Why Kubernetes Needs to Learn GPUs, with Saiyam Pathak
Kube Signals starts where the keynote ends: with the trends that platform teams will have to operationalize next. In this special episode, Brian Teller speaks with Saiyam Pathak about his KubeCon India keynote and the shift from developer platforms to AI factories. They examine what GPU scarcity, shared accelerators, and AI workloads mean after the conference slides meet real infrastructure. In this interview: Why GPU infrastructure is becoming a platform-engineering concern How DRA, HAMI, MIG, and MPS change GPU allocation and utilization Where isolation, scheduling, and observability become harder for AI platforms Which cloud-native AI trends and projects platform engineers need to watch Sponsor This episode is sponsored by LearnKube. Download the free book, The Technical Guide to Kubernetes Rightsizing, to understand what Prometheus and Grafana cannot tell you about safely reducing requests and limits. More info Find all the links and info for this episode here: https://ku.bz/4QZDqrnf- Interested in sponsoring an episode? Learn more.