用于多层Web应用程序的轻量级自动资源缩放

Lenar Yazdanov, C. Fetzer
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引用次数: 18

摘要

动态资源扩展是云计算的一个关键特性。用户可以动态获取或释放应用程序所需的容量。基于预定义策略(规则)的最广泛使用和最实用的动态扩展方法。例如,RightScale等IaaS提供商要求应用程序所有者手动设置缩放规则。此任务假定用户具有在云上运行的应用程序的专业知识。然而,这并不总是正确的。在本文中,我们提出了一个轻量级的自适应多层缩放框架VscalerLight,它在线学习缩放策略。我们的框架执行多层web应用程序的细粒度垂直资源扩展。本文介绍了VscalerLight的设计与实现。我们根据广泛使用的RUBiS基准来评估框架。结果表明,在VscalerLight控制下的应用程序保证了SLA规定的95百分位响应时间。
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Lightweight Automatic Resource Scaling for Multi-tier Web Applications
Dynamic resource scaling is a key property of cloud computing. Users can acquire or release required capacity for their applications on-the-fly. The most widely used and practical approach for dynamic scaling based on predefined policies (rules). For example, IaaS providers such as RightScale asks application owners to manually set the scaling rules. This task assumes, that the user has an expertise knowledge about the application being run on the cloud. However, it is not always true. In this paper we propose a lightweight adaptive multi-tier scaling framework VscalerLight, which learns scaling policy online. Our framework performs fine-grained vertical resource scaling of multi-tier web application. We present the design and implementation of VscalerLight. We evaluate the framework against widely used RUBiS benchmark. Results show that the application under control of VscalerLight guarantees 95th percentile response time specified in SLA.
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