下一代数据中心EA系统的性能工程下一代数据中心EA系统的性能工程

J. Rolia, L. Cherkasova, R. Friedrich
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引用次数: 1

摘要

软件性能工程(SPE)方法作为一种管理开发系统无法满足其性能需求的风险的方法已经使用了20多年。一般来说,SPE提倡使用面向性能的设计原则来指导设计决策,并使用预测性能模型来评估设计备选方案对性能的影响。SPE方法已经成功地用于在信息技术(IT)项目生命周期的早期识别和克服系统设计错误,防止错误被构建到系统中,从而变得昂贵和耗时。虽然这些方法已经在一些IT项目领域中得到了成功的应用,但是它们并没有在企业应用系统的重要领域中得到广泛的应用。本文探讨了其中的原因,并探讨了随着新的EA平台和数据中心技术的出现,SPE所扮演的角色。我们发现,传统上由SPE处理的许多风险已经被现有EA平台的性质、当今EA IT项目的性质以及对业务流程建模的关注所减轻。此外,下一代数据中心的新EA和IT系统管理平台将进一步降低未来EA系统的设计和实现中的一些性能风险。然而,我们期望要构建的EA系统的性质变得更加复杂。因此,一些熟悉的性能风险将与新的运行时风险一起重新出现。我们相信SPE方法可以帮助减轻这些风险,并描述必须解决的研究挑战,以实现这一目标。
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Performance engineering for EA systems in next generation data centresPerformance engineering for EA systems in next generation data centres
Software Performance Engineering (SPE) methods have been in use for over two decades as an approach to manage the risks of developing systems that fail to satisfy their performance requirements. In general, SPE advocates the use of performance oriented design principles to guide design decisions and predictive performance models to assess the performance impact of design alternatives. SPE methods have been used successfully to identify and overcome system design blunders early in the Information Technology (IT) project lifecycle before the blunders are built into a system and become expensive and time consuming to correct. While the methods have been used successfully in some IT project domains, they are not widely applied in the important domain of Enterprise Application (EA) systems. This experience paper considers the reasons for this and explores the role of SPE as new EA platform and data centre technologies become available.We find that many risks traditionally addressed by SPE have been mitigated by the nature of existing EA platforms, the nature of today's IT projects for EA, and an attention to business process modeling. Furthermore, the design and implementation of future EA systems will see some performance risks reduced even further by new EA and IT system management platforms for Next Generation Data Centres. However, we expect that the nature of EA systems to be built is becoming more complex. As a result some familiar performance risks will re-emerge along with new runtime risks. We believe that SPE methods can help to mitigate such risks and describe research challenges that must be addressed to make this a reality.
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