The New Stack Podcast11 Des 2025

Kubernetes GPU Management Just Got a Major Upgrade

Nvidia Distinguished Engineer Kevin Klues noted that low-level systems work is invisible when done well and highly visible when it fails — a dynamic that frames current Kubernetes innovations for AI. At KubeCon + CloudNativeCon North America 2025, Klues and AWS product manager Jesse Butler discussed two emerging capabilities: dynamic resource allocation (DRA) and a new workload abstraction designed for sophisticated AI scheduling.

DRA, now generally available in Kubernetes 1.34, fixes long-standing limitations in GPU requests. Instead of simply asking for a number of GPUs, users can specify types and configurations. Modeled after persistent volumes, DRA allows any specialized hardware to be exposed through standardized interfaces, enabling vendors to deliver custom device drivers cleanly. Butler called it one of the most elegant designs in Kubernetes.

Yet complex AI workloads require more coordination. A forthcoming workload abstraction, debuting in Kubernetes 1.35, will let users define pod groups with strict scheduling and topology rules — ensuring multi-node jobs start fully or not at all. Klues emphasized that this abstraction will shape Kubernetes’ AI trajectory for the next decade and encouraged community involvement.

Learn more from The New Stack about dynamic resource allocation:

Kubernetes Primer: Dynamic Resource Allocation (DRA) for GPU Workloads

Kubernetes v1.34 Introduces Benefits but Also New Blind Spots

Join our community of newsletter subscribers to stay on top of the news and at the top of your game.

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(300)

Why CPUs still matter in the age of AI agents

As AI evolves from conversational chatbots to autonomous agents, CPUs are becoming an increasingly important part of the infrastructure equation. In this episode, The New Stack speaks with Bhumik Pate...

11 Aug 26min

Why Doist Says Less AI Can Deliver More

Doist CTO Gonçalo Silva says AI is reshaping software development, but success depends on restraint rather than rapid feature expansion. Instead of chasing every AI capability, Doist prioritizes “subt...

31 Jul 35min

Why your company should (try to) build its own AI SRE

As AI coding agents accelerate software development, they also create new challenges for site reliability engineers (SREs), who are increasingly responsible for debugging systems that no single human ...

30 Jul 30min

Nvidia

In this episode with The New Stack Agents, Frederic Lardinois, NVIDIA’s Joey Conway says advances in AI over the past year have dramatically improved the capabilities of local models, making them prac...

23 Jul 32min

Meet Brain, the AI that decides when Azure is officially down

In this episode, Mark Russinovich, CTO of Microsoft Azure revealed Brain, the AI-powered AIOps system that continuously monitors Azure’s health, detects incidents, identifies root causes, and increasi...

14 Jul 19min

What comes after attention? This startup says it already knows.

Subquadratic is beginning to back up its ambitious claims with benchmarks and third-party validation for its SubQ 1.1 Small model, which uses its proprietary Sparse Attention (SSA) architecture to dra...

7 Jul 20min

“The harness is where the hard work is”: Harness bets on agents that enterprises can trust in production

Harness has introduced Autonomous Worker Agents, a new capability that allows enterprises to replace rigid CI/CD pipeline scripts with AI agents that can deploy applications, run tests, and perform se...

2 Jul 19min

Public cloud vs. on-prem: Summit on where each workload belongs

More than two decades after AWS helped usher in the public cloud era, many organizations are reassessing whether a cloud-first strategy still delivers the cost and operational benefits it once promise...

25 Jun 36min