1. Akka.NET The Future of Distributed Programming in .NET
Aaron Stannard,
Co-founder Akka.NET
@Aaronontheweb

2. High Expectations for Backend Developers

3. And the obvious ways to scale are wrong.

4. Enterprise CRUD App

5. Scenario 1: Surge in User Activity

6. Obvious Solution: Sharding

7. Brittle

8. Scenario 2: Real-time User Interactivity

9. Obvious Solution: Read-after-Write

10. Reality

11. Why is Distributed Programming Hard?

12. Enter the Actor Model

13. Actor Model Core Concepts

14. Actor Model for .NET

15. Akka.NET Modules Akka – core actor library
Akka.Remote – cross-node actor deployment / communication
Akka.Cluster – elastic actor networks (HA)
Akka.Persistence – event-sourcing, durable actor state & recovery
Akka.Streams – streaming workflows
Akka.Cluster.Tools – cluster singleton, distributed pub sub
Akka.Cluster.Sharding – durable state partitioning
Akka.DData – eventually consistent data replication

16. What's an Actor?

17. Actors live in a family tree

18. Actors process one message at a time

19. Properties of Messages

20. Messaging Patterns

21. Messaging Protocols

22. Communicate with Actors via Reference

23. Actor References Have Transparent Locations

24. Akka.Remote & Akka.Cluster: Location Doesn't Matter

25. Benefits of Clustering

26. Elastic (Join)

27. Elastic (Leave)

28. No Configuration Changes

29. Recover from Failures

30. Decentralized

31. Fastest Response Time?

32. Stateful Apps Serve Results from Memory

33. State Locality

34. State Makes Protocols Work

35. CAP Theorem

36. CAP Terminologies

37. CAP & Protocols

38. Clustering is for AP (by default)

39. Fault and Resource Isolation with Actors

40. Actor Lifecycle Phases

41. "Just let it crash"

42. DeathWatch: Subscribe to Actors' Lifecycle

43. Petabridge