SALESFORCE.COM AND THE ENVIRONMENT:

Transcription

1 SALESFORCE.COM AND THE ENVIRONMENT: Reducing Carbon Emissions in the Cloud

2 03 Executive Summary 04 Introduction 05 Approach & Methodology 06 Summary of Findings 08 How does salesforce.com s cloud platform deliver exceptional energy and carbon efficiency? 12 Conclusion 14 Footnotes 15 Appendix

3 Executive Summary Despite their similar labels, various cloud computing offerings differ greatly in their environmental impact and their potential to improve on the environmental footprint of legacy IT models. To more rigorously assess the environmental impact of cloud computing, salesforce.com engaged WSP Environment & Energy to compare the energy use and carbon footprint of its cloud platform and services against equivalent on-premises and virtualized data center deployments. Our analysis shows that salesforce.com s massively scalable, multitenant cloud computing platform is substantially more carbon efficient that on-premises systems or even virtualized data center deployments (also known as private cloud deployments). Specifically, the study found that: A salesforce.com transaction is on average 95% more carbon efficient than when processed in an equivalent on-premises deployment; A salesforce.com transaction is on average 64% more carbon efficient than when processed in an equivalent private cloud deployment; and Salesforce.com s estimated total customer carbon emissions footprint for 2010 is at least 19 times smaller than an equivalent onpremises deployment, and is 3 times smaller than an equivalent private cloud deployment. Salesforce.com s cloud platform enables much higher utilization of servers; uses elastic provisioning to better match server capacity to demand; and applies multitenancy to serve thousands of organizations with one set of shared infrastructure. Further, salesforce.com appears to be leading the way in designing, building and operating cloud service hubs that minimize energy use for a given amount of computing power (not only at an operational level). Further, they can employ energy-saving innovations at a scale that only the largest on premises or virtualized data center owner / operators could feasibly manage. For those few companies that do have a scale of operations appropriate to a large-scale task-specific infrastructure, this study identifies the key drivers that will let them optimize for the greatest efficiency as well. This study shows that there are clear and significant energy and carbon emission reduction benefits associated with the migration of services and applications to a cloud environment, and also details how salesforce.com s cloud platform enables further efficiencies over a private cloud / virtualized data center deployment. While individual companies may begin to realize lowered emissions at the local scale by decommissioning their equipment and using cloud services to more efficiently run their businesses, cumulative reductions in carbon emissions at the platform level signal an untapped potential to significantly reduce global carbon emissions (expressed across salesforce.com s existing and growing customer base). P.03

4 Introduction The use of IT is increasingly being positioned as a tool to realize environmental sustainability goals, allowing companies to measure, analyze, manage and report on environmental data to mitigate risk and reduce their overall impact 1. At the same time, the choice of IT infrastructure and services is increasingly being seen as a component of a company s carbon footprint that can enable control of their scale and growth over time. Specifically, cloud computing has emerged as a solution that reduces hardware requirements, provides scalability and offers direct energy and carbon emissions reductions; as well as enabling more efficient business processes, scalability and improved communication and collaboration. While a previous report 2 captured how cloud computing broadly offers the potential to greatly reduce the environmental impact of IT (mostly due to its flexible, scalable model), not all cloud models are the same and there are varying degrees of efficiency within various types of clouds. As businesses continue to evaluate a move to the cloud, a greater understanding of specific cloud computing providers environmental performance may be another factor to consider. The degree to which businesses and, more broadly, the environment may stand to gain when choosing between on premises computing, a private cloud and a multitenant public cloud is less well known. Commissioned by salesforce.com, WSP Environment & Energy (WSP) performed a quantitative analysis of salesforce.com s cloud platform to compare the energy and carbon efficiency of its service offering within the context of equivalent on-premises and private cloud deployments to better quantify the potential impact of cloud computing. P.04

