1. vFabric SI/SO RoadShow vFabric Platform Deep Dive April 18th, 2011

2. Session Roadmap Cloud Application Platform Key Drivers VMware’s IT as a Service Vision VMware vFabric Combines Spring framework and tools with vFabric platform services to speed delivery of next-generation apps that are instantly scalable and cloud-portable

3. VMware Solutions for Cloud Computing End User Computing vFabric vCloud Infrastructure 3

5. ProductiveWeb Servers/Load Balancers Build: Java Spring + Blueprint App Servers Google AE Public VMForce Messaging Cache Servers PaaS Pool Public/Hybrid IaaS – vSphere/vCD Problems: Time Cost Static Provides: Self-Service Optimization of Resources Dynamic Database

6. Users are booking rooms Use Case: App Intelligence for “Just-in-Time” Infrastructure Hotel room promotioncomes online Hotel room promotion ends Traffic Policy-based Capacity

8. Spring Is Java Developers’ Choice “ At least 2 million Java developers have some level of proficiency with Spring Core, and this represents at least 50% of enterprise Java developers Spring ” Websphere WebLogic “ A majority of [enterprise Java] users interviewed by Forrester use Spring ” “ Half say the adoption of Spring has reduced the time to complete a project by more than 25%, and one in four have reduced the time by over 50% Source: Indeed.com Job Trends, Feb 2010 ”

9. Innovation Reigns Supreme Web Cloud Platform Services Batch Social Media Security Mobile Integration 8

10. Spring Ref Arch: Robust Web 2.0 Applications Built for Scale HQ Agent HQ Agent Application Responses REST / MVC Plugin Mobile & Security App Controller Social & Web Services X X GORM RabbitMQ Plugin App Cache Grails Spring RPC Broker tc Server tc Server Application Requests Web Application Server Web Application Server File Systems Website Analytics HQ Server Data Cache RDBMS tc Server tc Server Other Data Systems Data Cache Server Management Server

11. Spring Ref Arch: Enterprise Integration in the Cloud HQ Agent HQ Agent Application Events SI Flow SI Flow X X App Cache App Cache Spring Spring RPC Broker tc Server tc Server Application Events Application Server Application Server File Systems Bus Trans Monitoring HQ Server Data Cache RDBMS tc Server tc Server Other Data Systems Data Cache Server Management Server

12. Spring Ref Arch: Distributed Partitioned Batch Processing Scheduler Launch Script HQ Agent HQ Agent Partition Responses Batch Admin Controller App Controller Batch Admin Controller App Controller X X Partition Handler Aggregator App Cache Partition Spring Spring RPC Broker tc Server tc Server Partition Requests Batch Server Batch Server File Systems Batch Admin HQ Server Data Cache RDBMS tc Server tc Server Other Data Systems Data Cache Server Management Server

14. Is a New Style of Infrastructure Needed? We need a platform that can Run these new apps. Dynamic Load Balancing Elastic App Server Performance Management Global Data Management Developers & Architects And… IT Operations Policy Driven Automation Cloud Messaging

15. Tomcat tc Server JEE Server Elastic Application Server: Lightweight Application Platform Lightweight App Container Heavyweight App Container Enterprise Capabilities Enterprise Capabilities (?) tc Server is Enterprise Tomcat – The best of both worlds Optimized for Cloud/Virtualization Same great high performance, low complexity, lean platform (10 MB Server) Best platform to run Spring (or any non-EJB Java) applications on Has Features/Capabilities Enterprises need and expect Management, Monitoring, Diagnostics, Support

16. SpringSource tc Server: Key Highlights Familiar Spring + Tomcat experience Deep performance insight into Spring apps Agile Spring development experience via STS Developer Efficiency Performance & SLA management of Spring apps Application provisioning and server administration Rich alert definition, workflows, and control actions Group availability & event dashboards Secure unidirectional agent communications Operational Control Lean server (10 MB) ideal for virtual environments Template-driven server instance creation Integrated experience with VMware environments Open, secure API for all operations Deployment Flexibility

17. SpringSource tc Server: Key Highlights Familiar Spring + Tomcat experience Deep performance insight into Spring apps Agile Spring development experience via STS Developer Efficiency Performance & SLA management of Spring apps Application provisioning and server administration Rich alert definition, workflows, and control actions Group availability & event dashboards Secure unidirectional agent communications Operational Control Lean server (10 MB) ideal for virtual environments Template-driven server instance creation Integrated experience with VMware environments Open, secure API for all operations Deployment Flexibility

