9.2 KiB
stage | group | info |
---|---|---|
Verify | Runner | 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 | 1 vCPU, 3.75GB RAM | 2 vCPUs, 8GB RAM | 4 vCPUs, 16GB 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: keyword in your .gitlab-ci.yml
file.
CI/CD jobs that run on medium
and 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.
Example of how to tag a job
To use a machine type other than small
, add a tags:
keyword to your job.
For example:
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:2.5 |
- |
privileged (run Docker in Docker) |
true |
false |
-
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.
-
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 and #4070.
NOTE: The final disk space your jobs can use will be less than 25GB. Some disk space allocated to the instance will be occupied by the operating system, the Docker image, and a copy of your cloned repository.
Pre-clone script
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
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 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
lets Gitaly serve the full CI/CD fetch traffic. See Git fetch caching.
The 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 cache-repo
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/gitlab
repository on GitLab.com. - Save the data as a
.tar.gz
. - Upload it into the Google Cloud Storage bucket.
When a job ran with this configuration, the output looked similar to:
$ eval "$CI_PRE_CLONE_SCRIPT"
Downloading archived master...
Extracting tarball into /builds/gitlab-org/gitlab...
Fetching changes...
Reinitialized existing Git repository in /builds/gitlab-org/gitlab/.git/
The Reinitialized existing Git repository
message shows that
the pre-clone step worked. The runner runs git init
, which
overwrites the Git configuration with the appropriate settings to fetch
from the GitLab repository.
CI_REPO_CACHE_CREDENTIALS
must contain the Google Cloud service account
JSON for uploading to the gitlab-ci-git-repo-cache
bucket.
Note that this bucket should be located in the same continent as the runner, or you can incur network egress charges.
config.toml
The full contents of our config.toml
are:
NOTE:
Settings that are not public are shown as X
.
Google Cloud Platform
concurrent = X
check_interval = 1
metrics_server = "X"
sentry_dsn = "X"
[[runners]]
name = "docker-auto-scale"
request_concurrency = X
url = "https://gitlab.com/"
token = "SHARED_RUNNER_TOKEN"
pre_clone_script = "eval \"$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"