From Data Center Metrics to Data Center Analytics: How to Unlock the Full Business Value of DCIM

WHITE PAPER April 2013 From Data Center Metrics to Data Center Analytics: How to Unlock the Full Business Value of DCIM Peter Gilbert Vice President, Business Unit Strategy, CA DCIM Kaushik Ramakrishnan Associate Practice Engagement Manager, Sustainability Practice, Infosys Ronald Diersen Principal Consultant, Sustainability Practice, Infosys

Table of Contents Executive Summary 3 Section 1: Challenge 4 Plugging the Data Center Performance Gap Section 2: Opportunity 6 Making DCIM Metrics Meaningful Section 3: Benefits 10 Greater Visibility, Efficiency and Sustainability Section 4: 12 Conclusions Section 5: 13 References Section 6: 13 About the Authors 2

Executive Summary Challenge Data centers are the factories of the Internet age, providing the infrastructure for the delivery of digital business services. The performance of the data center has become intrinsically linked to an organization s overall success. To remain profitable and competitive, organizations need to ensure that every resource is consumed economically and every asset utilized optimally. With fragmented operations, tools and information, many organizations are failing to collate and analyze the metrics needed to bridge the data center performance divide. Opportunity By embracing Data Center Infrastructure Management (DCIM), organizations can bring consistency, predictability and control to operational metrics while also improving service assurance. DCIM provides the integrated framework and automated formulas needed to convert metrics into meaningful analytics. From centralizing data collection, managing physical capacity and assets, and integrating with critical IT management applications, DCIM unifies the processes, tools and raw data needed to provide an accurate view of data center performance across both IT and facilities. Benefits DCIM analytics is a key stepping stone to greater DCIM maturity and a more efficient, effective and reliable data center. It enables organizations to minimize energy consumption and total cost of ownership while maximizing agility and availability. It also offers the critical link between data center performance and business impact, so organizations can transform the data center from a cost center to a source of added value. 3

Section 1: Challenge Plugging the Data Center Performance Gap It can impair the customer experience. It can inhibit competitive advantage. It can impede operational efficiency. A performance gap in the data center isn t just a problem for IT; it s a problem for the entire business. In today s IT-dependent world, the data center plays an integral role in whether your business achieves success or failure, profit or deficit, market gains or losses. Given such high stakes, organizations need to be able to bridge every performance gap, whether it involves resources, costs, availability or capacity. However, with data center complexity and density on the increase, the root causes of inefficiency and performance issues are getting harder to find and even harder to fix. The average kilowatt consumption per data center rack rose from 2.1 in 2011 to 2.7 in 2012; 1 capacity is up too, with organizations predicting a 7-percent increase over the next two years. 2 Without the right tools and processes, a hotter, denser data center will become increasingly difficult to manage. For many enterprises, these complexities are already taking their toll on data center operations. According to IDC, 84 percent of organizations experienced issues with data center power, space and cooling capacity, assets or uptime in the past year. 2 As well as maximizing data center performance, organizations must maximize the utilization of their existing assets. Given ongoing budget constraints, CIOs need to ensure that their operations stay in tune with the achieve more for less mantra that continues to chime in every data center. Fighting the fragmentation foe To achieve their optimization goals, organizations must first overcome one of today s greatest data center foes: fragmentation. It delays, it complicates and, ultimately, it costs both in time and money. Fragmentation exists in three key areas: Operations: For most large organizations, the data center is managed by two distinct groups IT and facilities. With budgetary and operational responsibility for systems, physical security, power and capacity divided between these groups, the efficiency and performance of the data center has become veiled in a shroud of operational silos. As a result, improvement and innovation opportunities are going untapped, with nearly 60 percent of organizations believing their data centers are inefficient or only moderately efficient. 2 Tools: Divided operations means divided tools and processes, which delays both incident resolution and the provisioning of new services. According to IDC, only 37 percent of organizations have a single set of tools in use across both IT and facilities. 2 This disjointed approach to monitoring and management is exacerbated by the diversity of today s data centers. With different IT systems featuring their own management consoles and virtualization enabling the rapid provisioning of new resources, both assets and tools are constantly multiplying. 4

