非侵入式、带外和开箱即用的云系统监控

Sahil Suneja, C. Isci, Vasanth Bala, E. D. Lara, Todd W. Mummert
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引用次数: 35

摘要

数据中心中虚拟机(VM)的急剧增加以及VM供应的高度动态和瞬态特性已经彻底改变了数据中心的操作。然而,这些环境的管理仍然是使用传统代理的重新设计版本来执行的,这些代理最初是为管理物理系统而开发的,或者最近通过更新的虚拟化感知替代方案来执行,这些替代方案需要客户机的合作和可访问性。我们表明,这些现有的方法不适合监控和管理云中的(虚拟)系统,因为它们依赖于客户合作和运行状况,并且它们在云中不断增长的生命周期管理开销。在这项工作中,我们首先提出了近场监测(NFM),这是我们基于云操作原则设计的非侵入式带外云监测和分析方法,旨在解决现有技术的局限性。NFM通过将监视推到目标系统范围之外,将系统执行从监视和分析功能中分离出来。通过利用和扩展VM自省技术,我们的框架提供了简单、标准的接口来监视云中正在运行的系统,这些系统不需要客户机协作或修改,并且对客户机执行的影响最小。通过将监视和分析与目标系统上下文分离,NFM提供了“永远在线”的监视,即使在目标系统没有响应时也是如此。NFM还可以“开箱即用”地适用于任何云实例,因为它消除了在被监视系统中安装和维护代理或挂钩的需要。我们用基于两个虚拟化平台的两个真实系统原型描述了我们的框架的端到端实现。我们讨论了由我们解耦的执行、监控和分析架构带来的新的云分析机会。我们展示了构建在我们框架之上的四个应用程序,并展示了它们用于跨时间和跨系统分析的用途。
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Non-intrusive, out-of-band and out-of-the-box systems monitoring in the cloud
The dramatic proliferation of virtual machines (VMs) in datacenters and the highly-dynamic and transient nature of VM provisioning has revolutionized datacenter operations. However, the management of these environments is still carried out using re-purposed versions of traditional agents, originally developed for managing physical systems, or most recently via newer virtualization-aware alternatives that require guest cooperation and accessibility. We show that these existing approaches are a poor match for monitoring and managing (virtual) systems in the cloud due to their dependence on guest cooperation and operational health, and their growing lifecycle management overheads in the cloud. In this work, we first present Near Field Monitoring (NFM), our non-intrusive, out-of-band cloud monitoring and analytics approach that is designed based on cloud operation principles and to address the limitations of existing techniques. NFM decouples system execution from monitoring and analytics functions by pushing monitoring out of the targets systems' scope. By leveraging and extending VM introspection techniques, our framework provides simple, standard interfaces to monitor running systems in the cloud that require no guest cooperation or modification, and have minimal effect on guest execution. By decoupling monitoring and analytics from target system context, NFM provides ``always-on'' monitoring, even when the target system is unresponsive. NFM also works ``out-of-the-box'' for any cloud instance as it eliminates any need for installing and maintaining agents or hooks in the monitored systems. We describe the end-to-end implementation of our framework with two real-system prototypes based on two virtualization platforms. We discuss the new cloud analytics opportunities enabled by our decoupled execution, monitoring and analytics architecture. We present four applications that are built on top of our framework and show their use for across-time and across-system analytics.
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