Ensuring Application Performance via Solutions Architecture & Capacity Modeling

1. Transform – Transform Business Service Delivery with Service Assurance (SA) Alex Syed, Justin Sebastian Bank of America CC033SN Ensuring Application Performance via Solutions Architecture & Capacity Modeling

2. Agenda • Business Trends & Technology • Performance at the Speed of Business • “Load Test” vs. Engineering • Performance Engineering Framework • Architecture & Performance • Performance Budget • Volume Model example • Profiling example • Large project example • Modeling (CA Capacity Management) Examples • Hardware Comparison – Capacity Manager • Volume Forecast – Optimizer • Greenfield Simulation – Capacity Manager 3

3. Growth through Acquisition Customers … … … … … … … … Customer Segment Focus Product/Channel Focus Geographic Focus Acquisition 4

4. Technology continues to evolve at a rapid pace Consumers are becoming more comfortable with technology, particularly mobile technology, and it is changing the way business is conducted across industries And we will only see the pace of innovation speed up 5 Source: Bill Nuti – Chairman & CEO NCR

5. Changing Consumer Behaviors: Consumers are spending more time online and are increasingly focused on social networking and user generated content Always Addressable Customer Socially Networked Digital Omnivore Digital Native Did you know? Online ratings and reviews topped the list of what was most influential to shoppers. Did you know? Become relevant Give them assurance Preference Presence Personalization By 2013,2 billion mobile subscriberswill have used mobile phones for contactless mobile payments, mobile banking or over-the-air person-to-person payments. Give them back their time Did you know? 83% of consumers are more likely to choose one retailer over another if they make it easier to personalize and control where, when and how they interact. Did you know? 70% of consumers don’t have enough time. 50% said they actually have more money than time. 6 Source: Bill Nuti – Chairman & CEO NCR

6. Out with the old & in the with the new? – how about both Channel Preferences are Expanding But The Branch is Still Important User satisfaction 50 Online 40 30 ATM Frequency of use Mobile (SMS or app) Automated phone system 20 In Person Online chat 10 Email Phone with a person Market Penetration, Frequency of Use, and Satisfaction Levels of Each Channel 10% 20% 30% 40% 50% 60% 70% 80% Penetration* *Penetration refers to the percentage of adults who have used each channel Frequency of use is the average number of times a user communicated through each channel in the past year 7 Source: How US Banking Customers Use Different Channels: Forrester Jul 2010

7. Changing Institutional Focus Past Present Future Technology has redefined banking convenience and access Consumers primarily focused on convenient access to branch and online banking. In addition to expecting a ubiquitous branch network and 24/7 online banking, consumers are interested in mobile applications and personal financial management services. Consumers will demand additional services like peer-to-peer instant technologies and ‘always-on’ access that allows banks to be present wherever they are. Ubiquitous Branch Network Mobile Applications Peer-to-Peer Payments • Extremely likely, Very likely Online Banking Personal Financial Management Services ‘Always On’ Access 8

8. Future of Banking: Transactional to Transformational 1992 “Mobile” Branch “Online” Branch A “ATM” Branch Micro Branch Express Branch Iconic Branch B A great experience creates a great relationship 9 Source: Bill Nuti – Chairman & CEO NCR

9. Technology Imperative • Technology must adapt to changes in customer expectations • Always there, always on, always with me • More interactive • More self-service • Rapid innovation • Differentiated Service • Non-traditional competitors are advancing • Major Themes • Faster speed to market, lower cost to build and operate • Protect the core – change the edge • More automation, less hand-offs • Operating cost should not be a barrier to a richer customer experience • No sacrifice to the security, privacy and integrity that our customers expect 10

10. Agenda • Business Trends & Technology • Performance at the Speed of Business • “Load Test” vs. Engineering • Performance Engineering Framework • Architecture & Performance • Performance Budget • Volume Model example • Profiling example • Large project example • Modeling (CA Capacity Management) Examples • Hardware Comparison – Capacity Manager • Volume Forecast – Optimizer • Greenfield Simulation – Capacity Manager 11

11. What makes high performers, high performers? 12

12. Evolving Toward Performance-Driven Development Adds Quality, Reduces Costs Most organizations spend time performing these activities Source: IDC, 2006 13

