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Older offsets can overwrite newer ones in Kafka if not handled properly.

Kafka's parallel processing depends on partitions, not just consumers or threads.

Kafka can help ensure messages are processed once, but requires careful design.

Backpressure helps manage message flow in Kafka during traffic spikes.

Kafka's commitSync waits for confirmation, while commitAsync continues immediately.

Kafka consumer offsets help track message processing to avoid loss and duplication.

Kafka consumers can use multiple threads to speed up message processing, but it complicates ordering and offset management.

Backpressure prevents system overload by managing message processing rates in Kafka.

Kafka rebalance can lead to lost or duplicated work if not handled carefully.

Kafka consumers resume processing from the last committed offset after a crash.

Kafka consumers can pause and resume message processing to handle backpressure effectively.