Three Pillars of Modern Data Center Operations Jonathan Koomey HeatSpring Expert Jon Koomey on the Tracking, Procedures and Physical Principles of Modern Data Center Operations. This article originally appeared on DataCenterKnowledge.com on 2/2/2016 Modern enterprise data centers are some of the most technically sophisticated business activities on earth. Ironically enough, they are also often bastions of inefficiency, with equipment utilization much below ten percent and 30 percent of the servers in those facilities being comatose (using electricity but performing no useful information services). The operators of these facilities also struggle to keep pace with rapid changes in deployments of computing equipment. These problems have led to much attention being paid to improving data center management. While almost every enterprise data center has taken steps to improve its operations, virtually all are much less efficient, much more costly, and far less flexible than they could be. Those failings ultimately prevent data centers from delivering maximum business value to the companies that own them. Well-managed data centers use what I call the three pillars of modern data center operations: tracking, procedures, and physical principles. TRACKING Running a data center requires accurate real-time measurements of temperature, humidity, and airflow, as well as detailed inventories of equipment characteristics, vintage, and performance. Most Data Center Infrastructure Management (DCIM) tools deliver this information using sensors spread throughout each facility. DCIM software often requires customization to be most effective in any particular application, but it has become much more sophisticated over time. The most advanced facilities use radiofrequency identification (RFID) technology to “tag” each piece of IT equipment, physical tags that tie each server to a particular spot on the rack, and “over the network” tracking of equipment status. Whenever equipment is moved, RFID readers help update equipment status in the central tracking database, and when equipment conditions change, the devices update the central database with that new information over the network. DCIM software is like the dashboard of a car, which gives information on vehicle speed and engine temperature in real time. Many data center managers mistakenly think that once they have a DCIM tool, they have all they need to manage their facilities, but nothing could be further from the truth. Such tools are necessary (because they offer a detailed picture of the current status of the data center) but they are not sufficient. PROCEDURES Because the equipment in data centers is constantly changing, sometimes in unpredictable ways, well-managed facilities need well-defined and empirically grounded procedures for design, deployment, maintenance, and decommissioning of computing and infrastructure equipment. That means procedures based on best practices as defined by Lawrence Berkeley National Laboratory, The Green Grid, Open Compute Project, ITI, the TBM Council, and others. RFID tracking tools and over-the-network data collection (as described above) make procedures for accurate inventory tracking much easier to implement. DCIM sensor measurements can make it easier to define operational procedures for the data center. In the most interesting case, sensor data can be combined with machine learning algorithms to automate some data center operations, thus simplifying the design of human procedures. Such procedures are like simple rules that drivers use to maintain safety, like “if you see a pedestrian, slow down” or “turn into the skid.” PHYSICAL PRINCIPLES The last of the three pillars involves applying knowledge of the physical laws, engineering designs, and technological constraints affecting reliable delivery of power and cooling in the facility. Because data centers are constantly changing, and because of the complexity of air and heat flows, it is essential to apply engineering simulation tools to both data center design and operations. That means taking the information from tracking tools and incorporating it into software that simulates airflow, power distribution, and heat transfer. The best of these tools rely in part on sophisticated Computational Fluid Dynamics software, extensive libraries of the power and airflow characteristics of thousands of different kinds of IT equipment, and visual analyzers to simply and accurately predict the effects of changes in IT deployments. These computer models need to be calibrated with real measurements from a data center to ensure they accurately characterize the facility’s operations, but once calibrated, they can be used to predict the effects of changes in IT equipment configurations on airflow, temperature, efficiency, reliability, available capacity, and cost without having to actually move or install that equipment. When properly used, such engineering simulation tools are like the headlights of a car, showing clearly what’s on the road ahead. They show the costs and risks of operational plans and are just as important as careful tracking and appropriate procedures for proper management of data center operations. The three pillars, taken together, constitute the most reliable means of delivering business value from the data center. No modern data center manager should be without them. Enroll in Modernizing Enterprise Data Centers for Fun and Profit with expert Jon Koomey, earn 10 AIA LU Credits, and access templates and best practices in data center optimization and performance. This course provides a road map for managers, directors, and senior directors in Technology Business Management (TBM), drawing upon real-world experiences from industry-leading companies like eBay and Google. The course is designed to help transform enterprise IT into a cost-reducing profit center by mapping the costs and performance of IT in terms of business key performance indicators (KPIs). Want free training? Enroll in Jon Koomey’s free lecture ‘Why Predictive Modeling is Essential for Managing a Modern Computing Facility.’ You’ll Learn how data center designers and operators can, just as for the design of computers decades ago, simulate the effects on energy use and reliability of different data center designs, without the time, expense, and business continuity risks of making changes with physical equipment. Download Jonathan Koomey’s FREE Data center Measurement Technology and Management Bundle tool & access White Papers, Total Cost of Ownership Models and Presentations powered by Advanced iFrame. Get the Pro version on CodeCanyon. Business Originally posted on April 8, 2016 Written by Jonathan Koomey Jonathan Koomey is a Research Fellow at the Steyer-Taylor Center for Energy Policy and Finance at Stanford University. He has also held visiting professorships at Yale University (Fall 2009), Stanford University (2003-4 and Fall 2008), and the University of California, Berkeley’s Energy and Resources Group (Fall 2011), and was a Lecturer in Management at Stanford’s Graduate School of Business in Spring 2013. For more than eleven years he led Lawrence Berkeley National Laboratory’s (LBNL’s) End-Use Forecasting group, which analyzes markets for efficient products and technologies for improving the energy and environmental aspects of those products. The group developed recommendations for policymakers at the U.S. Environmental Protection Agency and the U.S. Department of Energy on ways to promote energy efficiency and prevent pollution. Koomey is also a Research Affiliate of the Energy and Resources Group at the University of California, Berkeley, and serves on the Editorial Board of the journal Contemporary Economic Policy. Dr. Koomey holds M.S. and Ph.D. degrees from the Energy and Resources Group at the University of California at Berkeley, and a B.A. in History of Science from Harvard University. He is the author or coauthor of nine books and more than two hundred articles and reports on energy efficiency and supply-side power technologies, energy economics, energy policy, environmental externalities, and global climate change. He has also published extensively on critical thinking skills. More posts by Jonathan