242 lines
8.5 KiB
Markdown
242 lines
8.5 KiB
Markdown
---
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type: reference
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---
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# Optimizing GitLab for large repositories
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Large repositories consisting of more than 50k files in a worktree
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often require special consideration because of
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the time required to clone and check out.
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GitLab and GitLab Runner handle this scenario well
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but require optimized configuration to efficiently perform its
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set of operations.
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The general guidelines for handling big repositories are simple.
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Each guideline is described in more detail in the sections below:
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- Always fetch incrementally. Do not clone in a way that results in recreating all of the worktree.
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- Always use shallow clone to reduce data transfer. Be aware that this puts more burden
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on GitLab instance due to higher CPU impact.
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- Control the clone directory if you heavily use a fork-based workflow.
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- Optimize `git clean` flags to ensure that you remove or keep data that might affect or speed-up your build.
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## Shallow cloning
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> Introduced in GitLab Runner 8.9.
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GitLab and GitLab Runner always perform a full clone by default.
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While it means that all changes from GitLab are received,
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it often results in receiving extra commit logs.
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Ideally, you should always use `GIT_DEPTH` with a small number
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like 10. This will instruct GitLab Runner to perform shallow clones.
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Shallow clones make Git request only the latest set of changes for a given branch,
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up to desired number of commits as defined by the `GIT_DEPTH` variable.
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This significantly speeds up fetching of changes from Git repositories,
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especially if the repository has a very long backlog consisting of number
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of big files as we effectively reduce amount of data transfer.
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The following example makes GitLab Runner shallow clone to fetch only a given branch;
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it does not fetch any other branches nor tags.
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```yaml
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variables:
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GIT_DEPTH: 10
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test:
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script:
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- ls -al
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```
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## Git strategy
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> Introduced in GitLab Runner 8.9.
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By default, GitLab is configured to always prefer the `GIT_STRATEGY: fetch` strategy.
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The `GIT_STRATEGY: fetch` strategy will re-use existing worktrees if found
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on disk. This is different to the `GIT_STRATEGY: clone` strategy
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as in case of clones, if a worktree is found, it is removed before clone.
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Usage of `fetch` is preferred because it reduces the amount of data to transfer and
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does not really impact the operations that you might do on a repository from CI.
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However, `fetch` does require access to the previous worktree. This works
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well when using the `shell` or `docker` executor because these
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try to preserve worktrees and try to re-use them by default.
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This does not work today for `kubernetes` executor and has limitations when using
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`docker+machine`. `kubernetes` executor today always clones into ephemeral directory.
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GitLab also offers the `GIT_STRATEGY: none` strategy. This disables any `fetch` and `checkout` commands
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done by GitLab, requiring you to do them.
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## Git clone path
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> Introduced in GitLab Runner 11.10.
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[`GIT_CLONE_PATH`](../yaml/README.md#custom-build-directories) allows you to
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control where you clone your sources. This can have implications if you
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heavily use big repositories with fork workflow.
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Fork workflow from GitLab Runner's perspective is stored as a separate repository
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with separate worktree. That means that GitLab Runner cannot optimize the usage
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of worktrees and you might have to instruct GitLab Runner to use that.
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In such cases, ideally you want to make the GitLab Runner executor be used only
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for the given project and not shared across different projects to make this
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process more efficient.
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The [`GIT_CLONE_PATH`](../yaml/README.md#custom-build-directories) has to be
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within the `$CI_BUILDS_DIR`. Currently, it is impossible to pick any path
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from disk.
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## Git clean flags
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> Introduced in GitLab Runner 11.10.
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[`GIT_CLEAN_FLAGS`](../yaml/README.md#git-clean-flags) allows you to control
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whether or not you require the `git clean` command to be executed for each CI
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job. By default, GitLab ensures that you have your worktree on the given SHA,
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and that your repository is clean.
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[`GIT_CLEAN_FLAGS`](../yaml/README.md#git-clean-flags) is disabled when set
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to `none`. On very big repositories, this might be desired because `git
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clean` is disk I/O intensive. Controlling that with `GIT_CLEAN_FLAGS: -ffdx
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-e .build/`, for example, allows you to control and disable removal of some
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directories within the worktree between subsequent runs, which can speed-up
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the incremental builds. This has the biggest effect if you re-use existing
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machines and have an existing worktree that you can re-use for builds.
