This article presents a comprehensive design for a layered storage and unified scheduling platform that archives MySQL historical data, reduces storage costs, ensures high‑performance queries, and enables efficient data analysis through tiered hot, warm, and cold storage using big‑data technologies.
This case study details how NetEase Interactive Entertainment’s data team tackled massive log‑management chaos, storage bloat, and high overseas costs by standardizing logs, sharing a real‑time ODS layer, automating lifecycle management, tiered storage, and peak‑shaving compute scheduling, ultimately saving millions of yuan.
This article details Huolala's comprehensive big‑data cost‑control system—covering data‑asset measurement, budgeting, auxiliary governance, storage tiering, and elastic compute management—to dramatically reduce both storage and compute expenses while maintaining service quality across diverse workloads.
This article explains how to achieve storage tiering on Linux hosts by virtualizing fast SSDs and slower HDDs into a single device, detailing two approaches—kernel block‑device drivers and LVM‑based solutions—along with their implementation steps, open‑source projects, and trade‑offs.
