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Designing Fault-Tolerant Event Streams with Raft Consensus in Go

From leader election to log replication: A ground-up implementation for distributed state consistency.

Alex Rivera
Alex Rivera
Staff Infrastructure Engineer
·
Published on Aug 25, 2026
14 min read
Designing Fault-Tolerant Event Streams with Raft Consensus in Go

Building high-availability distributed systems requires strong consistency guarantees. Here is how we implemented Raft consensus for an internal distributed log.

1. Raft State Machine & Node Roles

In a distributed cluster, nodes transition between three distinct roles: Follower, Candidate, and Leader. If a follower misses heartbeats during its randomized election timer, it converts to a candidate and requests votes.

Alex Rivera

Written by Alex Rivera

Building resilient distributed systems and vector database engines. Previously at AWS & Stripe.

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