This article explains how to build an effective multi‑level caching system in microservice architectures, covering client‑side browser caching, application‑layer static resource caching with CDN and Nginx, and service‑layer caches using in‑process and distributed solutions like Redis, plus consistency strategies.
This article explains why caching is essential for reducing CPU and I/O pressure, outlines key cache attributes such as throughput and hit rate, compares popular local cache libraries, describes distributed cache options, and details the design, consistency, monitoring, and hot‑key handling of a transparent multilevel cache architecture.
The article introduces Youzan's Transparent Multilevel Cache (TMC), detailing its three‑layer architecture, hotspot detection and local caching mechanisms, integration approaches for Java applications, stability and consistency features, and performance results from real‑world e‑commerce campaigns.
This article explains the design, architecture, and implementation of Transparent Multilevel Cache (TMC), a solution that adds application‑level hotspot detection and local caching to reduce cache hot‑spot pressure, improve consistency, and boost performance for Java services in high‑traffic scenarios.
The article explains Youzan’s Transparent Multilevel Cache (TMC), detailing its architecture, hotspot detection, local caching, consistency mechanisms, and real‑world performance gains during flash‑sale events, showing how it reduces cache pressure and improves latency for Java‑based services.
This article explains Youzan's Transparent Multilevel Cache (TMC), detailing its architecture, transparent Java integration, hotspot detection and local caching mechanisms, and demonstrates its real‑world performance gains during flash‑sale events and large‑scale marketing campaigns.
This article shares a senior architect’s ten‑year journey with caching, covering local page and object caches, refresh policies, distributed solutions like Redis and Memcached, pagination caching techniques, multi‑level cache architectures, common pitfalls, and practical optimization lessons for high‑performance backend systems.
This article shares a senior architect’s decade‑long journey with caching, covering page‑level and object caches, refresh mechanisms, distributed solutions like Redis and Memcached, pagination caching techniques, and multi‑level cache architectures, while highlighting practical pitfalls and performance gains.
This article explains why a multi‑level cache combining JVM‑level Caffeine and distributed Redis is essential for modern Spring Boot applications, outlines design challenges, provides step‑by‑step integration instructions, and demonstrates performance gains with benchmark results and core implementation code.
