As open-source projects grow, governance becomes a bottleneck. Tracking enhancement proposals across repositories, enforcing deadlines, ensuring process compliance - these don't scale with volunteer maintainers.

Enter the VEP Police Agent - an AI agent built with LangGraph, MCP, and LLMs for KubeVirt, a CNCF project for running VMs on Kubernetes. It autonomously monitors the enhancement proposal lifecycle: discovering proposals across GitHub, tracking compliance in parallel, performing cross-domain risk analysis, and delivering prioritized alerts via Slack and email.

We'll dive into the architecture: a LangGraph state machine with parallel nodes, a two-tier LLM strategy (fast models for MCP tool-calling, powerful models for reasoning), and phase-aware analysis that keeps alerts context-sensitive. A live demo will show the agent catching real governance issues in real time.

While built for KubeVirt, the patterns apply to any project facing governance growing pains.

Achieving high VM density in Kubernetes demands advanced memory management. This talk details our journey building the VM higher density solution for OpenShift Virtualization (KubeVirt).

With Kubernetes swap previously in Beta, we needed an immediate way to enable worker node swap. Enter wasp-agent: our custom project to mimic K8s swap externally. We will explore the technical hurdles of this approach, detailing our experiments with Linux cgroups, runtime hooks, and evictions.

As we trace the solution’s evolution from Dev Preview to GA, attendees will learn about memory overcommit mechanisms (FPR, KSM). Crucially, we'll detail our transition plan: deprecating wasp-agent to adopt the newly GA'ed native Kubernetes swap, highlighting the platform tunings required for maintainability and consistency.

Finally, we'll evaluate deployment strategies, comparing Operator-driven automation against manual methods, and the trade-offs of enabling swap at install-time vs on a running cluster.