Performance and scalability testing and measurements of cloud-based software services are necessary for future optimizations and growth of cloud computing. Scalability, elasticity, and efficiency are interrelated aspects of cloud-based software services’ performance requirements. In this work, we use a technical measurement of the scalability of cloud-based software services. Our technical scalability metrics are inspired by metrics of elasticity. We used two cloud-based systems to demonstrate the usefulness of our metrics and compare their scalability performance in two cloud platforms: Amazon EC2 and Microsoft Azure. Our experimental analysis considers three sets of comparisons: first we compare the same cloud-based software service hosted on two different public cloud platforms; second we compare two different cloud-based software services hosted on the same cloud platform; finally, we compare between the same cloud-based software service hosted on the same cloud platform with two different auto-scaling policies. We note that our technical scalability metrics can be integrated into a previously proposed utility oriented metric of scalability. We discuss the implications of our work.

中文翻译：

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基于云的软件服务的可伸缩性分析比较

基于云的软件服务的性能和可伸缩性测试以及测量对于将来的优化和云计算的增长是必需的。可伸缩性，弹性和效率是基于云的软件服务性能要求的相互关联的方面。在这项工作中，我们使用了基于云的软件服务可伸缩性的技术度量。我们的技术可扩展性指标受弹性指标的启发。我们使用了两个基于云的系统来演示指标的有用性，并比较它们在两个云平台（Amazon EC2和Microsoft Azure）中的可伸缩性性能。我们的实验分析考虑了三组比较：首先，我们比较了托管在两个不同公共云平台上的基于云的软件服务；其次，我们比较了托管在同一云平台上的两种不同的基于云的软件服务；最后，我们将托管在相同云平台上的相同基于云的软件服务与两种不同的自动扩展策略进行比较。我们注意到，我们的技术可扩展性度量可以集成到先前提出的面向实用程序的可扩展性度量中。我们讨论工作的意义。