Automated Performance Tuning with Bayesian Optimization

Automated Performance Tuning with Bayesian Optimization

Linux Foundation via YouTube Direct link

KEY TAKEAWAYS

20 of 32

20 of 32

KEY TAKEAWAYS

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Automated Performance Tuning with Bayesian Optimization

Automatically move to the next video in the Classroom when playback concludes

  1. 1 Intro
  2. 2 TWITTER RUNS ON MICROSERVICES
  3. 3 A PERFORMANCE STACK AT TWITTER
  4. 4 TUNING AT THE JVM LAYER
  5. 5 PERFORMANCE OPTIMIZATION
  6. 6 CONSTRAINTS
  7. 7 PERFORMANCE TUNING
  8. 8 OPTIMIZATION OF A BLACK BOX FUNCTION
  9. 9 BAYESIAN OPTIMIZATION EXAMPLE
  10. 10 ALTERNATIVE APPROACHES
  11. 11 BAYESIAN OPTIMIZATION EXPERIENCES AT TWITTER
  12. 12 MICROSERVICE STACK
  13. 13 OPTIMIZING A MICROSERVICE BY TUNING THE JVM
  14. 14 A SAMPLING OF JVM PARAMETERS
  15. 15 SET-UP
  16. 16 EVALUATION
  17. 17 PERFORMANCE OF THE OPTIMUM RESULT
  18. 18 GC COST
  19. 19 OPTIMIZED SETTINGS
  20. 20 KEY TAKEAWAYS
  21. 21 AUTOTUNE AS A SERVICE
  22. 22 WHAT DOES AURORA BRING TO THE TABLE
  23. 23 AURORA BASICS
  24. 24 LAUNCHING AN EXPERIMENT
  25. 25 A BRIEF DIVERSION
  26. 26 RUNNING AN EXPERIMENT
  27. 27 FINISHING AN EXPERIMENT
  28. 28 CLOSING THE LOOP
  29. 29 THE VIRTUOUS CIRCLE
  30. 30 BEYOND THE JVM
  31. 31 CONCLUSION
  32. 32 WHAT'S NEXT

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.