Information: Until the operational divide in the data center is bridged, organizations will continue to be plagued with disparate information whether it involves service delivery data, asset inventories or power consumption metrics. Fragmentation, however, is just the beginning of the information management challenge: A lack of centralized control and standard formats also leads to inaccuracy and inconsistency. The deficit in accurate information often proves the most detrimental for the data center. According to IDC: The primary factor limiting the ability of most data center teams to effectively plan, optimize and operate their data centers is the lack of reliable authoritative, relevant and timely information that they can use to manage the data center and all the assets in it. 2 Counting the cost For some enterprises, the impact of fragmented operations and flawed management information has already extended well beyond the doors of the data center to the heart of the business. For example, a quarter of organizations had to roll back or delay an application deployment due to issues with power, space and cooling capacity, assets or uptime in the data center. 2 Such disruption is just the beginning of the growing and powerful bond between operational constraints and business outcomes (see Figure A). This bond is not just relevant to organizations running their own facilities; outsourced operations are equally exposed to the data center performance gap. For enterprises that have adopted an outsourced or cloud-based model, understanding and addressing such constraints can be even harder, unless they have full visibility of their provider s performance across the entire data center operation and that means both IT and facilities. Figure A. Business impact index Data Center Constraint Capacity management Slow provisioning of additional resources Poor visibility of future demand Service delivery Inconsistent systems availability Protracted problem resolution Resource management High cooling requirements and water consumption Poor energy efficiency Asset management Incomplete inventory Inaccurate record of utilization Business Impact Delays new revenue generation Prevents profitable growth Dilutes customer satisfaction and loyalty Impedes staff productivity Reduces eco-competitiveness by increasing capital expenditure (CAPEX) and operational expenditure (OPEX) requirements Drives up costs and carbon emissions Impedes transformation and innovation Leads to unnecessary expenditure on new assets 5

The need to provide such granular visibility as part of core operations has compelled some managed service providers (MSPs) to take the lead in adopting DCIM strategies and solutions. For example, Logicalis has demonstrated such innovation by offering its customers energy efficiency, sustainability data, cost transparency and power reliability, which has enabled it to differentiate its managed services offerings. The UK service provider chose to deploy a DCIM solution because of its ability to provide a bridge between facilities infrastructure assets and IT devices. 3 Unifying IT and facilities is a key facet of DCIM, one that is making it increasingly popular with MSPs and end user organizations alike. Gartner estimates a 39-percent compound annual growth rate (CAGR) for the DCIM market from 2012 through 2016. 4 Collecting and interpreting data DCIM offers organizations the single pane of glass they need to continuously improve data center performance. It enables organizations to collect, analyze and manage information about a data center s assets, resource utilization and operational status so they can control and optimize the environment more effectively. Unlocking these benefits, however, can be a considerable challenge. The end-to-end nature of DCIM means that as well as being highly effective, it s also highly complex. As Forrester Research warns: The data volumes involved in DCIM solutions are high, and even more importantly, the interpretation of the results of this data collection so that it can be presented in an easily consumable format is one of the most critical aspects of the DCIM solution. Data must be aggregated, filtered and then correlated across multiple sources, and over time present actionable knowledge to the operators. 5 For many organizations, the challenge starts much earlier in the process than data aggregation and interpretation. With a lack of standardized metrics and collaboration between IT and facilities, the first DCIM hurdle is determining what data to capture and how to do it. Section 2: Opportunity Making DCIM Metrics Meaningful Today s data center is under constant and extreme surveillance, from the floor space used and the assets deployed to the resources consumed and the emissions generated. This has given rise to a new data center phenomenon: metric sprawl. With power consumption recognized as a key contributor to not only economical and environmental performance but also overall availability, energy efficiency has become the focal point for this sprawl. From Power Usage Effectiveness (PUE) and power overhead multipliers to energy productivity and reuse, every kilowatt is being put under the metric microscope. Behind each metric is a wealth of raw data that needs to be captured on a regular basis, often in real time. Initially IT and facilities departments took a manual approach to gathering such data, but as the metric landscape has expanded, an automated approach has become essential. 6

