Drinking a River of IoT Data with Akka.NET

Drinking a River of IoT Data with Akka.NET

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Akka. Persistence

22 of 26

22 of 26

Akka. Persistence

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Classroom Contents

Drinking a River of IoT Data with Akka.NET

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  1. 1 Intro
  2. 2 Actor model: the origin
  3. 3 What happened in 2015?
  4. 4 Classic scaling can't keep up
  5. 5 Free lunch was over
  6. 6 Parallelism is the salvation
  7. 7 Amdahl's Law
  8. 8 Can actor models help?
  9. 9 Messages
  10. 10 The Actor System
  11. 11 The actor hierarchy
  12. 12 Fault Tolerance - Supervision
  13. 13 General development ideas
  14. 14 Character Actor
  15. 15 Connection situation
  16. 16 Momentary threshold
  17. 17 Periodic threshold
  18. 18 Your typical loT stack
  19. 19 Why Normalization?
  20. 20 Timestamp correction & buckets
  21. 21 Gap filling
  22. 22 Akka. Persistence
  23. 23 After a system restart
  24. 24 Start learning
  25. 25 Deployment
  26. 26 Conclusion

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