预测软件可伸缩性的度量

E. Weyuker, Alberto Avritzer
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引用次数: 28

摘要

对于大多数企业来说,软件系统的可伸缩性是一个重要的问题。重要的是,随着客户群的增加,系统必须处理显著增加的负载,系统准备好处理增加的流量,这样用户就不会遇到不可接受的系统性能。出于这个原因,我们引入了一个新的度量,PNL度量,它可以用来预测性能问题的概率超过可接受水平的可能负载。通过一个案例研究说明了PNL度量在大型工业软件系统中的应用。提供了对软件建模和收集数据所采取的步骤的描述,以及PNL度量的计算以及从该系统的计算中得出的含义。项目使用这些信息来帮助规划额外的容量,以便客户体验到的性能可能仍然是可接受的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A metric to predict software scalability
Software system scalability is an important issue for most businesses. It is essential that as the customer base increases, and therefore the system has to deal with significantly increased loads, the system is prepared to handle the increased traffic so that the users do not encounter unacceptable system performance. For this reason we introduce a new metric, the PNL metric, that can be used to predict the likely loads at which the probability of performance problems will exceed acceptable levels. A case study is described that demonstrates the application of the PNL metric to a large industrial software system. A description of the steps taken to model the software and collect data is provided, as well as the computation of the PNL metric and implications derived from the computation for this system. This information was used by the project to help plan for additional capacity so that the performance experienced by customers was likely to remain acceptable.
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