计算机工程 ›› 2018, Vol. 44 ›› Issue (3): 1-7.doi: 10.3969/j.issn.1000-3428.2018.03.001

所属专题: 云计算专题

• 云计算专题 • 上一篇    下一篇

私有云平台资源监控与优化系统

杨光a,谢锐b,薛广涛a   

  1. (上海交通大学 a.电子信息与电气工程学院; b.网络信息中心,上海 200240)
  • 收稿日期:2017-03-22 出版日期:2018-03-15 发布日期:2018-03-15
  • 作者简介:杨光(1990—),男,硕士,主研方向为云计算、虚拟化技术;谢锐(通信作者),高级工程师;薛广涛,教授。
  • 基金项目:
    国家高技术研究发展计划项目(2015AA01A202)。

Resource Monitoring and Optimization System on Private Cloud Platform

YANG Guanga,XIE Ruib,XUE Guangtaoa   

  1. (a.School of Electronic Information and Electrical Engineering; b.Network Information Center,Shanghai Jiaotong University,Shanghai 200240,China)
  • Received:2017-03-22 Online:2018-03-15 Published:2018-03-15

摘要: 目前中大型的私有云集群通常分布在全国多数据中心且同时运行大量虚拟机实例,对其产生的大量监控数据进行实时分析与离线统计,将面临巨大的计算、存储与网络压力。为此,设计一个面向大型私有云的资源监控与优化系统。采用大数据方法对数据进行分布式计算,解决对大型私有云的监控问题,同时基于采集的监控数据,通过热迁移机制减少因集群物理资源分配不均匀导致的资源浪费。实验结果表明,该系统可以满足用户对私有云的实时监控与离线统计需求,并提升13%以上的物理资源利用率。

关键词: 监控系统, 资源优化, 自动化运维, 私有云平台, 分布式计算

Abstract: For enterprise level private cloud systems,thousands of virtual machine instances are deployed on multiple data centers across the nation,which will generate massive raw data for the monitoring system to persist and process.This makes a significant pressure on computing,storage and network for monitoring system providing real-time monitor and statistical reports.Aiming at this problem,this paper designs a monitoring system for large scale private cloud by using whole set of big data method which makes the work distributed to solve the challenge mentioned above.Meanwhile,with the collected monitoring data,it uses thermal migration mechanism to reduce the waste of physical resources caused by unevenly distribution.Experimental result shows that this system can satisfy real-time monitoring as well as offline statistics and enhance above 13% physical resource utilization rate.

Key words: monitoring system, resource optimization, automated operation and maintenance, private cloud platform, distributed computing

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