18. Developer Efficiency: Deep Performance Insight into Spring Apps

19. Developer Efficiency:Deep Performance Insight into Spring Apps (cont’d)

20. Rich visual tools for rapidly building modern applications Spring 3.0, Spring Roo, Groovy & Grails tools Encourages agile development and testing Tight integration with tc Server minimizes application redeploys/restarts Links performance issues to code traces highlighted in Spring Insight Supports flexible deployment targets tc Server, Java EE servers, VMware, Cloud, etc. SpringSource Tool Suite Spring Roo Grails Spring (Core, Rich Web, Integration) Groovy Java tc Server (Spring Insight) Developer Efficiency:Agile Spring Development Experience

21. SpringSource tc Server: Key Highlights Familiar Spring + Tomcat experience Deep performance insight into Spring apps Agile Spring development experience via STS Developer Efficiency Performance & SLA management of Spring apps Application provisioning and server administration Rich alert definition, workflows, and control actions Group availability & event dashboards Secure unidirectional agent communications Operational Control Lean server (10 MB) ideal for virtual environments Template-driven server instance creation Integrated experience with VMware environments Open, secure API for all operations Deployment Flexibility

22. Operational Control: Production Deployment Architecture Server 1 Server 1 Server 2 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 tc Server Instance 1 Management Server Administration, Provisioning, Groups, Metrics, Alerts, Events, Access Control, Agent Upgrades, etc. Web Dashboard Spring Agent Agent Agent Open API Spring Spring Spring Inventory, Metric, Audit, … Seamlessly Upgradeable Spring Hyperic Monitoring Web Servers, App Servers, Databases, Caching, Messaging, Directories, Virtualization, etc.

23. Apache Tomcat Servlet 2.5 (JSR 154) Java Server Pages 2.1 (JSR 245) Clustering Features Session & context attribute replication Load balancing Improved over Tomcat 5.x Advanced I/O Features Improvements in Memory Usage Stable, Fast, Lightweight Tomcat Compatibility Runs existing Tomcat applications Leverages existing skill-sets Enterprise Capabilities Run multiple instances per install Centralizes tc Server install/updates Enterprise-ready stable release Security vulnerabilities & bug fixes Fixes will be in upstream open source release Built, certified and pre-tuned Advanced Scalability Options Non-blocking (NIO) connectors High concurrency connection pool Advanced Diagnostics Detects deadlocks and slow running requests Provides access to SQL behind slow requests Identifies time spent in garbage collection Operational Control: Enhanced Tomcat-compatible Server

24. Operational Control: Application Provisioning Provision applications to single server or group of servers Manage deployed applications View application status Start, stop, reload, and undeploy applications

25. Operational Control: Server Administration & Configuration Centralized administration of server configuration and defaults Out of box pre-tuned configurations JVM Options, production configurations, automated boot scripts, Windows service wrapper Server Instance Templates

26. Operational Control: Performance & SLA Mgmt of Spring apps Automatically Monitor Application, Data Access, Custom Components @Controller, @Service, @Component, @Transactional, @Repository, @ManagedResource Executions Per Second, Average Execution Time, Maximum Time, Minimum Time, etc. Monitor Performance and Execute Control Operations inside Spring Transaction Manager, Hibernate Session, Message Listener, JMS, JavaMail, Thread Pool, etc. Start/Stop Listener, Set Max Messages, Set Receive Timeout, Set Pool Size, Set Keep Alive, etc.

