Keynote II: Kafka and the Rise of Event-Driven Microservices
summary
Argues that Kafka turns all business activity into durable event streams so applications and analytics share a single source of truth, enabling real-time joins of app events with change‑data‑capture logs, replay from offset=0, and scalable stream processing. Demonstrates retail inventory and customer‑360 pipelines, banks moving credit‑card processing and fraud detection to per‑event pipelines, and vehicle sensor telemetry. Explains stream-table duality, shows log compaction for unbounded keyed history and tiered storage for effectively infinite retention.
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chapters (8)
- 0:00Introduction and audience check
- 1:07Why event-driven architectures
- 7:32Kafka's stream-table duality
- 11:50Events as triggers and data streams
- 17:27Streaming platform and Kafka's role
- 19:52Trends driving Kafka adoption
- 21:40Business impact of event-driven systems
- 23:09Q&A: Long-term event storage
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