Over ten years of BAT architecture experience, shared generously!
The article explains what cache penetration is in high‑concurrency architectures, why it occurs, and presents four practical mitigation strategies—including caching empty values, using Bloom filters, validating request data, and applying rate‑limiting—to protect backend databases from overload.
This article explains Nginx’s core concurrency mechanisms—including its multi‑process architecture, event‑driven model, I/O multiplexing techniques like epoll, and non‑blocking I/O—highlighting how they provide high stability, low resource consumption, and excellent performance for high‑traffic network services.
This article explains Redis master‑slave replication, covering the roles of master and replica, the full‑copy synchronization process, the incremental sync mechanism, and the step‑by‑step workflow illustrated with diagrams to help engineers implement reliable high‑availability data stores.
This guide explains how to tune Nginx for maximum performance by leveraging multi‑core CPUs, increasing concurrent connections, enabling zero‑copy file transfer, and optimizing keep‑alive settings, with concrete configuration examples and practical recommendations.
Learn how Nginx’s powerful caching mechanism can slash response times by up to tenfold, reduce backend load, and increase throughput, with detailed explanations of the caching workflow, essential configuration directives, micro‑cache tricks, and FastCGI caching examples for high‑traffic services.
This guide explains how to build a million‑request‑per‑second microservice system by properly splitting business domains, partitioning data with vertical and horizontal sharding, applying robust rate‑limiting techniques, and implementing circuit‑breaking and degradation strategies to maintain stability.
This article explains the fundamentals of distributed communication, outlines essential elements such as serialization, transport protocols, service discovery, load balancing, security, and reliability, and reviews popular frameworks like gRPC, Dubbo, Thrift, and OpenFeign for building robust backend architectures.
This article explains Redis cache penetration, its causes such as malicious attacks and faulty business logic, and presents four mitigation strategies—Bloom filters, caching empty values, rate limiting, and authentication with validation—to protect database performance and system stability.
This article explains what a cache avalanche is, why it occurs in distributed systems, and presents practical mitigation techniques such as multi‑level caching, staggered expirations, mutex locks, and hotspot isolation to keep backend services stable under high load.
This article explains practical techniques to stop Redis cache penetration—including using Bloom filters to pre‑check keys, caching empty responses, applying request rate limiting, and adding authentication checks—while outlining each method's advantages and drawbacks.
