You have 3 consumers reading from 6 Kafka partitions. One consumer crashes. The remaining 2 need to pick up its partitions. That handoff isn’t as smooth as you’d hope.

Your event log has 100 million records. Key ‘user-42’ has been updated 500 times. You only care about the latest value. But deleting old entries would break consumers who haven’t caught up yet.

Events arrive out of order. User updates overwrite each other. Here’s how partition keys, sequence numbers, and causal ordering keep things straight.

Your consumer retried a bad message 10,000 times. It will never succeed. Dead letter queues catch the messages that can’t be processed so the rest of your system keeps moving.

Exactly-once delivery is impossible across boundaries. Here’s the pattern that actually works: at-least-once delivery with idempotent consumers.

Kafka says exactly-once. Your consumer processed the message twice anyway. Here’s why exactly-once is impossible across system boundaries.