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Varanus: In Situ Monitoring for Large Scale Cloud Systems

机译:Varanus:对大型云系统的原位监测

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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 Current monitoring solutions, including many of those in the open-source domain, rely on outdated concepts including manual configuration and centralised data collection and adapt poorly to membership churn.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.
机译:监测是维护和开发计算机系统的重要方面,该计算机系统难以与系统的大小成比例的困难。随着云计算的出现,对强大监测工具的需求变得更加明显。基础架构作为服务(IAAS)云允许最终用户将大量虚拟机部署为动态和瞬态架构的一部分。当前的监控解决方案,包括开源域中的许多人,依赖于过时的概念,包括手动配置和集中数据收集,并适应会员漏洞。在本文中,我们建议开发云监控系统,为大型云系统提供可扩展和强大的查找,数据收集和分析服务。代替集中管理监控我们使用分层的八卦协议提出多层架构,以聚合监控信息,并促进查找,信息收集和冗余容量的识别。这允许资源感知数据收集和存储在正在监视系统上的存储架构。这反过来可以使监控能够在原地上完成,而无需进行重要的额外基础设施,以便于监控服务。我们评估了这种方法,反对替代监测范式并展示我们的解决方案如何适应云计算上下文中的使用。

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