Raft

How to Read This Post Each scenario shows a diagram first, then a short note on why the pattern matters. Complexity increases as you scroll. Algorithm Approach Strength Trade-off Raft Leader-based Understandable, widely adopted Leader bottleneck Paxos Proposer-based Formally proven, flexible Notoriously hard to implement Multi-Paxos Optimized Paxos Fewer round-trips with stable leader Complex recovery ZAB Leader-based Ordered broadcast (ZooKeeper) Tightly coupled to ZK Level 1 — Why Consensus? 1. The Agreement Problem %%{init: {'theme':'dark', 'themeVariables': {'primaryTextColor':'#e5e7eb','secondaryTextColor':'#e5e7eb','tertiaryTextColor':'#e5e7eb','textColor':'#e5e7eb','nodeTextColor':'#e5e7eb','edgeLabelText':'#e5e7eb','clusterTextColor':'#e5e7eb','actorTextColor':'#e5e7eb'}}}%% flowchart TB C[Client] -->|"SET x=5"| N1["Node Ax = 5 ✓"] C -->|"SET x=5"| N2["Node Bx = 5 ✓"] C -->|"SET x=5"| N3["Node C⚡ crashed"] N1 -->|"what is x?"| Q{{"Do all nodesagree x=5?"}} N2 -->|"what is x?"| Q N3 -->|"???"| Q Q -->|"With consensus"| YES["All agree on x=5even with failures"] Q -->|"Without consensus"| NO["Inconsistent statesplit brain possible"] style C fill:#4a9eff,stroke:#2d7ed8,color:#fff style N1 fill:#51cf66,stroke:#37b24d,color:#fff style N2 fill:#51cf66,stroke:#37b24d,color:#fff style N3 fill:#ff6b6b,stroke:#d44,color:#fff style Q fill:#ffd43b,stroke:#f59f00,color:#333 style YES fill:#51cf66,stroke:#37b24d,color:#fff style NO fill:#ff6b6b,stroke:#d44,color:#fff The core problem. Distributed nodes must agree on a single value even when some nodes crash or messages are delayed. Without consensus, you get split-brain — two parts of the system believing different things. ...

Introduction Building robust distributed systems requires understanding fundamental patterns that solve common challenges like consensus, fault tolerance, request distribution, and asynchronous communication. This comprehensive guide uses visual diagrams to illustrate how these patterns work, making complex distributed systems concepts easier to understand and implement. We’ll explore: Raft Consensus Algorithm: How distributed systems agree on shared state Circuit Breaker Pattern: Preventing cascading failures in microservices Load Balancing Algorithms: Distributing traffic efficiently across servers Message Queue Patterns: Asynchronous communication strategies Part 1: Raft Consensus Algorithm The Raft consensus algorithm ensures that a cluster of servers maintains a consistent, replicated log even in the face of failures. It’s designed to be more understandable than Paxos while providing the same guarantees. ...