--- stage: Verify group: Continuous Integration info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments comments: false type: index, howto --- # Migrating from CircleCI If you are currently using CircleCI, you can migrate your CI/CD pipelines to [GitLab CI/CD](../introduction/index.md), and start making use of all its powerful features. Check out our [CircleCI vs GitLab](https://about.gitlab.com/devops-tools/circle-ci-vs-gitlab/) comparison to see what's different. We have collected several resources that you may find useful before starting to migrate. The [Quick Start Guide](../quick_start/README.md) is a good overview of how GitLab CI/CD works. You may also be interested in [Auto DevOps](../../topics/autodevops/index.md) which can be used to build, test, and deploy your applications with little to no configuration needed at all. For advanced CI/CD teams, [custom project templates](../../user/admin_area/custom_project_templates.md) can enable the reuse of pipeline configurations. If you have questions that are not answered here, the [GitLab community forum](https://forum.gitlab.com/) can be a great resource. ## `config.yml` vs `gitlab-ci.yml` CircleCI's `config.yml` configuration file defines scripts, jobs, and workflows (known as "stages" in GitLab). In GitLab, a similar approach is used with a `.gitlab-ci.yml` file in the root directory of your repository. ### Jobs In CircleCI, jobs are a collection of steps to perform a specific task. In GitLab, [jobs](../jobs/index.md) are also a fundamental element in the configuration file. The `checkout` keyword is not necessary in GitLab CI/CD as the repository is automatically fetched. CircleCI example job definition: ```yaml jobs: job1: steps: - checkout - run: "execute-script-for-job1" ``` Example of the same job definition in GitLab CI/CD: ``` yaml job1: script: "execute-script-for-job1" ``` ### Docker image definition CircleCI defines images at the job level, which is also supported by GitLab CI/CD. Additionally, GitLab CI/CD supports setting this globally to be used by all jobs that don't have `image` defined. CircleCI example image definition: ```yaml jobs: job1: docker: - image: ruby:2.6 ``` Example of the same image definition in GitLab CI/CD: ```yaml job1: image: ruby:2.6 ``` ### Workflows CircleCI determines the run order for jobs with `workflows`. This is also used to determine concurrent, sequential, scheduled, or manual runs. The equivalent function in GitLab CI/CD is called [stages](../yaml/README.md#stages). Jobs on the same stage run in parallel, and only run after previous stages complete. Execution of the next stage is skipped when a job fails by default, but this can be allowed to continue even [after a failed job](../yaml/README.md#allow_failure). See [the Pipeline Architecture Overview](../pipelines/pipeline_architectures.md) for guidance on different types of pipelines that you can use. Pipelines can be tailored to meet your needs, such as for a large complex project or a monorepo with independent defined components. #### Parallel and sequential job execution The following examples show how jobs can run in parallel, or sequentially: 1. `job1` and `job2` run in parallel (in the `build` stage for GitLab CI/CD). 1. `job3` runs only after `job1` and `job2` complete successfully (in the `test` stage). 1. `job4` runs only after `job3` completes successfully (in the `deploy` stage). CircleCI example with `workflows`: ```yaml version: 2 jobs: job1: steps: - checkout - run: make build dependencies job2: steps: - run: make build artifacts job3: steps: - run: make test job4: steps: - run: make deploy workflows: version: 2 jobs: - job1 - job2 - job3: requires: - job1 - job2 - job4: requires: - job3 ``` Example of the same workflow as `stages` in GitLab CI/CD: ```yaml stages: - build - test - deploy job 1: stage: build script: make build dependencies job 2: stage: build script: make build artifacts job3: stage: test script: make test job4: stage: deploy script: make deploy ``` #### Scheduled run GitLab CI/CD has an easy to use UI to [schedule