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Rough seas ahead for "in-house" data centers


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This is a keynote talk I gave at the Samsung CIO forum in San Jose, CA, November 1, 2012

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Rough seas ahead for "in-house" data centers

  1. 1. Rough seas ahead for “in- house” data centers Jonathan Koomey, Ph.D. Samsung CIO Forum San Jose, CA November 1, 2012 1  Copyright  Jonathan  G.  Koomey  2012  
  2. 2. What the NY Times didn’t say… 2  Copyright  Jonathan  G.  Koomey  2012  
  3. 3. Two common ways to use the word “cloud” •  “The cloud” •  “Cloud computing”* *this is the way I mainly use the term 3  Copyright  Jonathan  G.  Koomey  2012  
  4. 4. Data centers are where the world of bits meets the world of atoms 4Copyright  Jonathan  G.  Koomey  2012  
  5. 5. 5 Electricity  Flows  in  Data  Centers Copyright  Jonathan  G.  Koomey  2012  
  6. 6. Data centers used 1.3% of global electricity and 2% of US electricity in 2010* *For details see Koomey 2011 6Copyright  Jonathan  G.  Koomey  2012  
  7. 7. Delivery of IT services is increasing rapidly, but at the same time… 7Copyright  Jonathan  G.  Koomey  2012  
  8. 8. information technology is becoming more energy efficient at a furious pace 8Copyright  Jonathan  G.  Koomey  2012  
  9. 9. Example: Servers (via Intel) •  Usage Driven •  Variable Utilization •  Proportional Energy Use •  Optimized Efficiency •  Technology Scope: •  CPU and Memory •  Power Delivery, Fans, etc. •  Instrumentation Approaching “Ideal” Server Behavior Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark* and MobileMark*, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. Configurations: Dual Socket Server. For full configuration information, please see backup. For more information go to Xeon™  5160   Xeon™  E5-­‐2660   2012   2006   Data from Source:    Winston  Saunders,  Intel   9  Copyright  Jonathan  G.  Koomey  2012  
  10. 10. Data center costs are strongly affected by IT power use, particularly server power 10Copyright  Jonathan  G.  Koomey  2012  
  11. 11. Annualized data center costs 11 Source:    Koomey  et  al.  2009a   x  2   Copyright  Jonathan  G.  Koomey  2012  
  12. 12. Low power DRAM and SSDs are worth more than you think 12   Picture  courtesy  of  Samsung  Electronics  Co.  Ltd   Copyright  Jonathan  G.  Koomey  2012  
  13. 13. What’s 1 W of IT savings worth? 13   Infrastructure  capital  savings  apply  to  new  construcNon  or  exisNng  faciliNes  that  are  power/cooling   constrained.    Those  savings  total  $8.6M/MW  for  cloud  faciliNes  and  $15M/MW  for  others,  from  UpNme   insNtute.    PUE  =  1.1,  1.5,  and  1.8  for  Cloud,  New,  and  ExisNng  data  centers,  respecNvely.    Electricity  price   =$0.039/kWh  for  cloud  faciliNes  and  $0.066/kWh  for  new/exisNng  data  centers.  All  costs  in  2012  dollars.   Copyright  Jonathan  G.  Koomey  2012  
  14. 14. In spite of our historical progress, there’s still great potential for improving the energy efficiency of data centers 14Copyright  Jonathan  G.  Koomey  2012  
  15. 15. Many efficiency opportunities, particularly in IT equipment 15 Source:    Masanet  et  al.  2011   Copyright  Jonathan  G.  Koomey  2012  
  16. 16. Improving the energy efficiency of data centers is as much about people and institutions as it is about technology 16Copyright  Jonathan  G.  Koomey  2012  
  17. 17. Why asset management is key Slide  courtesy  of  Winston  Saunders,  Intel   17  Copyright  Jonathan  G.  Koomey  2012  
  18. 18. Lesson 1: Big potential for efficiency improvements, especially in “in-house” data centers 18Copyright  Jonathan  G.  Koomey  2012  
  19. 19. Lesson 2: Fixing misplaced incentives is the most important step toward realizing this potential 19Copyright  Jonathan  G.  Koomey  2012  
  20. 20. Now on to cloud computing… 20Copyright  Jonathan  G.  Koomey  2012  
  21. 21. For users, cloud computing offers infinitely scalable computing on demand 21Copyright  Jonathan  G.  Koomey  2012  
  22. 22. So why should cloud users care about power use? 22Copyright  Jonathan  G.  Koomey  2012  
  23. 23. Power use strongly affects costs for “in-house” IT services (the alternative to relying on the cloud) AND 23Copyright  Jonathan  G.  Koomey  2012  
  24. 24. Cloud computing suppliers have at least four big advantages on power and costs over “in-house” IT 24Copyright  Jonathan  G.  Koomey  2012  
  25. 25. 1) Diversity: spread loads over many users, improving hardware utilization 25Copyright  Jonathan  G.  Koomey  2012  
  26. 26. 2) Economies of scale: implementing technical + organizational changes is cheaper and easier than for small IT shops 26Copyright  Jonathan  G.  Koomey  2012  
  27. 27. 3) Flexibility: management of virtual servers easier and cheaper than physical servers 27Copyright  Jonathan  G.  Koomey  2012  
