From Blind Spots to Breakthroughs: Real-Time AI Factory Observability that Cuts Costs and Boosts Performance

Your AI infrastructure is only as effective as your visibility into it, and right now, most teams are flying blind. In this hands-on workshop, you’ll learn how to use real-time observability to reduce costs, eliminate waste, and keep your AI Factory running at peak performance. We’ll dive into practical techniques to:

• Identify GPU underutilization, throttling, and idle capacity across both cloud and on-premises deployments before they burn through your budget.
• Monitor token usage for inference workloads (including NVIDIA NIM containers) to catch cost spikes and inefficiencies as they happen.
• Correlate slow inference jobs or degraded model performance to root-cause issues anywhere in the stack, so you can fix problems without throwing more hardware or cloud spend at them.

Through live demonstrations, you’ll see how real-time telemetry and AI-driven correlation turn raw metrics into immediate, actionable insights, helping you cut unnecessary spend, speed up troubleshooting, and ensure your models deliver maximum value. If you’re responsible for making AI infrastructure faster, leaner, and more cost-efficient, this is the one workshop you can’t afford to miss.

Optimized Infrastructure: Maximizing Resource Utilization and Performance in Large-Scale Inferencing Systems.

Join Virtana’s Senior Director of Production Management, Meeta Lalwani along with RunPod’s Head of Engingeering, Brennen Smith and SqueezeBits CEO, Hyungjun Kim