er Image Builder stack component, or the Vertex AIOrchestrator 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.

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

access.

📦 GCP GCS bucket (resource type: gcs-bucket)

Authentication methods: implicit, user-account, service-account, oauth2-token,

impersonation

Supports resource instances: True

Authentication methods:

🔒 implicit

🔒 user-account

🔒 service-account

🔒 oauth2-token

🔒 impersonation

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: gs://{bucket-name}

GCS bucket name: {bucket-name}

[...]

────────────────────────────────────────────────────────────────────────────────

Please select a resource type or leave it empty to create a connector that can be used to access any of the supported resource types (gcp-generic, gcs-bucket, kubernetes-cluster, docker-registry). []: gcs-bucket

Would you like to attempt auto-configuration to extract the authentication configuration from your local environment ? [y/N]: y

Service connector auto-configured successfully with the following configuration:

Service connector 'gcp-interactive' of type 'gcp' is 'private'.

'gcp-interactive' gcp Service

Connector Details

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