pipelines](../pipelines/schedules.md). Also, [rules](../yaml/README.md#rules) can be used to determine if jobs should be included or excluded from a scheduled pipeline. CircleCI example of a scheduled workflow: ```yaml commit-workflow: jobs: - build scheduled-workflow: triggers: - schedule: cron: "0 1 * * *" filters: branches: only: try-schedule-workflow jobs: - build ``` Example of the same scheduled pipeline using [`rules`](../yaml/README.md#rules) in GitLab CI/CD: ```yaml job1: script: - make build rules: - if: '$CI_PIPELINE_SOURCE == "schedule" && $CI_COMMIT_REF_NAME == "try-schedule-workflow"' ``` After the pipeline configuration is saved, you configure the cron schedule in the [GitLab UI](../pipelines/schedules.md#configuring-pipeline-schedules), and can enable or disable schedules in the UI as well. #### Manual run CircleCI example of a manual workflow: ```yaml release-branch-workflow: jobs: - build - testing: requires: - build - deploy: type: approval requires: - testing ``` Example of the same workflow using [`when: manual`](../yaml/README.md#whenmanual) in GitLab CI/CD: ```yaml deploy_prod: stage: deploy script: - echo "Deploy to production server" when: manual ``` ### Filter job by branch [Rules](../yaml/README.md#rules) are a mechanism to determine if the job runs for a specific branch. CircleCI example of a job filtered by branch: ```yaml jobs: deploy: branches: only: - master - /rc-.*/ ``` Example of the same workflow using `rules` in GitLab CI/CD: ```yaml deploy_prod: stage: deploy script: - echo "Deploy to production server" rules: - if: '$CI_COMMIT_BRANCH == "master"' ``` ### Caching GitLab provides a caching mechanism to speed up build times for your jobs by reusing previously downloaded dependencies. It's important to know the different between [cache and artifacts](../caching/index.md#cache-vs-artifacts) to make the best use of these features. CircleCI example of a job using a cache: ```yaml jobs: job1: steps: - restore_cache: key: source-v1-< .Revision > - checkout - run: npm install - save_cache: key: source-v1-< .Revision > paths: - "node_modules" ``` Example of the same pipeline using `cache` in GitLab CI/CD: ```yaml image: node:latest # Cache modules in between jobs cache: key: $CI_COMMIT_REF_SLUG paths: - .npm/ before_script: - npm ci --cache .npm --prefer-offline test_async: script: - node ./specs/start.js ./specs/async.spec.js ``` ## Contexts and variables CircleCI provides [Contexts](https://circleci.com/docs/2.0/contexts/) to securely pass environment variables across project pipelines. In GitLab, a [Group](../../user/group/index.md) can be created to assemble related projects together. At the group level, [variables](../variables/README.md#group-level-environment-variables) can be stored outside the individual projects, and securely passed into pipelines across multiple projects. ## Orbs There are two GitLab issues open addressing CircleCI Orbs and how GitLab can achieve similar functionality. - [issue #1151](https://gitlab.com/gitlab-com/Product/-/issues/1151) - [issue #195173](https://gitlab.com/gitlab-org/gitlab/-/issues/195173) ## Build environments CircleCI offers `executors` as the underlying technology to run a specific job. In GitLab, this is done by [runners](https://docs.gitlab.com/runner/). The following environments are supported: Self-managed runners: - Linux - Windows - macOS GitLab.com shared runners: - Linux - Windows - [Planned: macOS](https://gitlab.com/gitlab-com/gl-infra/infrastructure/-/issues/5720) ### Machine and specific build environments [Tags](../yaml/README.md#tags) can be used to run jobs on different platforms, by telling GitLab which runners should run the jobs. CircleCI example of a job running on a specific environment: ```yaml jobs: ubuntuJob: machine: image: ubuntu-1604:201903-01 steps: - checkout - run: echo "Hello, $USER!" osxJob: macos: xcode: 11.3.0 steps: - checkout - run: echo "Hello, $USER!" ``` Example of the same job using `tags` in GitLab CI/CD: ```yaml windows job: stage: - build tags: - windows script: - echo Hello, %USERNAME%! osx job: stage: - build tags: - osx script: - echo "Hello, $USER!" ```