5 Approach & Methodology WSP developed a quantitative model that calculates the life cycle carbon emissions of salesforce.com s cloud platform (called Force.com), and compared the results to the equivalent services provided within an on-premises and private cloud deployment. The methodology used to develop this independent model is in line with the assessment methodology developed by the Global e-sustainability Initiative (GeSI) 3 and other best practice standards. This model quantifies energy use and carbon emissions on a per-transaction and per-user basis and considers three deployment scenarios: on premises, private cloud and salesforce.com s cloud platform. Within each of the three deployment scenarios, three organizational sizes are considered: small (under 100 users), medium (under 500 users), and large (over 500 users, up to 10,000) to account for non-linear server scaling requirements. Results are expressed in terms of percentage savings in estimated carbon emissions. The footprint of salesforce.com s multitenant cloud platform 4 was assessed by collecting energy consumption data, architecture configuration and annual transaction information from the company s data center operations as of December 31, 2010 for the preceding one year period. The on-premises 5 and private cloud 6 deployments were modeled based on prior research completed by WSP, with additional input and modeling recommendations from subject matter experts including Accenture and Jonathan G. Koomey, PhD., Consulting Professor at Stanford University. On Premises: Software is purchased and provisioned on dedicated hardware by a single company. The equipment and facility is owned and operated on-site by the individual company. Private Cloud (i.e. Virtualized Data Center): Software is licensed and provisioned on a virtualized and dedicated capacity based system to a single company by an outsourced data center service provider. The equipment and facility is owned and operated off-site by a data center service provider. Salesforce.com s Cloud: Software is licensed and provisioned on a shared multitenant architecture to many companies as an internet-based software-as-a-service provider. The equipment is owned and operated by the service provider the equipment is located in private suites at a data center service provider. The critical inputs for this analysis include: Users: Number of users required by the system at any given period of time. Transactions: Measured API and Web requests processed by the platform, per day over a one year period 7. Server Count: Number of servers required to support the platform and business applications. This is inclusive of business continuity and disaster recovery. Device Utilization: Computational load that a device (server, network, or storage array) is handling relative to the specified peak load. Internet Transmission: Energy required for data transfer through access technologies and the internet backbone for salesforce.com s cloud platform and private cloud environments. Power Consumption per type of IT hardware: Calculated energy consumed by a server at a given rate of device utilization and estimated power for networking and storage equipment. Embedded Energy for IT hardware: LCA estimates of embedded energy on a per-server basis. Data Center Power Usage Effectiveness (PUE): Defined as the ratio of overall power drawn by the data center facility to the power delivered to the IT hardware. This is a location specific data center efficiency metric that accounts for energy consumption of active cooling, power conditioning, lighting, and other critical data center infrastructure 8. P.05

6 Summary of Findings 95% average estimated decrease in carbon emissions per-transaction The results of the analysis show that salesforce.com s cloud platform delivers significantly lower carbon emissions on a pertransaction and per-user basis when compared to both on-premises and private cloud deployments. On-Premise Figure 1: Comparison of estimated carbon emissions of on premise, private cloud and salesforce.com s cloud platform on a per-transaction processed basis. Private Cloud 64% average estimated decrease in carbon emissions per-transaction Salesforce.com s Cloud Platform Estimated avoided carbon emissions from using salesforce.com s cloud platform are: A salesforce.com transaction is on average 95% more carbon efficient than when processed in an equivalent on-premises deployment; A salesforce.com transaction is on average 64% more carbon efficient than when processed in an equivalent private cloud deployment; and Salesforce.com s estimated total customer carbon emissions footprint is at least 19 times smaller than an equivalent on-premises deployment, and is 3 times smaller than an equivalent private cloud deployment. The study focuses on a per-transaction metric to compare the efficiency of each deployment, which provides a greater depth of analysis of the inherent differences in platform efficiency. With an emphasis on transactions, rather than the number of users, the methodology better reflects the key indicator of efficiency for a cloud computing solution - the number of transactions that can be processed over a period of time (not only the equivalent number of users that the solution can support). This methodology also enables a more accurate comparison of salesforce..com cloud platform to a private cloud solution which is typically sized based upon both transactions required and the number of users. The carbon efficiency advantages that salesforce.com s cloud platform offers compared to on premises is significant. Dedicated infrastructure associated with on premises deployments typically operate at very low utilization levels and do not benefit from the key features of public cloud computing; multitenancy and elastic provisioning which offer scalability (both up and down) and higher utilization rates 9. While a private cloud does benefit from elastic provisioning and higher utilization rates, it is clear that multitenancy is a critical driver of carbon efficiency. As organizations continue to evaluate a potential move to the cloud, corporate IT and sustainability managers should consider these key differences across each deployment scenario which affects both business performance and environmental value. While a per-transaction metric provides a more holistic comparison of efficiency, businesses with on-premises solutions are required to size their IT Figure 2: Comparison of estimated carbon emissions of on premises by size of organization to salesforce.com s cloud platform on a per-user processed basis. infrastructure based upon number of users. When compared at this level, the analysis found that estimated carbon emission reductions by organization size range between 50% and 90%. This indicates that while deployment size does matter, the advantage that salesforce.com s cloud platform provides over a traditional on-premises solution remains significant and provides additional proof points for a comparison of carbon efficiency. On-Premises 1-99 Users Small: 90% estimated decrease in carbon emissions by using salesforce.com on a per-user basis On-Premises Users On-Premises 500+ Users Medium: 86% estimated decrease in carbon emissions by using salesforce.com on a per-user basis Large: 50% estimated decrease in carbon emissions by using salesforce.com on a per-user basis Salesforce.com s Cloud Platform P.06

