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Cirun configuration

File: .cirun.yml

API documentation for Cirun.yml file.

Runners: runners​

It contains the spec for the runners that will be spun on each commit.

runners:
  - name: gpu-runner
    cloud: gcp
    gpu: nvidia-tesla-t4
    instance_type: n1-standard-1
    machine_image: ubuntu-minimal-2004-lts
    preemptible: true
    labels:
      - cirun-gpu-runner

Name: name​

Name of the runner.

Cloud: cloud​

Name of the cloud provider, here are the possible options:

  • Google Cloud Platform
cloud: gcp
  • Amazon Web Services
cloud: aws
  • DigitalOcean
cloud: do
  • Azure
cloud: azure
  • Openstack
cloud: openstack
  • Oracle
cloud: oracle

GPU: gpu​

Name of the GPU if runner is required with a GPU. See Cloud provider's documentation for gpu names.

gpu: nvidia-tesla-t4
note

This flag also installs nvidia-drivers in the given VM

note

For using GPUs on AWS, we recommend using NVIDIA Deep Learning AMI from AWS Marketplace. See the Custom Images section for the documentation on how to use that. Also note this flag is not required for NVIDIA Deep Learning AMI image on AWS.

Instance Type: instance_type​

Name of the instance depending on the cloud provider.

instance_type: n1-standard-1  # For GCP
instance_type: t3.nano  # For AWS
instance_type: s-1vcpu-1gb  # For DigitalOcean
instance_type: Standard_DS1_v2  # For Azure
instance_type: m1.small  # For Openstack

Machine Image: machine_image​

The OS image for the runner.

GCP​

GCP supports two types of images with multiple format options:

Custom Images (disk images created from instances or uploaded):

# Simple name (searches in ubuntu-os-cloud project by default)
machine_image: ubuntu-minimal-2004-lts

# Project-scoped format (project:image) - recommended for custom images
machine_image: "my-project:my-custom-image"

# Full projects path
machine_image: "projects/my-project/global/images/my-custom-image"

# HTTP self-link URL
machine_image: "https://www.googleapis.com/compute/v1/projects/my-project/global/images/my-image"

Machine Images (snapshots of entire VM instances including attached disks):

# Project-scoped format (project:image)
machine_image: "my-project:my-machine-image"

# Full projects path
machine_image: "projects/my-project/global/machineImages/my-machine-image"

# HTTP self-link URL
machine_image: "https://www.googleapis.com/compute/beta/projects/my-project/global/machineImages/my-machine-image"

AWS​

Amazon Machine image ID

machine_image: ami-06fd8a495a537da8b

DigitalOcean​

Slug of the machine image, can be obtained from DigitalOcean CLI via: doctl compute image list --public

machine_image: ubuntu-20-04-x64

Azure​

Machine image takes 4 parameters(publisher, offer, sku, version) for available images on Azure. For custom images, it takes only one parameter(id). Images can be obtained from Azure CLI via: az vm image list --output table

machine_image:
  publisher: Canonical
  offer: UbuntuServer
  sku: "18.04-LTS"
  version: latest

Openstack​

In OpenStack cloud by default you are provided with cirros image, you can also build your custom image and use them. You can see all your images in the dashboard or can also use the OpenStack CLI command openstack image list.

machine_image: cirros-0.5.2-x86_64-disk

Preemptible: preemptible​

Option to chose low cost instances, also knows as preemptible in GCP and Spot in AWS, default is false. This is not applicable for DigitalOcean and Openstack as they don't support preemptible instances.

preemptible: true

Region: region​

Region to spin up runners in your cloud account.

region: us-central1-b  # Zone for GCP

Labels: labels​

Add label(s) to your runner definition, so that you can add the same or subset of these labels in the "runs-on" param in .github/workflows/.yml So that this runner is created for running the workflow.

labels:
  - cirun-runner
  - cirun-gpu-runner
Labels

Labels must start with prefix cirun-

Extra configuration: extra_config​

This section is specific to the cloud provider and can be used to add extra configuration for the runner.

