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Distributed locks ensure only one server performs a task, avoiding duplication.

Distributed caching spreads data across multiple servers for better performance and reliability.

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

In distributed systems, timestamps don't always reflect the true order of events.

Sharding splits databases into smaller parts to improve performance and scalability.

Consistent hashing helps distribute data across servers with minimal movement.

Lamport Timestamps help order events in distributed systems while preserving causality.

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