Dynamic Resource Allocation (DRA) introduces a new paradigm for requesting, configuring, and sharing GPU resources in Kubernetes. It enables fine-grained, flexible resource management for AI/ML workloads in a unified and customizable manner.

This session provides a concise guide and live demo on installing, configuring and using DRA. Attendees will learn how to use DRA to effectively manage GPU resources in a kind cluster on a local Linux machine, covering the following use cases:

- A single pod/container using a dedicated GPU
- Multiple containers within a single pod sharing a dedicated GPU
- Multiple pods/containers sharing a dedicated GPU using different strategies: Time-Slicing and Multiple Process Service (MPS)
- Multiple pods/containers sharing multiple GPUs with Multiple Instance GPU (MIG)
- Layered GPU sharing across multiple pods/containers, such as Time-Slicing on MIG and MPS on MIG