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Cirun configuration

File: .cirun.yml

API documentation for Cirun.yml file.

Runners: runners​

It containers 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​

It can be seen from "gcloud compute images list"

machine_image: "ubuntu-minimal-2004-lts"

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"  # Example 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, some of the examples are:

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

Custom Disk Size for Azure​

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

    extra_config:
      storageProfile:
        osDisk:
          diskSizeGB: 512

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: cache-disk
        diskSizeGb: 122
        source: "projects/<PROJECT-ID>/regions/<ZONE>/disks/cache-disk"
        type: "PERSISTENT"
        mode: READ_WRITE
        interface: SCSI

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"