The article analyzes why manual capacity adjustments break down at ten‑million‑QPS scale, then walks through metric‑driven autoscaling, anti‑flapping algorithms, headroom planning, predictive scaling, stateful service challenges, and multi‑dimensional strategies to achieve a cost‑stable dynamic balance.
The article outlines how Tencent Cloud's TDSQL‑C tackles the four core pain points of traditional databases—elasticity, tuning difficulty, cost waste, and operational complexity—by adopting a storage‑compute‑separated, Serverless architecture, AI‑driven predictive scaling, a self‑learning optimizer, and the AI Navigator management system, delivering up to 30% performance gains and 20% cost reduction in real‑world use cases.
This article details Qunar's end‑to‑end solution for forecasting traffic spikes, estimating required CPU resources, and automatically scaling hotel services using a combined flow‑calendar, algorithmic prediction, and Ops‑driven auto‑scaling pipeline, improving stability and operational efficiency.
