Redlock

Prerequisite: Part 6 of the System Design Masterclass. Read Part 5: Kafka & Event-Driven to understand event sourcing patterns before tackling lock coordination. Answer-first: Distributed locks solve the mutual exclusion problem across independent servers — ensuring only one server can modify a shared resource at a time. Redis Redlock provides high-performance locking using majority quorum across multiple master nodes; etcd provides stronger guarantees via Raft consensus at the cost of higher latency. ...

← Previous | Series hub | Next → Chapter 8: Synchronizing Clusters with Distributed Locks In a standalone Go application, preventing two Goroutines from overwriting the same data (Race Condition) is achieved via sync.Mutex. However, when your system scales out to 10 servers behind a Load Balancer, sync.Mutex is useless because it only locks local RAM. You need a Distributed Lock. 1. Basic Redis Locks Answer-first: A basic Redis lock utilizes SET resource id NX PX ttl. It works for simple caching but suffers from Single Point of Failure vulnerabilities if the Redis Master crashes before syncing. ...