LLM Observability

Definitions

1. The practice of instrumenting and analyzing large language model systems so teams can understand their behavior, performance, cost, and failure modes. LLM observability usually includes traces, prompts, responses, tool calls, and evaluation signals.

   In plain English: Monitoring and inspecting how large language model systems behave.

   Example: "Better LLM observability showed that most failures were caused by stale retrieval data, not by the model hallucinating on its own."

Related Terms

• Gemini Model
• Phi Model
• AI Debugging
• AI Logging
• AI Trace
• LLM Benchmark
• LLM Chain
• LLM Gateway
• LLM Judge
• LLM Security