DCIM solutions not only automate, they also integrate at an operational, tool and information level (see Figure B). Deploying a DCIM solution is not only fundamental to simplifying the calculation of operational metrics; it also enables data center managers to perform meaningful analysis, thus improving both strategic and tactical decisions. Figure B. Simplifying the journey from raw data to real-time analytic. Traditional Energy Management in a Data Center 100 s or 1,000 s of data points to collect manually IT OPERATIONS AND FACILITIES STAFF CA Technologies DCIM approach Centrally monitor equipment in one or many data centers IT OPERATIONS AND FACILITIES STAFF CA ecosoftware BMS Chiller UPS BMS BMS Chiller UPS Chiller UPS Utility Meter Generator CRAC Load: Servers Storage Mainframe Utility Meter Generator CRAC DC Power System BMS Load: Servers Storage Mainframe Utility Meter Generator CRAC DC Power System BMS Load: Servers Storage Mainframe DC Power System Chiller Utility Meter Generator UPS CRAC Load: Servers Storage Mainframe Chiller Utility Meter Generator UPS CRAC Load: Servers Storage Mainframe DC Power System DC Power System Data flows Energy flows People Although metrics are invaluable for tracking and benchmarking performance, they don t enable organizations to actually improve their performance. To achieve this, organizations must go beyond DCIM metrics to DCIM analytics. Unlocking greater business value DCIM analytics enable organizations to trend real-time and historical data to identify how different workloads or business processes impact data center operations and performance at different times. By performing DCIM analytics in real time, data center managers can also pinpoint when normal thresholds are breached whether it involves power intensity, humidity levels or server availability. This enables problem resolution to start earlier, resulting in less downtime and performance degradation for the business. 7

Taking an analytical approach is essential for progressing along the DCIM maturity curve. The Green Grid defines DCIM maturity on a scale of zero to five, with level two being considered best practice and level five as visionary. 9 Analytics is fundamental for reaching levels four and five where the greatest business value can be achieved yet most organizations are still struggling to move beyond level one, due to the lack of a consistent and centralized approach. Building a personalized metric map for actionable analytics There is no one size fits all formula for DCIM analytics. For analytics to result in actionable information, IT and facilities departments must first identify what metrics best suit their business and data center environments. And they must do it together, as a unified team. How to achieve valuable business insight from DCIM analytics Every analytic is founded on one or more metrics. Select the wrong ones and the analysis process will become worthless. Select the right ones and the business will have an unrivalled insight into how to optimize data center operations to deliver greater value. By considering these factors as part of the journey from DCIM metrics to DCIM analytics, organizations will be able to maximize business outcomes. Data center s age: Older facilities may not be able to capture the raw data that feeds today s more sophisticated metrics and analytics without additional investment. Data center s tier: The classification will help dictate the most relevant data to collate and analysis to undertake. For example, a Tier II facility will have less of a focus on high availability than a Tier IV data center. Business model: The usage of a data center will be a key factor in determining the analytics portfolio. For example, the operator of a facility that provides services to external third parties will want visibility of overall data center efficiency and resilience, particularly the shared spaces in the data center, as well as information that enables accurate customer billing based on agreed-upon service levels and resource consumption. Although the operators of an internal facility will want visibility of overall data center efficiency, they will also need analytics on individual assets, groups of assets required to deliver selected services, and associated costs. Regulatory compliance: Some sectors and their data center operations are subject to greater regulation than others for example, mandatory carbon reporting, which should be reflected in the DCIM metric and analytical stack. Strategic goals: To stay eco-competitive, organizations need to demonstrate the attainment of sustainability goals within the data center for example, a reduction of carbon emissions. This will require access to before and after analytics. Reporting requirements: The data center provides a service, whether it is to external customers or internal business departments, and these customers increasingly want real-time and historical performance reports and analytics that support ongoing decision-making. With most organizations still at the early stages of the DCIM maturity curve, it s advisable to limit the initial selection to just a handful of metrics particularly for energy efficiency, where data collation and analysis is at its most complex. 8

