信息技术. 数据中心. 数据中心关键绩效指标全面调查指南

[中文适用范围]： 本文档描述了数据中心关键性能指标（KPIs）整体方法的背景、动机和一般概念，以调查KPIs的状态。它讨论了整体调查方法在聚合不同上下文中的KPI、在单个上下文中聚合两个或多个KPIs、在多个上下文中聚合两个或多个KPIs以及将多个KPIs聚合为单个指标方面的有用性。本文档介绍了一种基于传统蜘蛛网图的数据中心KPIs状态观察方法和一种包括KPIs操作状态上限和下限的控制图方法。本文档介绍了两种方法的SWOT分析结果。本文档中描述的方法旨在用于数据中心的自我监控，而不是数据中心之间的比较。具体而言，本文档： a) 描述了数据中心KPIs整体调查方法的背景、动机和一般概念； b) 分析了整体调查方法在聚合KPIs方面的有用性； c) 描述了一种基于蜘蛛网图的KPIs状态观察方法和一种扩展蜘蛛网图以观察KPIs操作状态的控制图； d) 描述了表示不同KPIs以跟踪数据中心整体资源有效性的替代和/或附加方法； e) 介绍了本文档中描述的整体调查方法的SWOT分析结果。 [外文原描述]： ISO/IEC TR 20913:2016 describes backgrounds, motivation, and general concept of holistic methodology for data centre key performance indicators (KPIs) to investigate the status of KPIs. It discusses the usefulness of holistic investigation methodology in terms of aggregating a KPI across different contexts, aggregation of two or more KPIs within a single context, aggregation of two or more KPIs across multiple contexts, and aggregation of the multiple KPIs into a single indicator. This document presents a conventional spider web chart-based data centre KPIs status observation method and a control chart method including upper bound and lower bound of the operational status of KPIs. This document presents SWOT analysis results for both methodologies. The methods described in this document are aimed at the self-monitoring of a data centre, not comparison among data centres. Specifically, ISO/IEC TR 20913:2016 a) describes backgrounds, motivation, and general concept of holistic investigation methodology for data centre KPIs, b) analyses the usefulness of holistic investigation methodology for aggregating KPIs, c) describes a spider web chart-based KPIs status observation method and a control chart extending spider web chart to observe the operational status of KPIs, d) describes alternative and/or additional methods of representing dissimilar KPIs to track holistic resource effectiveness of the data centre, and e) presents SWOT analysis results for holistic investigation methods described in this document.