27. Operational Control: Performance & SLA Mgmt of Spring apps (cont’d) Monitor Application Server Status, Health, and Response Times Availability, Throughput, Utilization, Connection & Thread Pool Health, Deadlock Detection, Garbage Collection

28. Operational Control: Alert Workflows and Control Actions

29. SpringSource tc Server: Key Highlights Familiar Spring + Tomcat experience Deep performance insight into Spring apps Agile Spring development experience via STS Developer Efficiency Performance & SLA management of Spring apps Application provisioning and server administration Rich alert definition, workflows, and control actions Group availability & event dashboards Secure unidirectional agent communications Operational Control Lean server (10 MB) ideal for virtual environments Template-driven server instance creation Integrated experience with VMware environments Open, secure API for all operations Deployment Flexibility

30. Deployment Flexibility: tc Server Instance Templates Streamlines process of spinning up new server instances Script-driven templates deliver uniquely named server instances in seconds Run multiple instances based on a single set of server binaries Pre-packaged templates for popular configurations provided out of the box Separates server runtime, configuration, and applications in a way that makes testing changes and making updates a breeze Instance templates contain: Server, web, and context configuration files Parameterized properties files (ex. ports, etc.) Custom scripts, custom shared resource libraries, etc. Web applications (ex. Spring Insight) Example use cases: Dev, QA, Performance Test, Staging, and Production templates Templates for multiple instances on a machine serving a specific application

31. Deployment Flexibility: tc Server Instances (large physical box) tc Server Instance X tc Server Instance 1 tc Server Instance m . . . Spring Spring Spring Spring Spring . . . tc Server ver Y (shared binaries) tc Server ver X (shared binaries) Operating System & JVM Single lightweight (10MB) install for multiple running instances Shared binaries eases upgrades of all instances Separates configuration and code from server runtime Multiple server versions can be installed per machine

32. Medium Virtual Machine Deployment Flexibility: tc Server Instances (virtualized platform) tc Server Instance 1 tc Server Instance m . . . Small VM Small VM Spring Spring Spring Spring tc Server (shared binaries) tc Server tc Server OS & JVM OS & JVM Operating System & JVM Virtual Infrastructure Platform Complete flexibility to deploy large, medium, and small “machines” Lightweight footprint ensures maximum resource utilization

33. Is a New Style of Infrastructure Needed? We need a platform that can Run these new apps. Dynamic Load Balancing Elastic App Server Performance Management Global Data Management Developers & Architects And… IT Operations Policy Driven Automation Cloud Messaging

34. Data in the Cloud tc Server Spring Edition Hyperic & Spring Insight Your Java Spring App Trace, Monitor, Alert, Manage Built with SpringSource Tool Suite Lightweight App Runtime Session & Object/Data Store, Geo Replication & Partitioning, Active Queries & Notifications, … GemFire Enterprise Distributed Data Fabric GemFire Data Management Other Data Systems File Systems Databases

35. Yet Another Piece of Middleware? Why YAPOM ? Execution Excellence Make your applications run 4 to 40 times faster Ingest / Digest / Distribute vast amounts of data with extremely low latency Higher ROI of IT investments & Lower Cost Per Transaction A 4x Performance Increase is like getting 3 free computers that take no space or electricity Enables applications to survive network outages and distressed networks Data Awareness – especially across applications/systems Supports High Availability, Fault Tolerance, and Site Failover with zero additional design/development costs

37. High Availability

38. System Integration

39. Data Distribution

40. Persistence

41. Load Balancing

42. Data Transformation

43. Event Propagation

44. Transactions

45. Data Replication

46. Service Loose Coupling

47. Guaranteed Delivery

48. Queries

50. Distributed Task Assignment

51. Map-Reduce, Scatter-Gather

52. Business Event Detection

53. Result Summarization

54. Real-time Analysis

55. Event Driven Architectures= GemFire combines select features from all of these products and combines them into a low-latency, linearly scalable, memory-based data fabric

56. Open PaaS : Productivity, Portability and Scalability VMware vSphere Infrastructure Platform Private SpringSource Application Platform GemFire Data Virtualization Platform Your Java Spring App Powered by VMware & Salesforce technology Build applications using familiar Spring skills and the SpringSource Tool Suite Eclipse IDE Public Other Platforms Deploy your apps to the Private or Public platform of your choice

57. Scaling the Tiers The web and application tiers can be easily combined and virtualized. Nodes can be added or removed on the fly. Load Balancer Add/remove web/application servers Web Tier Application Tier The database only grows by moving the VM to a larger machine Database Tier The disk systems can be virtualized and can grow on demand Storage Tier

59. Failure of Server A and Server B makes some data unavailable

61. Must acquire distributed locks on data for update

62. Scalability is not linear and limited to a handful of nodes

64. Memory-based Performance GemFire uses memory on a peer machine to make data updates durable, allowing the updating thread to return 10x to 100x faster than updates that must be written through to disk, without risking any data loss. Typical latencies are in the few hundreds of microseconds instead of in the tens to hundreds of milliseconds. Perform GemFire can optionally write updates to disk, or to a data warehouse, asynchronously and reliably.

