一句话：提出基于热力图的可视化监控工具 CloudHeatMap，支持大规模云系统近实时健康与性能监测。
大规模云系统（LCS）的遥测数据复杂且规模庞大，传统监控工具难以从中及时提取关键洞察，运维人员不易快速定位性能问题。本文提出 CloudHeatMap，一种基于热力图的可视化工具，用于对大规模云系统健康状态进行近实时监控。它通过直观展示调用量、响应时间等关键指标，帮助操作者迅速识别异常与性能瓶颈。作者以 IBM Cloud Console 为案例进行研究，表明该工具能够增强运维监控与决策支持。评估以案例研究为主，展示了实际部署效果，但未给出与传统工具的量化对比。
Cloud computing is essential for modern enterprises, requiring robust tools to monitor and manage Large-Scale Cloud Systems (LCS). Traditional monitoring tools often miss critical insights due to the complexity and volume of LCS telemetry data. This paper presents CloudHeatMap, a novel heatmap-based visualization tool for near-real-time monitoring of LCS health. It offers intuitive visualizations of key metrics, such as call volumes and response times, enabling operators to quickly identify performance issues. A case study on the IBM Cloud Console shows the tool's effectiveness in enhancing operational monitoring and decision-making.
@inproceedings{SohanaPSM25,
title = {CloudHeatMap: Heatmap-Based Monitoring for Large-Scale Cloud Systems},
author = {Sarah Sohana and William Pourmajidi and John Steinbacher and Andriy Miranskyy},
booktitle = {FSE},
year = {2025},
doi = {10.1145/3696630.3728588}
}