Distributed Locks

Part 2: Real-Time Multi-Warehouse Inventory Management

← Previous Chapter: Part 1: Order Fulfillment Fundamentals | Series Hub | Next Chapter: Part 3: Allocation Algorithms → Answer-first: Atomic stock reservations using Redis Lua scripts eliminate race conditions under 50,000+ RPS flash sales. Reserved stock automatically expires after a 15-minute lease if checkout is not completed.

Part 6: Distributed Locks, Mutex Invariants & Concurrency in Go

← Previous Chapter: Part 5: Asynchronous Messaging & Kafka KRaft | Series Hub: System Design Masterclass | Next Chapter: Part 7: Idempotency Key Architecture & Financial API Design → Prerequisite: Read Part 5: Asynchronous Messaging, Kafka KRaft & Event-Driven Systems to understand event streams before coordinating state across concurrent distributed workers. Answer-first: Distributed mutual exclusion in high-throughput Go microservices requires monotonic fencing tokens verified by the underlying storage engine to prevent race conditions during unexpected network partitions or garbage collection pauses. While Redis Redlock provides high-throughput probabilistic locking, Etcd Raft leases guarantee CP linearizability, sustaining zero double-spend anomalies across mission-critical financial microservices. ...

Part 8: Redis Distributed State vs. Dapr Virtual Actors Showdown

📖 Series Navigation: ← Previous Chapter: Modular Monolith vs Microservices vs SpinKube Wasm | Series Hub Part 8: Redis Distributed State vs. Dapr Virtual Actors Showdown Answer-first: Redis in-memory state with Lua scripts excels at high-throughput (100k+ QPS), low-latency caching and raw data manipulation. However, for complex distributed state machines, turn-based concurrency, and long-lived stateful AI agent context, Dapr Virtual Actors eliminate race conditions, distributed locking overhead, and manual lifecycle plumbing via single-threaded mailboxes and automatic hydration. ...