SRL:用于多云环境的可伸缩性规则语言

K. Kritikos, Jörg Domaschka, A. Rossini
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引用次数: 56

摘要

云计算的好处导致了基础设施和平台的激增,这些基础设施和平台涵盖了许多基于云的应用程序的供应和部署需求。然而,应用程序的需求可能在其生命周期中发生变化。因此,应该调整其供应和部署,以便应用程序能够在整个生命周期中交付其目标服务质量。现有的解决方案通常只支持简单的适应场景,即可伸缩性规则将固定指标的条件映射到针对单个云环境的单个扩展操作(例如,向外扩展应用程序组件)。然而,这些解决方案无法支持复杂的适应场景,在这些场景中,可伸缩性规则可以将自定义指标的条件映射到针对多云环境的多个扩展操作。在本文中,我们提出了可伸缩性规则语言(SRL),这是一种用于指定支持多云应用程序复杂适应场景的可伸缩性规则的语言。SRL提供了基于eclipse的工具支持,因此,建模人员不仅可以指定可伸缩性规则,还可以在语法和语义上验证这些规则。此外,SRL与云建模语言(Cloud modeling Language, Cloud ML)集成得很好,从而允许建模者将其可伸缩性规则与供应和部署模型的组件和虚拟机关联起来。
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SRL: A Scalability Rule Language for Multi-cloud Environments
The benefits of cloud computing have led to a proliferation of infrastructures and platforms covering the provisioning and deployment requirements of many cloud-based applications. However, the requirements of an application may change during its life cycle. Therefore, its provisioning and deployment should be adapted so that the application can deliver its target quality of service throughout its entire life cycle. Existing solutions typically support only simple adaptation scenarios, whereby scalability rules map conditions on fixed metrics to a single scaling action targeting a single cloud environment (e.g., Scale out an application component). However, these solutions fail to support complex adaptation scenarios, whereby scalability rules could map conditions on custom metrics to multiple scaling actions targeting multi-cloud environments. In this paper, we propose the Scalability Rule Language (SRL), a language for specifying scalability rules that support such complex adaptation scenarios of multi-cloud applications. SRL provides Eclipse-based tool support, thus allowing modellers not only to specify scalability rules but also to syntactically and semantically validate them. Moreover, SRL is well integrated with the Cloud Modelling Language (Cloud ML), thus allowing modellers to associate their scalability rules with the components and virtual machines of provisioning and deployment models.
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