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

Drinking a River of IoT Data with Akka.NET

NDC Conferences
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