Real-Time, Distributed Applications w/ Akka.NET, Kubernetes, .NET Core, and Azure Kubernetes Service
summary
Shows a working pipeline that uses Akka.NET actors (about 1k memory per actor, 50,000 actors/sec on a D2v2 VM) with Akka.Persistence (event sourcing to MongoDB) and clustered consistent-hashing routers to guarantee single-entity ownership. Deploys containers built with .NET Core and Docker into Kubernetes stateful sets on Azure Kubernetes Service, performs rolling upgrades via Azure Pipelines with graceful 10–40s state handoff, and keeps the live stock-price stream running.
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chapters (35)
- 0:00Introduction
- 1:16RealTime Applications
- 2:03What Makes an Application RealTime
- 4:24Statefulness
- 6:05Managing State
- 7:28Roadmap
- 8:24Topology Awareness
- 8:42Deployment Mechanism
- 9:16AkkaNET
- 9:31Kubernetes
- 10:06Actors
- 11:23Actor
- 12:30Actor Reference
- 15:35Actor Properties
- 16:02Actor Mailbox
- 17:07Cheap Resources
- 17:34Actor Hierarchy
- 18:44Child Per Entity
- 20:42Summary
- 25:57Roles
- 27:07How it Cluster Forms
- 27:37Mesh Networks
- 30:35Clustered Router
- 31:42Consistent Hashing
- 33:28Pie Slices
- 33:59Consistent Hash Router
- 35:31Moving State
- 35:49Consistency Issues
- 36:19Persistence
- 37:20Clustered routers
- 39:55Why Kubernetes
- 41:18Kubernetes Core Concepts
- 44:55IKS Cluster
- 45:26Key Terms
- 48:40Methodology
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