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Cloud Slam Co D Presentation

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Confronting the Data Center Crisis: A Cost - Benefit Analysis of the IBM Computing on Demand (CoD) Cloud Offering

Reducing TCO and Enabling New Capability, Faster Time to Results,
and New Business Models

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Cloud Slam Co D Presentation

  1. 1. 1 Confronting the Data Center Crisis: A Cost - Benefit Analysis of the IBM Computing on Demand (CoD) Cloud Offering Reducing TCO and Enabling New Capability, Faster Time to Results, and New Business Models April, 2009 Dr. Srini Chari chari@cabotpartners.com Phone: 203 205 0705 Cabot http://www.cabotpartners.com Prepared for Cloud Slam 09 Partners Sponsored in part by IBM
  2. 2. 2 Outline Cloud computing for commercial enterprises Data center challenges and solutions Workload classification-making the case for cloud computing IBM Computing on Demand (CoD) cloud offering A cost-benefit framework for IBM CoD using the Uptime Institute model for TCO Customer examples highlighting business value Copyright © 2009 Cabot Partners Group, Inc.
  3. 3. 3 IT Clouds vs. Airline Transportation – Transport IT to the Cloud! Unlike typical analogies of cloud computing to commodity electric utilities, IT clouds are more analogous to the airline transportation industry with a range of business models. IT Industry Transportation Cost Model Business Impact In-House Own planes CapEx, OpEx, Total control and Data Center long term responsible for or Private entire infrastructure Cloud (not- including service outsourced) levels Private Cloud Lease planes and CapEx and Control of (outsourced) service OpEx in infrastructure but medium term not fully responsible lease for service levels Public Cloud Commercial Pay as you use, Almost no control of airlines very short infrastructure or term/trip/user service levels Hybrid Charter planes Pay for duration, Some control of short to medium infrastructure and term/trip depend on provider for service levels for duration Copyright © 2009 Cabot Partners Group, Inc.
  4. 4. 4 Data center challenges  Escalating energy costs – about 11% annually while new server spend expected to be flat1  Industry is defining new metrics for energy efficiency2  Data centers account for about 25% of enterprise IT budgets and is growing at 20% annually3  Investment required to build a large-enterprise data center has risen to $500M, from $150M, over the past 5 years and larger data centers take 2 years or more to design and build and are expected to last for 12 years3  Server utilization typically tops off at 5%-15% and results in wasted energy and unemployed capital3  Difficult to forecast whether a 50% increase in demand would require 25% or 100% more server and data center capacity3 1. Jed Scaramella, “Worldwide Server Power and Cooling Expense 2006-2010 Forecast”, September 2006. 2. John R. Stanley, Kenneth Brill, and Jonathan Koomey, “Four Metrics Define Data Center “Greenness””, White Paper, Uptime Institute. 3. McKinsey on Business Technology, Innovations in IT Management, Number 14, Winter 2008. Copyright © 2009 Cabot Partners Group, Inc.
  5. 5. 5 Data center solution approaches  McKinsey3 suggests a centralized governance model with the CIO empowered by the CEO to manage data centers by:  managing IT assets aggressively through virtualization,  providing incentives to IT personnel to improve forecasting and minimize deviations from real demand,  treating data center resources as scarce resources and ensuring that business units implement a total cost of ownership (TCO) model for new systems and applications,  implementing new metrics for data center efficiencies that account for energy, utilization, and floor space.  What’s also needed is a comprehensive approach especially for emerging web and analytic workloads that includes  energy-efficient and computationally dense systems,  software for better systems and power management and utilization, and  flexible delivery models such as cloud computing that adapt easily to computing demands. 3. McKinsey on Business Technology, Innovations in IT Management, Number 14, Winter 2008. Copyright © 2009 Cabot Partners Group, Inc.
