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 DOI:10.1145/1735223.1735234	                                             Erik	Brynjolfsson,	Paul	Hofmann,	and	John	Jordan


economic and
Business dimensions
Cloud Computing and electricity:
Beyond the Utility Model
Assessing the strengths, weaknesses, and general applicability
of the computing-as-utility business model.




B
            U s iN e s s e s re LY No less on          cloud computing and                     use, paid for via subscription, and ac-
            electricity than on IT. Yet                the electricity model                   cessed over the Web.” From an aca-
            corporations don’t need a                  Definitions for cloud computing         demic perspective: “Cloud computing
            “Chief Electricity Officer”                vary. From a practitioner standpoint:   refers to both the applications deliv-
            and a staff of highly trained              “Cloud computing is on-demand ac-       ered as services over the Internet and
professionals to manage and integrate                  cess to virtualized IT resources that   the hardware and systems software
electricity into their businesses. Does                are housed outside of your own data     in the data centers that provide those
the historical adoption of electricity of-             center, shared by others, simple to     services. … The data center hardware
fer a useful analogy for today’s innova-                                                       and software is what we will call a
tions in cloud computing?                                                                      cloud. When a cloud is made available
    While the utility model offers some                an overly simplistic                    in a pay-as-you-go manner to the pub-
insights, we must go beyond this sim-                                                          lic, we call it a public cloud; the service
ple analogy to understand cloud com-                   reliance on the utility                 being sold is utility computing.”1
puting’s real challenges and opportu-                  model risks blinding                        Both definitions imply or explicitly
nities. Technical issues of innovation,                                                        use the “utility” model that embeds the
scale, and geography will confront                     us to the real                          logic of water supply, electrical grids, or
managers who attempt to take advan-                    opportunities and                       sewage systems. This model is ubiqui-
tage of offsite resources. In addition,                                                        tous. While it has important strengths,
business model challenges related to                   challenges of                           it also has major weaknesses.
complementarity,              interoperability,        cloud computing.                            Hardware providers introduced the
and security will make it difficult for                                                        language of “utility” computing into the
a stable cloud market to emerge. An                                                            market. But perhaps the most rigorous
overly simplistic reliance on the util-                                                        and vigorous assertion of the electric-
ity model risks blinding us to the real                                                        ity model comes from Nicholas Carr,
opportunities and challenges of cloud                                                          an independent blogger in his recent
computing.                                                                                     book, The Big Switch: “At a purely eco-

32   communications of th e ac m   | m ay 2 0 1 0 | vo l . 5 3 | n o. 5
viewpoints

                                     nomic level, the similarities between         technical Weaknesses                                 consistency and scalability at the same
                                     electricity and information technology        of the utility model                                 time. The problem of scalable data stor-
                                     are even more striking. Both are what         The Pace of Innovation. The pace of in-              age in the cloud with an API as rich as
                                     economists call general-purpose tech-         novation in electricity generation and               SQL makes it difficult for high-volume,
                                     nologies. … General-purpose technolo-         distribution happens on the scale of                 mission-critical transaction systems to
                                     gies, or GPTs, are best thought of not as     decades or centuries.8 In contrast,                  run in cloud environments.
                                     discrete tools but as platforms on which      Moore’s Law is measured in months.                       Meanwhile, companies of a certain
                                     many different tools, or applications,        In 1976, the basic computational pow-                size can get the best of both worlds by
                                     can be constructed. … Once it becomes         er of a $200 iPod would have cost one                deploying private clouds. Intel, for ex-
                                     possible to provide the technology cen-       billion dollars, while the full set of ca-           ample, is consolidating its data centers
                                     trally, large-scale utility suppliers arise   pabilities would have been impossible                from more than 100 eventually down to
                                     to displace the private providers. It may     to replicate at any price, much less in a            about 10. In 2008 the total fell to 75, with
                                     take decades for companies to abandon         shirt pocket. Managing innovative and                cost savings of $95 million. According to
                                     their proprietary supply operations and       rapidly changing systems requires the                Intel’s co-CIO Diane Bryant, 85% of In-
                                     all the investment they represent. But        attention of skilled, creative people,               tel’s servers support engineering com-
                                     in the end the savings offered by utili-      even when the innovations are creat-                 putation, and those servers run at 90%
                                     ties become too compelling to resist,
                                     even for the largest enterprises. The
                                     grid wins.”4

