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---
stage: Verify
group: Runner
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
---
# SaaS runners on Linux
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 `us-east1`.
## Machine types available for private projects (x86-64)
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.
| | Small | Medium | Large |
|-------------------|---------------------------|---------------------------|--------------------------|
| Specs | 2 vCPU, 8 GB RAM | 4 vCPUs, 16 GB RAM | 8 vCPUs, 32 GB RAM |
| GitLab CI/CD tags | `saas-linux-small-amd64` | `saas-linux-medium-amd64` | `saas-linux-large-amd64` |
| Subscription | Free, Premium, Ultimate | Free, Premium, Ultimate | Premium, Ultimate |
The `small` machine type is the default. Your job runs on this machine type if you don't specify
a [tags:](../../yaml/index.md#tags) keyword in your `.gitlab-ci.yml` file.
CI/CD jobs that run on `medium` and `large` machine types consumes CI minutes at a different rate than CI/CD jobs on the `small` machine type.
Refer to the CI/CD minutes [cost factor](../../../ci/pipelines/cicd_minutes.md#cost-factor) for the cost factor applied to the machine type based on size.
## GPU-enabled SaaS runners on Linux **(PREMIUM SAAS)**
We offer GPU-enabled SaaS runners for heavy compute including ModelOps or HPC workloads. Available to Premium and Ultimate plan customers, jobs on these instances consume the CI/CD minutes allocated to your namespace.
| | Standard |
|-------------------|---------------------------|
| Specs | 4 vCPU, 16 GB RAM, 1 Nvidia Tesla T4 GPU (or similar) |
| GitLab CI/CD tags | `saas-linux-medium-amd64-gpu-standard` |
## Example of how to tag a job
To use a machine type other than `small`, add a `tags:` keyword to your job.
For example:
```yaml
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"
```
## SaaS runners for GitLab projects
The `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.
## SaaS runners on Linux settings
Below are the settings for SaaS runners on Linux.
| Setting | GitLab.com | Default |
|-------------------------------------------------------------------------|------------------|---------|
| Executor | `docker+machine` | - |
| Default Docker image | `ruby:3.1` | - |
| `privileged` (run [Docker in Docker](https://hub.docker.com/_/docker/)) | `true` | `false` |
- **Cache**: These runners share a
[distributed cache](https://docs.gitlab.com/runner/configuration/autoscale.html#distributed-runners-caching)
that's stored in a Google Cloud Storage (GCS) bucket. Cache contents not updated in
the last 14 days are automatically removed, based on the
[object lifecycle management policy](https://cloud.google.com/storage/docs/lifecycle).
- **Timeout settings**: Jobs handled by the SaaS Runners on Linux
**time out after 3 hours**, regardless of the timeout configured in a
project. For details, see issues [#4010](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/4010)
and [#4070](https://gitlab.com/gitlab-com/gl-infra/reliability/-/issues/4070).
NOTE:
SaaS runner instances are provisioned with a 25 GB storage volume. The underlying disk space of the storage volume
is shared by the operating system, the Docker image, and a copy of your cloned repository.
This means that the available free disk space that your jobs can use is **less than 25 GB**.
## Pre-clone script (deprecated)
WARNING:
This feature was [deprecated](https://gitlab.com/gitlab-org/gitlab/-/issues/391896) in GitLab 15.9
and is planned for removal in 16.0. Use [`pre_get_sources_script`](../../../ci/yaml/index.md#hookspre_get_sources_script) instead. This change is a breaking change.
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
[`pre_clone_script`](https://docs.gitlab.com/runner/configuration/advanced-configuration.html#the-runners-section)
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 `git init`
To use this feature, define a [CI/CD variable](../../../ci/variables/index.md) called
`CI_PRE_CLONE_SCRIPT` that contains a bash script.
NOTE:
The `CI_PRE_CLONE_SCRIPT` variable does not work on GitLab SaaS Windows or macOS runners.
### Pre-clone script example
This example was used in the `gitlab-org/gitlab` project until November 2021.
The project no longer uses this optimization because the
[pack-objects cache](../../../administration/gitaly/configure_gitaly.md#pack-objects-cache)
lets Gitaly serve the full CI/CD fetch traffic. See [Git fetch caching](../../../development/pipelines/performance.md#git-fetch-caching).
The `CI_PRE_CLONE_SCRIPT` was defined as a project CI/CD variable:
```shell
(
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 `cache-repo`](https://gitlab.com/gitlab-org/gitlab/-/blob/5fb40526c8c8aaafc5f92eab36d5bbddaca3893d/.gitlab/ci/cache-repo.gitlab-ci.yml)
that was responsible for keeping that archive up-to-date. Every two hours on a scheduled pipeline,
it did the following:
1. Create a fresh clone of the `gitlab-org/gitlab` repository on GitLab.com.
1. Save the data as a `.tar.gz`.
1. Upload it into the Google Cloud Storage bucket.
When a job ran with this configuration, the output looked similar to:
```shell
$ eval "$CI_PRE_CLONE_SCRIPT"
Downloading archived master...
Extracting tarball into /builds/gitlab-org/gitlab...
Fetching changes...
Reinitialized existing Git repository in /builds/gitlab-org/gitlab/.git/
```
The `Reinitialized existing Git repository` message shows that
the pre-clone step worked. The runner runs `git init`, which
overwrites the Git configuration with the appropriate settings to fetch
from the GitLab repository.
`CI_REPO_CACHE_CREDENTIALS` must contain the Google Cloud service account
JSON for uploading to the `gitlab-ci-git-repo-cache` bucket.
This bucket should be located in the same continent as the
runner, or [you can incur network egress charges](https://cloud.google.com/storage/pricing).
## `config.toml`
The full contents of our `config.toml` are:
NOTE:
Settings that are not public are shown as `X`.
**Google Cloud Platform**
```toml
concurrent = X
check_interval = 1
metrics_server = "X"
sentry_dsn = "X"
[[runners]]
name = "docker-auto-scale"
request_concurrency = X
url = "https://gitlab.com/"
token = "SHARED_RUNNER_TOKEN"
pre_clone_script = "eval \"$CI_PRE_CLONE_SCRIPT\""
executor = "docker+machine"
environment = [
"DOCKER_DRIVER=overlay2",
"DOCKER_TLS_CERTDIR="
]
limit = X
[runners.docker]
image = "ruby:3.1"
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"
```
|
