Building Fault Tolerant KV Storage System - Part 2

Sat, 04 Oct 2025 16:16:17 +0530

We previously discussed replicated state machines, leader election in the RAFT consensus algorithm, and log-based state maintenance. Now, we’ll focus on log replication across peer servers. We’ll also examine how RAFT ensures that the same commands are applied to the state machine at a given log index on every peer, because of the leader’s one-way log distribution to followers.

Leader Initialisation

Once a candidate becomes leader we call setupLeader function which initiates go routine for each peer in the RAFT cluster, Each go routine of respective peer is responsible for replicating new log entries or sending heartbeat via AppendEntries RPC.

Building Fault Tolerant KV Storage System - Part 1

Fri, 03 Oct 2025 20:38:34 +0530

This blog post is part of a series detailing my implementation of a fault-tolerant key-value server using the RAFT consensus protocol. Before diving into RAFT and its mechanics, it’s crucial to grasp the concept of a replicated state machine and its significance in building systems that are both fault-tolerant and highly available.

Replicated State Machine

A replicated state machine is essentially a collection of identical machines working together. One machine acts as the “master,” handling client requests and dictating the system’s operations. The other machines, the “replicas,” diligently copy the master’s state. This “state” encompasses all the data necessary for the system to function correctly, remembering the effects of previous operations. Think of a key-value store: the state would be the key-value pairs themselves, replicated across all machines to maintain consistency and resilience. Having the master’s state copied across multiple machines enables us to use these replicas in several ways. They can take over as the new master if the original fails, or handle read operations to reduce the load on the master. Because the state is copied across machines, network issues like latency, packet loss, and packet reordering significantly affect how closely a replica’s state matches the master’s. The difference between the master’s (most up-to-date) state and a replica’s state is known as replication lag. Generally, we aim to minimize this lag, and different systems offer varying levels of consistency (which we will discuss later when covering replication in RAFT).

#Replication on Learning Loop

Building Fault Tolerant KV Storage System - Part 2

Leader Initialisation

Building Fault Tolerant KV Storage System - Part 1

Replicated State Machine