Above the Clouds: A Berkeley View of CloudComputingMichael ArmbrustArmando FoxRean GriffithAnthony D. JosephRandy H. KatzAndrew KonwinskiGunho LeeDavid A. PattersonAriel RabkinIon StoicaMatei ZahariaElectrical Engineering and Computer SciencesUniversity of California at BerkeleyTechnical Report No. UCB/EECS-2009-28http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.htmlFebruary 10, 2009Copyright 2009, by the author(s).All rights reserved. Permission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copies arenot made or distributed for profit or commercial advantage and that copiesbear this notice and the full citation on the first page. To copy otherwise, torepublish, to post on servers or to redistribute to lists, requires prior specificpermission. Acknowledgement The RAD Lab's existence is due to the generous support of the foundingmembers Google, Microsoft, and Sun Microsystems and of the affiliatemembers Amazon Web Services, Cisco Systems, Facebook, Hewlett-Packard, IBM, NEC, Network Appliance, Oracle, Siemens, and VMware; bymatching funds from the State of California's MICRO program (grants 06-152, 07-010, 06-148, 07-012, 06-146, 07-009, 06-147, 07-013, 06-149, 06-150, and 07-008) and the University of California Industry/UniversityCooperative Research Program (UC Discovery) grant COM07-10240; andby the National Science Foundation (grant #CNS-0509559).Above the Clouds: A Berkeley View of Cloud ComputingMichael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz,Andy Konwinski, Gunho Lee, David Patterson, Ariel Rabkin, Ion Stoica, and Matei Zaharia(Comments should be addressed to [email protected])UC Berkeley Reliable Adaptive Distributed Systems Laboratory∗http://radlab.cs.berkeley.edu/February 10, 2009KEYWORDS: Cloud Computing, Utility Computing, Internet Datacenters, Distributed System Economics1 Executive SummaryCloud Computing, the long-held dream of computing as a utility, has the potential to transform a large part of theIT industry, making software even more attractive as a service and shaping the way IT hardware is designed andpurchased. Developers with innovative ideas for new Internet services no longer require the large capital outlaysin hardware to deploy their service or the human expense to operate it. They need not be concerned about over-provisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or under-provisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companieswith large batch-oriented tasks can get results as quickly as their programs can scale, since using 1000 servers for onehour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium forlarge scale, is unprecedented in the history of IT.Cloud Computing refers to both the applications delivered as services over the Internet and the hardware andsystems software in the datacenters that provide those services. The services themselves have long been referred to asSoftware as a Service (SaaS). The datacenter hardware and software is what we will call a Cloud. When a Cloud ismade available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold isUtility Computing. We use the term Private Cloud to refer to internal datacenters of a business or other organization,not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but doesnot include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility Computing. Wefocus on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SaaS Users.From a hardware point of view, three aspects are new in Cloud Computing.1. The illusion of infinite computing resources available on demand, thereby eliminating the need for Cloud Com-puting users to plan far ahead for provisioning.2. The elimination of an up-front commitment by Cloud users, thereby allowing companies to start small andincrease hardware resources only when there is an increase in their needs.3. The ability to pay for use of computing resources on a short-term basis as needed (e.g., processors by the hourand storage by the day) and release them as needed, thereby rewarding conservation by letting machines andstorage go when they are no longer useful.We argue that the construction and operation of extremely large-scale, commodity-computer datacenters at low-cost locations was the key necessary enabler of Cloud Computing, for they uncovered the factors of 5 to 7 decreasein cost of electricity, network bandwidth, operations, software, and hardware available at these very large economies∗The RAD Lab’s existence is due to the generous support of the founding members Google, Microsoft, and Sun Microsystems and of the affiliatemembers Amazon Web Services, Cisco Systems, Facebook, Hewlett-Packard, IBM, NEC, Network Appliance, Oracle, Siemens, and VMware; bymatching funds from the State of California’s MICRO program (grants 06-152, 07-010, 06-148, 07-012, 06-146, 07-009, 06-147, 07-013, 06-149,06-150, and 07-008) and the University of California Industry/University Cooperative Research Program (UC Discovery) grant COM07-10240; andby the National Science Foundation (grant #CNS-0509559).1of scale. These factors, combined with statistical multiplexing to increase utilization compared a private cloud, meantthat cloud computing could offer services below the costs of a medium-sized datacenter and yet still make a goodprofit.Any application needs a model of computation, a model of storage, and a model of communication. The statisticalmultiplexing necessary to achieve elasticity and the illusion of infinite capacity requires each of these resources tobe virtualized to hide the implementation of how they are multiplexed and shared. Our view is that different utilitycomputing offerings will be distinguished based on the level of abstraction presented to the programmer and the levelof management of the resources.Amazon EC2 is at one end of the spectrum. An EC2 instance looks much like physical hardware, and users cancontrol nearly the entire software stack, from the kernel upwards. This low level makes it inherently difficult forAmazon to offer automatic scalability and failover, because the semantics