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A similar experience is available when you configure the Seldon Core Model Deployer through the ZenML dashboard:

Managing Seldon Core Authentication

The Seldon Core Model Deployer requires access to the persistent storage where models are located. In most cases, you will use the Seldon Core model deployer to serve models that are trained through ZenML pipelines and stored in the ZenML Artifact Store, which implies that the Seldon Core model deployer needs to access the Artifact Store.

If Seldon Core is already running in the same cloud as the Artifact Store (e.g. S3 and an EKS cluster for AWS, or GCS and a GKE cluster for GCP), there are ways of configuring cloud workloads to have implicit access to other cloud resources like persistent storage without requiring explicit credentials. However, if Seldon Core is running in a different cloud, or on-prem, or if implicit in-cloud workload authentication is not enabled, then you need to configure explicit credentials for the Artifact Store to allow other components like the Seldon Core model deployer to authenticate to it. Every cloud Artifact Store flavor supports some way of configuring explicit credentials and this is documented for each individual flavor in the Artifact Store documentation.