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The CAP Theorem explains the trade-offs in distributed systems during network failures.

Cascading failures occur when one service's failure impacts others, causing widespread issues.

Consistent hashing helps distribute data across servers with minimal movement.

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

Dependency failures can disrupt applications, but resilience patterns can help manage them.

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

Distributed backpressure helps manage the flow of work between services to prevent overload.

ZooKeeper coordinates distributed systems using an ensemble of servers and the ZAB protocol.

Failover ensures systems remain operational by managing leader changes during failures.

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