  6. 6. 6 Some specific IT solutions from IBM  Energy efficient systems and next generation data centers that reduce TCO4, 5  Improve asset utilization through  virtualization  workload management  consolidation  Significant recent IBM cloud computing6 and dynamic infrastructure7 announcements that include a comprehensive roadmap of  systems  software  services 4. Srini Chari, “IBM System x iDataPlex: The Newest Economical Workhorse in the Computing Cloud for Next Generation HPC Data Centers”, Cabot Partners White Paper, April, 2008, ftp://ftp.software.ibm.com/common/ssi/sa/wh/n/xsw03016usen/XSW03016USEN.PDF 5. Srini Chari, “A Total Cost of Ownership Study (TCO) Comparing the IBM Blue Gene/P with Other Cluster Systems for High Performance Computing”, Cabot Partners White Paper, November 2008, http://www-03.ibm.com/systems/resources/tcopaper_finalfinal_2008.pdf 6. IBM Cloud Computing, http://www.ibm.com/ibm/cloud/ 7. IBM Prepares to Take on 21st Century Infrastructure, http://www.networkworld.com/news/2009/020909-ibm-dynamic-infrastructure.html Copyright © 2009 Cabot Partners Group, Inc.
  7. 7. 7 High level IT workload classification by application Private Hybrid Public - Free Web Search Web 2.0 and Web Transactional Analytics Web Applications Public – Pay HPC Workload Variability VW for Use Virtualization Could Help Business Intelligence/Analytics Workload Schedulers Could Help Traditional Transaction IT workload Processing and ERP size Bubble dimension indicative of aggregate IT workload size Compute Intensive/Job measured in MIPS or FLOPS Trends indicated by the arrow are qualitative based on several recent public announcements on cloud computing and other industry research on workload characteristics Copyright © 2009 Cabot Partners Group, Inc.
  8. 8. 8 Typical low variability workload graph – common in enterprise business applications Peak Capacity Aggregate Workload In House Capacity Average Utilization W(t) Time •Shaded area represents under provisioning of IT resources that could lead to dissatisfied users and adverse business impacts •In house capacity designed for peak results in some over provisioning and wasted resources Copyright © 2009 Cabot Partners Group, Inc.
  9. 9. 9 Pulsed (high variability) workload graph – common in departmental or SMB HPC Peak Capacity Aggregate Workload In House Capacity Average Utilization W(t) Time •Shaded area represents under provisioning of IT resources that could lead to dissatisfied users and adverse business impacts • In house capacity designed for peak results in excessive over provisioning and wasted resources Copyright © 2009 Cabot Partners Group, Inc.
  10. 10. 10 Many pulsed (medium variability) workload graph – common in large enterprise HPC Peak Capacity Aggregate Workload In House Capacity Average Utilization W(t) Time •Shaded area represents under provisioning of IT resources that could lead to dissatisfied users and adverse business impacts • In house capacity designed for peak results in some excessive over provisioning and wasted resources but average utilization improves compared with the single pulse case Copyright © 2009 Cabot Partners Group, Inc.
  11. 11. 11 IBM Computing on Demand (CoD) – Infrastructure as a Service (IaaS)* Computing on Demand Base Access  One year annual membership  Server management node  Virtual Private Network (VPN) access  Client scheduling GUI  Variable / Dynamic Computing on Demand Capacity Models – Reserve by the week/hour  Dedicated – “Pay for use” – Dedicated resources: 1-3 year – Utilize CoD Cloud commitment infrastructure – Custom Environment – choice of data – Highly-secure, virtual center, servers, storage, dedicated clusters dedicated to one client at a time switch, WAN/LAN high availability network, add-on services – Automated network and – Leased by IBM Global Financing server provisioning (Click to Enlarge in Screen Show) CoD Cloud Centers  Tokyo  New York (POK) – 200 CPU’s (System x) – 7,000 CPU’s (System x, System p)  Future locations based on  London customer need – 7,800 CPU’s (System x); dedicated only * Obtained from IBM Copyright © 2009 Cabot Partners Group, Inc.
