GCP Python clients for any particular GCP service.This generic GCP resource type is meant to be used with Stack Components that are not represented by one of the other, more specific resource types like GCS buckets, Kubernetes clusters, or Docker registries. For example, it can be used with the Google Cloud Image Builder stack component, or the Vertex AI Orchestrator and Step Operator. It should be accompanied by a matching set of GCP permissions that allow access to the set of remote resources required by the client and Stack Component (see the documentation of each Stack Component for more details).

The resource name represents the GCP project that the connector is authorized to access.

GCS bucket

Allows Stack Components to connect to GCS buckets. When used by Stack Components, they are provided a pre-configured GCS Python client instance.

The configured credentials must have at least the following GCP permissions associated with the GCS buckets that it can access:

storage.buckets.list

storage.buckets.get

storage.objects.create

storage.objects.delete

storage.objects.get

storage.objects.list

storage.objects.update

For example, the GCP Storage Admin role includes all of the required permissions, but it also includes additional permissions that are not required by the connector.

If set, the resource name must identify a GCS bucket using one of the following formats:

GCS bucket URI (canonical resource name): gs://{bucket-name}

GCS bucket name: {bucket-name}

GKE Kubernetes cluster

Allows Stack Components to access a GKE cluster as a standard Kubernetes cluster resource. When used by Stack Components, they are provided a pre-authenticated Python Kubernetes client instance.

The configured credentials must have at least the following GCP permissions associated with the GKE clusters that it can access:

container.clusters.list

container.clusters.get