End-to-End Observability for vLLM and TGI: from DCGM to Tokens

Running large language model inference servers in production exposes gaps that neither stock Prometheus dashboards nor the official documentation of vLLM or TGI cover completely. This article maps the layers that matter, names the exact signals to scrape and flags the traps most teams only hit after real traffic arrives. Audience: SREs, ML platform engineers and observability engineers who operate or are about to operate vLLM or TGI on GPUs. Why LLM serving breaks standard observabili...