13. Performance Framework Coverage with Key Disciplines Define Measure Analyze Improve Control Tech Design Review Code Review Performance Test Non-Functional Requirements Production Feedback Plan Analyze Design Build Test Deploy Application Volume Models Unit Design Review Unit Level Tuning Performance Budgets Application Profiling Monitoring Strategy Individual Services Partner Domains Development System and Workload Models Early Design Models Performance Prototyping Architecture Perf Eng Prod Support Capacity Planning Enterprise Modeling / Simulation Production Feedback Definition Improvement Verification • Environment Diagrams • Recommendations (Code Design) • Toolset Recommendation • Key Monitor Metric List • End to End Volume Matrix • Development and Architecture Performance Targets • Analysis of production performance data to create a feedback loop on both testing and requirements • Optimized Code Units • Infrastructure Capacity and Performance Assessment • Application Performance Validation • Confirmation delivered code is as designed • Prototyping Results • Application performance assessment • Verification decisions will perform as designed High Level Deliverables Enterprise • Holistic understanding of enterprise performance of both application and infrastructure 14

14. Journey of the Performance Architecture team • From 2006 through 2010 the Performance team experienced unprecedented growth expanding from the core 4 applications to over 140 at the close of 2010. • 2011 launched the Performance Engineering Pilot - High Profile Engagements across key Transition & critical to success initiatives (large conversion & key front end application) • 2012 alignment within Architecture – moving to the beginning of the SDLC. Number of applications & initiatives grew exponentially by the end of the last year • 2013 portends both an increase in the number of applications but also full maturation of capability and enterprise wide processes Shift from Expansion to Quality Quality of Service 2011- 2013 1Studies indicate 5-6x Cost Benefits from Early Lifecycle Performance Approach 2006 - 2008 2009- 2010 Pre-TCOE Application Expansion 4 140 Current State 1Performance-Driven Software Development: How IT Shops Can More Efficiently Meet Performance Requirements, by Carey Schwaber with Christopher Mines and Lindsey Hogan, February 28, 2006 15

15. Performance Budgets Project Description • Rollout of a new “Offers” capability via an online banking. Not only understand the end to end transaction timings but also the potential impact to the online channel. • What we delivered • Clear Requirements via creation of Performance Budgets • 26 use case with defined budgets • Used to establish testing targets for development & testing teams • Iterative feedback loop from production to update the budgets as capability rolls out. 16

16. Volume Model Project Description • Requested to create volume models for new Transfer Funds capability What we delivered • Document the flows (Online and Batch) • Derive / Characterize workload • Assemble volume model Online Batch Core App 17

17. Profiling - Application Efficiency - Overtime ~$10MM in Hard Dollar savings over 12 month period Project Description • Tune the application – using CPU as a key symptom….bring down the hardware cost curve What we delivered • Profiling of code using Compuware DynaTrace • Collaboration with prod support, development, performance test and architects • Additional capabilities to prod w/o additional hardware • Opened the door to including profiling as a core capability as part of software development 18

18. Large project – Establishing a brand new channel Partial List of Applications Project Description • Scope performance changes across all impacted applications and platforms What we delivered • Determine the level of risk posed by each application and associated changes • Alignment of services (from the Perf Framework) relative to the risk • Close to 50 performance defects logged before “volume” test started • Successful deployment and rollout 19

19. Agenda • Business Trends & Technology • Performance at the Speed of Business • “Load Test” vs. Engineering • Performance Engineering Framework • Architecture & Performance • Performance Budget • Volume Model example • Profiling example • Large project example • Modeling (CA Capacity Management) Examples • Hardware Comparison – Capacity Manager • Volume Forecast – Optimizer • Greenfield Simulation – Capacity Manager 20

20. P vs. X – Hardware Comparison (Capacity Manager) Project Description • What are the benefits and impacts from migrating current App X servers from AIX based IBM System P to the Linux based IBM System X? What we delivered • The Performance Architecture team conducted “what-if” analysis, to simulate a migration from the current IBM P Series to the IBM X Series. • The models address each server in isolation, considering only the effect of changed Total Processing Power on an individual server’s workload. System X resulted in significantcapacity gains Largest gains are on the web tiers New IBM P7 Series out performed the X Series for overall system capacity 21

21. Volume Impact forecast (Optimizer) Project Description • Scale workload volumes on a target back office application to reflect 4x increase and project to breaking point. Validate that a single site of a Hot/Hot architecture can support 100% of production volumes. What we delivered • Captured peak hour system and business volume metrics from a peak day • Created two distinct models to reflect the Consolidation Servers and Downstream workloads – peaks are different • Validated simulated workloads against a production baseline. • Stressed model to breaking point to note deficiencies. 22

22. Greenfield simulation (Capacity Manager) Project Description • Expand image retrieval support & conversion while maintaining business SLA’s . Help decide which application call flow would be the most optimum. What we delivered • Two evaluations based on different call flows. • Requirements based solely on High Level Design documentation – no test/production data available or used. • For each option, model system utilization, end to end retrieval times, peak hour performance capability, maximum file size capability etc. 23

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