AI workloads are exposing the limits of traditional scheduling assumptions in Kubernetes. When GPUs and other specialized accelerators enter the picture, platform design becomes far more complex. This session explains how Kubernetes must evolve to support accelerated computing at scale, with a focus on GPU allocation, Dynamic Resource Allocation (DRA), scheduling behavior, quota design, and capacity planning. The talk connects these technical mechanisms to the broader goal of building reliable and efficient AI platforms. Attendees will understand the operational implications of running accelerated workloads, the common pitfalls teams encounter, and the architectural patterns that can help improve fairness, utilization, and performance.

KubeVirt is changing the conversation around modernization by allowing organizations to run virtual machines and containers side by side on Kubernetes. This session removes the confusion and fear often associated with the technology by explaining how KubeVirt works, what use cases it solves, and how it can help unify operations across traditional and cloud native workloads. The talk covers virtual machine lifecycle management, networking, storage, day-2 operations, and the practical trade-offs of adopting KubeVirt in enterprise environments. Attendees will see how platform teams can reduce fragmentation, simplify operations, and create a common control plane for both legacy and modern applications.