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Kafka uses brokers for data handling and KRaft controllers for metadata management.

RPC allows one service to call a function in another service over the network.

gRPC allows efficient communication between services using a structured request-response model.

Crash failures stop a service, while network failures disrupt communication.

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

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

Kafka uses different strategies to assign partitions to consumers in a group efficiently.

Kafka producers use ACKs, retries, and idempotence to ensure reliable message delivery.

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

Kafka maintains message order within partitions using keys for routing.

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

Kafka Partition Reassignment moves replicas between brokers while keeping data safe.

ZooKeeper watches notify clients of changes, avoiding constant polling and reducing server load.

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