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

Causality in distributed systems helps understand how events influence each other, beyond just timestamps.

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

Consistent hashing helps distribute data across servers with minimal movement.

Physical time tells when events happen, while logical time tells their order.

Paxos is a protocol that helps distributed systems agree on one value despite failures.

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

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

Leader election ensures a single node coordinates tasks in distributed systems, even after failures.

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

Quorum and majority help distributed systems maintain data consistency and availability.

Fail-stop means a system stops and stays down, while fail-recover means it can come back but needs to be ready.

Log replication ensures data consistency by requiring majority acknowledgment before committing changes.

Bully, Raft, and ZooKeeper are distinct algorithms for leader election in distributed systems.

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