Cloud computing provides inherent advantages over in-house IT in terms of power usage and costs. These advantages include increased hardware utilization through diversity of users, economies of scale in implementing efficiency changes, easier management of virtual servers, and greater flexibility to address institutional problems. As carbon pricing increases, these economic benefits will further accelerate the trend toward cloud computing over traditional internal data centers.

1. Power-related advantages of
cloud computing
Jonathan G. Koomey, Ph.D.
http://www.koomey.com
Project Scientist, LBNL and Consulting
Professor, Stanford University
May 17, 2010
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2. Your choice:
Current in-house IT
or
cloud computing?
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3. Cloud computing
• Users pay for computing cycles and
don’t worry about the back end
• Manage virtual servers—characteristics
of physical servers less important
• Can be internal (replacing standard
data centers) or external (e.g., Google,
Microsoft, Amazon etc.)
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4. My claim:
Powerful economic trends will
push users more and more
towards cloud computing
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5. One of the main drivers of
those trends is more efficient
power use by cloud
computing providers
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6. Data center costs are strongly
affected by IT power use,
particularly server power
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7. Key definitions
• ATC = Annualized total costs
• IT = Capital cost of IT equipment
• INFkw = Power-related infrastructure capital
costs
• INFnon-kW = Non-power-related infrastructure
capital costs
• EC = Energy costs
• O&M = Operation and maintenance costs
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8. Two important equations
Power related terms
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9. Current server W/k$
∑: 25 to 100
Watts/k$ is the
Numbers
current range next to points
represent
watts/
thousand
2009 dollars.
Source:
Koomey et al.
2009a.
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10. Some anecdotal data on
Watts/k$ over time
∑: Watts/k$
doubled every
4-5 years in the
past decade
See Koomey et al. 2009a for details. 10

11. Annualized data center costs
x2
Source: Koomey et al. 2009a 11

12. Improving the energy
efficiency of data centers is as
much about people and
institutions as it is about
technology
12

13. Corporate Average Datacenter
Efficiency (CADE)
Facility IT Domain
Domain
Q4 Q1
Facility IT Asset
CapEx Asset Utilization
Utilization
Facility IT Energy
Energy, Energy Efficiency
CO2 OpEx Efficiency
Q3 Q2
© 2008, 2010 Uptime Institute 13

14. Efficiency opportunities
• Think “whole system redesign” (RMI)
• Align incentives to minimize True TCO
• Implement consistent metrics and track
over time
• Improve asset management and
utilization (multiple benefits)
• Improve efficiency of systems (e.g.
cooling) and components (e.g. power
supplies)
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15. Misplaced incentives
• Energy, efficiency, and performance metrics
not standardized
• Not charging per kW but per square foot
• Split accountability
– Who pays the bills, IT or facilities?
– Who bears the risk of failure?
• Hierarchy and culture differences
• Piling safety factor upon safety factor
• Not focusing on total costs for delivering
computing services
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16. Cloud computing suppliers
have at least four inherent
advantages on power and
costs over “in-house” IT.
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17. 1) Diversity: spread loads
over many users,
improving hardware
utilization
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18. 2) Economies of scale:
implementing technical +
organizational changes is
cheaper per computation
than for small IT shops
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19. 3) Flexibility: management
of virtual servers easier and
cheaper than physical
servers
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20. 4) Enabling structural
change: Often easier to
shift to cloud providers
than to fix institutional
problems in internal IT
organizations
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21. Carbon taxes will accelerate
these trends (and accentuate
regional differences in sources
of power generation)
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22. Maximum effect of $19/t CO2
price on data center costs
CO2 tax
Assumes coal-fired power generation and CO2 tax of $19/t CO2
(comparable to the current price in the European emissions trading system).
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CO2 tax = 2 ¢/kWh delivered; electricity price = 6.9 ¢/kWh (2009 $).

23. Big picture: Better to move
bits than atoms
CO2 emissions for downloads and physical CDs
Physical CDs Digital downloads
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Source: Weber et al. 2009

24. Conclusions
• Cloud computing’s inherent cost advantages
will continue to drive customers to use it
• Power efficiency is one of the main sources of
these advantages (and pricing carbon will
make the case more compelling)
• Conventional internal data centers will still be
important for certain kinds of applications, but
will diminish in importance over time
• Issues about liability, property rights, and
security in the cloud will need to be sorted out,
but the economic benefits will create pressure
to do just that
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25. 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/
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26. References
• 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>.
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27. 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 G., Stephen Berard, Marla Sanchez, and Henry Wong.
2009b. Assessing trends in the electrical efficiency of computation over time.
Oakland, CA: Analytics Press. August 17. <http://www.intel.com/pressroom/kits/
ecotech>
• 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. 2009. The
Energy and Climate Change Impacts of Different Music Delivery Methods.
Analytics Press. August 17. <http://www.intel.com/pressroom/kits/ecotech>
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