An effective LLM monitoring setup tracks a combination of performance metrics, including latency, throughput, request rates, token usage, and error rates, alongside quality metrics such as hallucination rate, factual accuracy, relevance, toxicity, and user feedback.

Authors

• Person: Not available Organization: TTMS
  LLM Observability: How to Monitor AI When It Thinks in Tokens | TTMS

Sources

• LLM Observability: How to Monitor AI When It Thinks in Tokens | TTMS ttms.com TTMS via serper

Referenced by nodes (4)

• hallucination rate concept
• latency concept
• factual correctness concept
• toxicity concept