Reacting to an Event-Driven World
summary
Explains how Apache Kafka (via IBM Event Streams) becomes the durable event log while reactive libraries and frameworks (Vert.x, Reactor/Reactive Streams, RxJava, Akka) provide nonblocking processing, backpressure and flow control; shows a GitHub demo with a coffee-order UI proving manual offset commit avoids lost work vs auto-commit, how consumer groups and partitions control ordering and scale, how replication and leader election give resiliency, and why connectors/clients—not Kafka alone—are needed for a truly responsive system.
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chapters (22)
- 0:00Introduction and speakers
- 1:06Event-driven architecture overview
- 3:12Coffee shop demo and event backbone
- 6:43Limitations of Kafka alone
- 7:25Reactive programming basics
- 9:13Reactive streams and futures
- 10:17Reactive manifesto explained
- 13:08Reactive architecture patterns
- 14:55Kafka for reactive systems
- 15:35Message vs event in Kafka
- 17:41Kafka resiliency features
- 21:12Leader election and client handling
- 22:15Resilient producers configuration
- 24:23Consumer offset management
- 27:53Kafka elasticity and scaling
- 33:28Partitions and consumer groups
- 34:12Getting started with Kafka
- 34:53Reactive Kafka frameworks
- 37:40Vert.x Kafka connector demo
- 45:13Demo application and resources
- 46:17Reactive systems benefits summary
- 48:01Q&A session begins
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