Implementing the Raft distributed consensus protocol in Go
18 days ago
- #go
- #raft
- #distributed-systems
- The article discusses implementing Raft, a distributed consensus algorithm, in Go, focusing on leader election and log replication.
- A distributed key-value store is built on top of Raft, demonstrating how to model a state machine and commands for replication.
- The implementation includes HTTP endpoints for interacting with the Raft cluster, supporting both strict and relaxed read operations.
- Detailed explanation of persistent state management, including efficient disk writing strategies to avoid unbounded latency.
- Leader election process is covered, including timeouts, vote requests, and transitioning to leader state upon quorum.
- Log replication mechanics are explained, including how leaders send uncommitted messages and followers handle these messages.
- The article mentions considerations like race conditions, deadlocks, unbounded memory, and the potential need for Jepsen testing.
- A test rig is described for validating cluster behavior under various conditions, including node failures and message recovery.
- References to additional resources and implementations are provided for further learning and comparison.