65. Data-Aware Function Routing Data Aware Function Execute Batch Controller or Client Scatter-Gather (Map-Reduce) Function GemFire provides ‘data aware function routing’ – moving the behavior to the correct data instead of moving the data to the behavior.

66. Data Distribution Distribute GemFire can keep clusters that are distributed around the world synchronized in real-time and can operate reliably in Disconnected, Intermittent and Low-Bandwidth network environments.

67. GemFire virtualizes the database into the application tier Cloud Ready Add/remove web/application/data servers Add/remove disk GemFire server is a small Java jar file that can be easily deployed with Java applications. Optional reliable, asynchronous feed to Data Warehouse or Archival Database

68. Is a New Style of Infrastructure Needed? We need a platform that can Run these new apps. Dynamic Load Balancing Elastic App Server Performance Management Global Data Management Developers & Architects And… IT Operations Policy Driven Automation Cloud Messaging

69. More Than Just Data – How do I Distribute Cloud Information? Application Data Lives Here Application MessagingThat Won’t Fail RabbitMQ Message Bus Application Data Sleeps Here GemFire Data Fabric File Systems Applications Databases Devices Other Systems Cloud Services

70. Who uses AMQP Over 500 known commercial users recorded by AMQP vendors, examples: National Science Foundation OOI Cyber infrastructure Frankfurt Stock Exchange “EUREX 12 is FIXML over AMQP Eurex is the very first exchange to introduce AMQP as a standard protocol on its system, thus easing the monitoring of positions and risk related data for its members and ensuring market integrity for all participants.” JPMorgan sends 1 billion AMQP messages per day 60 production system (50% CAGR, unforced) NASA’s Nebula Cloud Computing project Second Life Developer clouds: VMforce, Engine Yard, Joyent, Heroku

71. Basic use cases Event I need to know when to do something Data fragment I need to give you a piece of this data without you needing to understand the whole schema Routing Control who gets which message, without changing sender and receiver Publish Tell everyone who wants to know about this Batch Producer and consumer can run at independent times Load share Add more consumers to scale up

72. Where AMQP fits What goes in here will clean up if it is OPEN, UBIQUITOUS, & ADAPTABLE async sync reliable unreliable copyright (c) Rabbit Technologies Ltd.

74. Consumers create queues; these buffer messages for push to consumers

75. Queues are stateful, ordered, and can be persistent, transient, private, shared.

76. Exchanges are stateless routing tables.

77. Consumers tell queues to bind to named exchanges; each binding has a pattern e.g. “tony” or “*.ibm.*”

78. Producers send messages to exchanges with a routing key e.g. “tony”, or ordered set of keys e.g. “buy.ibm.nyse”

80. Rabbit is great for developers Developer platform integration

81. Is a New Style of Infrastructure Needed? We need a platform that can Run these new apps. Dynamic Load Balancing Elastic App Server Performance Management Global Data Management Developers & Architects And… IT Operations Policy Driven Automation Cloud Messaging

82. Is a New Style of Infrastructure Needed? We need a platform that can Run these new apps. Dynamic Load Balancing Elastic App Server Performance Management Global Data Management Developers & Architects And… IT Operations Policy Driven Automation Cloud Messaging

83. Need: Measure & Manage Custom Apps Against Business Goals Web-based Application Infrastructure End-user App Server Web Server Database Is performance within SLAs? What is source of bottlenecks? How is infrastructure impacting application response times? Can I automate corrective actions? How can I improve performance? App Server Physical or Virtual Infrastructure

84. Need: Go Beyond Red Light, Green Light Availability

85. Need: Application Visibility Across Physical and Virtual Worlds

86. If You Can Measure It, You Can Manage It

87. If You Can Measure It, You Can Manage It

88. Identifying Key Performance Metrics Is trouble coming? Are we meeting obligations? How can unique knowledge help?

89. What to Measure for Custom Developed Applications?

90. Examples of Collected Metrics

91. Track Events Alongside Collected Metrics Event Tracking and Correlation Provides history of log, configuration, alert and security events with performance data.

