How Distributed Locks Prevent Race Conditions Across Microservices

In distributed systems, multiple service replicas running simultaneously can access shared resources concurrently, risking issues like double-charging users or overselling inventory. A distributed lock ensures only one node can execute a critical operation at a time, unlike single-server mutex solutions. Redis is the most common implementation, using the SET NX EX command to atomically acquire a lock with an auto-expiring TTL that prevents deadlocks if a process crashes. Fencing tokens — monotonically increasing numbers issued per lock acquisition — further protect against stale processes writing outdated data. While Redis locks are fast and simple to deploy, scenarios requiring strong consistency or long-held locks are better served by tools like ZooKeeper or message queues.