DDD, Event Sourcing and Actors
summary
Describes implementing event sourcing with C#, EventStore and Proto.Actor, replacing per-command stream reads by actors that hold aggregate state in memory and only restore once, which reduces reads and speeds throughput. Demonstrates a cluster running hundreds of thousands of actors and systems handling tens of thousands of commands per second and billions of messages per month. Shows projection actors that buffer and snapshot writes to avoid scaling bottlenecks on read models, notes clustering/operational caveats but reports significant performance gains in production.
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chapters (14)
- 0:00Introduction
- 2:58Event sourcing challenges
- 8:45Parallel world of systems
- 10:48The actor model approach
- 14:13Implementing actors
- 17:28Scaling and benefits
- 20:25Code structure and decoupling
- 23:14Projection scaling issues
- 25:15Competing consumer problems
- 29:08Actor-based projections
- 32:00Efficient state management
- 36:16Implementation details
- 40:14Infrastructure deployment
- 44:38Final thoughts and QA
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