PUE has become the de facto entry-level metric for energy efficiency; nearly 90 percent of organizations managing 2,000 servers or more measure their PUE. 6 Although a much smaller percentage report this figure in a publicly accountable manner, an increasing number of customers are requesting PUE as a performance metric in managed and hosting service contracts. Despite its ubiquitous status, PUE is no longer the Holy Grail of energy efficiency in the data center, and has been the subject of strident criticism, notably from Greenpeace: While PUE can be a useful diagnostic tool for a data center operator, it is a poor metric for determining how green a data center is, as it does not account for how companies are managing computer resources inside the data center, and in some circumstances, it penalizes better performance. 7 The limitations of PUE have helped fuel the emergence of new energy-related metrics. For example, the Green Grid, the purveyor of PUE, has also developed Carbon Usage Effectiveness (CUE), which addresses a data center s carbon emissions an area that many organizations have so far overlooked. According to the Uptime Institute, less than a quarter of organizations collect carbon reporting data for their data centers. 6 Expanding the DCIM remit Energy efficiency and carbon reporting are just the tip of the DCIM metric and analytics iceberg, however. With a growing link between environmental performance and brand status, organizations also need to embrace other sustainability measures as their DCIM maturity increases. For example, energy reuse and water consumption are key factors to consider. Yet only a third of organizations currently collect water usage information for their data center operations. 6 DCIM also enables organizations to collate and integrate other key performance indicators that are equally fundamental to the overall performance and efficiency of the data center, such as mean time to failure and CPU utilization. As such, DCIM is a natural extension to broader IT service assurance initiatives and can play a key role in integrating performance management and optimization across multiple data center environments, whether they are on-premise or off-premise, in or out of the cloud. Given the breadth of DCIM, not all organizations will enter on a sustainability ticket. According to Forrester Research, Inc. infrastructure and operations (I&O) professionals are investing in DCIM to: Improve availability Manage capacity constraints Lower operating costs Improve capital resource efficiency (CAPEX management) Provide detailed financial modeling Manage their carbon footprint 5 Taking an automated approach Regardless of the entry point, generating the raw data needed for DCIM analytics can be a highly automated process, with best-of-breed DCIM solutions including built-in algorithms and visualization across the IT and facilities stack. 9

This automation can not only help accelerate the DCIM value chain from raw data to real-time analytic but also free up resources. For example, Logicalis was able to reduce the time spent producing quarterly reports and managing PUE by 93 percent after deploying a DCIM solution. 3 Although automation can also be extended to the analysis process, even the outputs from the most sophisticated solution will still require additional intelligence and interpretation from a skilled DCIM practitioner to deliver maximum business value. It s therefore fundamental that organizations have the right skills to support this final and critical stage of the DCIM analytics process, whether it means recruiting new staff or partnering with an experienced external provider. Section 3: Benefits Greater Visibility, Efficiency and Sustainability Making the transition from metrics to analytics is essential for achieving a greater level of DCIM maturity. The greater the maturity level an organization attains, the greater the efficiency and sustainability gains it can expect to achieve. For example, by increasing its DCIM maturity, Logicalis has been able to make energy savings of 5 percent in the first 12 months. 3 The holistic approach of DCIM means it can not only help unlock such savings, but also enable a more unified management approach on a daily basis by eradicating fragmentation at an operational, tool and information level. For example, Fujitsu uses a range of DCIM metrics across its IT, facilities and procurement divisions to provide local control and central visibility. IT equipment utilization (ITEU) and IT equipment energy efficiency (ITEE) are used by the IT systems manager and the IT infrastructure manager, while the facilities team uses PUE and green energy coefficient (GEC). These individual metrics are then rolled up into one over-arching metric: data center performance per energy (DPPE), which is used by Fujitsu s CIO to continuously assess the efficiency of the data center, as well as the results of energy-saving efforts. Thanks to this approach, Fujitsu s managers are able to set targets and implement measures to reach them. The company has already improved its PUE by 60 percent and its ITEE by 14 percent. 8 As organizations broaden the scope of their DCIM metrics and analytics to encompass all operational pillars a prerequisite for the higher maturity levels they should be able to achieve similar gains across all data center assets and resources. Floor space can be used more intelligently, power consumed more economically, virtual machines allocated more effectively. All of this leads to measurable savings (see Figure C). 10