                                     strengths of the utility model
                                     Carr correctly highlights the concept
                                     of a general-purpose technology. This
                                     class of technology has historically
                                     been the greatest driver of productivity
                                     growth in modern economies. They not
                                     only contribute directly, but also by cat-
                                     alyzing myriad complementary innova-
                                     tions.3 For electricity, this includes the
                                     electric lighting, motors, and machin-
                                     ery. For IT, this includes transaction
                                     processing, ERP, online commerce and
                                     myriad other applications and even
                                     business model innovations.
                                         Some of the economies of scale and
                                     cost savings of cloud computing are
                                     also akin to those in electricity genera-
                                     tion. Through statistical multiplexing,
                                     centralized infrastructure can run at
                                     higher utilization than many forms of
                                     distributed server deployment. One
                                     system administrator, for example, can
                                     tend over 1,000 servers in a very large
                                     data center, while his or her equivalent
                                     in a medium-sized data center typical-
                                     ly manages approximately 140.7                ed by others, unlike managing stable                 utilization—a combination of strategic
                                         By moving data centers closer to          technologies.                                        importance and operational perfor-
                                     energy production, cloud computing                The Limits of Scale. The rapid avail-            mance that would negate any arguments
                                     creates additional cost savings. It is far    ability of additional server instances is a          for shifting that load to a cloud vendor.
                                     cheaper to move photons over the fiber-       central benefit of cloud computing, but              Ironically, even as the utility model is
                                     optic backbone of the Internet than it        it has its limits. In the first place, paral-        being touted for computing, the highly
                                     is to transmit electrons over our power       lel problems are only a subset of diffi-             centralized approach is becoming less
                                     grid. These savings are captured when         cult computing tasks: some problems                  effective for electricity itself: an emerg-
illustration by st ua rt bra dford




                                     data centers are located near low-cost        and processes must be attacked with                  ing distributed power generation sys-
                                     power sources like the hydroelectric          other architectures of processing, mem-              tem features smaller nodes running
                                     dams of the northwest U.S.                    ory, and storage, so simply renting more             micro-hydro, wind, micro-turbines and
                                         Along with its strengths, however,        nodes will not help. Secondly, many                  fuel cells. What’s more, many enterpris-
                                     the electric utility analogy also has         business applications rely on consis-                es do in fact generate their own electric-
                                     three technical weaknesses and three          tent transactions supported by RDBMS.                ity or steam, for the same reasons they
                                     business model weaknesses.                    The CAP Theorem says one cannot have                 will continue to keep certain classes of

                                                                                                                     m ay 2 0 1 0 | vo l . 5 3 | n o. 5 | c o m m u n i c at i o n s o f t he acm   33
viewpoints

