Power-related advantages of
Jonathan G. Koomey, Ph.D.
Project Scientist, LBNL and Consulting
Professor, Stanford University
May 17, 2010
Current in-house IT
• 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.)
Powerful economic trends will
push users more and more
towards cloud computing
One of the main drivers of
those trends is more efficient
power use by cloud
Data center costs are strongly
affected by IT power use,
particularly server power
• ATC = Annualized total costs
• IT = Capital cost of IT equipment
• INFkw = Power-related infrastructure capital
• INFnon-kW = Non-power-related infrastructure
• EC = Energy costs
• O&M = Operation and maintenance costs
• Think “whole system redesign” (RMI)
• Align incentives to minimize True TCO
• Implement consistent metrics and track
• Improve asset management and
utilization (multiple benefits)
• Improve efficiency of systems (e.g.
cooling) and components (e.g. power
• Energy, efficiency, and performance metrics
• 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
Cloud computing suppliers
have at least four inherent
advantages on power and
costs over “in-house” IT.
1) Diversity: spread loads
over many users,
2) Economies of scale:
implementing technical +
organizational changes is
cheaper per computation
than for small IT shops
3) Flexibility: management
of virtual servers easier and
cheaper than physical
4) Enabling structural
change: Often easier to
shift to cloud providers
than to fix institutional
problems in internal IT
Carbon taxes will accelerate
these trends (and accentuate
regional differences in sources
of power generation)
Maximum effect of $19/t CO2
price on data center costs
Assumes coal-fired power generation and CO2 tax of $19/t CO2
(comparable to the current price in the European emissions trading system).
CO2 tax = 2 ¢/kWh delivered; electricity price = 6.9 ¢/kWh (2009 $).
Big picture: Better to move
bits than atoms
CO2 emissions for downloads and physical CDs
Physical CDs Digital downloads
Source: Weber et al. 2009
• 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
Key web sites
• EPA on data centers + 2007 Report to Congress
• LBNL on data centers: http://hightech.lbl.gov/
• The Green Grid: http://www.thegreengrid.org/
• The Uptime Institute: http://www.uptimeinstitute.org
• SPEC power: http://www.spec.org/power_ssj2008/
• 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. <http://enterprise.amd.com/us-en/AMD-Business/
• 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.
• Koomey, Jonathan. 2008. "Worldwide electricity used in data centers."
Environmental Research Letters. vol. 3, no. 034008. September 23.
• 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 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/
• 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. <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>