A Study of the Impact of Network Partitioning Faults on Cloud Systems

Google分布式系统被设计为即使在设备、机器和**网络出现故障的情况下仍高度可用。网络分区故障带来了一个独特的挑战：它们是最难处理的故障之一，但不幸的是，在现代数据中心中越来越多地发生这种故障。**我们的目标是对五个广泛使用的**模仿谷歌内部系统的生产质量系统中与网络分区相关的故障进行深入的特征研究。我们的目标是更好地了解网络分区对现代分布式系统的**影响，了解导致用户可见系统故障的特定事件序列**，并对这些系统故障进行表征，以确定**提高系统容错能力的机会。我们计划利用我们的发现来设计网络分区测试**(NPTest)框架，这是一个可以创建和修复网络分区的系统级测试框架。为了产生更广泛的影响，我们计划将NPTest开源。**这个项目描述了现代网络复杂故障的影响，并有可能对技术产生**广泛的影响，包括构建Web规模系统的Google Canada。此外，对于**数据中心(包括位于加拿大的200多个中心)，该研究计划将提高**各种系统的可靠性，并为广泛的云应用带来好处，包括**医疗信息学、在线社交网络、人工智能和机器学习系统、**智能能量分配系统和文本分析等领域的应用。最后，该计划将为培训尖端网络和分布式系统**技术方面的高素质人员提供宝贵的**机会。

Google distributed systems are designed to be highly available despite failures of devices, machines, and**networks. Network-partitioning faults impose a unique challenge: They are some of the most**complex-to-handle faults but unfortunately are increasingly occurring in modern data centers.**We aim to conduct an in-depth characterization study of network-partitioning-related failures in five widely**used production-quality systems that mimic Google's internal systems. Our goal is to better understand the**impact of network partitioning on modern distributed systems, to understand the specific sequence of events**that lead to user-visible system failures, and to characterize these system failures to identify opportunities for**improving system fault tolerance. We plan to use our findings to design the network partitioning testing**(NPTest) framework, a system-level testing framework that can create and heal network partitions. For a wider**impact, we plan to make NPTest open source.**This project characterizes the impact of complex faults of modern networks and has the potential to have a**wide influence on technology, including Google Canada, which builds Web-scale systems. Furthermore, for**data centers (including the more than 200 centers located in Canada), this research program will improve the**reliability of a wide range of systems and bring benefits to a wide set of cloud applications, including**applications in fields such as medical informatics, online social networks, AI and machine learning systems,**smart energy distribution systems, and text analytics. Finally, this program will provide an invaluable**opportunity for training highly qualified personnel on cutting-edge networking and distributed systems**technology.