335 lines
16 KiB
Markdown
335 lines
16 KiB
Markdown
---
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comments: false
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type: index, howto
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---
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# Migrating from Jenkins
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A lot of GitLab users have successfully migrated to GitLab CI/CD from Jenkins. To make this
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easier if you're just getting started, we've collected several resources here that you might find useful
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before diving in. Think of this page as a "GitLab CI/CD for Jenkins Users" guide.
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First of all, our [Quick Start Guide](../quick_start/README.md) contains a good overview of how GitLab CI/CD works.
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You may also be interested in [Auto DevOps](../../topics/autodevops/index.md) which can potentially be used to build, test,
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and deploy your applications with little to no configuration needed at all.
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For advanced CI/CD teams, [templates](#templates) can enable the reuse of pipeline configurations.
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Otherwise, read on for important information that will help 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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## Managing the 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 comes with the move, and successfully managing them. There are a few
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things we have found that helps this:
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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 will be 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, sharing this document with them,
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and so on will help 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, will not be 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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## Important product differences
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There are some high level differences between the products worth mentioning:
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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/README.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#manually-executing-pipelines)
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- by [API call](../triggers/README.md)
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- by [webhook](../triggers/README.md#triggering-a-pipeline-from-a-webhook)
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- by [ChatOps](../chatops/README.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/README.md#rules).
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- GitLab [pipeline scheduling concepts](../pipelines/schedules.md) are also different than with Jenkins.
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- You can reuse pipeline configurations using the [`include` keyword](../yaml/README.md#include)
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and [templates](#templates). Your templates can be kept in a central repo (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/README.md#extends) to reuse configuration
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within a single pipeline configuration.
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- All jobs within a single stage always run in parallel, and all stages run in sequence. We are planning
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to allow certain jobs to 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/README.md#parallel) keyword can automatically parallelize tasks,
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like tests that support parallelization.
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- Normally all jobs within a single stage run in parallel, and all stages run in sequence.
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There are different [pipeline architectures](../pipelines/pipeline_architectures.md)
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that allow you to change this behavior.
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- The new [`rules` syntax](../yaml/README.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/README.md#artifacts) and [`dependencies`](../yaml/README.md#dependencies)
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keywords. When finished, the planned [Workspaces](https://gitlab.com/gitlab-org/gitlab/issues/29265)
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feature will allow you to more easily 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/README.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](../yaml/README.md#whenmanual). These can
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also leverage [`protected environments`](../yaml/README.md#protecting-manual-jobs-premium)
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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), and we recommend using
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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 will be slower and may be less consistent. We have extensive docs 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, simply uninstall it and then [install and register the runner](../runners/README.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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There are some important differences in the way Runners work in comparison to agents:
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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/README.md#shared-specific-and-group-runners).
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They will self-select jobs from the scopes you've defined automatically.
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- You can also [use tags](../runners/README.md#using-tags) 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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which will let configure them to be provisioned as needed, and scaled down when not.
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This is 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](../../user/gitlab_com/index.md#shared-runners)
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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/gitlab-org/customers-gitlab-com/issues/414)
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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, we use the more highly structured [YAML](https://yaml.org/) format, which
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places scripting elements inside of `script:` blocks separate from the pipeline specification itself.
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This is a strength of GitLab, in that it helps keep the learning curve much simpler to get up and running
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and avoids some of the problem of unconstrained complexity which can make your Jenkinsfiles hard to understand
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and manage.
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That said, we do of course still value DRY (don't repeat yourself) principles and 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/README.md#extends), and `include:` can
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be used to [reuse pipeline configurations](../yaml/README.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](../pipelines/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 a built-in container, NPM, and Maven registry that you
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can leverage. You can see the complete list of packaging features (which includes links to documentation)
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in the [Packaging section of our documentation](../../README.md#package).
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## Integrated features
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Where you may have used plugins to get things like code quality, unit tests, security scanning, and so on 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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If they aren't working as expected, or if you'd like to see what's available, our [CI feature index](../README.md#feature-set) has the full list
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of bundled features and links to the documentation for each.
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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 menu.
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A group administrator 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), which can
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be used by all projects in the group. An instance adminsitrator 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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## Converting Declarative Jenkinsfiles
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Declarative Jenkinsfiles contain "Sections" and "Directives" which are used to control the behavior of your
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pipelines. There are equivalents for all of these in GitLab, which we've documented below.
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This section is based on the [Jenkinsfile syntax documentation](https://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 will be executed. For GitLab, we use the [GitLab Runner](../runners/README.md)
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to provide this capability. You can configure your own runners in Kubernetes or on any host, or take advantage
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of our shared runner fleet (note that the shared runner fleet is only available for GitLab.com users.) The link above will bring you to the documentation which will describe how to get
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up and running quickly. We also support using [tags](../runners/README.md#using-tags) 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/README.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 will apply 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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```
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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 will 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` and `after_script` keywords](../yaml/README.md#before_script-and-after_script):
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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 also lets you define stages, but is a little bit more free-form to configure. The GitLab [`stages` keyword](../yaml/README.md#stages)
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is a top level setting that enumerates the list of stages, but 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/README.md#stage).
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Note that, 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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```
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#### `steps`
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The `steps` section is equivalent to the [`script` section](../yaml/README.md#script) of an individual job. This is
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a simple YAML array 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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```
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### Directives
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#### `environment`
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In GitLab, we use the [`variables` keyword](../yaml/README.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/README.md),
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including the section on [protected variables](../variables/README.md#protected-environment-variables) which 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/README.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 an easy to use
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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, which 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're not using container images with Docker/Kubernetes, for example on Mac or FreeBSD, then the `shell` executor does require you to
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set up your environment either in advance or as part of the jobs. You could create a `before_script`
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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/README.md#when) which is used to indicate when a job should be
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run in case of (or despite) failure, but most of the logic for controlling pipelines can be found in
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our very powerful [`only/except` rules system](../yaml/README.md#onlyexcept-basic)
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(see also our [advanced syntax](../yaml/README.md#onlyexcept-basic)):
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```yaml
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my_job:
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only: [branches]
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```
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