Implementing Raft: A Deep Dive into Distributed Consensus

2024-12-21

This is the first post in a series detailing the Raft distributed consensus algorithm and its Go implementation. Raft solves the problem of replicating a deterministic state machine across multiple servers, ensuring service availability even with server failures. The post introduces core Raft components: the state machine, log, consensus module, leader/follower roles, and client interaction. It discusses Raft's fault tolerance, the CAP theorem, and the choice of Go as the implementation language. Subsequent posts will delve into the algorithm's implementation.

Read more
Development Distributed Consensus