Inside the Social Network's (Datacenter) Network

Arjun Roy, Hongyi Zeng, Jasmeet Bagga, G. Porter, A. Snoeren
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引用次数: 814

Abstract

Large cloud service providers have invested in increasingly larger datacenters to house the computing infrastructure required to support their services. Accordingly, researchers and industry practitioners alike have focused a great deal of effort designing network fabrics to efficiently interconnect and manage the traffic within these datacenters in performant yet efficient fashions. Unfortunately, datacenter operators are generally reticent to share the actual requirements of their applications, making it challenging to evaluate the practicality of any particular design. Moreover, the limited large-scale workload information available in the literature has, for better or worse, heretofore largely been provided by a single datacenter operator whose use cases may not be widespread. In this work, we report upon the network traffic observed in some of Facebook's datacenters. While Facebook operates a number of traditional datacenter services like Hadoop, its core Web service and supporting cache infrastructure exhibit a number of behaviors that contrast with those reported in the literature. We report on the contrasting locality, stability, and predictability of network traffic in Facebook's datacenters, and comment on their implications for network architecture, traffic engineering, and switch design.
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在社交网络(数据中心)网络内部
大型云服务提供商已经投资于越来越大的数据中心,以容纳支持其服务所需的计算基础设施。因此,研究人员和行业从业者都集中了大量的精力来设计网络结构,以便以高效的方式有效地互连和管理这些数据中心内的流量。不幸的是,数据中心运营商通常不愿分享其应用程序的实际需求,因此很难评估任何特定设计的实用性。此外,文献中提供的有限的大规模工作负载信息,无论好坏,迄今为止主要是由单个数据中心运营商提供的,其用例可能并不广泛。在这项工作中,我们报告了在Facebook的一些数据中心观察到的网络流量。虽然Facebook运营着许多传统的数据中心服务,比如Hadoop,但它的核心Web服务和支持缓存的基础设施表现出了许多与文献报道不同的行为。我们报告了Facebook数据中心中网络流量的对比性、稳定性和可预测性,并评论了它们对网络架构、流量工程和交换机设计的影响。
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