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This article introduces core queueing theory concepts such as Kendall notation, M/M/1 and M/M/c models, Little’s Law, Erlang formulas, and demonstrates their practical application through a detailed Python simulation of a bank service system.
This article details how Qunar's ATPCO international fare system was analyzed and optimized through performance profiling, application of Little's Law and Amdahl's Law, code refactoring, cache replacement, pruning of search space, and concurrency improvements such as ForkJoinPool to dramatically reduce response times and CPU pressure.
This article explains the essential practice of limiting work-in-progress in product development, using the ancient Chinese engineer Pan Jixun's "water‑constriction" strategy as an analogy to illustrate how reducing WIP accelerates delivery cycles and instantly reveals problems, supported by Little's Law and real‑world examples.