Flash sale systems face extreme traffic spikes that can overwhelm databases. This article presents a layered filtering architecture that uses caching, rate limiting, and queue-based throttling to reduce database QPS from 100,000 to just 100. The design involves multiple layers: a CDN for static assets, a Redis cache for hot data, a rate limiter to control request flow, and a message queue to smooth out spikes. Each layer filters out requests, ensuring only a small fraction reach the database. This pattern is widely used in e-commerce platforms like Alibaba and JD.com. For developers building high-traffic systems, understanding this architecture is crucial for ensuring stability and performance. The post provides concrete numbers and design considerations, making it a valuable reference for system architects.
A deep dive into a layered filtering architecture that reduces database QPS from 100,000 to 100 in flash sale systems.