Any concept.
clear in 60 seconds.

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

Kafka Streams uses tumbling and hopping windows for time-based data aggregation.

Kafka Streams uses local state for quick data access and changelogs for recovery.

Kafka Streams offers higher-level abstractions, while Kafka Consumer provides direct control.

Kafka uses state stores to remember previous events in stateful stream processing.

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

Kafka consumers have three important states: Position, Committed Offset, and Application State.

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

Kafka's assign() method allows manual control of partition assignments for consumers.

Kafka's subscribe() lets the group manage partitions, while assign() gives control to the application.

Kafka's `seek()` lets you replay only specific messages, saving time.

Kafka's pause temporarily stops reading messages, while seek changes the reading position.

You can replay Kafka events safely by separating live and replay processes.

Poison messages in Kafka can cause infinite retries, risking system stability.

Kafka consumer reprocessing involves safely replaying events to correct system states.

Kafka uses Dead Letter Topics to handle messages that repeatedly fail processing.

Kafka uses retry topics and delayed retries to manage message failures efficiently.

Classifying failures and using controlled retries in Kafka prevents outages.

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

Backpressure helps manage message flow in Kafka during traffic spikes.

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

Kafka uses partitions to allow parallel processing while ensuring message order with keys.

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

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