7 Case Study Salesforce.com customers Nimbus and Altium realize significant carbon savings from salesforce.com s cloud platform. 86% estimated decrease in carbon emissions per-user 80% estimated decrease in carbon emissions per-user While the estimates for on premises organizations are compelling, WSP engaged with two salesforce.com customers who have transitioned their IT operations to saleforce.com s cloud platform to determine whether actual reductions in energy were achieved. Nimbus provides Business Process Management software, training and consulting services to global clients from 10 offices around the world and has been a salesforce.com customer and partner since All of the company s human resources, finance, marketing, sales, support, timesheets, audit, project and employee holiday tracking applications are now run on salesforce.com s cloud platform. Similarly, Altium, a Sydney, Australia based provider of electronic design tools, recently transitioned from an on premises infrastructure to salesforce. com s cloud platform for support of all of its CRM, purchase requisition, HR, costing / liabilities management, electronic testing, events registration and customer licensing system needs. WSP worked with both companies to quantify the environmental value of using salesforce.com s cloud platform by assessing the hardware, software and corresponding energy consumption Medium On-Premises Altium demands of the on premises system that was required to support the businesses activities as well as the added services currently provided from salesforce.com. Due to a lack of available on premises transaction data, WSP modeled the estimated savings on a per-user basis. In the case of Nimbus, by retiring their on premises equipment and fully moving to salesforce.com s cloud platform, the realized emissions reductions achieved are roughly in line with the estimates projected in the study on a per-user basis. Salesforce.com s Cloud Platform Figure 3: Comparison of estimated avoided carbon emissions for an on premises medium sized business ( users), Altium s estimated avoided emissions and salesforce.com s cloud platform footprint on a per-user basis. We used salesforce.com s cloud platform to reduce our IT carbon emissions by 95% over our previous on premises system, stated Ian Gotts, CEO, Nimbus. Our transition to salesforce.com enabled the retirement of a significant portion of our on premises IT hardware infrastructure, Alan Perkins, CIO, Altium. The result is an estimated 80% reduction in the energy and carbon footprint per user.

