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Network partitions occur when servers are operational but can't communicate, affecting system performance.

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

Raft's safety rules guarantee that committed entries are preserved even after leader failures.

Leader election helps distributed systems select one coordinator from many nodes.

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

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

Fetch limits control data size from Kafka, while poll records limit processed records.

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

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

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

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

Message delivery semantics define how messages are sent in distributed systems and handle failures.

2-Phase Commit helps maintain data consistency in transactions across multiple databases.