Multi-tenant GPU clusters force platform teams into ugly trade-offs. Static partitioning wastes hardware; looser sharing pushes risk onto operators. A node can look healthy while part of its GPU inventory is no longer safe to assign. The question is not whether GPUs can be shared, but whether they can be shared safely.

This session examines Dynamic Resource Allocation through a multi-tenancy lens. Speakers show how DRA improves shared accelerator infrastructure, why device taints, binding conditions, admin access, and finer authorization matter, and what still requires policy above Kubernetes.

Using upstream Kubernetes and the open source NVIDIA DRA driver as references, attendees learn how to evaluate access boundaries, degraded-device handling, and the difference between schedulable and safe-to-reuse. They leave with a framework for multi-tenant GPU platforms and the controls still needed around DRA.