8 How does salesforce.com s cloud platform deliver exceptional energy and carbon efficiency? Our research uncovered that the salesforce.com multitenancy architecture is the key to substantial energy and carbon efficiency performance that it enables as compared to on premises or a private cloud. Specifically, the multitenancy design combined with salesforce.com s unique code architecture result in a remarkably low, but highly utilized, number of servers. Two additional key drivers which impact the energy and carbon efficiency include Elastic Provisioning and Data Center Efficiency (typically expressed as PUE). Multitenancy & Code Architecture Cloud computing is defined by many authorities as serving multiple customers simultaneously with a shared server infrastructure 10. Within an on-premises solution, IT managers must provision infrastructure against a homogeneous peak, whereas cloud computing providers are able to match diverse peak demands against diverse average demands by sharing its infrastructure resources across its platform. By aggregating the weakly correlated workloads of large numbers of companies 11 and leveraging the concept of diversity, cloud service providers are consistently able to realize dramatically smaller peak-to-average ratios, which greatly reduces the need for idle capacity held in reserve. Many cloud providers utilize a multitenant approach by relocating the redundancy of traditional models into a central location; using dedicated equipment specifically allocated to individual customers. When capacity is allocated in terms of installing and activating additional servers for a customer, server utilization rates are effectively lower than in the multitenant model that allocates server processing cycles not server hardware units. Further, in non-multi-layer architecture such as those modeled in the private cloud, every customer requires its own set of software and (virtual) hardware to be regularly and redundantly updated. This occurs one customer at a time and utilizes relatively large chunks of capacity, frequently resulting in over-provisioning of hardware and more energy consumption across the system. Salesforce.com s cloud platform combines the aggregation of workloads with a multitenant architecture that lets tens of thousands of organizations share what is logically a single infrastructure stack, and runs upon a shared version of software 12. Designed with the assumption of sharing built in from the bottom up, salesforce.com s stack maintains separation of customer data and tasks at the logical layer, eliminating any need for provision and management of a customer s capacity at the level of either a physical or a virtual machine. As the salesforce.com community of users grows, the platform design can efficiently manage the way in which the physical infrastructure supports each application and allows changes or upgrades including performance enhancements to be applied instantly across the board. This integrated approach results in a per-single watt of server productivity improvement (i.e. fewer watts to process the same information) that is instantly scaled across the entire infrastructure, achieving a significant multiplier effect in efficiency that reduces energy consumption, and is a feature not typically achieved in virtualized data center environments. Further, the multitenant environment enables the highly efficient use of the company s hardware assets. By serving an equivalent number of transactions, salesforce.com s cloud infrastructure uses a fraction of the quantity of servers required per customer, per application than that of a virtualized data center hosting or private cloud approach 13. P.08

9 Multitenancy & Code Architecture Continued.. As mentioned, additional efficiency potential also resides in the application code and configuration. Optimized code and configuration requires less processing, memory utilization, and data fetches that ultimately result in additional savings of physical consumption of CPU, disk, memory, and network devices. Above the code, salesforce.com customers can use a variety of different business applications, as well as offer access and portals for their customers to use. Through the use of efficient code, further supported by elastic provisioning, the platform can serve far more users with fewer servers than an equivalent on premises solution. As a result, salesforce.com s physical infrastructure can be precisely targeted, efficiently utilized and reliably assured of providing required performance (regardless of customer or user type). Figure 4: Critical features with salesforce.com s cloud platform, *number of salesforce.com customers as of February 24, 2010 Multitenant Code and Architecture Metadata Layer Optimized Processing & Storage Highly Efficient Provisioning Predictable Load Balancing Continual Analysis & Improvement Massive Economies of Scale: 92,300 Customers* Physical Layer Energyefficient Servers Microenergy Optimized Physical Layer Power Management Consumption Standardized Architecture Higher Server Utilization Fewer Servers P.09

