1、Information technology Data centres Guidelines on holistic investigation methodology for data centre key performance indicators Technologies de linformation Centres de donnes Lignes directrices relatives la mthodologie de recherche holistique pour les indicateurs de performance cl du centre de donne
2、s TECHNICAL REPORT ISO/IEC TR 20913 First edition 2016-11-15 Reference number ISO/IEC TR 20913:2016(E) ISO/IEC 2016 ii ISO/IEC 2016 All rights reserved COPYRIGHT PROTECTED DOCUMENT ISO/IEC 2016, Published in Switzerland All rights reserved. Unless otherwise specified, no part of this publication may
3、 be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below or ISOs member body in the country of the
4、requester. ISO copyright office Ch. de Blandonnet 8 CP 401 CH-1214 Vernier, Geneva, Switzerland Tel. +41 22 749 01 11 Fax +41 22 749 09 47 copyrightiso.org www.iso.org ISO/IEC TR 20913:2016(E) ISO/IEC TR 20913:2016(E)Foreword iv Introduction v 1 Scope . 1 2 Normative references 1 3 T erms, definitio
5、ns and abbr e viat ed t erms 1 3.1 Terms and definitions . 1 3.2 Abbreviated terms . 2 4 Background and motivation . 2 4.1 General concept of holistic investigation method 2 4.2 Usefulness of spider web chart methods for visualizing data centre KPIs . 3 4.3 Usefulness of aggregating data centre KPIs
6、 . 4 5 Spider w eb chart-based KPIs status observ ation method 4 5.1 Principles for constructing a spider web chart using KPIs . 5 5.1.1 Selection of axis on a spider web chart 5 5.1.2 Presentation of KPIs on axes . 5 5.2 Example of a holistic approach . 5 5.3 Example of holistic approach of data ce
7、ntre by use of a spider web chart . 6 6 C ontr ol chart method e xt ending a basic spider w eb chart t o observ e the operational status 11 6.1 Motivation for control chart method for energy efficiency monitoring .11 6.2 Control chart approach for energy efficiency monitoring 11 7 Considerations for
8、 applying holistic investigation methods .14 8 SWOT analysis results for holistic investigation methods .14 Bibliogr aph y .16 ISO/IEC 2016 All rights reserved iii Contents Page ISO/IEC TR 20913:2016(E) Foreword ISO (the International Organization for Standardization) and IEC (the International Elec
9、trotechnical Commission) form the specialized system for worldwide standardization. National bodies that are members of ISO or IEC participate in the development of International Standards through technical committees established by the respective organization to deal with particular fields of techn
10、ical activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the work. In the field of information technology, ISO and IEC have established a joint techni
11、cal committee, ISO/IEC JTC 1. The procedures used to develop this document and those intended for its further maintenance are described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the different types of document should be noted. This document was draft
12、ed in accordance with the editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives). Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO and IEC shall not be held responsible for identifying any or all such pa
13、tent rights. Details of any patent rights identified during the development of the document will be in the Introduction and/or on the ISO list of patent declarations received (see www.iso.org/patents). Any trade name used in this document is information given for the convenience of users and does no
14、t constitute an endorsement. For an explanation on the meaning of ISO specific terms and expressions related to conformity assessment, as well as information about ISOs adherence to the WTO principles in the Technical Barriers to Trade (TBT) see the following URL: Foreword - Supplementary informatio
15、n. The committee responsible for this document is ISO/IEC JTC 1, Information technology, SC 39, Sustainability for and by Information Technology.iv ISO/IEC 2016 All rights reserved ISO/IEC TR 20913:2016(E) Introduction The ISO/IEC 30134 series defines key performance indicators (KPIs) for data centr
16、e resource effectiveness. There are many aspects to be considered in order to improve data centre resource effectiveness. As for resources, it may include not only energy, but also water and other natural resources. As for data centre components, they include air conditioning, power supply, servers,
17、 storages, and network equipment. However, it is difficult to include all aspects into one KPI, so multiple KPIs are under development, which measure each aspects of resource effectiveness improvement. Resource effectiveness improvement in each aspect will be performed by measuring each KPI. On the
18、other hand, there is a need to observe the state and trend of data centre as a whole, or holistically, by monitoring multiple KPIs in a single view. Analysis of the KPIs from the overall perspective is also referred to as a holistic investigation method. This document describes a spider web chart-ba
19、sed method and control chart method extending the functionality of the conventional spider web chart for viewing and analysing KPIs for data centre resource effectiveness. It also investigates considerations for applying holistic investigation methods to resource effectiveness evaluation of multiple
20、 data centre KPIs. The usefulness and applicability of holistic methods are discussed using a SWOT analysis. The methods described in this document are intended for analysis and continuous improvement of a specific data centre and not for comparing different data centres. ISO/IEC 2016 All rights res
21、erved v Information technology Data centres Guidelines on holistic investigation methodology for data centre key performance indicators 1 Scope This document describes backgrounds, motivation, and general concept of holistic methodology for data centre key performance indicators (KPIs) to investigat
22、e 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 int
23、o 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 m
24、ethods described in this document are aimed at the self-monitoring of a data centre, not comparison among data centres. Specifically, this document a) describes backgrounds, motivation, and general concept of holistic investigation methodology for data centre KPIs, b) analyses the usefulness of holi
25、stic 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 tr
26、ack holistic resource effectiveness of the data centre, and e) presents SWOT analysis results for holistic investigation methods described in this document. 2 Normative references There are no normative references in this document. 3 T erms, d efinitions and abbr e viat ed t erms 3.1 T erms and defi
27、niti ons For the purposes of this document, the following terms and definitions apply. ISO and IEC maintain terminological databases for use in standardization at the following addresses: IEC Electropedia: available at http:/ /www.electropedia.org/ ISO Online browsing platform: available at http:/ /