Figure C. Actionable analytics drive better business outcomes. IT Operation DCIM Metrics DCIM Analytics Business Outcome Capacity management IT Shared Facilities Rack space Floor area Power consumption Network bandwidth Storage space Cooling requirements Future capacity requirements; predicted spend on energy; correlation between capacity and future orders for additional capacity More accurate forecasting for CAPEX and OPEX; faster response to new business opportunities Service delivery Availability Recoverability Mean time to failure (MTTF) Mean time to failure (MTTF) Power availability Power chain resilience and redundancy Business downtime; performance against agreed SLAs; root cause analysis; planned resilience to outages Greater productivity; higher user/customer satisfaction Planned downtime Catastrophic failures Resource management IT equipment energy efficiency (ITEE) Data center infrastructure efficiency (DCIE) Carbon usage effectiveness Water usage effectiveness Temperature Coefficient of performance (COP) Energy, carbon and water usage per unit of business outputs (e.g., service delivery costs per dollar of revenue) Lower resource consumption and costs; greater eco-competiveness IT equipment utilization (ITEU) Power usage effectiveness Air flow Energy Star rating Asset management Deployed hardware utilization ratio (DH-UR) Physical location; volume of assets Effective usage of assets Informed procurement decisions; avoid duplication and unnecessary orders; track assets from delivery to placement 11

Seize the competitive advantage with DCIM analytics The aim of DCIM analytics is not limited to making the data center more efficient. It s also designed to deliver better value to the business value that isn t measured just in cost savings. Availability is also a critical currency in today s dynamic data centers. As Forrester confirms, The ultimate measure of success for an I&O group is the availability of services that meet increasingly stringent service-level agreements (SLAs). As one vendor said, quoting a customer, If our data center becomes more efficient, then we get a pat on the back. If the data center goes down, we get fired. As it turns out, Forrester finds that power failure is the most common cause of significant disaster declarations or major business disruptions not extreme scenarios like terrorism or severe weather conditions. 5 By embracing DCIM analytics, organizations can not only resolve such problems, but also prevent them from happening in the first place. DCIM solutions offer organizations exceptional visualization capabilities, which allow them to map how performance problems in the data center impact service delivery and the overall business. IT and facilities departments can also answer critical what if questions before they decide to embark on transforming or constructing a data center. This foresight will help maximize return on investment and minimize environmental impact. DCIM analytics not only helps to close the data center performance gap, but also helps open up new gateways to success. It provides organizations with the efficiency and visibility needed to unlock new revenue streams, to provision new services faster and to increase eco-competitiveness. DCIM analytics enables organizations to seize today s opportunities and tomorrow s advantage. Section 4: Conclusions The data center divide is getting bigger, and it is putting more than just operational performance levels at risk. DCIM enables organizations to close the gap by providing an integrated and automated management approach for both IT and facilities. To realize the full business value of DCIM, organizations need to do more than just capture metrics; they need to analyze and act. There is no one-size-fits-all approach to DCIM analytics, but the outcome is always the same: a positive impact on the triple bottom line operational, financial and environmental. 12

