- Machine types available for private projects (x86-64)
- Example of how to tag a job
- SaaS runners for GitLab projects
- SaaS runners on Linux settings
- Pre-clone script
When you run jobs on SaaS runners on Linux, the runners are on auto-scaled ephemeral virtual machine (VM) instances.
Each VM uses the Google Container-Optimized OS (COS) and the latest version of Docker Engine.
The default region for the VMs is
For the SaaS runners on Linux, GitLab offers a range of machine types for use in private projects. For Free, Premium, and Ultimate plan customers, jobs on these instances consume the CI/CD minutes allocated to your namespace.
|Specs||1 vCPU, 3.75GB RAM||2 vCPUs, 8GB RAM||4 vCPUs, 16GB RAM|
|GitLab CI/CD tags|
|Subscription||Free, Premium, Ultimate||Free, Premium, Ultimate||Premium, Ultimate|
small machine type is the default. Your job runs on this machine type if you don’t specify
a tags: keyword in your
CI/CD jobs that run on
large machine types will consume CI minutes at a different rate than CI/CD jobs on the
small machine type.
Refer to the CI/CD minutes cost factor for the cost factor applied to the machine type based on size.
To use a machine type other than
small, add a
tags: keyword to your job.
stages: - Prebuild - Build - Unit Test job_001: stage: Prebuild script: - echo "this job runs on the default (small) instance" job_002: tags: [ saas-linux-medium-amd64 ] stage: Build script: - echo "this job runs on the medium instance" job_003: tags: [ saas-linux-large-amd64 ] stage: Unit Test script: - echo "this job runs on the large instance"
gitlab-shared-runners-manager-X.gitlab.com fleet of runners are dedicated for
GitLab projects and related community forks. These runners are backed by a Google Compute
n1-standard-2 machine type and do not run untagged jobs. Unlike the machine types used
for private projects, each virtual machine is re-used up to 40 times.
Below are the settings for SaaS runners on Linux.
|Default Docker image||-|
Cache: These runners share a distributed cache that’s stored in a Google Cloud Storage (GCS) bucket. Cache contents not updated within the last 14 days are automatically removed, based on the object lifecycle management policy.
With SaaS runners on Linux, you can run commands in a CI/CD
job before the runner attempts to run
git init and
git fetch to
download a GitLab repository. The
can be used for:
- Seeding the build directory with repository data
- Sending a request to a server
- Downloading assets from a CDN
- Any other commands that must run before the
To use this feature, define a CI/CD variable called
CI_PRE_CLONE_SCRIPT that contains a bash script.
CI_PRE_CLONE_SCRIPTvariable does not work on GitLab SaaS Windows or macOS runners.
This example was used in the
gitlab-org/gitlab project until November 2021.
The project no longer uses this optimization because the
lets Gitaly serve the full CI/CD fetch traffic. See Git fetch caching.
CI_PRE_CLONE_SCRIPT was defined as a project CI/CD variable:
( echo "Downloading archived master..." wget -O /tmp/gitlab.tar.gz https://storage.googleapis.com/gitlab-ci-git-repo-cache/project-278964/gitlab-master-shallow.tar.gz if [ ! -f /tmp/gitlab.tar.gz ]; then echo "Repository cache not available, cloning a new directory..." exit fi rm -rf $CI_PROJECT_DIR echo "Extracting tarball into $CI_PROJECT_DIR..." mkdir -p $CI_PROJECT_DIR cd $CI_PROJECT_DIR tar xzf /tmp/gitlab.tar.gz rm -f /tmp/gitlab.tar.gz chmod a+w $CI_PROJECT_DIR )
The first step of the script downloads
gitlab-master.tar.gz from Google Cloud Storage.
There was a GitLab CI/CD job named
that was responsible for keeping that archive up-to-date. Every two hours on a scheduled pipeline,
it did the following:
- Create a fresh clone of the
gitlab-org/gitlabrepository on GitLab.com.
- Save the data as a
- Upload it into the Google Cloud Storage bucket.
When a job ran with this configuration, the output looked similar to:
$ eval "$CI_PRE_CLONE_SCRIPT" Downloading archived master... Extracting tarball into /builds/gitlab-org/gitlab... Fetching changes... Reinitialized existing Git repository in /builds/gitlab-org/gitlab/.git/
Reinitialized existing Git repository message shows that
the pre-clone step worked. The runner runs
git init, which
overwrites the Git configuration with the appropriate settings to fetch
from the GitLab repository.
CI_REPO_CACHE_CREDENTIALS must contain the Google Cloud service account
JSON for uploading to the
Note that this bucket should be located in the same continent as the runner, or you can incur network egress charges.
The full contents of our
Google Cloud Platform
concurrent = X check_interval = 1 metrics_server = "X" sentry_dsn = "X" [[runners]] name = "docker-auto-scale" request_concurrency = X url = "https://gitlab.com/" token = "SHARED_RUNNER_TOKEN" pre_clone_script = "eval \"$CI_PRE_CLONE_SCRIPT\"" executor = "docker+machine" environment = [ "DOCKER_DRIVER=overlay2", "DOCKER_TLS_CERTDIR=" ] limit = X [runners.docker] image = "ruby:2.5" privileged = true volumes = [ "/certs/client", "/dummy-sys-class-dmi-id:/sys/class/dmi/id:ro" # Make kaniko builds work on GCP. ] [runners.machine] IdleCount = 50 IdleTime = 3600 MaxBuilds = 1 # For security reasons we delete the VM after job has finished so it's not reused. MachineName = "srm-%s" MachineDriver = "google" MachineOptions = [ "google-project=PROJECT", "google-disk-size=25", "google-machine-type=n1-standard-1", "google-username=core", "google-tags=gitlab-com,srm", "google-use-internal-ip", "google-zone=us-east1-d", "engine-opt=mtu=1460", # Set MTU for container interface, for more information check https://gitlab.com/gitlab-org/gitlab-runner/-/issues/3214#note_82892928 "google-machine-image=PROJECT/global/images/IMAGE", "engine-opt=ipv6", # This will create IPv6 interfaces in the containers. "engine-opt=fixed-cidr-v6=fc00::/7", "google-operation-backoff-initial-interval=2" # Custom flag from forked docker-machine, for more information check https://github.com/docker/machine/pull/4600 ] [[runners.machine.autoscaling]] Periods = ["* * * * * sat,sun *"] Timezone = "UTC" IdleCount = 70 IdleTime = 3600 [[runners.machine.autoscaling]] Periods = ["* 30-59 3 * * * *", "* 0-30 4 * * * *"] Timezone = "UTC" IdleCount = 700 IdleTime = 3600 [runners.cache] Type = "gcs" Shared = true [runners.cache.gcs] CredentialsFile = "/path/to/file" BucketName = "bucket-name"