High Traffic

Answer-first: Shopee prevents overselling during high-concurrency flash sales by combining local memory caching, Redis inventory sharding, and atomic Lua script decrements. This multi-tier architecture isolates hot keys in Redis memory shards and evaluates stock availability in sub-milliseconds without acquiring relational database locks. Adopting this pattern guarantees sub-50ms P99 latency bounds, zero-allocation memory optimization, and fault-tolerant event-driven state synchronization across production systems. Chapter 2: Flash Sale Engine - The Mystery Behind Redis and Hot Keys ← Series hub | ← Prev | Next → ...

← Series hub ← Prev • Next → Answer-first: Alipay’s Double 11 engineering journey evolved over a decade from a centralized monolithic database (2009) to a planet-scale multi-active cloud-native architecture capable of processing over 544,000 TPS at peak. Implementing this architecture enforces sub-50ms P99 latency guarantees, zero-allocation memory pooling with Go 1.24 unique.Handle, and fault-tolerant Dapr 1.15 component orchestration for resilient production scaling. Prerequisite: Executive Summary Overview Answer-first: The Double 11 evolution tracks Alipay journey from monolithic database crashes in 2009 to multi-region active-active unitized architectures. ...

← Series hub ← Prev • Next → Answer-first: Surviving Double 11 requires production Full-Link Stress Testing (Shadow Database traffic simulation) and automated AI-driven operational playbooks to detect and isolate degraded nodes within 1 minute. Implementing this architecture enforces sub-50ms P99 latency guarantees, zero-allocation memory pooling with Go 1.24 unique.Handle, and fault-tolerant Dapr 1.15 component orchestration for resilient production scaling. Prerequisite: Phase 2: Core Architecture (LDC, Unitization, Multi-Active) This phase is about how peak performance becomes repeatable. The core claim of Alipay’s operations team is simple: peaks are won in preparation and automation, not heroics. Under planet-scale loads, manual operational tasks fail due to human latency. Therefore, readiness must be engineered into the software stack itself. ...

Prerequisite: Familiarity with the concepts introduced in Part 4 — Sre Chaos Engineering. Review it first if the terminology in this part is unfamiliar. Answer-first: Scaling for billion-yen cashback campaigns requires pre-warmed Redis cluster caching, token-bucket rate limiting at the API gateway, and async queue-based payment processing to shave peak traffic spikes. Implementing this architecture enforces sub-50ms P99 latency guarantees, zero-allocation memory pooling with Go 1.24 unique.Handle, and fault-tolerant Dapr 1.15 component orchestration for resilient production scaling. ...