Reactive Pipeline Talk
summary
A reactive pipeline is implemented end-to-end: a Scala Akka Streams consumer reads Kafka, forwards payloads over Akka Streams + RSocket bridge to a Java Project Reactor receiver that publishes to a second Kafka topic; backpressure propagates so the source only consumes when downstream requests data, demonstrated with random processing delays and a running Docker Kafka cluster — the demo works. Notes: RSocket docs are sparse and the Java side depends on Project Reactor, signaling via flux.empty for completion.
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chapters (14)
- 0:00Introduction to talk
- 2:10Speaker introductions
- 3:15Why reactive in enterprise
- 7:32Legacy app challenges
- 8:13Reactive solutions overview
- 10:43Reactive pipeline demo setup
- 13:19Demo code walkthrough
- 21:14Live reactive pipeline demo
- 23:51Demo conclusions and insights
- 26:16Reactive streams benefits
- 27:40Project Reactor limitations
- 28:45Modular microservices approach
- 30:07Project Loom and reactive
- 31:50Final thoughts and Q&A
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