LLMs and AWS: Observability Maturity from Foundation to AIOps

LLMs and AWS: Observability Maturity from Foundation to AIOps

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intro

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1 of 29

intro

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LLMs and AWS: Observability Maturity from Foundation to AIOps

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  1. 1 intro
  2. 2 preamble
  3. 3 agenda
  4. 4 quick intro about myself
  5. 5 amazon bedrock
  6. 6 overview of genai apps
  7. 7 what is observability?
  8. 8 observability in llms: what exactly is it?
  9. 9 insight into the core: direct llm observability
  10. 10 beyond the surface: indirect llm observability
  11. 11 llm observability: observability maturity model for aws bedrock integrated applications
  12. 12 why observability matters for llms
  13. 13 pillars shaping indirect llm observability
  14. 14 llm specific metrics
  15. 15 prompt engineering properties
  16. 16 performance metrics, logging, and tracing for rag models
  17. 17 tracing
  18. 18 visualization tools
  19. 19 alerting and incident management
  20. 20 security and compliance
  21. 21 cost optimization
  22. 22 aiops capabilities
  23. 23 why you need maturity model?
  24. 24 maturity framework
  25. 25 level 1: foundation llm observability
  26. 26 measure progress with business outcomes
  27. 27 best practices
  28. 28 pitfalls to avoid
  29. 29 thank you

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