s to provide GCP credentials to the step operator:use the gcloud CLI to authenticate locally with GCP. This only works in combination with the local orchestrator.Copygcloud auth login

zenml step-operator register <STEP_OPERATOR_NAME> \
    --flavor=vertex \
    --project=<GCP_PROJECT> \
    --region=<REGION> \
#   --machine_type=<MACHINE_TYPE> # optionally specify the type of machine to run on

configure the orchestrator to use a service account key file to authenticate with GCP by setting the service_account_path parameter in the orchestrator configuration to point to a service account key file. This also works only in combination with the local orchestrator.Copyzenml step-operator register <STEP_OPERATOR_NAME> \
    --flavor=vertex \
    --project=<GCP_PROJECT> \
    --region=<REGION> \
    --service_account_path=<SERVICE_ACCOUNT_PATH> \
#   --machine_type=<MACHINE_TYPE> # optionally specify the type of machine to run on

(recommended) configure a GCP Service Connector with GCP credentials coming from a service account key file or the local gcloud CLI set up with user account credentials and then link the Vertex AI Step Operator stack component to the Service Connector. This option works with any orchestrator.Copyzenml service-connector register <CONNECTOR_NAME> --type gcp --auth-method=service-account --project_id=<PROJECT_ID> --service_account_json=@<SERVICE_ACCOUNT_PATH> --resource-type gcp-generic

# Or, as an alternative, you could use the GCP user account locally set up with gcloud
# zenml service-connector register <CONNECTOR_NAME> --type gcp --resource-type gcp-generic --auto-configure

zenml step-operator register <STEP_OPERATOR_NAME> \
    --flavor=vertex \
    --region=<REGION> \
#   --machine_type=<MACHINE_TYPE> # optionally specify the type of machine to run on

zenml step-operator connect <STEP_OPERATOR_NAME> --connector <CONNECTOR_NAME>

We can then use the registered step operator in our active stack:

# Add the step operator to the active stack

zenml stack update -s <NAME>