The Design and Operation of CloudLab

The Design and Operation of CloudLab
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发表时间:
2019-07
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通讯作者:
Dmitry Duplyakin;R. Ricci;Aleksander Maricq;Gary Wong;Jonathon Duerig;E. Eide;L. Stoller;Mike Hibler;David Johnson;Kirk Webb;Aditya Akella;Kuang-Ching Wang;Glenn Ricart;L. Landweber;C. Elliott;M. Zink;E. Cecchet;Snigdhaswin Kar;Prabodh Mishra
Dmitry Duplyakin;R. Ricci;Aleksander Maricq;Gary Wong;Jonathon Duerig;E. Eide;L. Stoller;Mike Hibler;David Johnson;Kirk Webb;Aditya Akella;Kuang-Ching Wang;Glenn Ricart;L. Landweber;C. Elliott;M. Zink;E. Cecchet;Snigdhaswin Kar;Prabodh Mishra
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作者:
Dmitry Duplyakin;R. Ricci;Aleksander Maricq;Gary Wong;Jonathon Duerig;E. Eide;L. Stoller;Mike Hibler;David Johnson;Kirk Webb;Aditya Akella;Kuang-Ching Wang;Glenn Ricart;L. Landweber;C. Elliott;M. Zink;E. Cecchet;Snigdhaswin Kar;Prabodh Mishra

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鉴于云计算,网络系统和相关领域的研究的高度经验性质,测试床在研究生态系统中起着重要作用。在本文中,我们介绍了一个这样的设施CloudLab,该设施通过提供可编程硬件的原始访问,在大规模上进行研究,并为可重复研究创建共享平台,从而支持系统研究。我们介绍了设计CloudLab并运行四年的经验,为近4,000名用户提供了在2,250台服务器,开关和其他数据中心设备上运行79,000多个实验的用户。从这一经验中,我们绘制了两个主题组织的课程。第一组来自有关CloudLab使用的数据的分析:用户如何与之交互,使用它的用途以及对设施设计和操作的影响。我们的第二组课程来自研究算法在“引擎盖下”使用的方式,例如资源分配,对用户体验和行为具有重要的(有时甚至是意外)的影响。这些课程对于一般的IaaS设施的设计师和运营商,特别是系统测试台,以及在理解这些系统的构建方式方面具有价值。
Given the highly empirical nature of research in cloud computing, networked systems, and related fields, testbeds play an important role in the research ecosystem. In this paper, we cover one such facility, CloudLab, which supports systems research by providing raw access to programmable hardware, enabling research at large scales, and creating a shared platform for repeatable research. We present our experiences designing CloudLab and operating it for four years, serving nearly 4,000 users who have run over 79,000 experiments on 2,250 servers, switches, and other pieces of datacenter equipment. From this experience, we draw lessons organized around two themes. The first set comes from analysis of data regarding the use of CloudLab: how users interact with it, what they use it for, and the implications for facility design and operation. Our second set of lessons comes from looking at the ways that algorithms used "under the hood," such as resource allocation, have important-- and sometimes unexpected--effects on user experience and behavior. These lessons can be of value to the designers and operators of IaaS facilities in general, systems testbeds in particular, and users who have a stake in understanding how these systems are built.