  IT in house: reliability, strategic advan-                                                           the user and pose severe new security
  tage, or cost visibility.                                                                            issues not encountered by on-premise
     Latency: Distance is Not Dead. One of               if the utility model                          computing behind firewalls.
  the few immutable laws of physics is                   were adequate,
  the speed of light. As a result, latency                                                             conclusion
  remains a formidable challenge. In the                 the challenges to                             If the utility model were adequate, the
  network realm, the demands for nearly                  cloud computing                               challenges to cloud computing could
  instantaneous execution of machine-to-                                                               be solved with electricity-like solu-
  machine stock trades has led financial                 could be solved                               tions—but they cannot. The reality is
  services firms to locate their data cen-               with electricity-like                         that cloud computing cannot achieve
  ters as physically close to stock exchang-                                                           the plug-and-play simplicity of electric-
  es as possible. The read/write limits of               solutions—but                                 ity, at least, not as long as the pace of
  magnetic disks can only drop so far, but               they cannot.                                  innovation, both within cloud comput-
  increased speed comes at the cost of ca-                                                             ing itself, and in the myriad applica-
  pacity: big disks are slow, and fast disks                                                           tions and business models it enables,
  are small. For many classes of applica-                                                              continues at such a rapid pace. While
  tions, performance, convenience, and                                                                 electric utilities are held up as models
  security considerations will dictate that                                                            of simplicity and stability, even this in-
  computing be local. Moving data cen-                   iTunes store helped it quadruple reve-        dustry is not immune from the trans-
  ters away from their customers may save                nues in four years. The tight integration     formative power of IT.8,9 Innovations
  on electricity costs, but those savings are            between Apple’s ERP system and the            like the “smart grid” are triggering fun-
  often outweighed by the costs of latency.              billing engine handling some 10 mil-          damental changes at a pace not seen
                                                         lion sales per day would have been dif-       since the early days of electrification.
  Beyond electricity: the                                ficult, if not impossible, in the cloud.          The real strength of cloud computing is
  Business model of the cloud                                Lock-in and Interoperability. Lock-in     that it is a catalyst for more innovation. In
  Important as the technical differences                 issues with electricity were addressed        fact, as cloud computing continues to be-
  are between electricity and cloud com-                 long ago by regulation of monopolies,         come cheaper and more ubiquitous, the
  puting, the business model differences                 then later by legal separation of gen-        opportunities for combinatorial innova-
  are even more profound.                                eration from transmission and the             tion will only grow. It is true that this inev-
      Complementarities and Co-invention.                creation of market structures. Markets        itably requires more creativity and skill
  Like electricity, IT is a general-purpose              work because electrons are fungible.          from IT and business executives. In the
  technology. This means that critical                   The rotary converter that enabled in-         end, this not something to be avoided. It
  benefits come from the co-inventions                   terconnection of different generating         should be welcomed and embraced.
  that the basic technology makes pos-                   technologies in the 1890s has no ana-
  sible. It took 30 to 40 years for the full             log for the customer of multiple cloud        References
                                                                                                       1. armbrust, m. et al. a view of cloud computing.
  benefits of electricity to redound to                  vendors, and won’t anytime soon. For             Commun. ACM 53, 4 (apr. 2010), 50–58.
  America’s factories.5 Initially, assembly              enterprise computing to behave like           2. bresnahan, t., greenstein, s., brownstone, d. and flamm,
                                                                                                          k. technical progress and co-invention in computing and
  lines and production processes were                    line voltage will require radically differ-      in the uses of computers. Brookings Papers on Economic
  not redesigned to take advantages of                   ent management of data than what is              Activity—Microeconomics (1996), 1–83.
                                                                                                       3. brynjolfsson, e. and saunders, a. Wired for Innovation:
  electricity: large central steam engines               on anyone’s technology roadmap.                  How IT is Reshaping the Economy. mit Press,
  were simply replaced with large elec-                      Perhaps most critically, bits of infor-      cambridge, ma, 2010.
                                                                                                       4. carr, n. The Big Switch: Rewiring the World, from
  tric motors, and then hooked up to the                 mation are not electrons. Depending on           Edison to Google. norton, new york, 2008.
  same old crankshafts and cogs. Only                    the application, its engineering, and its     5. david, P. the dynamo and the computer: an historical
                                                                                                          perspective on the modern productivity paradox.
  with the reinvention of the production                 intended use, cloud offerings will not           American Economic Review 80, 2 (1990), 355–361.
  process was the potential of electrifica-              be interchangeable across cloud pro-          6. foley, J. Plug into the cloud. InformationWeek (sept.
                                                                                                          28, 2008).
  tion realized. Today, electricity has ma-              viders. Put more simply, the business         7. hamilton, J. internet-scale service efficiency. in
                                                                                                          Proceedings of the Large-Scale Distributed Systems
  tured to become a relative commodity.                  processes supported by enterprise com-           and Middleware (LADIS) Workshop, (sept. 2008).
  In contrast, computing is still in the                 puting are not motors or light bulbs.         8. hughes, t. Networks of Power: Electrification
                                                                                                          in Western Society, 1880–1930. Johns hopkins
  midst of an explosion of innovation                        Security. The security concerns with         university Press, baltimore, md, 1983.
  and co-invention.2 Firms that simply                   cloud computing have no electricity           9. Waltz, d. and king, J. Information Technology and
                                                                                                          America’s Energy Future. computing research
  replace corporate resources with cloud                 analog. No regulatory or law enforce-            association White Paper, Washington, d.c., 2009.
  computing, while changing nothing                      ment body will audit a company’s
  else, are doomed to miss the full ben-                 electrons, but processes related to           Erik Brynjolfsson (erikb@mit.edu) is a professor at the
  efits of the new technology.                           customer data, trade secrets, and clas-       mit sloan school and the director of the mit center for
                                                                                                       digital business in cambridge, ma.
      The opportunities, and risks, from                 sified government information are all
  IT-enabled business model innova-                      subject to stringent requirements and         Paul hofmann (paul.hofmann@sap.com) is a vice
                                                                                                       president at saP labs in Palo alto, ca.
  tion and organizational redesigns are                  standards of auditability. The typically
  reshaping entire industries.3 For in-                  shared and dynamic resources of cloud         John Jordan (jmj13@smeal.psu.edu) is a senior lecturer
                                                                                                       in the smeal college of business at Penn state university.
  stance, Apple’s transition from a per-                 computing (including CPU, network-
  petual license model to the pay-per-use                ing, and so forth) reduce control for         copyright held by author.


