: build
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```
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#### `steps`
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The `steps` section is equivalent to the [`script` section](../yaml/index.md#script) of an individual job. The `steps` section is a YAML array
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with each line representing an individual command to be run:
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```yaml
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my_job:
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script:
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- echo "hello! the current time is:"
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- time
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```
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### Directives
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#### `environment`
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In GitLab, we use the [`variables` keyword](../yaml/index.md#variables) to define different variables at runtime.
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These can also be set up through the GitLab UI, under CI/CD settings. See also our [general documentation on variables](../variables/index.md),
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including the section on [protected variables](../variables/index.md#protect-a-cicd-variable). This can be used
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to limit access to certain variables to certain environments or runners:
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```yaml
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variables:
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POSTGRES_USER: user
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POSTGRES_PASSWORD: testing_password
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```
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#### `options`
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Here, options for different things exist associated with the object in question itself. For example, options related
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to jobs are defined in relation to the job itself. If you're looking for a certain option, you should be able to find
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where it's located by searching our [complete configuration reference](../yaml/index.md) page.
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#### `parameters`
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GitLab does not require you to define which variables you want to be available when starting a manual job. A user
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can provide any variables they like.
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#### `triggers` / `cron`
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Because GitLab is integrated tightly with Git, SCM polling options for triggers are not needed. We support a
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[syntax for scheduling pipelines](../pipelines/schedules.md).
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#### `tools`
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GitLab does not support a separate `tools` directive. Our best-practice recommendation is to use pre-built
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container images. These images can be cached and can be built to already contain the tools you need for your pipelines. Pipelines can
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be set up to automatically build these images as needed and deploy them to the [container registry](../../user/packages/container_registry/index.md).
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If you don't use container images with Docker or Kubernetes, but use the `shell` executor on your own system,
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you must set up your environment. You can set up the environment in advance, or as part of the jobs
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with a `before_script` action that handles this for you.
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#### `input`
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Similar to the `parameters` keyword, this is not needed because a manual job can always be provided runtime
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variable entry.
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#### `when`
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GitLab does support a [`when` keyword](../yaml/index.md#when) which is used to indicate when a job should be
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run in case of (or despite) failure. Most of the logic for controlling pipelines can be found in
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our very powerful [`rules` system](../yaml/index.md#rules):
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```yaml
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my_job:
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script:
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- echo
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rules:
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- if: $CI_COMMIT_BRANCH
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```
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## Additional resources
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For help making your pipelines faster and more efficient, see the
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[pipeline efficiency documentation](../pipelines/pipeline_efficiency.md).
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