Application-aware latency monitoring for cloud tenants via CloudWatch+

Dapeng Liu, Dan Pei, Youjian Zhao
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Abstract

A tenant hosted by a cloud platform typically runs a lot of applications, each of which not only has its own service capacity but also differs in revenue or business importance. Thus we argue that it is crucial for a cloud platform to provide fine-grained and application-aware performance monitoring for each tenant, rather than current monitors that can only handle overall metrics. In this paper, we propose CloudWatch+, a tool that focuses on detecting the latency of web-based applications. A cloud platform equipping with CloudWatch+ can automatically learn and distinguish web-based applications it is hosting, and detect latency anomalies for each application based on its own status. Our evaluation using the real data from a cloud platform with over 200 tenants demonstrates that the detection results of CloudWatch+ are more detailed than those of Amazon CloudWatch, which misses most alarms while some tenants' specific applications experience bad performance. Meanwhile, CloudWatch+ is also realtime and light-weight.
通过CloudWatch+监视云租户的应用程序感知延迟
由云平台托管的租户通常运行许多应用程序,每个应用程序不仅有自己的服务能力,而且在收入或业务重要性方面也有所不同。因此,我们认为,对于云平台来说,为每个租户提供细粒度和应用程序感知的性能监视,而不是只能处理总体指标的当前监视器,这是至关重要的。在本文中,我们提出了CloudWatch+,一个专注于检测基于web的应用程序延迟的工具。配备CloudWatch+的云平台可以自动学习和区分其托管的基于web的应用程序,并根据每个应用程序自身的状态检测延迟异常。我们使用超过200个租户的云平台的真实数据进行评估,结果表明CloudWatch+的检测结果比Amazon CloudWatch更详细,Amazon CloudWatch漏过大部分告警,而部分租户的特定应用表现不佳。同时,CloudWatch+也是实时和轻量级的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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