GPUs, Kubernetes & AI Infrastructure Realities

At KubeCon 2026, Pete Flecha and John Nicholson sit down with VMware by Broadcom’s Frank Denneman to explore one of the biggest infrastructure conversations happening in AI today: should Kubernetes workloads run on bare metal or virtualized infrastructure? The discussion dives deep into how AI workloads are changing infrastructure design, why Kubernetes and virtualization are becoming increasingly connected, and how technologies like DRS and Dynamic Resource Allocation (DRA) are evolving to support modern GPU-intensive environments. Frank explains the operational, security, and resource management challenges organizations face as AI adoption accelerates — especially when dealing with expensive GPU clusters, multi-tenant AI workloads, and the rise of AI agents. Topics include: Why virtualization still matters for Kubernetes and AI GPU scheduling, topology awareness, and resource isolation DRA (Dynamic Resource Allocation) in Kubernetes AI infrastructure efficiency and GPU utilization Security and isolation for AI agents and workloads Token governance and AI operational guardrails Lessons learned from decades of virtualization applied to AI infrastructure If you’re trying to understand where Kubernetes, virtualization, and AI infrastructure are headed next, this is a conversation you won’t want to miss.