Drinking a River of IoT Data with Akka.NET

Explore the challenges and solutions of processing massive IoT data streams using Akka.NET in this comprehensive conference talk. Dive into the actor model and its implementation in Akka.NET, learning how it simplifies stateful code development, scaling, and resilience. Discover strategies for handling millions of connected devices, overcoming traditional scaling bottlenecks, and leveraging parallelism. Gain insights into the actor system, hierarchy, and fault tolerance through supervision. Examine practical development ideas, including character actors, connection situations, and threshold management. Understand the importance of data normalization, timestamp correction, and gap filling in IoT stacks. Learn about Akka.Persistence for system recovery and explore deployment considerations. No prior Akka.NET knowledge required.

Intro
Actor model: the origin
What happened in 2015?
Classic scaling can't keep up
Free lunch was over
Parallelism is the salvation
Amdahl's Law
Can actor models help?
Messages
The Actor System
The actor hierarchy
Fault Tolerance - Supervision
General development ideas
Character Actor
Connection situation
Momentary threshold
Periodic threshold
Your typical loT stack
Why Normalization?
Timestamp correction & buckets
Gap filling
Akka. Persistence
After a system restart
Start learning
Deployment
Conclusion