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The article explains consistency concepts in distributed systems—including strong and weak (eventual) consistency, CAP and FLP theorems, and key protocols such as 2PC, 3PC, and Paxos—detailing their mechanisms, advantages, and challenges.
This article explains the challenges of mutual exclusion and idempotency in distributed environments, compares thread‑level and process‑level solutions, describes the principles and typical implementations of distributed locks (Zookeeper, Redis, Tair, Cerberus), and introduces GTIS as a reliable idempotency framework.
This article provides a thorough overview of distributed systems, explaining their definition, core concepts such as partition and replication, key challenges, essential characteristics, typical components and protocols, a practical request flow example, and a curated list of real‑world implementations to help readers build a solid learning roadmap.
The article explains the importance of isolating resources such as CPU, network, and disk in distributed architectures, describes thread, process, cluster, data‑read/write, static, and crawler isolation methods, and provides concrete code examples and best‑practice recommendations for backend developers.
This article introduces core concepts of distributed systems, including node and replica models, various consistency levels, data distribution strategies, lease and quorum mechanisms, replica control protocols such as primary‑secondary, two‑phase commit, MVCC, Paxos, and the CAP theorem, providing a comprehensive overview for architects.
This article examines the challenges of mutual exclusion and idempotency in distributed environments, explains their underlying principles, compares multithread and multiprocess approaches, and presents practical distributed‑lock implementations such as Zookeeper, Redis, Tair, and the Cerberus framework, as well as the GTIS solution for idempotency.
This article provides a comprehensive overview of distributed system fundamentals, covering system models, node concepts, failure types, replication strategies, consistency levels, data distribution methods, replica control protocols such as primary‑secondary, two‑phase commit, lease‑based caching, quorum, MVCC, Paxos, and the CAP theorem.
The article explains why resource isolation is essential for distributed architectures, describes common isolation methods such as thread, process, cluster, data, static and crawler isolation, and provides concrete examples and code snippets for Netty, Dubbo, Tomcat, and Hystrix to illustrate practical implementations.
This article explains why session sharing is required in micro‑service and distributed environments and presents four practical solutions—Nginx ip_hash load balancing, Tomcat session replication, Redis centralized session cache, and cookie‑based sharing—detailing their implementations, code snippets, and pros and cons.
The article explains why resource isolation is essential in distributed architectures and details various isolation strategies—including thread, process, cluster, data read/write, static, and crawler isolation—illustrated with Netty, Dubbo, Tomcat examples, code snippets, and a comparison of thread‑pool versus semaphore isolation in Hystrix.