Consensus Algorithms

Learn how distributed systems achieve agreement despite uncertainties

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The Consensus Problem

In distributed systems, consensus algorithms ensure that all participating nodes agree on a single data value despite potential failures or network issues. This is crucial for systems like blockchain, databases, and replicated services.

Key Challenges

  • Handling node failures
  • Managing network delays
  • Preventing data corruption
// Simplified consensus scenario
const propose = (value) => {
  return new Promise((resolve) => {
    setTimeout(() => {
      console.log(`Proposing value: ${value}`);
      resolve(value);
    }, Math.random() * 1000);
  });
};

Popular Algorithms

1. Paxos

A consensus algorithm that allows a distributed system to agree on a single value even when some nodes fail.

2. Raft

A more understandable consensus algorithm that emphasizes leader election and log replication.

Practical Example: Raft

Raft splits consensus into three primary components: leader election, log replication, and commit process. Here's a simplified pseudocode example demonstrating Raft's core:

// Raft Node State
enum State {
  FOLLOWER,
  CANDIDATE,
  LEADER
};

class RaftNode {
  constructor() {
    this.state = State.FOLLOWER;
    this.currentTerm = 0;
  }

  becomeCandidate() {
    this.state = State.CANDIDATE;
    this.currentTerm++;
    console.log(`Election initiated: Term ${this.currentTerm}`);
  }
};

Ready to experiment with consensus algorithms?

Try the Interactive Demo