Streams and Tables in Apache Kafka: Elasticity, Fault Tolerance & Advanced Concepts

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This post dives into the architectural underpinnings of elasticity and fault tolerance in stream processing with Kafka Streams and ksqlDB. It explains how the stream-table duality, specifically the use of changelog topics, ensures fault tolerance for tables by providing a durable source of truth. It details how this mechanism also enables elastic scaling by allowing state to be restored on new instances during rebalancing. The post further elaborates on the benefits of topic compaction for reducing storage footprint and recovery time, and introduces the concept of standby replicas to minimize recovery time during failures and scale-in events.