Event Processing in Action
summary
Argues that modeling a CI pipeline as events turns business flows into code: a pull request created starts builds, an event processor normalizes XML to JSON, and a build completed event carries full, immutable data used by a notification service and dashboard. Team expects ~30 event types and ends up with ~200; producers publish one canonical event each, consumers filter or republish, and the system gains traceability and easy refactoring but needs strong monitoring to handle volume and lost events.
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chapters (22)
- 0:00Start
- 1:00WHO AM I?
- 4:04DOMAIN - CONTINUOUS INTEGRATION TOOL
- 7:05EVENT PROCESSING
- 8:27EVENT-DRIVEN ARCHITECTURE
- 11:26PRINCIPLES OF EDA
- 13:50EVENT-PROCESSING NETWORK
- 16:04EVENT OBJECT DESIGN
- 17:49THE NAME PAST TENSE
- 20:02THE NAME - WHAT HAPPENED
- 21:35HOW MANY DATA?
- 27:27STATE-CHANGE EXAMPLE
- 28:09DETECTABLE-CONDITION EXAMPLE
- 28:58CONSUMERS
- 31:44CHALLENGES
- 35:22PREDICATE REQUIRED
- 41:10EVENT CAN DEPEND ON CONSUMED EVENT
- 42:08PRODUCER OR CONSUMER?
- 44:07SAME EVENT BY DIFFERENT PRODUCERS
- 46:20MORE THAN ONE AT A TIME
- 47:02PUBLISH OR NOT PUBLISH???
- 48:48WHY YOU SHOULD CONSIDER EVENTS?
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