Drinking a river of IoT data with Akka NET
summary
Claims Akka.NET scales IoT ingestion to very large fleets using the actor model, with 2 million messages on a laptop versus Petabridge’s 50 million messages claim. Implementation uses Akka.Remote for cross-node actor references, Akka.Persistence for event‑sourced device state, an App Service as a pausable ingestion buffer, and a parent/proxy pattern that spawns per‑device actors plus a hot/cold storage split (working set in memory, cold SQL for long history). Deploys require pausing ingestion, draining inboxes, and automated restart/sharding to avoid bottlenecks.
AI-written summary · about
chapters (19)
- 0:00Start
- 2:30Erlang
- 8:03Actor Model
- 10:23Immutable Messages
- 10:57Actor System
- 11:51Create an Actor System
- 23:02Thresholds and Alerts
- 28:20Normalizing Data
- 29:26Clock Drift
- 31:42Gap Filling
- 34:36The Parent Proxy Pattern
- 37:03Location Transparency
- 40:04Actor Selection
- 41:35Switchable Behaviors
- 47:30A Persistent Actor
- 48:18Receive Persistent Actor
- 56:44Dependency Injection
- 58:35Deployment
- 59:41Conclusion
related talks
48mProcess IoT information using Akka.NET
01h 14mAkka.NET: The Future of Distributed Programming in .NET
44mDeath to Latency: Building Reactive, Cloud Native Apps with Akka NET
47mNetworks and Types — the Future of Akka
48mStreaming all the things with Akka Streams
01h 20mAkka Streams for Large Scale Data Processing
37mAkka Present and Future
48mReliable messaging in the world of actors
