Exploring LLM Observability with Traceloop's Gal Kleinman
The AI Native Dev - from Copilot today to AI Native Software Development tomorrow
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Enhancing Observability in LLM Applications
This chapter explores the significance of observability in distributed systems, particularly through the OpenTelemetry framework. It highlights best practices for monitoring Large Language Model (LLM) applications, emphasizing the need for effective evaluation metrics and real user feedback. The discussion also addresses the challenges of managing trace data in large-scale machine learning environments, outlining strategies for efficient evaluation and debugging.
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