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Testing of complex, large-scale distributed storage systems: a CERN disk storage case study

机译:测试复杂的大型分布式存储系统:CERN磁盘存储案例研究

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Complex, large-scale distributed systems are frequently used to solve extraordinary computing, storage and other problems. However, the development of these systems usually requires working with several software components, maintaining and improving a large codebase and also providing a collaborative environment for many developers working together. The central role that such complex systems play in mission critical tasks and also in the daily activity of the users means that any software bug affecting the availability of the service has far reaching effects.Providing an easily extensible testing framework is a pre-requisite for building both confidence in the system but also among developers who contribute to the code. The testing framework can address concrete bugs found in the odebase thus avoiding any future regressions and also provides a high degree of confidence for the people contributing new code. Easily incorporating other people's work into the project greatly helps scaling out manpower so that having more developers contributing to the project can actually result in more work being done rather then more bugs added.In this paper we go through the case study of EOS, the CERN disk storage system and introduce the methods and mechanisms of how to achieve all-automatic regression and robustness testing along with continuous integration for such a large-scale, complex and critical system using a container-based environment.
机译:复杂的大规模分布式系统通常用于解决非凡的计算,存储和其他问题。但是,这些系统的开发通常需要使用多个软件组件,维护和改进大型代码库,还需要为许多一起工作的开发人员提供协作环境。如此复杂的系统在任务关键型任务以及用户的日常活动中发挥着核心作用,这意味着影响服务可用性的任何软件错误都将产生深远的影响。提供易于扩展的测试框架是构建该系统的先决条件不仅对系统充满信心,而且对代码做出贡献的开发人员也是如此。测试框架可以解决在odebase中发现的具体错误,从而避免将来出现任何退步,并且还为贡献新代码的人员提供了高度的信心。轻松地将其他人的工作纳入项目中,可以极大地减少人力,从而使更多的开发人员为该项目做出贡献实际上可以导致完成更多的工作,而不是增加更多的错误。在本文中,我们对EOS(CERN)进行了案例研究磁盘存储系统,并介绍了如何使用基于容器的环境为这样的大规模,复杂和关键系统实现全自动回归和健壮性测试以及持续集成的方法和机制。

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