10 Elastic Provisioning With application availability and uptime as top priorities in IT operations, infrastructure planning is typically conducted with a conservative mindset that fails to keep infrastructure capacity close to actual demand, thus reducing operational efficiency. This is particularly true for on-premises deployments where IT managers over provision hardware to absorb demand fluctuations over time, thereby reducing iterative server capacity adjustments which significantly affects utilization. Cloud providers manage capacity more diligently since over-provisioning at the cloud s operational scale is proportionally more expensive in hardware and energy costs. With growing expertise in demand modeling and more sophisticated tools to manage the number of running servers, less overprovisioning is needed to serve the same cloud user base, with server utilization rates of greater than 90% possible 14. While servers that operate at higher utilization rates consume more power, the increase, specifically related to salesforce.com s cloud platform, is more than offset by the performance gains and resulting elimination of idle servers. For example, a server running at 5% utilization can easily consume more than half of its peak power, whereas increasing the utilization rate from 5% to 20% will allow the server to process four times the previous load while energy consumption may only increase by a small percentage 15. As a result, increasing utilization rates allows the same tasks to be performed with far fewer servers. The way in which cloud services are provisioned and sold to the customer has significant impact on the IT infrastructure requirements and overall energy and carbon efficiency of a particular service. For example, the private cloud deployment modeled in this analysis was based on the Amazon Web Services (AWS) platform, where AWS sells computing capacity in units of a Virtual Machine Instance (similar in a way to how on-premises deployments need to be scaled), rather than by the service delivered or capacity used by a customer 16. This approach dramatically affects the estimated carbon efficiency of the service for a particular customer, and affects a private cloud provider s ability to dynamically manage its infrastructure and optimize resource and energy efficiency based on actual usage patterns. Salesforce.com s multitenant structure and software-as-a-service model enables a more efficient use of hardware by allowing it to predict in advance when a given customer load will be higher and then direct under-used server capacity from other hardware to process another customer s transactions. Contrast this approach to a typical private cloud where servers are reserved for one specific application within a single organization. Private cloud deployments are not able to achieve the same utilization of scale as salesforce.com, due to its pre-purposed, power-up in advance arrangement, and they typically lack the comparable quantity of multipleorganization, global customer transactions at their disposal to enable their server utilization to be as high as salesforce.com. Scaled across the entire platform of customers, salesforce.com can easily move equipment and scale up or down as required to match customer performance expectations. This ability gives it an added advantage over virtualized-only data center providers. P.10

11 Data Center Efficiency Power Usage Effectiveness Ratio (PUE) is a measure of how efficiently a data center uses its power and has a significant impact on the overall carbon footprint. Standardizing and measuring average PUE across companies can be difficult. However, the US EPA released an update 17 to its initial 2007 Report to Congress 18 that reported an average industry PUE of 1.91, with most businesses averaging While many businesses do not have the expertise or ability to manage PUE beyond current trends, nearly all of the cloud computing providers that own and operate data centers are aggressively driving down PUE to levels near the theoretical potential of 1.0. Salesforce.com s specific architecture enables the very efficient use of the hardware required to operate the platform and when combined with the use of efficient data centers enables it to achieve an average PUE for its services of While much attention is focused on what cloud computing and data center providers are doing to reduce the cooling demands associated with powering servers, another approach is to aggressively improve the efficiency of the data architecture and infrastructure required to support services. PUE will continue to be an important metric and driver of IT s carbon footprint. However, perhaps an increased focus on a metric of watts or carbon emissions per unit of useful work completed (i.e. transactions) would yield a different perspective on performance; rather than measuring the efficiency achieved in powering unnecessary or even idle servers. Other Considerations In addition to the drivers described above, the analysis considers the carbon emissions footprint associated with producing, distributing, and disposing of the required IT hardware and equipment for each scenario, with the total impact depending heavily on the type of equipment used, refresh cycles, and end-of-life practices. According to the model, this footprint represents approximately 4-13% of the total carbon footprint. This is another aspect where cloud computing realizes a lower carbon footprint by requiring significantly fewer servers to support a given user base or transaction load and over the life cycle of a server and data center, this had a considerable effect. P.11

12 Conclusion Cloud services are replacing on-premises deployments for most computing needs. As observed in this analysis, there are clear and significant energy efficiency and carbon emission reduction benefits associated with the migration of services and applications to a cloud environment. Both customers and service providers will benefit from the transition and management of data and services to large scale cloud environments. This transition will bring continual improvement in the efficiency of the key drivers that impact energy consumption and carbon emissions. Further, cloud computing does have the potential to positively impact our environment, but focusing on energy efficiency alone will not suffice. Cloud providers must also actively select and invest in renewable energy to power their data centers and influence policy making at the national and global scale. Given the increasing proportion of energy consumption and carbon emissions that data centers represent, cloud providers should be a very influential voice. The potential of cloud computing as a transforming force in IT is evident. This study concludes that cloud computing will also play a crucial role in the sustainability of IT; mitigating the environmental footprint of tomorrow s information society. But not all clouds are created equal. While this study provides further evidence of the dramatic benefits of cloud computing over traditional onpremises deployments, it begins to detail the differences in carbon emissions performance between private cloud and public cloud platforms such as those offered by salesforce.com. While both offer improvements in energy efficiency and fewer carbon emissions per-transaction processed and per-user, private clouds, or virtualized data centers, fall short in delivering upon the true potential of cloud computing. Private clouds do not enjoy the benefits of multitenancy and elastic provisioning, which, when combined with economies of scale, deliver a highly efficient physical infrastructure. As corporate IT managers and sustainability leaders consider a potential move to a cloud computing environment, a better understanding of these differences, in addition to the business performance and financial aspects is critical. P.12

