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An empirical study for evaluating the performance of multi-cloud APIs

机译:评估多云API性能的实证研究

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AbstractThe massive use of cloud APIs for workload orchestration and the increased adoption of multiple cloud platforms prompted the rise of multi-cloud APIs. Multi-cloud APIs abstract cloud differences and provide a single interface regardless of the target cloud platform. Identifying whether the performance of multi-cloud APIs differs significantly from platform-specific APIs is central for driving technological decisions on cloud applications that require maximum performance when using multiple clouds. This study aims to evaluate the performance of multi-cloud APIs when compared to platform-specific APIs. We carried out three rigorous quasi-experiments to measure the performance (dependent variable) of cloud APIs (independent variable) regarding CPU time, memory consumption and response time. jclouds and Libcloud were the two multi-cloud APIs used (experimental treatment). Their performance were compared to platform-specific APIs (control treatment) provided by Amazon Web Services and Microsoft Azure. These APIs were used for uploading and downloading (tasks) 39 722 files in five different sizes to/from storage services during five days (trials). Whereas jclouds performed significantly worse than platform-specific APIs for all performance indicators on both cloud platforms and operations for all five file sizes, Libcloud outperformed platform-specific APIs in most tests (p-value not exceeding 0.00125,A-statistic greater than 0.64). Once confirmed by independent replications, our results suggest that jclouds developers should review the API design to ensure minimal overhead whereas jclouds users should evaluate the extent to which this trade-off affect the performance of their applications. Multi-cloud users should carefully evaluate what quality attribute is more important when selecting a cloud API.HighlightsThe performance of multi-cloud differs significantly from platform-specific APIs.jclouds performed significantly worse than platform-specific APIs in all tests.Libcloud outperformed platform-specific APIs in most tests.Multi-cloud users should evaluate what quality attribute is more important.
机译: 摘要 大量使用云API进行工作流程编排,并且越来越多的采用云平台推动了多云API的兴起。多云API可以抽象出云差异并提供单个接口,而与目标云平台无关。识别多云API的性能是否与特定于平台的API显着不同,对于在使用多个云时需要最高性能的云应用程序制定技术决策至关重要。与平台特定的API相比,本研究旨在评估多云API的性能。我们针对CPU时间,内存进行了三个严格的准实验,以测量云API(自变量)的性能(因变量)消耗和响应时间。 jclouds和Libcloud是使用的两个多云API(实验性处理)。将它们的性能与Amazon Web Services和Microsoft Azure提供的特定于平台的API(控制处理)进行了比较。这些API用于在五天内将五种不同大小的39 722个文件上传/从存储服务上载(任务)( trials )。尽管jclouds在云平台和所有五个文件大小的操作上的所有性能指标均比平台API差很多,但是Libcloud在大多数测试中均优于平台API( p -value不超过0.00125, A 统计值大于0.64)。一旦得到独立复制的确认,我们的结果表明jclouds开发人员应审查API设计以确保最小的开销,而jclouds用户应评估这种权衡对应用程序性能的影响程度。多云用户在选择云API时应仔细评估哪种质量属性更为重要。 突出显示 多云的性能与特定于平台的API明显不同。< / ce:para> jclouds在所有测试中的性能均比特定平台的API差。 < ce:label>• Libcloud的表现优于特定平台大多数测试中的API。 多云用户应评估哪个质量属性更为重要。

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