92. Hyperic Inventory and Configuration Tracking Maintain exact, real-time inventory of resources Hyperic Auto-Discovery Continuously runs to discover new inventory and modified inventory properties such as IP set changes or configuration changes. These too can be used as the basis for alerts.

93. Group Resources to Understand Real Utilization Create groups to determine if problems are localized Create groups for like resources, e.g., all web servers Create groups that share a dependency, e.g., that share a similar host Remote Diagnostics Hyperic HQ allows users to run real-time diagnostics like cpuinfor, cpuperc, df, top, netstat, ifconfig, and who across groups and operating systems simultaneously.

94. If You Can Measure It, You Can Manage It

97. CPU, Memory, Disk utilization

98. Relate Physical & Virtual Performance to Individual ApplicationsHyperic virtualization plugins Collect metrics inside and outside the VMs, and monitors consumption by both allocation and availability.

99. Establish Baselines and Automate Anomaly Detection Automatic baseline calculation for dynamic metrics Out-of-Band Metrics Identified and Bubble-up to Dashboard Hyperic Enterprise SmartTrendBaselines performance over any given period, and these baselines can be used to set alerts.

100. If You Can Measure It, You Can Manage It

101. Define Alert Conditions and Automated Response Control Actions Any script can be run remotely from Hyperic HQ and will be logged with the event history of the resource. With Hyperic HQ Enterprise these can be scheduled or run as a response to an alert.

102. Automate Response via Control Actions & Scripts

103. Define a Recovery Alert Opposite Condition to Problem Link to Problem Alert This Is Set on Problem Alert. Not Available for Recovery Alert Definition

104. Example Alert-based Actions Stop or Restart a Problem Service Remove Server from Load Balancer Configuration Execute External Process Script Issue Remote API Calls Integrate with Issue Tracking System Scale Server Deployment (e.g. add additional VMs to handle load) Perform Actions Against HQ API

105. If You Can Measure It, You Can Manage It

106. Establish Support Escalation Workflows

107. Example Escalations Defcon 1: Page on-call and email ops, wait 5 minutes, then page all. High Priority: Page on-call and email ops every 30 minutes Med Priority: Email ops every 4 hours Med Priority w/ Suppress: Suppress for 20 minutes, then email ops every 4 hours Low Priority: Email ops every 24 hours Low Priority w/ Suppress: Suppress for 20 minutes, then email ops every 24 hours Low Priority no Email: Used for warnings in Ops Center only, no notification

108. Acknowledge Escalation and Suspend Actions

109. If You Can Measure It, You Can Manage It

110. Learn from Gathered Metric Data Discrepancies in behavior among identical Apache servers Load balancer configuration the culprit: Expected results following fix

111. If You Can Measure It, You Can Manage It

112. Hyperic Provides Top Down Visibility to Meet Goals Modern Application Management Monitoring for custom applications Best tool to manage Spring apps Top to bottom insight and control Deep visibility into applications & services Spans physical, virtual, and cloud Managing The World’s Largest Infrastructure

114. SNMP

115. Script Control ActionTicketing / Process Management

116. Hyperic Architecture Overview User Interface HQ Database

117. Hyperic Server Considerations for Production Application Server Sizing CPU Memory Database Server Sizing Disk I/O Other Considerations Firewalls and other Security Software (agent and server) User Accounts Use of a Virtual IP Address HA Configuration

118. Lessons From Hyperic QA on Server Sizing Performance test environment H/W config: Dual Quad Core CPUs 16 GB of RAM (2 - 6GB dedicated to JVM heap, depending on what is being tested) Standalone MySQL DB w/ 7 disk RAID0 Array Our test profile includes: 1000 platforms 4000 servers 10000 services 100K to 150K metrics/min 20000 to 50000 alert definitions

119. Hyperic Agent Architecture: Open Plugin Flexibility

120. Agent Upgrades via Hyperic UI

121. Push Plugins via Hyperic UI

122. Data Collection via the Hyperic Agent

123. Anatomy of a Custom Plugin

124. System Information Gatherer and Reporter (SIGAR) In-Depth

125. Is a New Style of Infrastructure Needed? We need a platform that can Run these new apps. Dynamic Load Balancing Elastic App Server Performance Management Global Data Management Developers & Architects And… IT Operations Policy Driven Automation Cloud Messaging

