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Large Scale Monitoring and Online Analysis in a Distributed Virtualized Environment

机译:分布式虚拟化环境中的大规模监控和在线分析

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摘要

Due to increase in number and complexity of the large scale systems, performance monitoring and multidimensional quality of service (QoS) management has become a difficult and error prone task for system administrators. Recently, the trend has been to use virtualization technology, which facilitates hosting of multiple distributed systems with minimum infrastructure cost via sharing of computational and memory resources among multiple instances, and allows dynamic creation of even bigger clusters. An effective monitoring technique should not only be fine grained with respect to the measured variables, but also should be able to provide a high level overview of the distributed systems to the administrator of all variables that can affect the QoS requirements. At the same time, the technique should not add performance burden to the system. Finally, it should be integrated with a control methodology that manages performance of the enterprise system. In this paper, a systematic distributed event based (DEB) performance monitoring approach is presented for distributed systems by measuring system variables (physical/virtual CPU utilization and memory utilization), application variables (application queue size, queue waiting time, and service time), and performance variables (response time, throughput, and power consumption) accurately with minimum latency at a specified rate. Furthermore, we have shown that proposed monitoring approach can be utilized to provide input to an application monitoring utility to understand the underlying performance model of the system for a successful on-line control of the distributed systems for achieving predefined QoS parameters.
机译:由于大规模系统的数量和复杂性的增加,性能监测和多维服务质量(QoS)管理已成为系统管理员的困难且易于出错的任务。最近,该趋势一直在使用虚拟化技术,这促进了通过在多个实例之间共享计算和内存资源的最低基础设施成本的多个分布式系统,并且允许动态创建更大的群集。有效的监控技术不仅是对测量变量的细粒度,而且还应该能够为分布式系统的高级概述提供给可能影响QoS要求的所有变量的管理员。与此同时,该技术不应为系统添加性能负担。最后,它应该与控制方法集成,该方法管理企业系统的性能。在本文中,通过测量系统变量(物理/虚拟CPU利用率和内存利用率),应用程序变量(应用程序队列大小,队列等待时间和服务时间)来提出基于系统的基于系统的(DEB)性能监测方法。 ,性能变量(响应时间,吞吐量和功耗),以指定的速率最小延迟。此外,我们已经表明,建议的监视方法可以用于提供应用程序监控实用程序的输入,以了解系统的底层性能模型,以实现用于实现预定义QoS参数的分布式系统的成功在线控制。

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