So You Want to Build An Event Driven System?
summary
Explains why event driven systems replace runtime coupling with publish/subscribe, shows concrete patterns that make them work: outbox pattern to prevent lost or duplicate events, the claim check pattern for large payloads, and the CloudEvents spec plus versioned types for schema governance. Demonstrates event storming for discovering business events, queues for controlled ingestion, OpenTelemetry-compatible tracing for causality, and a deployable Plant‑Based Pizza reference built on AWS that validates these choices in practice.
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chapters (30)
- 0:00Words and stories in software
- 1:45Learning from system failures
- 2:47Plant-Based Pizza company intro
- 3:30Coupling in synchronous systems
- 6:00Event-driven systems reverse dependencies
- 7:48Defining events and event-driven architecture
- 9:36Event-driven vs event-based systems
- 11:03Events as first-class citizens
- 12:10Commands, events, queries in messaging
- 13:13Thin events and callback problem
- 15:20Thick events and schema coupling
- 16:25Producer-consumer decoupling
- 19:14Business language via event-driven design
- 20:03Plant-Based Pizza to event-driven
- 21:06Event storming for business events
- 24:14Evolvability and governance in events
- 26:16Governance in event-driven architecture
- 27:40Schema evolution with CloudEvents
- 31:12Thin vs thick events balance
- 32:59Private and public events in microservices
- 36:10Eventual consistency in systems
- 37:13Consistency in payments
- 39:18Legacy integration with events
- 41:02Observability and tracing in events
- 42:25Synchronous API layers
- 44:33Asynchronous commands for tasks
- 47:41End-to-end event-driven flow
- 49:03Outbox pattern for failures
- 50:50Change data capture for events
- 51:30Adopting event-driven architecture
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