Data Centers in the Cloud: A Large Scale Performance Study

R. Birke, L. Chen, E. Smirni
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引用次数: 67

Abstract

With the advancement of virtualization technologies and the benefit of economies of scale, industries are seeking scalable IT solutions, such as data centers hosted either in-house or by a third party. Data center availability, often via a cloud setting, is ubiquitous. Nonetheless, little is known about the in-production performance of data centers, and especially the interaction of workload demands and resource availability. This study fills this gap by conducting a large scale survey of in-production data center servers within a time period that spans two years. We provide in-depth analysis on the time evolution of existing data center demands by providing a holistic characterization of typical data center server workloads, by focusing on their basic resource components, including CPU, memory, and storage systems. We especially focus on seasonality of resource demands and how this is affected by different geographical locations. This survey provides a glimpse on the evolution of data center workloads and provides a basis for an economics analysis that can be used for effective capacity planning of future data centers.
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云中的数据中心:大规模性能研究
随着虚拟化技术的进步和规模经济的好处,行业正在寻求可扩展的IT解决方案,例如内部托管或由第三方托管的数据中心。数据中心可用性(通常通过云设置)无处不在。尽管如此,对于数据中心的生产性能,特别是工作负载需求和资源可用性之间的相互作用,我们知之甚少。本研究通过在两年的时间内对生产中的数据中心服务器进行大规模调查,填补了这一空白。我们通过提供典型数据中心服务器工作负载的整体特征,重点关注其基本资源组件(包括CPU、内存和存储系统),对现有数据中心需求的时间演变进行了深入分析。我们特别关注资源需求的季节性以及这如何受到不同地理位置的影响。该调查提供了对数据中心工作负载演变的一瞥,并为可用于未来数据中心有效容量规划的经济分析提供了基础。
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