Multiple Cloudera AI Registries connected to a single Cloudera AI Inference service

Cloudera supports deploying Cloudera AI Inference service connecting to multiple Cloudera AI Registries in Cloudera AI 1.5.5 SP3 and higher releases.

This model allows you to maintain separate registries for different teams, projects, or environments, such as development, staging, and production, while using one centrally managed inference service to deploy and serve models. Each registry can be independently deployed, upgraded, or scaled, providing strong isolation and governance.

In this architecture, Cloudera AI Inference service acts as the unified inference layer that consumes models from any connected Cloudera AI Registry instance. Each Cloudera AI Registry has its own model catalog, versioning, access controls, and lifecycle management, but all models selected for serving are pushed to the same inference endpoint environment. This simplifies operational consistency because monitoring, autoscaling, and serving configurations are defined once within Cloudera AI Inference service, regardless of how many registries feed into it.

A key benefit of this approach is organizational flexibility. Different business units can maintain their own registries with customized access policies, resource configurations, or upgrade cycles. At the same time, the shared Cloudera AI Inference service ensures consistent model‑serving behavior and streamlined infrastructure use across the platform. This is especially useful for large enterprises or multi‑team environments where each group needs autonomy over model management but benefits from shared compute resources for inference.