When your LLM fails in production, how do you detect it? We explore tools like LangSmith, Arize, and OpenTelemetry for tracing, continuous evaluation, and alerting.
When an LLM fails in production, the impact can range from incorrect responses to hallucinations that affect business decisions. AI observability requires specialized tools that go beyond traditional monitoring: traceability of every model call, continuous evaluation of response quality, behavior drift detection, and automatic anomaly alerts. Tools like LangSmith, Arize, and OpenTelemetry for LLMs are making it possible to operate models in production with the same confidence as traditional software.