Parallel Coordinates Visualization in the ELK Stack

T. Galkin, M. Grigorieva
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引用次数: 1

Abstract

Modern large-scale distributed computing systems, processing large volumes of data, require mature monitoring systems able to control and track in re-sources, networks, computing tasks, queues and other components. In recent years, the ELK stack has become very popular for the monitoring of computing environment, largely due to the efficiency and flexibility of the Elastic Search storage and wide variety of Kibana visualization tools. The analysis of computing infrastructure metadata often requires the visual exploration of multiple parameters simultaneously on one graphical image. Stacked bar charts, heat maps, radar charts are widely used for the multivariate visual data analysis, but these methods have limitations on the number of parameters. In this research the authors propose to enhance the capacity of Kibana, adding Parallel Coordinates diagram - one of the most powerful method for visual interactive analysis of high-dimensional data. It allows to compare many variables together and observe correlations between them. This work describes the development process of Parallel Coordinates as a Kibana plugin, and demonstrates an example of visual data analysis based on the Nginx logs metadata.
ELK堆栈中的平行坐标可视化
现代大规模分布式计算系统需要处理大量数据,需要成熟的监控系统,能够对资源、网络、计算任务、队列等组件进行控制和跟踪。近年来,ELK堆栈已成为非常流行的计算环境的监控,很大程度上是由于弹性搜索存储和各种Kibana可视化工具的效率和灵活性。计算基础设施元数据的分析通常需要在一个图形图像上同时对多个参数进行视觉探索。叠层柱状图、热图、雷达图被广泛用于多变量可视化数据分析,但这些方法在参数数量上存在局限性。在这项研究中,作者建议通过添加并行坐标图(Parallel Coordinates diagram)来增强Kibana的能力,并行坐标图是高维数据可视化交互分析最强大的方法之一。它允许将许多变量一起比较并观察它们之间的相关性。本工作描述了Parallel Coordinates作为Kibana插件的开发过程,并演示了一个基于Nginx日志元数据的可视化数据分析示例。
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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