Rough seas ahead for "in-house" data centers

Rough seas ahead for “in-house” data centers

Jonathan Koomey, Ph.D. http://www.koomey.com Samsung CIO Forum

San Jose, CA November 1, 2012

1 Copyright Jonathan G. Koomey 2012

What the NY Times didn’t say…


Two common ways to use the word “cloud”

•  “The cloud”

•  “Cloud computing”*

*this is the way I mainly use the term


Data centers are where the world of bits meets the world

of atoms


5

Electricity Flows in Data Centers

Copyright Jonathan G. Koomey 2012

Data centers used 1.3% of global electricity and 2%

of US electricity in 2010*

*For details see Koomey 2011


Delivery of IT services is increasing rapidly, but at the

same time…


information technology is becoming more energy

efficient at a furious pace


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 http://www.intel.com/performance

Xeon™ 5160

Xeon™ E5-‐2660

2012

2006

Data from spec.org

Source: Winston Saunders, Intel


Data center costs are strongly affected by IT power use, particularly server power


Annualized data center costs

11

Source: Koomey et al. 2009a

x 2


Low power DRAM and SSDs are worth more than you think

12 Picture courtesy of Samsung Electronics Co. Ltd


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.


In spite of our historical progress, there’s still great potential for

improving the energy efficiency of data centers


Many efficiency opportunities, particularly in IT equipment

15

Source: Masanet et al. 2011


Improving the energy efficiency of data centers is as much about people and institutions as it is

about technology


Why asset management is key

Slide courtesy of Winston Saunders, Intel 17 Copyright Jonathan G. Koomey 2012

Lesson 1: Big potential for efficiency

improvements, especially in “in-house” data centers


Lesson 2: Fixing misplaced incentives is the most important step

toward realizing this potential


Now on to cloud computing…


For users, cloud computing offers infinitely scalable computing on demand


So why should cloud users care about power use?


Power use strongly affects costs for “in-house” IT

services (the alternative to relying on the cloud) AND


Cloud computing suppliers have at least four big

advantages on power and costs over

“in-house” IT


1) Diversity: spread loads over many users,

improving hardware utilization


2) Economies of scale: implementing technical + organizational changes is

cheaper and easier than for small IT shops


3) Flexibility: management of virtual servers easier and

cheaper than physical servers


4) Easier for users to shift to cloud providers than to

fix the institutional problems in their internal IT

organizations


My claim: Powerful economic trends

(driven by these energy advantages) will push users

more and more towards cloud computing


And there’s another interesting story here...


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


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.


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!


Sign up!: Uptime Server Roundup

•  Find and retire comatose servers •  Enroll at http://www.uptimeinstitute.com/

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


Key web sites

•  EPA on data centers + 2007 Report to Congress http://www.energystar.gov/datacenters

•  LBNL on data centers: http://hightech.lbl.gov/datacenters.html

•  The Green Grid: http://www.thegreengrid.org/ •  The Uptime Institute: http://www.uptimeinstitute.org

•  SPEC power: http://www.spec.org/power_ssj2008/


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. <http://people.eng.unimelb.edu.au/rtucker/publications/files/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. [http://www.barroso.org/]

•  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. <http://www.amd.com/koomey>

•  Koomey, Jonathan. 2007b. Estimating total power consumption by servers in the U.S. and the world. Oakland, CA: Analytics Press. February 15. <http://enterprise.amd.com/us-en/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. <http://www.uptimeinstitute.org/>

•  Koomey, Jonathan. 2008. "Worldwide electricity used in data centers." Environmental Research Letters. vol. 3, no. 034008. September 23. <http://stacks.iop.org/1748-9326/3/034008>.


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. <http://www.intel.com/pressroom/kits/ecotech>

•  Koomey, Jonathan. 2011. Growth in data center electricity use 2005 to 2010. Oakland, CA: Analytics Press. August 1. <http://www.analyticspress.com/datacenters.html>

•  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. <https://files.me.com/jgkoomey/u0zi7l>

•  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. <http://www.analyticspress.com/scienceofmeasurement.html>

•  Taylor, Cody, and Jonathan Koomey. 2008. Estimating energy use and greenhouse gas emissions of Internet advertising. Working paper for IMC2. February 14. <http://imc2.com/Documents/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. [http://dx.doi.org/10.1111/j.1530-9290.2010.00269.x]


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