  34   communications of th e ac m   | m ay 2 0 1 0 | vo l . 5 3 | n o. 5

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Economics of Cloud Computing

  • 1. v viewpoints DOI:10.1145/1735223.1735234 Erik Brynjolfsson, Paul Hofmann, and John Jordan economic and Business dimensions Cloud Computing and electricity: Beyond the Utility Model Assessing the strengths, weaknesses, and general applicability of the computing-as-utility business model. B U s iN e s s e s re LY No less on cloud computing and use, paid for via subscription, and ac- electricity than on IT. Yet the electricity model cessed over the Web.” From an aca- corporations don’t need a Definitions for cloud computing demic perspective: “Cloud computing “Chief Electricity Officer” vary. From a practitioner standpoint: refers to both the applications deliv- and a staff of highly trained “Cloud computing is on-demand ac- ered as services over the Internet and professionals to manage and integrate cess to virtualized IT resources that the hardware and systems software electricity into their businesses. Does are housed outside of your own data in the data centers that provide those the historical adoption of electricity of- center, shared by others, simple to services. … The data center hardware fer a useful analogy for today’s innova- and software is what we will call a tions in cloud computing? cloud. When a cloud is made available While the utility model offers some an overly simplistic in a pay-as-you-go manner to the pub- insights, we must go beyond this sim- lic, we call it a public cloud; the service ple analogy to understand cloud com- reliance on the utility being sold is utility computing.”1 puting’s real challenges and opportu- model risks blinding Both definitions imply or explicitly nities. Technical issues of innovation, use the “utility” model that embeds the scale, and geography will confront us to the real logic of water supply, electrical grids, or managers who attempt to take advan- opportunities and sewage systems. This model is ubiqui- tage of offsite resources. In addition, tous. While it has important strengths, business model challenges related to challenges of it also has major weaknesses. complementarity, interoperability, cloud computing. Hardware providers introduced the and security will make it difficult for language of “utility” computing into the a stable cloud market to emerge. An market. But perhaps the most rigorous overly simplistic reliance on the util- and vigorous assertion of the electric- ity model risks blinding us to the real ity model comes from Nicholas Carr, opportunities and challenges of cloud an independent blogger in his recent computing. book, The Big Switch: “At a purely eco- 32 communications of th e ac m | m ay 2 0 1 0 | vo l . 5 3 | n o. 5
  • 2. viewpoints nomic level, the similarities between technical Weaknesses consistency and scalability at the same electricity and information technology of the utility model time. The problem of scalable data stor- are even more striking. Both are what The Pace of Innovation. The pace of in- age in the cloud with an API as rich as economists call general-purpose tech- novation in electricity generation and SQL makes it difficult for high-volume, nologies. … General-purpose technolo- distribution happens on the scale of mission-critical transaction systems to gies, or GPTs, are best thought of not as decades or centuries.8 In contrast, run in cloud environments. discrete tools but as platforms on which Moore’s Law is measured in months. Meanwhile, companies of a certain many different tools, or applications, In 1976, the basic computational pow- size can get the best of both worlds by can be constructed. … Once it becomes er of a $200 iPod would have cost one deploying private clouds. Intel, for ex- possible to provide the technology cen- billion dollars, while the full set of ca- ample, is consolidating its data centers trally, large-scale utility suppliers arise pabilities would have been impossible from more than 100 eventually down to to displace the private providers. It may to replicate at any price, much less in a about 10. In 2008 the total fell to 75, with take decades for companies to abandon shirt pocket. Managing innovative and cost savings of $95 million. According to their proprietary supply operations and rapidly changing systems requires the Intel’s co-CIO Diane Bryant, 85% of In- all the investment they represent. But attention of skilled, creative people, tel’s servers support engineering com- in the end the savings offered by utili- even when the innovations are creat- putation, and those servers run at 90% ties become too compelling to resist, even for the largest enterprises. The grid wins.”4 strengths of the utility