13 Conclusion Continued Salesforce.com Delivering shared points of value to its customers & community. As identified through this study, cloud computing, and in particular, salesforce.com s cloud platform delivers measureable positive carbon efficiency benefits when compared to traditional on premises and even virtualized data center deployments. As identified, salesforce.com s cloud platform leverages the key design principles of a public cloud including multitenancy and elastic provisioning and is able to support its entire customer base on a very small number of servers through its efficient code design and architecture. While this results in a very low cost of operating capital and corresponding carbon emissions footprint, the true environmental benefits of this platform extend directly to salesforce.com s customers and indirectly to our broader society. Conceptually, this may be best illustrated by estimating the communitywide impact that the 92, salesforce.com customers are enabling by using its cloud platform to run their businesses (estimated by comparing the equivalent on premises footprint against salesforce.com s cloud platform footprint). When summed together, the resulting estimated avoided emissions from 2010 equate to over 170,900 tonnes of CO 2 e, which is equivalent to avoiding consumption of roughly 19.5 million gallons of gasoline 20. As the platform and community of users continues to grow, a projection through 2020 results in dramatic emissions reductions potential totaling 55 million tonnes of CO 2 e. When salesforce.com s customers cumulative carbon emissions impact are compared against an equivalent traditional on-premises deployment (i.e. had they not migrated to salesforce. com) the exponential savings becomes very compelling, and indicate the clear potential of cloud computing to broadly reduce global carbon emissions. This estimate assumes that companies either retire or re-allocate their on premises server capacity that was dedicated to the services now being provided by salesforce.com. Such significant savings will be possible for an increasing breadth of business applications as more companies embrace the benefits and opportunities afforded by cloud-based Software, Platform and Infrastructure-as-a-Service offerings, such as those currently offered by salesforce.com. As public clouds, they allow any corporate IT department or independent software vendor (ISV) to develop cloud-based applications and run them exclusively on highly efficient infrastructure, resulting in the entire IT ecosystem contributing to the potential for carbon emissions reductions. Alternative architectures to large-scale public clouds, such as virtualized data centers and private clouds, community clouds, and hybrid architectures are all expected to yield efficiency gains, though at a smaller scale. 25 Annual Footprint - tonnes of CO2e (millions) Figure 5: Estimated carbon emissions from salesforce.com s cloud platform and traditional on-premises deployment based upon salesforce.com subscribers (1999 through 2020) On Premises - tonnes of C02e footprint Salesforce.com - tonnes of C02e footprint P.13

