Dynamo: Facebook的数据中心范围电源管理系统

Qiang Wu, Qingyuan Deng, L. Ganesh, Chang-Hong Hsu, Yun Jin, Sanjeev Kumar, Bin Li, Justin Meza, YeeJiun Song
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引用次数: 118

摘要

数据中心的电力是一种稀缺资源,由于规划保守,常常得不到充分利用。这是因为数据中心供电层次结构过载和断路器跳闸的代价非常高,可能会导致长时间的服务中断。最近,有人提出并研究了动态服务器功率上限,它限制了服务器消耗的功率,作为减少这种损失的一种方法,从而能够更积极地利用所提供的数据中心功率。然而,文献中还没有针对数据中心范围内的电力监测和控制提出真正的大规模解决方案。在本文中,我们描述了Dynamo——一个数据中心范围的电源管理系统,它监视整个电源层次,并做出协调的控制决策,以安全有效地使用预置的数据中心电源。在过去的三年里,Dynamo已经被开发并部署到Facebook的所有数据中心。我们的主要见解是,在真实的数据中心中,电源层次结构中不同级别的不同电源和性能约束需要协调数据中心范围的电源管理。我们做出了三个主要贡献。首先,为了理解Dynamo的设计空间,我们提供了运行各种现代工作负载的数据中心的功率变化特征。这种特性使用了来自数万台服务器的细粒度电源样本,时间跨度超过6个月。其次,给出了Dynamo的详细设计。我们的设计解决了以前基于模拟的研究没有解决的几个关键问题。第三,所提出的技术和设计已经在服务数十亿用户的大型数据中心中进行了部署和评估。我们展示的生产结果显示,在过去6个月里,Dynamo已经防止了18次由于意外的电力激增而导致的潜在停电,Dynamo使生产Hadoop集群的性能提高了13%,搜索集群的性能提高了近40%,并且Dynamo已经使我们的一个数据中心的电力容量利用率提高了8%,并且正在采取更积极的电力订阅措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamo: Facebook's Data Center-Wide Power Management System
Data center power is a scarce resource that often goes underutilized due to conservative planning. This is because the penalty for overloading the data center power delivery hierarchy and tripping a circuit breaker is very high, potentially causing long service outages. Recently, dynamic server power capping, which limits the amount of power consumed by a server, has been proposed and studied as a way to reduce this penalty, enabling more aggressive utilization of provisioned data center power. However, no real at-scale solution for data center-wide power monitoring and control has been presented in the literature. In this paper, we describe Dynamo -- a data center-wide power management system that monitors the entire power hierarchy and makes coordinated control decisions to safely and efficiently use provisioned data center power. Dynamo has been developed and deployed across all of Facebook's data centers for the past three years. Our key insight is that in real-world data centers, different power and performance constraints at different levels in the power hierarchy necessitate coordinated data center-wide power management. We make three main contributions. First, to understand the design space of Dynamo, we provide a characterization of power variation in data centers running a diverse set of modern workloads. This characterization uses fine-grained power samples from tens of thousands of servers and spanning a period of over six months. Second, we present the detailed design of Dynamo. Our design addresses several key issues not addressed by previous simulation-based studies. Third, the proposed techniques and design have been deployed and evaluated in large scale data centers serving billions of users. We present production results showing that Dynamo has prevented 18 potential power outages in the past 6 months due to unexpected power surges, that Dynamo enables optimizations leading to a 13% performance boost for a production Hadoop cluster and a nearly 40% performance increase for a search cluster, and that Dynamo has already enabled an 8% increase in the power capacity utilization of one of our data centers with more aggressive power subscription measures underway.
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