Reactive Price Comparison: Better Prices Become an Obligation
summary
This talk explains how idealo uses reactive programming to improve price comparison: it describes moving to reactive systems (Reactive Streams / reactive architectures) so better prices are pushed to consumers rather than polled. It covers technologies and patterns for building asynchronous, backpressure-aware pipelines in the pricing workflow to ensure timely, reliable price updates.
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chapters (25)
- 0:00Reactive price comparison intro
- 1:09Real-time price necessity
- 2:13Idealo scaling
- 3:42Classical architecture challenges
- 5:50Frontend-backend separation
- 7:12Separate offer list issues
- 9:20Reactive principles
- 10:45Message-based real-time
- 12:20Isolation robustness
- 13:45Reacting to data changes
- 14:49Kafka Streams event sourcing
- 16:12Implementation challenges
- 18:22Synchronous API backup
- 19:46Stateless scalability
- 21:56Full vs delta updates
- 23:22Response time & availability
- 24:25Consistency vs latency
- 25:31Reactive benefits
- 26:53Production testing
- 27:58Stale data handling
- 29:21Business decisions
- 30:44Data modeling consistency
- 31:47Stakeholder integration
- 32:30Current status & optimizations
- 32:52Q&A
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