14 Footnotes 1 Global e-sustainability Initiative (GeSI). SMART 2020: Enabling the Low Carbon Economy in the Information Age Cloud Computing and Sustainability: The Environmental Benefits of Moving to the Cloud. Accenture & WSP. November Global e-sustainability Initiative (GeSI). An Assessment Methodology Salesforce.com s cloud platform: salesforce.com provided a complete Bill of Materials for the complete IT hardware used for production, programming, and business continuity/ disaster recover. The maximum power draw for each device was derived from online manufacture s specification sheet. The actual power draw of devices while in-use was calculated based on manufacture s configuration tools and verified with observed utilization. Production and programming servers are presumed to be utilized, while disaster recovery servers are idle on a 1-to-1 basis. The estimated number of users and measured daily transactions were provided by salesforce.com. 5 On-premises Approach: An estimate of the number of servers that salesforce.com s customers would need to support an equivalent platform if they were running on-premise was derived from a 2010 study commissioned by salesforce.com and performed by Nucleus Research Inc., then augmented with additional research and subject matter expert validation from Accenture and Jonathan Koomey. Twenty-five salesforce.com customers were surveyed resulting in a baseline estimate for the ratio of total users to on-premise servers for small, medium, and large customers, including disaster recovery on a 1-to-1 basis. Server configurations were sized from the HP and Dell Solution Advisor tool based on organization size requirements. 6 Private Cloud Approach: Deployment scenarios for each user group were based on Amazon Web Services EC2 instances required to run a standard Oracle Siebel v8 build. These estimates were calculated using HP s August 2008 benchmark report. The baseline was translated into AWS instance types and quantities needed to handle the three user-loads running Siebel Web, application, and database instances. A virtualized environment with dynamic load management was assumed, with production and programming servers presumed to be utilized, while redundant disaster recovery servers are idle assumed to be 3% of active servers. 7 Given the diversity and complexity in types of transactions, but lack of a standardized methodology to separate each type of transaction, WSP considered all transactions to require the same amount of energy load upon the IT hardware to process. 8 The Green Grid. Green Grid Data Center Power Efficiency Metrics: PUE and DCiE Silicon Valley Leadership Group. Case Study: Modeling and Managing Server Power at Sun Microsystems Multitenancy refers to a principle in software architecture where a single instance of the software runs on a server, serving multiple client organizations (tenants). 11 Law of Larger Numbers. Jakob Bernoulli. ISBN Power-related advantages of cloud computing. Jonathan G. Koomey, Uptime Institute The small foot print of a large cloud - the data center strategy of salesforce.com. Datacenter Dynamics. September The Future of the Data Center; Yankee Group. January The Green Grid. Five Ways to Reduce Data Center Server Power Consumption Performance and Scalability Benchmark: Siebel CRM Release 8.0 Industry Applications in HP BL460c Servers running Oracle Enterprise Linux 4.5 and Oracle 10gR2 DB on HP RX6600. An Oracle White Paper. August US Environmental Protection Agency (EPA). ENERGY STAR Data Center Infrastructure Rating Development Update US Environmental Protection Agency (EPA). Report to Congress on Server and Data Center Energy Efficiency Number of salesforce.com customers as of February 24, According to the US EPA Greenhouse Gas Equivalencies Calculator. P.14

