使用分层Gossip协议监控大规模云系统
Monitoring Large-Scale Cloud Systems with Layered Gossip Protocols
摘要：
监控是维护和开发计算机系统的一个基本方面，其难度与系统的大小成比例地增加。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，包括开源领域的许多解决方案，依赖于过时的概念，包括手动部署和配置、集中式数据汇集，并且对会员流失的适应性很差。在本文中，我们提出了一个云监控套件的发展，提供可扩展的和强大的查找，数据汇集和分析服务的大规模云系统。代替集中管理的监控，我们提出了一个多层体系结构，使用分层的八卦协议来聚合监控信息，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操作的资源感知数据汇集和存储架构。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。我们评估这种方法对替代监测范式，并证明我们的解决方案是如何很好地适应在云计算环境中使用。
英文摘要：
Monitoring is an essential aspect of maintaining and developing computer systems that 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 Current monitoring solutions, including many of those in the open-source domain rely on outdated concepts including manual deployment and configuration, centralised data collection and adapt poorly to membership churn. In this paper we propose the development of a cloud monitoring suite 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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