tree: a104c82ba3a5e5a7b5e5ce26ec987bf0921d408c [path history] [tgz]
  1. .gitignore
  2. deployment-mlir-nvidia-production.yaml
  3. deployment-mlir-nvidia-staging.yaml
  7. terraform.tfvars

This folder contains the Terraform configuration to spawn the build bots.

Before deploying anything new, use terraform plan to check that you're only modifying the parts that you intended to.


To set up your local machine to deploy changes to the cluster follow these steps:

  1. Install these tools:
    1. Terraform
    2. Google Cloud SDK
    3. kubectl
  2. Run llvm-zorg/buildbot/google/ to configure the Google Cloud SDK.
  3. To configure the GCP credetianls for terraform run:
     export GOOGLE_APPLICATION_CREDENTIALS=~/.config/gcloud/legacy_credentials/<your email>/adc.json
    Note: Some documentation recommends GOOGLE_CREDENTIALS for this, however this does not work for accessing the Google Cloud Storage backend in terraform. You need to set both variables, as they are required by different tools

Deploying to new Google Cloud project

When deploying this cluster to a completely new Google Cloud project, these manual steps are required:

  • You need to create the GCP project manually before Terraform works.
  • You also need to go to the Kubernetes page once, to enable Kubernetes and Container Registry for that project.
  • GPUs need to be enabled on Kubernetes by following these instructions.
  • Terraform needs to share a “state” between all users. The “backend” for this can be a “bucket” on Google Cloud Storage. So you need to create that bucket and give all users write access. In addition, you should enable “object versioning” to be able to access previous versions of the state in case it gets corrupted:
    gsutil versioning set on gs://<bucket name>
  • Store the secrets (see next section).


To keep secrets a secret, they MUST not be stored in version control. The right place on kubernetes is a “secret”. To create a kubernetes secret for the agent token:

kubectl create secret generic buildbot-token-mlir-nvidia --from-file=token=<file name>

The file in <file name> then must contain the password of the buildbot worker in plain text. In the Deployment of a container, the secret is defined as a special type of volume and mounted in the specified path. During runtime the secret can then be read from that file.

An example: The secret buildbot-token-mlir-nvidia is defined (as above) in Kubernetes. In the deployment mlir-nvidia it is used as a volume of type secret and then mounted at /secrets. During the runtime of the docker container, the script reads the secret from the file /secrets/token and uses it to create the worker configuration.

Using GPUs on Google Cloud

Terraform does not support deployments on GCP using a GPU at the moment. So we need to deploy such cases using plain Kubernetes configuration files. See this issue for more details. The buildbot mlir-nvidia is configured in deployment-mlir-nvidia.yaml in this folder.

For all non-GPU cases add a "kubernetes_deployment" to The contents is identical to the the Kubernetes file, just the markup is different.

Kubernetes files are also declarative, so you can re-deploy them when you made a change. They can be deployed with:

kubectl apply -f myfile.yaml