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599What Is Distributed Consensus?
600Why Consensus Is Hard
601The FLP Impossibility Result
602Crash-Stop vs Byzantine Failures
603Consensus Use Cases
604Safety vs Liveness Properties
605Quorums and Majority Agreement
606The CAP Trade-off in Consensus
607Consensus vs Consistency Models
608The Problem Paxos Solves
609Paxos Safety and Liveness Guarantees
610The Three Roles in Paxos
611Proposal Numbers and Ordering
612The Two-Phase Protocol
613The Prepare Phase
614The Accept Phase
615Handling Conflicts and Preemption
616Multi-Paxos for Log Replication
617Why Paxos Is Difficult in Practice
618Raft Overview: Understandability as a Design Goal
619Server States: Leader, Follower, Candidate
620Terms: Logical Time in Raft
621Leader Election: RequestVote RPC
622Election Timeouts and Randomization
623Log Structure and Entries
624AppendEntries RPC: Replication Mechanism
625Log Matching Property
626Commitment and the Commit Index
627Safety: Leader Completeness Property
628Election Restriction: Up-to-Date Check
629Log Inconsistencies and Repair
630Safety Argument: Committing Entries from Current Term
631Membership Changes: Joint Consensus
632Log Compaction: Snapshotting
633ZooKeeper: Coordination Service Built on Consensus
634etcd: Distributed Key-Value Store with Raft
635Consul: Service Discovery with Raft Consensus
636Consensus for Leader Election
637Distributed Locks via Consensus
638Configuration Management with Consensus
639Consensus Cluster Sizing Tradeoffs
640Performance Characteristics of Consensus
641Consensus in Multi-Region Deployments
642When NOT to Use Consensus
643Monitoring and Operating Consensus Clusters

599What Is Distributed Consensus?
600Why Consensus Is Hard
601The FLP Impossibility Result
602Crash-Stop vs Byzantine Failures
603Consensus Use Cases
604Safety vs Liveness Properties
605Quorums and Majority Agreement
606The CAP Trade-off in Consensus
607Consensus vs Consistency Models
608The Problem Paxos Solves
609Paxos Safety and Liveness Guarantees
610The Three Roles in Paxos
611Proposal Numbers and Ordering
612The Two-Phase Protocol
613The Prepare Phase
614The Accept Phase
615Handling Conflicts and Preemption
616Multi-Paxos for Log Replication
617Why Paxos Is Difficult in Practice
618Raft Overview: Understandability as a Design Goal
619Server States: Leader, Follower, Candidate
620Terms: Logical Time in Raft
621Leader Election: RequestVote RPC
622Election Timeouts and Randomization
623Log Structure and Entries
624AppendEntries RPC: Replication Mechanism
625Log Matching Property
626Commitment and the Commit Index
627Safety: Leader Completeness Property
628Election Restriction: Up-to-Date Check
629Log Inconsistencies and Repair
630Safety Argument: Committing Entries from Current Term
631Membership Changes: Joint Consensus
632Log Compaction: Snapshotting
633ZooKeeper: Coordination Service Built on Consensus
634etcd: Distributed Key-Value Store with Raft
635Consul: Service Discovery with Raft Consensus
636Consensus for Leader Election
637Distributed Locks via Consensus
638Configuration Management with Consensus
639Consensus Cluster Sizing Tradeoffs
640Performance Characteristics of Consensus
641Consensus in Multi-Region Deployments
642When NOT to Use Consensus
643Monitoring and Operating Consensus Clusters

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Lesson 619 of 1,919·17. Consensus AlgorithmsPro lesson

Server States: Leader, Follower, Candidate

The three states a Raft server can be in and the transitions between them that drive the protocol.

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