28、www.iso.org/obp 3.1.1 holistic investigation method data centre resource effectiveness investigation method considering multiple key performance indicators TECHNICAL REPORT ISO/IEC TR 20913:2016(E) ISO/IEC 2016 All rights reserved 1 ISO/IEC TR 20913:2016(E) 3.1.2 s p i d e r w e b c h a r t chart th
29、at consists of multiple performance indicators which are set in a circle like a spider web 3.2 A bbr e viat ed t erms IT Information Technology ITEEsv IT Equipment Energy Efficiency for Servers ITEUsv IT Equipment Utilization for Servers KPI Key Performance Indicator PUE Power Usage Effectiveness RE
30、F Renewable Energy Factor SWOT Strength Weakness Opportunity Threat 4 Background and motivation 4.1 General concept of holistic investigation method Improving the resource effectiveness and carbon footprint of a data centre requires the monitoring and analysis of multiple KPIs. ISO/IEC JTC 1/SC 39 h
31、as determined that it is impractical to aggregate multiple KPIs to determine the overall energy effectiveness of a data centre. There is a need to observe the state and trend of multiple KPIs in a single view. With any performance indicator, it is necessary to understand the expected upper and lower
32、 limits and general behaviour of the performance indicator. There are typically two approaches that are applicable to holistic investigation of data centre KPIs: Engineering/modeling method: This method has been used to establish baseline performance. This methodology requires the development of an
33、optimized economic and engineering model based on creating an idealized benchmark specific to each utility incorporating the topology, demand patterns, and population density of the service territory. Typical limitations of this approach are as follows: the engineering models that support it can be
34、very complicated, and the structure of the underlying components relationships can be obscured through a set of assumed coefficients used in the optimization process. Performance benchmarking method: This method includes a set of specific performance measurement indicators, such as volume billed per
35、 worker, consumed energy per product, quality of service (continuity, water quality, complaints), coverage, and key financial data. Usually, these indicators are presented in ratio form to control the scale of operations. These partial measures are generally available and provide the simplest way to
36、 perform comparisons: trends direct attention to potential problem areas. Among the methods mentioned above, the performance benchmarking method is useful for evaluating the resource efficiency of data centres because ISO/IEC JTC 1/SC 39 is offering a selection of energy effectiveness KPIs. The perf
37、ormance benchmarking method may be further categorized into two types: performance indicator-based methods and chart-based methods. Performance indicator-based methods: In this category, the performance of the target is evaluated by developing performance indicators for the target. For example, Hz f
38、or CPU and bytes for storage are typical performance indicators. This category allows accurate performance evaluation and comparison among targets, if the performance indicators are defined. Typical limitation of this approach is that it is difficult to compare the evaluation results if performance
39、indicators belong to different dimensions with different units.2 ISO/IEC 2016 All rights reserved ISO/IEC TR 20913:2016(E) Chart-based methods: This category depicts the targets performance by using chart methods, such as pie, bar, line, and spider web, etc. This category is useful for evaluating pe
40、rformance by displaying multiple performance indicators, making analysis easier. Since the chart-based approach supports multiple performance indicators simultaneously, it is appropriate for a holistic method. The spider web chart in particular is well suited for the display and analysis of multiple
41、 KPIs. A spider web chart is useful for displaying multiple KPIs in a single chart. It is also useful for displaying multiple measurement values of several KPIs in a single chart, for example, temporal measurement values of several KPIs. Thus, this document focuses on the spider web chart- based hol
42、istic KPI investigation methods. It is noted that the chart-based approach, especially spider web chart, has typical issues for applying a KPI investigation, such as scaling and normalization of KPI values, KPIs with different dimensions, ordering of KPIs in the chart, graphical interpretation of th
43、e chart, and so on. These typical issues are discussed in Clause 6 in detail. 4.2 Usefulness of spide r w eb chart methods fo r visualizing data c entr e KPIs The spider web chart consists of a bundle of performance indicators which are set in a circle. The indicators are usually normalized from zer
44、o to one, one indicating the highest possible performance, but unnormalized indicators may be utilized. Individual axes may need to be inverted in order for the different indicators to correlate. It is clear that the quality of the spider web charts depends on the validity, reliability, and comprehe
45、nsiveness of the performance indicators. It is known that the spider web chart has strength on visualizing the status of performance indicators. Regarding visualization capability, spider web charts provide a synoptic description of multiple performance measures and make trade-offs between performan
46、ce measures visible. Figure 1 shows a spider web chart consisting of three sets of performance measurements and five performance indices. In the figure, the values of each index are originally measured and unnormalized ones, and the farther from centre of the chart implies the better. Each green, bl
47、ue, and red polygon connecting measurement values of five index shows a single observation of the five indices, respectively. Using the chart, it is possible to visually compare the performance achievement among multiple performance measurements and indicators. F i g u r e 1 E x a m p l e o f a s p
48、i d e r w e b c h a r t c o n s i s t i n g t h r e e p e r f o r m a n c e m e a s u r e m e n t s ( g r e e n , b l u e , a n d r e d) ISO/IEC 2016 All rights reserved 3 ISO/IEC TR 20913:2016(E) Due to the advantages, spider web charts are popularly used to assess the performance of various evalua
49、tion objectives and to present a visual comparison of performance in various fields, especially business management. As discussed in this clause, the visualization capability of a spider web chart can help data centre administrators to monitor the specified performance KPIs of the data centre and their changes so that they can improve the efficiency of the data centre. For example, by regularly constructing the spider web chart showing the state of each KPI, the data centre administra
