大型云系统的现场监测

Jonathan Stuart Ward, A. Barker
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引用次数: 26

摘要

监控是维护和开发计算机系统的一个重要方面,其难度与系统的规模成正比。随着云计算的出现,对强大的监控工具的需求变得更加明显。基础设施即服务(IaaS)云允许最终用户部署大量虚拟机,作为动态和瞬态架构的一部分。当前的监控解决方案,包括许多开源领域的解决方案,依赖于过时的概念,包括手动配置和集中数据收集,并且难以适应会员流失。在本文中,我们建议开发一个云监控系统,为大型云系统提供可扩展和健壮的查找、数据收集和分析服务。为了代替集中管理的监控,我们提出了一种多层体系结构,使用分层八卦协议来聚合监控信息,并方便查找、信息收集和冗余容量的识别。这允许在被监视的系统上运行资源感知的数据收集和存储体系结构。这反过来又使监测能够在现场进行,而不需要大量额外的基础设施来促进监测服务。我们针对其他监控范例评估了这种方法,并演示了我们的解决方案如何很好地适应云计算上下文中的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Varanus: In Situ Monitoring for Large Scale Cloud Systems
Monitoring is an essential aspect of maintaining and developing computer systems which increases in difficulty proportional to the size of the system. The need for robust monitoring tools has become more evident with the advent of cloud computing. Infrastructure as a Service (IaaS) clouds allow end users to deploy vast numbers of virtual machines as part of dynamic and transient architectures. Current monitoring solutions, including many of those in the open-source domain, rely on outdated concepts including manual configuration and centralised data collection and adapt poorly to membership churn. In this paper we propose the development of a cloud monitoring system to provide scalable and robust lookup, data collection and analysis services for large-scale cloud systems. In lieu of centrally managed monitoring we propose a multi-tier architecture using a layered gossip protocol to aggregate monitoring information and facilitate lookup, information collection and the identification of redundant capacity. This allows for a resource aware data collection and storage architecture that operates over the system being monitored. This in turn enables monitoring to be done in situ without the need for significant additional infrastructure to facilitate monitoring services. We evaluate this approach against alternative monitoring paradigms and demonstrate how our solution is well adapted to usage in a cloud-computing context.
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