Kafka enables companies like LinkedIn, Netflix, and Uber to handle billions of messages daily through its distributed log architecture. It decouples services by allowing producers and consumers to communicate asynchronously, absorbs traffic spikes, and enables event replay for debugging. Messages are written to append-only partitions organized into topics across broker clusters. Key features include consumer groups for parallel processing, replication for durability, and three delivery guarantees (at-most-once, at-least-once, exactly-once). Partitioning strategy is critical—poor key selection creates hot partitions, while compound keys distribute load effectively. Trade-offs include added operational complexity, optimized throughput over latency, and ordering guarantees limited to single partitions. Event sourcing patterns use Kafka as the source of truth by appending state changes as events.
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