126. Private Application Cloud Platform Vision Your Java Spring App Load Balancer Deployment Policy Configure, Provision, Control Trace, Monitor, Alert Elastic App Runtime App and deployment policy uploaded to Cloud platform Platform configures required services and provisions app Launch application Inventory Messaging Service In-Memory SQL Elastic Data Fabric Policy-based Infrastructure Platform & Resource Pools (vSphere , vCloud Director)

127. Cloud Foundry Initially, CloudFoundry.com supports Spring for Java apps, Rails and Sinatra for Ruby apps, Node.js apps and apps for other JVM frameworks including Grails. Cloud Foundry also offers MySQL, Redis, and MongoDB data services. Open PaaS offering from VMware Currently in Beta Three Primary Flavors CloudFoundry.com – Complete Hosted PaaS CloudFoundry.org – The Community Site Cloud Foundry Micro-Cloud – PaaS for the Enterprise

128. Market Has Chosen Spring As Path Forward for Enterprise Java “In partnership with VMware, we are bringing Spring to Force.com.” “With VMware, we are making it easy for developers to create Spring Java apps in the cloud.” 2.5 million Spring Developers vFabric

130. VMware vFabric Cloud Application Platform Application Infrastructure for the Cloud Generation Integration Data Access Rich Web Batch Cloud APIs Social Media Frameworks & Tools vFabric Platform Services Dynamic Load Balancer Performance Management ERS (Apache) Hyperic Elastic App Server tc Server Policy-driven Automation vFabricAppDirector Global Data Management GemFire Cloud Messaging RabbitMQ Virtual Datacenter Cloud Infrastructure and Management

131. vFabric Vision: Optimized Cloud Infrastructure VMware vFabric Application Runtime and Data Services Application Deployment Policy Elastic Resource Utilization Build your application Configure and deploy Virtual Datacenter Infrastructure Platform & Resource Pools Transparent Visibility Policy-driven Automation Run and scale

132. Evolutionary Approach to Cloud Application Platform 4 3 Cloud Platform Cloud Data Management 2 Cloud App Runtime VM 1 Stage vFabric tc Server Virtualized Applications VM App Server 0 Virtualization & Spring

134. Partner Central: http://www.vmware.com/go/learnvfabric

135. vFabric Overview, PaaS Whiteboard, tcServer Demo, Hyperic Demo, Gemfire Presentation

136. SME Email List for Technical Questions

137. SME-SpringSource@vmware.comWebinars http://www.springsource.com/newsevents/webinars Avoid Pitfalls when Monitoring a Virtualized Environment Next-Generation Data Management in the Cloud for Java Apps Best Practices for Virtualizing Java Workloads Performance Tuning Production tc Server: Tuning for Throughput & Scale Upcoming: The NPC Story - Speedier Apps, Minimal Downtime, Lower Cost

138. VMware’s Commitment to Partners

139. Solution Provider Benefits Include... Training and Education Sales Engagement Branding and Customer Recognition Incentives/ Margin Intellectual Property & SET’s Demand Generation NFR & IUL Software

140. Temporary Program for Net New VMware vFabric Partners LEVEL REQUIREMENT Application/Agreement: Sign & Complete Ability to Sell: ACE, Workstation, Fusion, vSphere Essentials & Essentials Plus REGISTERED Go to www.vmware.com Partners- > Partner Programs Solution Provider - > Registered Apply Now Fill in the Details and Submit

141. Sign up for Partner Central and Partner University Partner Central is the exclusive online information resource, providing a single dedicated web portal for all VMware Partners.

142. Key Takeaways Cloud Application Platform Key Drivers VMware’s IT as a Service Vision VMware vFabric Combines Spring framework and tools with vFabric platform services to speed delivery of next-generation apps that are instantly scalable and cloud-portable

143. Questions? vFabric Platform Deep Dive April 18th, 2011

144. Appendix A Use Cases

145. tcServer Successes

147. From Hours to Minutes

148. Rapid Turnaround on Production Fixes

149. Proactive Problem Solving

150. H/A – 100% Uptime on Website

151. Improved Performance – 3X

152. Reduced Server CostsNotable Quote “In the newspaper environment, we constantly need to find new and innovative ways to monetize our content,” Perkinson continues. “Ideas for new features are coming through all the time, and for us to be able to turn those features around and get them to market quickly is absolutely key. But with Oracle WebLogic, developers were constantly task switching while waiting for Oracle WebLogic to deploy and start up our applications after each test and staging release.”

