Perspectives on GPU infrastructure, team productivity, and the future of ML operations.
AUROC tells you if predictions are good. Calibration tells you if you can trust them enough to automate. We explain why ECE is the metric that unlocks autonomous operations.
The story of building a GPU observability platform — from a frustration with opaque queues to a 150-endpoint platform with calibration-aware agents, LLM inference analytics, and HPC integration.
How VGAC's five-agent architecture uses a Prediction Impact Index to decide when to act, when to recommend, and when to defer to humans.
Prefill/decode phase imbalance, KV cache fragmentation, and NIXL transfer bottlenecks are invisible to traditional monitoring. Here's what to track instead.
The latest release adds LLM phase analysis, NVIDIA NIXL transfer monitoring, HPC policy visibility, and a Slurm script generator that knows your cluster state.
A 10% utilization improvement on a 100-GPU cluster saves a quarter million per year. The bottleneck isn't hardware — it's scheduling visibility.
With GPU demand outpacing supply 10:1, organizations need better ways to maximize the compute they have.
We're building the visibility layer GPU clusters have been missing. Submit with confidence, plan with clarity.
Queue uncertainty doesn't just waste compute — it wastes engineer time, delays projects, and erodes team morale.