Why Your GPU Is Idle: A Layer by Layer Troubleshooting Guide for Enterprise Inference

This article provides a detailed, layer-by-layer troubleshooting methodology for enterprise inference services where GPU utilization is unexpectedly low. It explains that low GPU usage is not inherently a fault and can be normal for latency-sensitive, lightly loaded, or retrieval-heavy workloads. The guide emphasizes a deterministic sequence: confirming demand, verifying request routing and pod scheduling, separating cold-start from steady-state execution, and measuring CPU, memory, storage, and network before tuning the GPU. It advises correlating queueing, concurrency, batching, and GPU metrics, and inspecting PCIe, NVLink, and power only after understanding the software path. The goal is to optimize for service objectives like p95/p99 latency rather than chasing 100% GPU utilization.