为企业数据中心构建端到端管理分析

Hai Huang, Yaoping Ruan, A. Shaikh, R. Routray, C. Tan, Sandeep Gopisetty
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引用次数: 1

摘要

近年来,现代数据中心的复杂性发生了显著的变化。一个典型的由大量不同类型的中间件和应用程序组成,这些中间件和应用程序托管在物理和虚拟服务器的异构池中,由虚拟和物理网络的复杂网络连接。因此,为了管理数据中心中的一切,系统管理员通常需要大量的管理工具,因为一个工具通常只管理一种类型的设备。不同管理工具之间的界限可能会限制系统管理员处理日常任务的效率,因为每个工具只提供整个被管理环境的部分视图。因此,使用传统的管理工具通常无法实现影响分析和问题确定等高级分析,因为它们需要整个数据中心的整体视图。在本文中,我们描述了一个名为DataGraph的应用程序、服务器、网络和存储设备的集成管理系统。我们的系统集成了跨异构点产品和代理的数据,用于管理和监控,以实现上述管理分析功能。引入一个公共数据模型来联合多个数据库存储库中不同工具收集的数据,因此不需要对现有的管理工具进行修改。实现了一个通用的集成web用户界面,以方便管理任务,否则将需要调用多个工具。我们在实验室环境中部署了这个工具,并通过几个案例研究演示了这些分析功能。
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Building end-to-end management analytics for enterprise data centers
The complexity of modern data centers has evolved significantly in recent years. One typically is comprised of a large number and types of middleware and applications that are hosted in a heterogeneous pool of both physical and virtual servers, connected by a complex web of virtual and physical networks. Therefore, to manage everything in a data center, system administrators usually need a plethora of management tools since one tool often manages only one type of devices. The boundaries between the different management tools can limit productivity of system administrators on their daily tasks as each tool only offers a partial view of the entire managed environment. As a result, advanced analytics such as impact analysis and problem determination are generally not achievable using the traditional management tools as they require a holistic view of the entire data center. In this paper, we describe an integrated management system for applications, servers, network and storage devices called DataGraph. Our system integrates data across heterogeneous point products and agents for management and monitoring to enable the above mentioned management analytics capabilities. A common data model is introduced to federate data collected by the different tools in multiple database repositories so no modifications are needed to existing management tools. A common integrated web user interface is implemented to facilitate management tasks that would otherwise require invoking multiple tools. We deployed this tool in a lab environment and demonstrated these analytics capabilities through several case studies.
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