  12. 12. 12 IBM Computing on Demand – IaaS/PaaS* CoD – Platform as a Service Customer Cloud Services IBM Cloud Services [GTS/SWG] Partner Cloud Services Developer Cloud SaaS with CoD Partners High Performance Cloud Business Client Test Cloud ( eg: Exa, Ingrain Rocks, … ) Test Drive Cloud (Dedicated, Variable, Desktop Cloud BCRS / IPS [GTS] Cloud Broker – Resellers More to come…. Dynamic, …) LotusLive™ Cloud ( eg: Nimbis, GridCore, … ) CoD - Infrastructure as a Service [STG] Operational Services Interfaces Platform Products Business Services Add On Services System x™ Aspera Hi Speed File Transfer Order Management VPN Network Connectivity Data Center Locations * Reporting BladeCenter® Data Center Security,HA 3D Visualization (DCV) Custom Internet access portal Contracts Online System p™ Storage Virtualization (GPFS) Provisioning, Monitoring Client Scheduling GUI Account Management System Storage™ Infrastructure Management SLA Management * * Centers operating in London, Tokyo, New York. Additional Centers under consideration in US, Europe and Asia * Obtained from IBM Copyright © 2009 Cabot Partners Group, Inc.
  13. 13. 13 Cost – Benefit framework for IBM CoD Through IBM client interviews across several industries and other industry and workload analyses, the benefits and costs are examined.  Benefits  Business Value: e.g. customer revenues, new business models, compliance regulations, better products, increased business insight, and new breakthrough capability,  Operational Value: e.g. faster time to results, more accurate analyses, more users supported, improved user productivity, better capacity planning,  IT Value: e.g. improved system utilization, manageability, administration, and provisioning, scalability, reduced downtime, access to robust proven technology and expertise.  Costs  Data Center Capital Purchases Avoided e.g. new servers, storage, networks, power distribution units, chillers, etc.  Data Center Facilities Not Built e.g. land, buildings, containers, etc.  Operational Costs: e.g. labor, energy, maintenance, software license, etc.  Other Costs: e.g. deployment and training, downtime, bandwidth, etc. Copyright © 2009 Cabot Partners Group, Inc.
  14. 14. 14 Ideal flat HPC large enterprise workload Peak Capacity = T In-House Capacity W(t) Aggregate Workload Time •Ideal Flat HPC Workload Occurs When Many Equal Intensity Pulses Coalesce with Perfect Sequencing and Scheduling of the Workload. Illustrates an Ideal Large Enterprise HPC Case. • In house capacity = Peak Capacity and Utilization is Maximized Copyright © 2009 Cabot Partners Group, Inc.
  15. 15. 15 TCO Analysis for IBM-CoD Dedicated vs. In-House8, 9 Dual Core x86 Cluster System with 840 CPUs (cores) and 1TB of Storage. 3 2.68 30% 2.5 30% TCO Annual Cost ($M) TCO 1.87 IBM CoD 2 Savings Savings Other OpEx 1.5 Site IT CapEx 1 Energy 0.5 0 In-House IBM CoD ($.25/CPU Hr.) 8. Jonathan Koomey, “A Simple Model for Determining True Total Cost of Ownership for Data Centers”, White Paper, The Uptime Institute, 2007. 9. TCO model adapted by Cabot Partners Copyright © 2009 Cabot Partners Group, Inc.
  16. 16. 16 Single Short Pulsed Workload Graph Peak Capacity = T In-House Capacity Aggregate Workload TP Time •Flat Pulsed HPC Workload Occurs When One Large Intensity Workload is Scheduled and Perfectly Balanced •In house capacity = Peak Capacity and Utilization is Approximately TP / T, where TP is the Duration of the Pulse Copyright © 2009 Cabot Partners Group, Inc.