  28. 28. 4) Easier for users to shift to cloud providers than to fix the institutional problems in their internal IT organizations 28Copyright  Jonathan  G.  Koomey  2012  
  29. 29. My claim: Powerful economic trends (driven by these energy advantages) will push users more and more towards cloud computing 29Copyright  Jonathan  G.  Koomey  2012  
  30. 30. And there’s another interesting story here... 30Copyright  Jonathan  G.  Koomey  2012  
  31. 31. Big picture: Often better to move bits than atoms 31  Source:    Weber  et  al.  2010   Physical  CDs   Digital  downloads   CO2  emissions  for  downloads  and  physical  CDs   Copyright  Jonathan  G.  Koomey  2012  
  32. 32. General conclusions •  Data centers responsible for about 1.3% of the world’s electricity use in 2010 (2% for US) •  Absolute electricity use has been growing fast but growth slowed 2005 to 2010 •  Delivery of IT services growing faster than electricity use (so electricity productivity is up!) •  The indirect productivity benefits of IT are likely to be more important than direct electricity use. 32Copyright  Jonathan  G.  Koomey  2012  
  33. 33. Lessons for “in-house” IT •  IT system and component efficiency (like from low-power SSDs and DRAM) matter •  “In-house” data centers facing challenges because of –  poor measurement and verification processes –  misplaced incentives –  competition from cloud and other providers –  pressure from the “C-level” •  IT becoming, less general purpose, more custom designed, and closer to tasks (more mobile) •  CIOs moving from “keepers of systems” to “brokers of information services”. Get ready! 33  Copyright  Jonathan  G.  Koomey  2012  
  34. 34. Sign up!: Uptime Server Roundup •  Find and retire comatose servers •  Enroll at server-roundup •  Submission deadline for this year’s contest: March 1, 2013 •  Submitted results can be anonymous •  Last time participants retired 20,000 servers and eliminated 5 MW of IT load 34  Copyright  Jonathan  G.  Koomey  2012  
  35. 35. Key web sites •  EPA on data centers + 2007 Report to Congress •  LBNL on data centers: datacenters.html •  The Green Grid: •  The Uptime Institute: •  SPEC power: 35Copyright  Jonathan  G.  Koomey  2012  
  36. 36. References •  Baliga, Jayant, Robert W. A. Ayre, Kerry Hinton, and Rodney S. Tucker. 2010. "Green Cloud Computing: Balancing Energy in Processing, Storage and Transport." In Press at the Proceedings of the IEEE. < Baliga_Ayre_Hinton_Tucker_JRLStrTrans.pdf> •  Barroso, Luzi André, and Urs Hölzle. 2007. "The Case for Energy-Proportional Computing." IEEE Computer. vol. 40, no. 12. December. pp. 33-37. [] •  Hilbert, Martin, and Priscila López. 2011. "The World's Technological Capacity to Store, Communicate, and Compute Information." Science. vol. 332, no. 6025. April 1. pp. 60-65. •  Koomey, Jonathan. 2007a. Estimating regional power consumption by servers: A technical note. Oakland, CA: Analytics Press. December 5. <> •  Koomey, Jonathan. 2007b. Estimating total power consumption by servers in the U.S. and the world. Oakland, CA: Analytics Press. February 15. < AMD-Business/Technology-Home/Power-Management.aspx> •  Koomey, Jonathan, Kenneth G. Brill, W. Pitt Turner, John R. Stanley, and Bruce Taylor. 2007. A simple model for determining true total cost of ownership for data centers. Santa Fe, NM: The Uptime Institute. September. <> •  Koomey, Jonathan. 2008. "Worldwide electricity used in data centers." Environmental Research Letters. vol. 3, no. 034008. September 23. < 1748-9326/3/034008>. 36Copyright  Jonathan  G.  Koomey  2012  
  37. 37. References (continued) •  Koomey, Jonathan G., Christian Belady, Michael Patterson, Anthony Santos, and Klaus-Dieter Lange. 2009a. Assessing trends over time in performance, costs, and energy use for servers. Oakland, CA: Analytics Press. August 17. <> •  Koomey, Jonathan. 2011. Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press. August 1. <> •  Koomey, Jonathan G., Stephen Berard, Marla Sanchez, and Henry Wong. 2011. "Implications of Historical Trends in The Electrical Efficiency of Computing." IEEE Annals of the History of Computing. vol. 33, no. 3. July-September. pp. 2-10. <> •  Masanet, Eric R., Richard E. Brown, Arman Shehabi, Jonathan G. Koomey, and Bruce Nordman. 2011. "Estimating the Energy Use and Efficiency Potential of U.S. Data Centers." Proceedings of the IEEE. vol. 99, no. 8. August. •  Stanley, John, and Jonathan Koomey. 2009. The Science of Measurement: Improving Data Center Performance with Continuous Monitoring and Measurement of Site Infrastructure. Oakland, CA: Analytics Press. October 23. <> •  Taylor, Cody, and Jonathan Koomey. 2008. Estimating energy use and greenhouse gas emissions of Internet advertising. Working paper for IMC2. February 14. < CarbonEmissions.pdf>. •  Weber, Christopher, Jonathan G. Koomey, and Scott Matthews. 2010. "The Energy and Climate Change Impacts of Different Music Delivery Methods." The Journal of Industrial Ecology. vol. 14, no. 5. October. pp. 754–769. [] 37  Copyright  Jonathan  G.  Koomey  2012