model Carr correctly highlights the concept of a general-purpose technology. This class of technology has historically been the greatest driver of productivity growth in modern economies. They not only contribute directly, but also by cat- alyzing myriad complementary innova- tions.3 For electricity, this includes the electric lighting, motors, and machin- ery. For IT, this includes transaction processing, ERP, online commerce and myriad other applications and even business model innovations. Some of the economies of scale and cost savings of cloud computing are also akin to those in electricity genera- tion. Through statistical multiplexing, centralized infrastructure can run at higher utilization than many forms of distributed server deployment. One system administrator, for example, can tend over 1,000 servers in a very large data center, while his or her equivalent in a medium-sized data center typical- ly manages approximately 140.7 ed by others, unlike managing stable utilization—a combination of strategic By moving data centers closer to technologies. importance and operational perfor- energy production, cloud computing The Limits of Scale. The rapid avail- mance that would negate any arguments creates additional cost savings. It is far ability of additional server instances is a for shifting that load to a cloud vendor. cheaper to move photons over the fiber- central benefit of cloud computing, but Ironically, even as the utility model is optic backbone of the Internet than it it has its limits. In the first place, paral- being touted for computing, the highly is to transmit electrons over our power lel problems are only a subset of diffi- centralized approach is becoming less grid. These savings are captured when cult computing tasks: some problems effective for electricity itself: an emerg- illustration by st ua rt bra dford data centers are located near low-cost and processes must be attacked with ing distributed power generation sys- power sources like the hydroelectric other architectures of processing, mem- tem features smaller nodes running dams of the northwest U.S. ory, and storage, so simply renting more micro-hydro, wind, micro-turbines and Along with its strengths, however, nodes will not help. Secondly, many fuel cells. What’s more, many enterpris- the electric utility analogy also has business applications rely on consis- es do in fact generate their own electric- three technical weaknesses and three tent transactions supported by RDBMS. ity or steam, for the same reasons they business model weaknesses. The CAP Theorem says one cannot have will continue to keep certain classes of m ay 2 0 1 0 | vo l . 5 3 | n o. 5 | c o m m u n i c at i o n s o f t he acm 33
  • 3. viewpoints IT in house: reliability, strategic advan- the user and pose severe new security tage, or cost visibility. issues not encountered by on-premise Latency: Distance is Not Dead. One of if the utility model computing behind firewalls. the few immutable laws of physics is were adequate, the speed of light. As a result, latency conclusion remains a formidable challenge. In the the challenges to If the utility model were adequate, the network realm, the demands for nearly cloud computing challenges to cloud computing could instantaneous execution of machine-to- be solved with electricity-like solu- machine stock trades has led financial could be solved tions—but they cannot. The reality is services firms to locate their data cen- with electricity-like that cloud computing cannot achieve ters as physically close to stock exchang- the plug-and-play simplicity of electric- es as possible. The read/write limits of solutions—but ity, at least, not as long as the pace of magnetic disks can only drop so far, but they cannot. innovation, both within cloud comput- increased speed comes at the cost of ca- ing itself, and in the myriad applica- pacity: big disks are slow, and fast disks tions and business models it enables, are small. For many classes of applica- continues at such a rapid pace. While tions, performance, convenience, and electric utilities are held up as models security considerations will dictate that of simplicity and stability, even this in- computing be local. Moving data cen- iTunes store helped it quadruple reve- dustry is not immune from the trans- ters away from their customers may save nues in four years. The tight integration formative power of IT.8,9 Innovations on electricity costs, but those savings are between Apple’s ERP system and the like the “smart grid” are triggering fun- often outweighed by the costs of latency. billing engine handling some 10 mil- damental changes at a pace not seen lion sales per day would have been dif- since the early days of electrification. Beyond electricity: the ficult, if not impossible, in the cloud. The real strength of cloud computing is Business model of the cloud Lock-in and Interoperability. Lock-in that it is a catalyst for more innovation. In Important as the technical differences issues with electricity were addressed fact, as cloud computing continues to be- are between electricity and cloud com- long ago by regulation of monopolies, come cheaper and more ubiquitous, the puting, the business model differences then later by legal separation of gen- opportunities for combinatorial innova- are even more profound. eration from transmission and the tion will only grow. It is true that this inev- Complementarities and Co-invention. creation of market structures. Markets itably requires more creativity and skill Like electricity, IT is a general-purpose work because electrons are fungible. from IT and business executives. In the technology. This means that critical The rotary converter that enabled in- end, this not something to be avoided. It benefits come from the co-inventions terconnection of different generating should be welcomed and embraced. that the basic technology makes pos- technologies in the 1890s has no ana- sible. It took 30 to 40 years for the full log for the customer of multiple cloud References 1. armbrust, m. et al. a view of cloud computing. benefits of electricity to redound to vendors, and won’t anytime soon. For Commun. ACM 53, 4 (apr. 2010), 50–58. America’s factories.5 Initially, assembly enterprise computing to behave like 2. bresnahan, t., greenstein, s., brownstone, d. and flamm, k. technical progress and co-invention in computing and lines and production processes were line voltage will require radically differ- in the uses of computers. Brookings Papers on Economic not redesigned to take advantages of ent management of data than what is Activity—Microeconomics (1996), 1–83. 3. brynjolfsson, e. and saunders, a. Wired for Innovation: electricity: large central steam engines on anyone’s technology roadmap. How IT is Reshaping the Economy. mit Press, were simply replaced with large elec- Perhaps most critically, bits of infor- cambridge, ma, 2010. 4. carr, n. The Big Switch: Rewiring the World, from tric motors, and then hooked up to the mation are not electrons. Depending on Edison to Google. norton, new york, 2008. same old crankshafts and cogs. Only the application, its engineering, and its 5. david, P. the dynamo and the computer: an historical perspective on the modern productivity paradox. with the reinvention of the production intended use, cloud offerings will not American Economic Review 80, 2 (1990), 355–361. process was the potential of electrifica- be interchangeable across cloud pro- 6. foley, J. Plug into the cloud. InformationWeek (sept. 28, 2008). tion realized. Today, electricity has ma- viders. Put more simply, the business 7. hamilton, J. internet-scale service efficiency. in Proceedings of the Large-Scale Distributed Systems tured to become a relative commodity. processes supported by enterprise com- and Middleware (LADIS) Workshop, (sept. 2008). In contrast, computing is still in the puting are not motors or light bulbs. 8. hughes, t. Networks of Power: Electrification in Western Society, 1880–1930. Johns hopkins midst of an explosion of innovation Security. The security concerns with university Press, baltimore, md, 1983. and co-invention.2 Firms that simply cloud computing have no electricity 9. Waltz, d. and king, J. Information Technology and America’s Energy Future. computing research replace corporate resources with cloud analog. No regulatory or law enforce- association White Paper, Washington, d.c., 2009. computing, while changing nothing ment body will audit a company’s else, are doomed to miss the full ben- electrons, but processes related to Erik Brynjolfsson (erikb@mit.edu) is a professor at the efits of the new technology. customer data, trade secrets, and clas- mit sloan school and the director of the mit center for digital business in cambridge, ma. The opportunities, and risks, from sified government information are all IT-enabled business model innova- subject to stringent requirements and Paul hofmann (paul.hofmann@sap.com) is a vice president at saP labs in Palo alto, ca. tion and organizational redesigns are standards of auditability. The typically reshaping entire industries.3 For in- shared and dynamic resources of cloud John Jordan (jmj13@smeal.psu.edu) is a senior lecturer in the smeal college of business at Penn state university. stance, Apple’s transition from a per- computing (including CPU, network- petual license model to the pay-per-use ing, and so forth) reduce control for copyright held by author. 34 communications of th e ac m | m ay 2 0 1 0 | vo l . 5 3 | n o. 5