Every Event, Everywhere, All at Once
summary
Starts from JDK1.1 examples like PreferenceChangeEvent to show how events model a past outcome, then contrasts commands vs facts and explains event streaming via message logs with consumer offsets (so a crashed consumer may replay from zero). Covers event sourcing with concrete stores such as EventStoreDB and MessageDB, recommends splitting streams on business boundaries, shows the CFKA retry/tombstone pattern and a pragmatic GDPR approach: delete the encryption key. Advises making events “as small as possible and as large as necessary” and using public vs private event contracts.
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chapters (15)
- 0:00Intro
- 2:00What is an Event?
- 6:59Event vs. Command
- 11:22Event Streaming
- 15:56Event-driven Architecture
- 18:10EventStorming
- 22:07Event Sourcing
- 25:56Event Store
- 27:26Tombstone Event
- 30:19Domain & Integration
- 33:09Event Granularity
- 35:35As small as possible & as large as necessary
- 36:19Bonus
- 36:35Mostly all the Events
- 37:25Outro
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