How does observability work in production LLMOps systems?

LLMOps observability tracks prompts, outputs, latency, token usage, and model behavior across requests.

Observability in LLMOps goes beyond traditional logging. It includes tracing prompt inputs, intermediate retrieval steps, model outputs, token consumption, latency per stage, and user feedback. Because LLMs are probabilistic, observability focuses on distributions and patterns rather than deterministic logs. Tools often use distributed tracing systems combined with prompt/version tracking and evaluation pipelines.