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Kafka uses retries and Dead Letter Queues to manage message processing failures.

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

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

Kafka allows safe message reprocessing by resetting consumer positions without altering data.

Backpressure helps manage message flow in Kafka during traffic spikes.

Classifying failures and using controlled retries in Kafka prevents outages.

Kafka consumers can fetch data in batches to improve throughput and reduce latency.

Graceful shutdown in Kafka ensures no data loss during consumer termination.

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

Kafka Schema Evolution allows safe changes to message structures without breaking existing consumers.

Kafka consumer lag shows how far behind consumers are from new messages.