3.Consensus Algorithms
Distributed Systems · 6 notes
- 3. Distributed Consensus Algorithmshistorical
Why distributed nodes need consensus, how Paxos, Raft, ZAB, and Gossip differ, and how consensus relates to strong or eventual consistency.
- 3.1 Paxoshistorical
Basic Paxos roles and two-phase decision flow, why contention is expensive, and how Multi-Paxos uses a stable leader to make repeated consensus practical.
- 3.2 ZABhistorical
An entry point to ZooKeeper Atomic Broadcast (ZAB), ZooKeeper's leader-based protocol for ordered, reliable state updates.
- 3.3 Rafthistorical
Raft's leader, follower, and candidate roles; leader election; replicated-log operation; quorum commitment; and recovery after leader failure.
- 3.4 Gossiphistorical
How gossip protocols spread information through randomized peer-to-peer exchanges, why they scale well, and the redundancy and convergence trade-offs they introduce.
- 3.5 Distributed Consistency Modelshistorical
A practical map of linearizability, eventual and causal consistency, read-your-writes, session consistency, monotonic reads and writes, and consistent-prefix reads.