一种基于运行时模型的云监控方法

Jin Shao, Hao Wei, Qianxiang Wang, Hong Mei
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引用次数: 132

摘要

监控在提高云计算服务质量方面发挥着重要作用。它帮助云自适应地扩展资源利用率,为服务开发人员识别服务中的缺陷,并发现众多最终用户的使用模式。然而,由于云中组件的异构性以及大量运行时信息带来的复杂性,云中的监控面临着许多新的挑战。在本文中,我们提出了一个用于云监控的运行时模型(RMCM),该模型通过关注常见的监控关注点来表示运行中的云的直观表示。由多种监视技术收集的原始监视数据由RMCM组织,以提供运行中的云的更直观的概要文件。我们将RMCM应用于灵活的监视框架的实现中,该框架可以通过对监视设施的自适应管理来实现运行时开销和监视功能之间的平衡。我们在真实云中使用监控框架的经验证明了我们方法的可行性和有效性。
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A Runtime Model Based Monitoring Approach for Cloud
Monitoring plays a significant role in improving the quality of service in cloud computing. It helps clouds to scale resource utilization adaptively, to identify defects in services for service developers, and to discover usage patterns of numerous end users. However, due to the heterogeneity of components in clouds and the complexity arising from the wealth of runtime information, monitoring in clouds faces many new challenges. In this paper, we propose a runtime model for cloud monitoring (RMCM), which denotes an intuitive representation of a running cloud by focusing on common monitoring concerns. Raw monitoring data gathered by multiple monitoring techniques are organized by RMCM to present a more intuitive profile of a running cloud. We applied RMCM in the implementation of a flexible monitoring framework, which can achieve a balance between runtime overhead and monitoring capability via adaptive management of monitoring facilities. Our experience of utilizing the monitoring framework on a real cloud demonstrates the feasibility and effectiveness of our approach.
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