This article explains four core load‑balancing algorithms—Round Robin, Weighted Round Robin, Random, and Least Connections—detailing their principles, advantages, drawbacks, and typical scenarios where each method best fits modern backend systems.
This article explains how to determine a 100 000‑QPS rate‑limiting threshold by covering the purpose of throttling, the three core elements of limiting, common algorithms, target dimensions, capacity estimation for single‑service and full‑link scenarios, pressure‑testing techniques, monitoring data, and adaptive configuration strategies.
This article explains the fundamentals and practical implementations of common rate‑limiting algorithms—including fixed‑window, sliding‑window, leaky‑bucket, and token‑bucket—provides Java and Redis code samples, discusses their advantages, pitfalls, and real‑world production scenarios, and offers performance‑tuning tips.
This article explains the time‑wheel algorithm, from its basic circular‑buffer principle to simple, round‑based, and hierarchical variants, and shows how Kafka implements a multi‑level timing wheel to achieve efficient, low‑memory delayed task execution.
