私有云平台资源监控与优化系统

Resource Monitoring and Optimization System on Private Cloud Platform

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。

For enterprise level private cloud systems,thousands of virtual maclalne instances are ueployeu oil mU,Ul-,l~ 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.