Section 5: References 1. Uptime Institute Annual Report: Data Center Density, Preliminary Results, 2012 2. IDC White Paper, sponsored by CA Technologies, The Data Center s Role in Delivering Business Innovation: Using DCIM to Enable a Common Management Approach, Doc #237737, November 2012 3. CA Technologies ROI case study with Logicalis, August 2012 4. Market Trends: Total Addressable DCIM Market Will Reach $1.7 Billion by 2016, Gartner, November 2012 5. Market Overview: Data Center Infrastructure Management Solutions, Forrester Research, Inc., March 29, 2012 6. Uptime Institute 2012 Data Center Industry Survey 7. Greenpeace, How Clean Is Your Cloud, April 2012 8. Green IT Promotion Council, Enhancing the Energy Efficiency and Use of Green Energy in Data Centers, September 2012 9. Data Center Maturity Model; White Paper #36, The Green Grid, 2011 Section 6: About the Authors Peter Gilbert Peter Gilbert is vice president of strategy for the DCIM, Energy and Sustainability business at CA Technologies, focusing on Data Center Infrastructure Management, energy management and sustainability management. He is responsible for the overall business and product strategy of CA Technologies in these areas. Prior to his current role, Peter was a principal architect in the Engineering Services group at CA Technologies and spent many years providing implementation consulting and technology advice to a wide range of organizations. Ronald Diersen As principal consultant in the Sustainability Practice for Infosys Ltd, Ronald Diersen utilizes IT professional experience spanning 30-plus years to help businesses identify opportunities and solve business problems. His primary focus is on sustainability (green IT) initiatives, with emphasis on infrastructure management and process improvements. He helps organizations positively impact their triple bottom line (environment, social, financial). Over the last 16 years, Ron has been fortunate to be involved in the design, implementation and operation of state-of-the-art data centers. The experience gave him invaluable insight into dealing with risks and opportunities in IT and facility infrastructures by utilizing sustainable products and services, technology, and globally recognized best practices and frameworks. 13

Kaushik Ramakrishnan Kaushik Ramakrishnan leads client engagement and business development for Infosys sustainability services and solutions, working with several clients across Europe. He helps clients realize the role of sustainability across the organization s value chain and the transformational opportunity that sustainability presents. Over the last 11 years, Kaushik has worked with clients across multiple sectors to deliver complex IT and business transformation projects. Within the sustainability practice, he has a specific interest in driving green IT solutions and optimizing the data center environmental footprint through a combination of the right data collection tools and intelligent analytics. Connect with CA Technologies at ca.com Agility Made Possible: The CA Technologies Advantage CA Technologies (NASDAQ: CA) provides IT management solutions that help customers manage and secure complex IT environments to support agile business services. Organizations leverage CA Technologies software and SaaS solutions to accelerate innovation, transform infrastructure and secure data and identities, from the data center to the cloud. CA Technologies is committed to ensuring our customers achieve their desired outcomes and expected business value through the use of our technology. To learn more about our customer success programs, visit ca.com/customer-success. For more information about CA Technologies go to ca.com. Some information in this publication is based upon CA Technologies or customer experience with the referenced software product in a variety of development and customer environments. Past performance of the software product in such development and customer environments is not indicative of the future performance of such software product in identical, similar or different environments. CA Technologies does not warrant that the software product can operate as specifically set forth in this publication. CA Technologies will support the referenced product only in accordance with (i) the documentation and specifications provided with the referenced product, and (ii) then-current maintenance and support policy of CA Technologies for the referenced product. Copyright 2013 CA Technologies. All rights reserved. All trademarks, trade names, service marks and logos referenced herein belong to their respective companies. This document is for your informational purposes only. CA Technologies assumes no responsibility for the accuracy or completeness of the information. To the extent permitted by applicable law, CA Technologies provides this document as is without warranty of any kind, including, without limitation, any implied warranties of merchantability, fitness for a particular purpose, or non-infringement. In no event can CA Technologies be liable for any loss or damage, direct or indirect, from the use of this document, including, without limitation, lost profits, business interruption, good will or lost data, even if CA Technologies is expressly advised in advance of the possibility of such damages. CA Technologies does not provide legal advice. Neither this document nor any CA Technologies software product referenced herein shall serve as a substitute for your compliance with any laws (including but not limited to any act, statute, regulation, rule, directive, policy, standard, guideline, measure, requirement, administrative order, executive order, etc. (collectively, laws ) referenced in this document. You should consult with competent legal counsel regarding any Laws referenced herein. acs3780_0413