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For exact parameters accepted by
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[`GIT_CLEAN_FLAGS`](../yaml/README.md#git-clean-flags), see the documentation
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for [`git clean`](https://git-scm.com/docs/git-clean). The available parameters
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are dependent on Git version.
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## Fork-based workflow
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> Introduced in GitLab Runner 11.10.
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Following the guidelines above, let's imagine that we want to:
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- Optimize for a big project (more than 50k files in directory).
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- Use forks-based workflow for contributing.
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- Reuse existing worktrees. Have preconfigured runners that are pre-cloned with repositories.
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- Runner assigned only to project and all forks.
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Let's consider the following two examples, one using `shell` executor and
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other using `docker` executor.
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### `shell` executor example
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Let's assume that you have the following [config.toml](https://docs.gitlab.com/runner/configuration/advanced-configuration.html).
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```toml
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concurrent = 4
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[[runners]]
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url = "GITLAB_URL"
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token = "TOKEN"
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executor = "shell"
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builds_dir = "/builds"
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cache_dir = "/cache"
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[runners.custom_build_dir]
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enabled = true
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```
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This `config.toml`:
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- Uses the `shell` executor,
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- Specifies a custom `/builds` directory where all clones will be stored.
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- Enables the ability to specify `GIT_CLONE_PATH`,
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- Runs at most 4 jobs at once.
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### `docker` executor example
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Let's assume that you have the following [config.toml](https://docs.gitlab.com/runner/configuration/advanced-configuration.html).
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```toml
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concurrent = 4
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[[runners]]
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url = "GITLAB_URL"
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token = "TOKEN"
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executor = "docker"
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builds_dir = "/builds"
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cache_dir = "/cache"
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[runners.docker]
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volumes = ["/builds:/builds", "/cache:/cache"]
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```
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This `config.toml`:
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- Uses the `docker` executor,
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- Specifies a custom `/builds` directory on disk where all clones will be stored.
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We host mount the `/builds` directory to make it reusable between subsequent runs
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and be allowed to override the cloning strategy.
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- Doesn't enable the ability to specify `GIT_CLONE_PATH` as it is enabled by default.
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- Runs at most 4 jobs at once.
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### Our `.gitlab-ci.yml`
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Once we have the executor configured, we need to fine tune our `.gitlab-ci.yml`.
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Our pipeline will be most performant if we use the following `.gitlab-ci.yml`:
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```yaml
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variables:
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GIT_DEPTH: 10
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GIT_CLONE_PATH: $CI_BUILDS_DIR/$CI_CONCURRENT_ID/$CI_PROJECT_NAME
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build:
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script: ls -al
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```
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The above configures a:
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- Shallow clone of 10, to speed up subsequent `git fetch` commands.
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- Custom clone path to make it possible to re-use worktrees between parent project and all forks
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because we use the same clone path for all forks.
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Why use `$CI_CONCURRENT_ID`? The main reason is to ensure that worktrees used are not conflicting
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between projects. The `$CI_CONCURRENT_ID` represents a unique identifier within the given executor,
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so as long as we use it to construct the path, it is guaranteed that this directory will not conflict
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with other concurrent jobs running.
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### Store custom clone options in `config.toml`
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Ideally, all job-related configuration should be stored in `.gitlab-ci.yml`.
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However, sometimes it is desirable to make these schemes part of Runner configuration.
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In the above example of Forks, making this configuration discoverable for users may be preferred,
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but this brings administrative overhead as the `.gitlab-ci.yml` needs to be updated for each branch.
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In such cases, it might be desirable to keep the `.gitlab-ci.yml` clone path agnostic, but make it
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a configuration of Runner.
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We can extend our [config.toml](https://docs.gitlab.com/runner/configuration/advanced-configuration.html)
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with the following specification that will be used by Runner if `.gitlab-ci.yml` will not override it:
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```toml
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concurrent = 4
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[[runners]]
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url = "GITLAB_URL"
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token = "TOKEN"
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executor = "docker"
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builds_dir = "/builds"
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cache_dir = "/cache"
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environment = [
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"GIT_DEPTH=10",
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"GIT_CLONE_PATH=$CI_BUILDS_DIR/$CI_CONCURRENT_ID/$CI_PROJECT_NAME"
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]
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[runners.docker]
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volumes = ["/builds:/builds", "/cache:/cache"]
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```
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This makes the cloning configuration to be part of given Runner
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and does not require us to update each `.gitlab-ci.yml`.
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