AWS Extra Configuration​

Custom Disk Size for AWS​

To customize the root volume size for runners spun up on AWS:

    extra_config:
      BlockDeviceMappings:
        - DeviceName: /dev/sda1
          VolumeSize: 75
          VolumeType: gp2

GCP Extra Configuration​

Custom Disk Size for GCP​

To customize the root volume size for runners spun up on GCP:

    extra_config:
      baseDisk:
        diskSizeGb: 101
      additionalDisk:
        diskSizeGb: 42
        diskType: "projects/<PROJECT-ID>/zones/<ZONE>/diskTypes/pd-balanced"
      existingDisk:
        deviceName: <DEVICE-NAME>
        diskSizeGb: 122
        source: "projects/<PROJECT-ID>/regions/<ZONE>/disks/<DISK-NAME>"
        type: PERSISTENT
        mode: READ_WRITE
        interface: SCSI

Project for GCP​

To customize the project to deploy the runner in GCP, you can set the project id in the extra_config section. The default project_id is the project id of the service account you have provided in the credentials on cirun dashboard.

    extra_config:
      project_id: my-project-id

Network Interfaces for GCP​

Custom network configuration for GCP instances. This is particularly important for certain instance types.

    extra_config:
      networkInterfaces:
        - network: "global/networks/default"
          accessConfigs:
            - type: ONE_TO_ONE_NAT
              name: "External NAT"
              networkTier: PREMIUM

GVNIC Network Interface (Required for third-generation machine types: C3, N2, N2D, T2A):

    extra_config:
      networkInterfaces:
        - nicType: GVNIC
          network: "global/networks/default"
          accessConfigs:
            - type: ONE_TO_ONE_NAT
              name: "External NAT"
              networkTier: PREMIUM
          stackType: IPV4_ONLY
          subnetwork: "projects/<PROJECT-ID>/regions/<REGION>/subnetworks/<SUBNET-NAME>"

Custom Images and GVNIC​

note

When using third-generation machine types (C3, N2, N2D, T2A) or Confidential VM instances, your custom image must be created with the GVNIC guest OS feature. This is done during image creation with:

gcloud compute images create my-image --source-disk=my-disk --guest-os-features=GVNIC

To check if an existing image has the GVNIC feature:

gcloud compute images describe my-image --project=my-project --format="value(guestOsFeatures[].type)"

Additionally, you must configure GVNIC network interface in your runner configuration as shown above.

See Using gVNIC and Machine Types for more details.

Service Accounts for GCP​

Configure service accounts for the instance.

    extra_config:
      serviceAccounts:
        - email: "my-service-account@my-project.iam.gserviceaccount.com"
          scopes:
            - "https://www.googleapis.com/auth/cloud-platform"
            - "https://www.googleapis.com/auth/compute"

Azure Extra Configuration​

Custom Disk Size for Azure​

To customize the root volume size for runners spun up on Azure:

    extra_config:
      storageProfile:
        osDisk:
          diskSizeGB: 512

Enable public IP address for Azure​

This will enable provisioning of public ip address on VMs created on Azure.

    extra_config:
      enable_public_ip: true

General Extra Configuration​

Custom Provisioning​

This is used to control how the runner is provisioned, for example, you can create a custom image that runs a custom startup script on the vm startup and then pull the runner provisioning script from cirun's API and run it, instead of cirun just running the provisioning script on startup. This gives you more control over the provisioning process and run custom scripts on the runner startup, before the runner is ready to run the workflows.

    extra_config:
      provision_via: pull_from_api

To pull the provisioning script from cirun's API, you need to set the provision_via to pull_from_api in your .cirun.yml file and then you need to call the API in your startup script to get the provisioning script.

The API endpoint is /api/runner-provision?runner_name=<runner_name> and it returns the provisioning script. You would need to call this API with cirun's API token in the header. The runner name is available in the runner tags in the runner's metadata in the key "Name".

Interactive Runner on Windows​

Cirun supports interactive runners on Windows for use cases such as:

  • Desktop GUI-based testing
  • QA workflows
  • Workloads that require an active session

This will start the runner in an interactive desktop session (instead of a headless background service), making it suitable for tools that require a GUI.

    extra_config:
      run_as: interactive

Custom Runner User on Windows​

Specifies the Windows user account to run the GitHub Actions runner under.

    extra_config:
      runner_user: runner

Custom Runner Path on Windows​

Overrides the default runner installation path on Windows.

    extra_config:
      runner_path: "C:\\r"

Environment Variables​

Configure custom environment variables to be automatically set on all runners. This is useful for setting non-sensitive configuration values that your workflows need.

    extra_config:
      env_vars:
        NODE_ENV: production
        API_ENDPOINT: https://api.example.com
caution

Do not use this for secrets or sensitive information. Environment variables set via env_vars may be visible in logs and process lists. For secrets, use GitHub's encrypted secrets or other secure secret management solutions.

note

These environment variables are set at the system level and will be available to all processes running on the runner, including your GitHub Actions workflows.