154. High Availability

155. Increased Developer Productivity

156. Greater Scalability and Improved User Experience

157. Virtual Cloud Infrastructure

158. Reduced Server Costs by 75%Virtual Cloud Infrastructure tcServer has enabled NPC International to implement an internal, private cloud of VMware-based virtual server resources, to maximize efficient usage of existing infrastructure. Because tc Server’s footprint is small, 12 tc Server instances are running on a single physical box, with additional capacity available to install more tc Server instances when needed. Consequently, tc Server enables NPC International to maximize internal server resources by eliminating the multiple machines necessary to run numerous application servers. “I could not have deployed the applications within VMware-based virtual machines without tc Server,” Brisbin says. “I need a small, lightweight server that starts in a few seconds. I need to run several instances so I can make use of all the CPU resources.” Confidential 110

159. GemFire Successes

161. Permanent Archival of every trade

162. Kept pace with fast ticking market data

163. Rapid, Event Based Position Calculation

164. Distribution of Position Updates Globally

165. Consistent Global Views of Positions

166. Pass the Book

167. Regional Close-of-day

168. High Availability

169. Disaster Recovery

171. real-life use case: Event-driven Risk and Pricing Use Case – Event Management Batch processing delays were costing money and limiting opportunities Running Pricing and Risk calculations in batch mode required special applications to be written that created a ‘buffers’ to ensure that regulatory obligations were not violated (BASEL II regulations). An initial attempt to produce event-detection processing on legacy technology would not scale. Only 43 priority products could be managed – other products could not take advantage of a known tactical advantage.

172. real-life use case: Event-driven Risk and Pricing Use Case – Event Management "The breakthrough for this tool came when we decided to put the event detection logic into our pricing models" Derek Joyce Chief Business Technologist for Equity Derivatives JPMorgan investment Bank Built and deployed the Event Workstation project in under 12 months Features: Real-time event detection, easier integration of new products, and control workflow to minimize business risk and meet all regulatory requirements Trader UI queries reduced from 20 minute to under 5 second response time 8 CPUs re-price 6000 complex and exotic instruments in under 3 minutes

173. Use Case – Mainframe Migration real-life use case: Mainframe-based Nightly Batch Run I/O Wait 9% CPU Busy 15% A mainframe-based, nightly customer account reconciliation batch run 0 120 60 min CPU Unavailable 15% Mainframe Batch now runs in 60 seconds COTS Cluster 93% Network Wait! Time could have been reduced further with higher network bandwidth

175. Regulatory compliance

176. Re-run risk calculations with 119 different scenarios

177. Up sell customersYou can move from batch to real-time processing!

178. real-life use case: Web 2.0 Portal – Customized ads Use Case – Web Portal 1 2 3 4 A popular online gambling site attracts new players through ads on affiliate sites Customized Banner Ad on affiliate site In a fraction of a second, the banner ad sever must: Generate a tracking id specific to the request Apply temporal, sequential, regional, contractual and other policies in order to decide which banner to deliver Customize the banner Record that the banner ad was delivered Banner Ad Server Affiliate's Web Server

179. real-life use case: Web 2.0 Portal – Customized ads Use Case – Web Portal Their initial RDBMS-based system Limited their ability to sign up new affiliates Limited their ability to add new products on their site Limited the delivery performance experienced by their affiliates and their customers Limited their ability to add additional internal applications and policies to the process Their new GemFire-based system Responded with sub-millisecond latency Met their target of 2500 banner ad deliveries per second Provides for future scalability Improved performance to the browser by 4x Cost less

181. ODBMS - Objectivity

182. jCache – GemFire, Oracle Coherence

183. JMS – SonicMQ, BEA Weblogic, IBM, jBoss

184. TIBCO Rendezvous

186. RabbitMQ Successes

187. BBC - real time content management Source feeds are collated, transformed and routed to their destinations

188. Pubsubat massive scale: “Twitter for Data in the Cloud” Oceanographic Observatory Institute

189. Putting it all together: The OOI National Network 125