Beyond Logs, Metrics and Traces: The New Observability Stack for Generative AI
About this session
This session will equip attendees with a comprehensive understanding of observability for generative AI systems. Participants will learn to track the entire AI execution path, from context and retrieval to model inference, tool use, agent state, and evaluation. The talk will demonstrate how to integrate AI-specific signals with traditional telemetry, avoiding siloed monitoring solutions. Attendees will be introduced to emerging operational signals such as semantic quality, task success, token economics, model routing, and agent behavior. By the end of the session, participants will have a clear framework for implementing the next generation of open observability standards tailored for AI-native systems.
Speaker
Key takeaways
- Attendees will learn how to think about observability across the full generative AI execution path, including context, retrieval, model inference, tool use, agent state, and evaluation.