  17. 17. 17 TCO analysis for IBM-CoD Variable or Dynamic vs. In-House Dual Core x86 Cluster System with 840 CPUs (cores) and 1TB of Storage. 69% TCO 69% TCO 3 Savings with 2.68 Savings with Dynamic CoD 61% TCO 2.5 Dynamic CoD 61% TCO Savings with Annual Cost ($M) Savings with IBM CoD 2 Variable CoD Variable CoD Other OpEx 1.5 Site IT CapEx 1.0 1 Energy .84 5 0.5 0 In-House IBM CoD - Variable IBM CoD - Dynamic  CoD-Variable assumes 1 week commitment and used 12 times a year ($.6/CPU Hour assumed)  CoD-Dynamic assumes 10 hour/day for 5 days commitment and used 24 times a year ($.8/CPU Hour assumed) Copyright © 2009 Cabot Partners Group, Inc.
  18. 18. 18 Customer cases highlighting business benefits- Summary  Top international wealth management savings company – New Capability  Major New York based financial conglomerate - Faster Time to Results  Ingrain Rocks-Solution provider for Petroleum E&P - New Business Model Copyright © 2009 Cabot Partners Group, Inc.
  19. 19. 19 Customer cases highlighting business benefits: Top international wealth management savings company – New Capability  Challenge: immediate solution for spike in 5 times the risk analysis resulting from new European MCEV regulations  Applications Used: actuarial software for risk analysis for regulatory compliance, new products, pricing, valuation, etc.  Alternatives Investigated:  Upgrading/adding existing servers in their in-house compute grid. Entailed expensive capital acquisition. Physical space was also a limiting factor.  Using the services and infrastructure provided by the ISV. The ISV’s HPC infrastructure was not robust and scalable to address the extreme computing needs for the added statistical analyses.  A “container” type solution was also evaluated. No available land in the vicinity to deploy a container solution.  Why IBM CoD was Chosen:  provided flexible and variable access to over 100 IBM System x servers for 3 weeks in a month.  pricing and terms were attractive and VPN access options made this environment secure, stable, and isolated from the existing compute grid.  additional savings of about 1PY were possible as IBM provided the support and service necessary to maintain this compute capacity.  IBM was able to collaboratively solve minor migration issues with application deployment on an IBM Windows HPC cluster at the CoD center.  Ongoing IBM CoD Value:  the CoD solution with variable pricing terms has been consistently used over the last 6 months with over 75% utilization  made feasible a previously “intractable” problem as alternative approaches did not satisfy the immediate business need  implemented an IBM CoD solution in one subsidiary in the United States. They’re now able to get 5-7 times more work done in the same timeframe or the same amount of work done 5 times faster.  It is expected that this solution would also be considered in the corporate parent organization in Europe and at other subsidiaries worldwide.  access to almost “infinite” resources and the pricing elasticity offered by IBM CoD make this solution well poised for future growth needs. Copyright © 2009 Cabot Partners Group, Inc.
  20. 20. Customer case highlighting business benefits: Major New York based 20 financial conglomerate - Faster Time to Results Challenges:  The internal IT group supports a wide range of internal clients and has to adhere to very stringent service level  expectations for risk analysis. End-users demand simple, reliable, timely, secure, and “transparent” IT services.  End-of-day analyses must be turned around in 10 hours or less.  The current financial crisis, increased regulations, and market volatility have spiked the demand for more  complex stochastic risk analyses. Applications Used: MG-ALFA from Milliman, Inc. on DataSynapse  Alternatives Investigated:  Adding more servers in the compute grid. This IT capital expansion was expensive and would be grossly  under-utilized when time critical risk analyses workload was not running. Why IBM CoD was Chosen:  Provided a flexible and dynamic access to between 200 and 350 CPUs.  There have been 4-5 times in the last year that an urgent increase in capacity of up to 500 CPUs was needed.  IBM was able to respond in a matter of hours to these business critical requests. In every case, IBM exceeded this firm’s expectations. Ongoing IBM CoD Value:  The solution has been consistently used for time critical analyses over the last 2-3 years often with 75%-100%  utilization. The firm expects increased scale and capacity use of CoD over the near future and is very pleased with IBM’s  exceptional service and support, rapid response to urgent requests, and deep expertise in HPC and grid computing. IBM’s deep relationships and expertise with software partners – Milliman and DataSynapse- were also  invaluable. Copyright © 2009 Cabot Partners Group, Inc.
