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Consensus ensures that distributed systems can agree on decisions even during failures.

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

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

Raft and Paxos are protocols that help computers agree on values in distributed systems.

Consistency models determine what data reads in distributed systems can see.

Raft consensus helps distributed systems elect leaders and replicate logs reliably.

Consistent hashing helps distribute data across servers with minimal movement.

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

Raft handles leader failure by allowing followers to elect a new leader through voting.

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

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

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

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

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

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

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