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What is the title of your presentation?

Implementing resource-driver for K8s Dynamic Resource Allocation (DRA)

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Submission format:

Dual Presentation: 35-minute presentation, limited to 2 speakers

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Who's presenting (email address)? 

email1, email2

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Primary topic:

Runtime Performance + Constrained Environments

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Detailed and focused description:

Dynamic Resource Allocation (DRA) is new approach for allocating HW resource in K8s. It gives much more flexibility and control over resources allocation to the component responsible for particular resource - "resource-driver". This session will show how to create such a resource-driver to utilize K8s DRA: custom resource definitions, API and sequence of event from DRA resource-driver point of view, as well as demo two existing DRA drivers in several use-cases: Nvidia GPU resource-driver, Intel GPU resource-driver and community example implementation of abstract resource-driver for /dev/null device.

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Top 1-3 key takeaways or "Benefits for Ecosystem"

Dynamic Resource Allocation (DRA) is a very new framework in K8s, and spreading the knowledge and sharing the experience in using the DRA as well as creating resource-drivers for it is vital for community to adapt the new framework in fastest possible way as well as increase the HW vendors' contribution to the K8s community.
We will walk through the core parts of the Dynamic Resource Allocation (DRA) resource-driver creation, its operations and expectations with two existing resource-driver examples: GPU resource driver from Nvidia, and GPU resource driver from Intel, and a community example driver (TBD) that can be easily forked as a base for resource-driver implementation. This is supposed to bring to K8s community the knowledge and experience of DRA from vendor and user perspective - how HW vendors and community in general can make use of HW resources in a more flexible, more granular way.