Automatic Generation of Runtime Checkers for Production Distributed Systems

Automatic Generation of Runtime Checkers for Production Distributed Systems

Strange Loop Conference via YouTube Direct link

Real-world failure study

31 of 39

31 of 39

Real-world failure study

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Classroom Contents

Automatic Generation of Runtime Checkers for Production Distributed Systems

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  1. 1 Intro
  2. 2 Runtime checker (aka. detector/monitor)
  3. 3 Importance of runtime checker
  4. 4 Current checking practice
  5. 5 Complex internals of modern software
  6. 6 Common to exhibit gray failures
  7. 7 A real-world gray failure
  8. 8 Failure root cause
  9. 9 Ideal runtime checkers
  10. 10 A new approach
  11. 11 Panorama: capture in-situ observability
  12. 12 Convert a program into in-situ observer
  13. 13 Identify observation boundary and identities
  14. 14 Extract evidence
  15. 15 Example of analysis
  16. 16 Detecting real-world gray failures
  17. 17 Timeline of detecting failure case f1
  18. 18 Latency overhead to observers
  19. 19 Program reduction approach
  20. 20 Why doing reduction?
  21. 21 identify long-running regions
  22. 22 select checking target candidates
  23. 23 reduce long-running methods
  24. 24 encapsulate checkers
  25. 25 insert watchdog hooks
  26. 26 Prevent side effects
  27. 27 Watchdog generation
  28. 28 Failure detection evaluation setup
  29. 29 Detecting real-world failures
  30. 30 Silent semantic violations
  31. 31 Real-world failure study
  32. 32 Oathkeeper: detect silent semantic violation
  33. 33 How to express semantics?
  34. 34 Oathkeeper workflow
  35. 35 Emitting semantic event traces
  36. 36 General semantic rule templates
  37. 37 Extracted semantic rules
  38. 38 Runtime overhead
  39. 39 Conclusions

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