This session highlights Outrigger, an initiative to evolve Kubernetes scheduling into a dynamic, collaborative framework. Building on the experience of developing the Multiarch Tuning Operator for OpenShift, the initiative leverages the Kubernetes' scheduling gates mechanism to go beyond multi-architecture-aware scheduling. It introduces a framework where multiple controllers can compete to inject augmented information into pod specifications, enabling smarter and more efficient pod placement across Kubernetes clusters.
The framework optimizes workload placement while coordinating with descheduling and autoscaling components.

This talk will explore how this community-driven approach connects observability platforms with Kubernetes’ scheduling ecosystem, closing the feedback loop for improved performance, SLA guarantees, cost savings, and energy efficiency. Attendees will also learn how this framework lays the foundation for a fully distributed, intelligent placement system for Kubernetes workloads.

Join us to discover how the Outrigger community extends its vision to foster collaboration and innovation to advance Kubernetes scheduling.