15 Appendix Model Overview The comparative study quantifies the greenhouse gas (carbon emissions) impacts from salesforce.com s cloud platform, and the estimated equivalent services provided by applications hosted on premises and in a virtualized data center environment. The functional unit of this study a transaction associated with the services provided by salesforce.com, including Sales Cloud, Service Cloud, Chatter, Jigsaw, Force.com Platform, Heroku and Database.com, which are internet-based CRM solutions delivered as software-as-a-service (SaaS) and platform-as-a-service (PaaS). The carbon footprint per transaction is derived by dividing the total system energy consumption by the number of active users and transactions for a given scenario and over a period of one year. A custom model was independently developed for this analysis based on elements of the ISO guidelines for Life Cycle Assessment, BSI PAS 2050 Specifications for the Assessment of Greenhouse gas (GHG) Emissions of Goods and Services, and the WRI/ WBCSD GHG Protocol, and the 2010 GeSi ICT Enablement Tool. Data Geographic: This analysis encompasses continuous services provided to global customers on a follow the sun basis ; 24 hours, 7 days a week, 365 days per year. Temporal: Time period considered: January 1st through December 31st Network run time assumes 8,760 hours per year. Primary data was provided by salesforce.com and its third party data center hosting services. Secondary data regarding virtualized data center (i.e. private cloud) assumptions was provided by Accenture. Secondary data for Materials was derived from the Eco-Invent database and other publicly available databases collated in SimaPro. Secondary server consumption data was derived from industry averages based on Koomey, J. G. Estimating Total Power Consumption by Servers in the U.S. and the World February 15, 2007 and the GreenGrid. GHG emissions included are stated as carbon dioxide equivalent (CO 2 eq) emissions and take into account the 6 primary GHG gases including, CO 2 (carbon dioxide), SF6 (sulphur hexafluoride), CH 4 (methane), N 2 O (nitrous oxide), HFCs (hydrofluorocarbons), PFCs (perfluorocarbons) The study includes the use phase of the product by the customer. While use is assumed to be the same rate (i.e. number of transactions), the efficiency and energy consumption associated with the scenarios is different. Materials Primary materials included in the study consist of servers and related network equipment (various sizes of servers, arrays, routers, and switches) used to host databases and applications, fulfill API requests, and process web transactions. Embedded emissions from physical hardware were estimated based on the weight and composition of each component which was derived from manufacture specification sheets. Emissions related to the material manufacture, assembly and recovery of servers and networking equipment are based on a 3 year amortization rate for data center hardware. Information on the Life Cycle Inventory of servers were also derived from the following papers: Weber C. Uncertainty and Variability in Carbon Footprinting for Electronic: Case Study of an IBM Rack-mount Server. Carnegie Mellon University. December Process Energy for IT Infrastructure Appropriate carbon emissions factors were applied to the energy consumption of specific data center locations from the U.S.EPA s egrid2007 Version 1.1, January For on-premise and private cloud assumptions, EPA egrid US average emission factors were used unless otherwise noted. Emission factors for data center electricity consumption in international locations was derived from IEA data sets: CO2 Emissions from Fuel Combustion (2009 Edition), IEA, Paris, International Electricity Emission Factors by Country, xls, and International Energy Agency, as cited by EIA for 1605b. Power consumption of salesforce.com servers was based on actual direct measurement of salesforce specific racks provided by third party hosting services. Datacenter specific PUE was also provided by these vendors. A storage consumption and network usage efficiency ratio were also applied based upon primary data provided by salesforce.com, and referenced from secondary data from the EPA, Green Grid and research by Jonathan Koomey, PhD. Research from the National Laboratory for Applied Network Research (NLANR) Project informed the path of data transfer (from a data center to a business customer). End of Life (EOL) Processes End of Life calculations include the emissions associated with decommissioning and recycling IT equipment amortized over the 3 years. Conservative assumption of 20% recycling and recovery for servers and network equipment was used. Model Exclusions Energy consumed during software development. Tertiary suppliers and process materials which are not significant (i.e. do not constitute an input to 95% of the product or process). Refrigerants (except where used in primary production of raw inputs). Embedded energy of capital equipment, transportation vehicles, buildings and their energy use not directly related to servers and associated equipment. Maintenance of capital equipment. Refrigerants (except where used in the primary production of raw inputs). P.15

16 About Salesforce.com Salesforce.com is the enterprise cloud computing company. Based on salesforce.com s real-time, multitenant architecture, the company s platform and CRM applications have revolutionized the way companies collaborate and communicate with their customers. Salesforce.com offers the fastest path to customer success with cloud computing. As of February 24, 2011, salesforce.com manages customer information for approximately 92,300 customers including Allianz Commercial, Dell, Japan Post, Kaiser Permanente, KONE, and SunTrust Banks. Its home page is About WSP Environment & Energy WSP Environment & Energy is one of the world s leading global consultancies, delivering solutions to environmental, energy, and sustainability issues. With over 1,000 people across 65 offices globally, WSP Environment and Energy offers a full-service consulting practice to a range of commercial and industrial clients, many of whom are Fortune 500 and FTSE 250 companies. WSP helps its clients increase business performance through process improvement, risk mitigation, and design and implementation of sustainable business practices. WSP Environment & Energy is part of WSP Group plc. Its home page is WSP authors and key contributors: Josh Whitney, Jon Taylor, Chris Kral This document makes reference to trademarks that may be owned by others. The use of such trademarks herein is not an assertion of ownership of such trademarks by WSP and is not intended to represent or imply the existence of an association between WSP and the lawful owners of such trademarks. Copyright 2011 WSP Environment & Energy. Acknowledgements The authors would like to thank Sue Amar and George Hu of salesforce.com for sponsoring this study, as well as Tom McAvoy from Accenture and Jonathan Koomey, Ph.D., Consulting Professor at Stanford University for their input, review and comments on the methodology and model.