
gs://zenml-bucket-sl

gs://zenml-core.appspot.comgs://zenml-core_cloudbuild

gs://zenml-datasets

Please select one or leave it empty to create a connector that can be used to access any of them []: gs://zenml-datasets

Successfully registered service connector `gcp-interactive` with access to the following resources:

┏━━━━━━━━━━━━━━━┯━━━━━━━━━━━━━━━━━━━━━┓

┃ RESOURCE TYPE │ RESOURCE NAMES      ┃

┠───────────────┼─────────────────────┨

┃ 📦 gcs-bucket │ gs://zenml-datasets ┃

┗━━━━━━━━━━━━━━━┷━━━━━━━━━━━━━━━━━━━━━┛

Regardless of how you came here, you should already have some idea of the following:

the type of resources that you want to connect ZenML to. This may be a Kubernetes cluster, a Docker container registry or an object storage service like AWS S3 or GCS.

the Service Connector implementation (i.e. Service Connector Type) that you want to use to connect to those resources. This could be one of the cloud provider Service Connector Types like AWS and GCP that provide access to a broader range of services, or one of the basic Service Connector Types like Kubernetes or Docker that only target a specific resource.

the credentials and authentication method that you want to use

Other questions that should be answered in this section:

are you just looking to connect a ZenML Stack Component to a single resource? or would you rather configure a wide-access ZenML Service Connector that gives ZenML and all its users access to a broader range of resource types and resource instances with a single set of credentials issued by your cloud provider?

have you already provisioned all the authentication prerequisites (e.g. service accounts, roles, permissions) and prepared the credentials you will need to configure the Service Connector? If you already have one of the cloud provider CLIs configured with credentials on your local host, you can easily use the Service Connector auto-configuration capabilities to get faster where you need to go.