Best AI Observability Tools in 2026: 8 Tools Compared
Eight LLM and AI agent observability platforms compared: what each tracks, pricing and free tiers, self-hosting options, and who each is built for.
Sejal Pandey
The GPU Metrics That Actually Matter
Most teams monitor three GPU metrics - utilization, temperature, memory. There are 50+ that matter, and the ones you skip cause your worst outages. A vendor-neutral guide across NVIDIA, AMD, and Intel Gaudi
Shekhar
Your LLM Is Slower Than You Think
60% GPU utilization and 3-second response times? GPU utilization is the wrong signal for LLM inference. Here's why TTFT, KV-cache pressure, and queue depth - not utilization - predict user-facing latency.
Shekhar
Predicting GPU Failures Before They Cost You
Predict GPU hardware failures 48–72 hours in advance. A guide to the five rate-based signals — ECC error trends, XID events, thermal ramp, row remap exhaustion, PCIe downtraining — and how to combine them into a composite health score.
Shekhar
Every Token Has a Price: Per-Request GPU Cost Attribution
Flat per-token pricing is wrong by 10–50× per request. Prefill vs decode, batch sharing, and cache effects break the math. How to attribute real GPU cost - compute, energy, and dollars - to each inference request.
Shekhar