Observability for LLM Systems: Metrics, Traces, Logs, and Testing in Production
End-to-end observability strategy for LLM inference and LLM applications
LLM systems fail in ways that traditional API monitoring cannot surface — queues fill silently, GPU memory saturates long before CPU looks busy, and latency blows up at the batching layer rather than the application layer. This guide covers an end-to-end observability strategy for LLM inference and LLM applications: what to measure, how to instrument it with Prometheus, OpenTelemetry, and Grafana, and how to deploy the telemetry pipeline at scale.