  21. 21. 21 Customer case highlighting business benefits:Ingrain Rocks-Solution provider for Petroleum E&P - New Business Model Challenges:  In 12-18 months, Ingrain desires to reduce end-to-end cycle time from months to days or less.  A key computational step is expected to become more critical as client-delivery time shrinks.  Ingrain’s business model is to avoid investing in IT in-house but they need global access to secure, flexible,  and “infinite” computing resources and must ensure that IT costs track client workload. Needed a stable and trusted partner for the long haul.  Applications Used:  Proprietary high resolution imaging algorithms to compute physical properties of reservoir rocks and also  compute multiphase flow at the pore scale. Parallel applications scale well into the 100s of processing nodes.  Alternatives Investigated:  Currently has cluster access through a local service to develop their applications. However, this model is  inadequate for anticipated future growth needs. Examined other service providers but none could meet their needs of access to a range of equipment,  configurations, capacity, price points, and global capability. Flexibility in machine configurations, allows Ingrain to optimize their application workload and tune the underlying algorithms. Why IBM CoD was Chosen: IBM was the only provider that was global and satisfied all of Ingrain’s needs by  providing access to a range of systems, flexible configurations, almost “infinite” capacity, and attractive price points. Mr. Stewart, CFO of Ingrain says “The IBM CoD solution is an absolute business necessity for Ingrain. It is a must have solution. IBM has provided outstanding service and support to help Ingrain migrate and optimize their applications on the CoD clusters. Ingrain has completed testing and quality assurance of their application in a very short time. Ingrain has observed a 15%-20% improvement in performance and can now scale the workload to much larger configurations”. Ongoing IBM CoD Value: Ingrain plans to continue to use this CoD solution for all their future client engagements  and expect their use of the CoD solution to grow in the future. This will allow them to tackle more challenging projects. In 12-18 months, Ingrain expects to have a very efficient end-to-end process that will enable them to deliver results to their clients in days or hours instead of a couple of months. Copyright © 2009 Cabot Partners Group, Inc.
  22. 22. 22 Cost-Benefit Analysis of IBM CoD - Summary  For a sample configuration using IBM CoD, TCO savings ranged from 30% to 69%  Top international wealth management savings company – New Capability  Major New York based financial conglomerate - Faster Time to Results  Ingrain Rocks-Solution provider for Petroleum E&P - New Business Model Copyright © 2009 Cabot Partners Group, Inc.
  23. 23. 23 More Information To learn more about the IBM Computing on Demand (CoD) solution, contact your IBM representative or visit http://ibm.com/deepcomputing/cod. To test drive IBM Computing on Demand, please visit http://ibm.com/systems/deepcomputing/cod/testdrive.html. To learn more about IBM Cloud Computing Solutions, please visit http://ibm.com/cloud. To learn more about IBM solutions for High Performance Computing, please visit http://ibm.com/deepcomputing. Copyright ® 2009. Cabot Partners Group. Inc. All rights reserved. Other companies’ product names or trademarks or service marks are used herein for identification only and belong to their respective owners. All data used in this study were obtained from public sources or from IBM. Cabot Partners does not guarantee the accuracy or currency of this information and the subsequent analyses. Changing market conditions and other factors could alter the conclusions of this study. An objective analysis is required and strongly encouraged for specific and custom deployments. Copyright © 2009 Cabot Partners Group, Inc.
  24. 24. 24 Questions? Copyright © 2009 Cabot Partners Group, Inc.

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