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Toward a Holistic Framework for Conducting Scientific Evaluations of OpenStack

机译:朝着对露天者进行科学评估的整体框架

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By massively adopting OpenStack for operating small to large private and public clouds, the industry has made it one of the largest running software project, overgrowing the Linux kernel. However, with success comes increased complexity, facing technical and scientific challenges, developers are in great difficulty when testing the impact of individual changes on the performance of such a large codebase, which will likely slow down the evolution of OpenStack. Thus, we claim it is now time for the scientific community to join the effort and get involved in the development of OpenStack, like it has been once done for Linux. In this spirit, we developed Enos, an integrated framework that relies on container technologies for deploying and evaluating OpenStack on any testbed. Enos allows researchers to easily express different configurations, enabling fine-grained investigations of OpenStack services. Enos collects performance metrics at runtime and stores them for post-mortem analysis and sharing. The relevance of the Enos approach to reproducible research is illustrated by evaluating different OpenStack scenarios on the Grid'5000 testbed.
机译:通过大规模采用OpenStack,为大型私人和公共云运行小而且,该行业已成为最大的运行软件项目之一,过度创建Linux内核。然而,随着成功增加了复杂性,面对技术和科学挑战,开发人员在测试个人变化对这种大码Base的性能的影响时,这可能会减缓露天术的演变。因此,我们声称现在是科学界的时间加入努力并参与开发的开发,就像它已经为Linux完成了。在这种精神中,我们开发了一个依赖于容器技术的综合框架,以便在任何测试平台上部署和评估OpenStack。 ENOS允许研究人员轻松表达不同的配置,从而实现了OpenStack服务的细粒度调查。 ENOS在运行时收集性能指标,并将其存储用于验尸分析和共享。通过评估网格5000测试台上的不同的OpenStack情景来说明ENOS方法对可重复研究的相关性。

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