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Deploy With Confidence

Deploy With Confidence. Minimize risks Improve business output Optimize resources. The Application Lifecycle. O B J E C T I V E S. BUSINESS AVAILABILITY. SYSTEM PERFORMANCE. APPLICATION READINESS. DEVELOPMENT. IT GOVERNANCE. DEPLOY. OPERATE. PLAN. DEVELOP. TEST. Virtual Machine.

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Deploy With Confidence

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  1. Deploy With Confidence Minimize risks Improve business output Optimize resources

  2. The Application Lifecycle O B J E C T I V E S BUSINESS AVAILABILITY SYSTEM PERFORMANCE APPLICATION READINESS DEVELOPMENT IT GOVERNANCE DEPLOY OPERATE PLAN DEVELOP TEST 3

  3. Virtual Machine Deployment Complexity Legacy APPLICATION ERP CRM Sessions Firewall DNS Indexes Customize Code Latency Connection SQL Call Encryption Throughput NETWORK WEB SERVER LOAD BALANCER APP SERVER DATABASE SECURITY No system-wide perspectiveSignificant time pressure 4

  4. of software projects fail to meet business objectivesGiga 40% of deployed applicationsare rolled back Gartner 50% of new ERP/CRM rollouts use more hardware to fix performance AMR 75% Deployment Risks 5

  5. When to Optimize/Tune Initial Rollout Projects User Expansions System Integrations New Geographies OS, App, System Updates Shared Infrastructures 6

  6. Optimization Methodology

  7. Phase 1: Plan & Organize Phase 2: Baseline Phase 3: Optimize Phase 4: Report Our Optimization Methodology Phase-driven approach to Performance Optimization Fully Plan the project Organize the Team Quantify the System Performance Iteratively Isolate and Eliminate Performance Bottlenecks Assess the Performance Improvements and Report 8

  8. Determine Business Objectives (Phase 1) 9

  9. Data Base Application Network Organize the Team (Phase 1) • Most problems result from interactions between components • Team structurestreamlines analysis and diagnosis ProTune Specialist DBA Project Manager Sys Admin Dev QA App Architect NW Admin Silo-centric Cross Discipline Team Plan 10

  10. Database Tier Distributed System Select Business Processes Infrastructure Tier Application Tier ~~~ ~~~ ProTune Database Servers Fire wall Fire wall Load Balancer Storage Streaming Media Server Application Servers Web Servers Apply Controlled Load Gather Metrics Measure Performance … Baseline the System (Phase 2) 11

  11. Compare Results to Targets (Phase 2) 12

  12. Database Tier Infrastructure Tier Application Tier Database Servers Fire wall Fire wall Load Balancer Storage Streaming Media Server Web Servers ProTune Application Servers Gather Metrics Measure Performance … Optimize the System tier by tier (Phase 3) • Diagnose by logical tiers • Employ component library tests for infrastructure tiers • Create specific tests for application and database tiers 13

  13. Develop Targeted Load Tests ~~~ ~~~ ProTune Controlled Load to Isolate Component Move to next Constraint ~~~ ~~~ Analyze Results and Recommend Changes Client Expert Implement Fix Iteratively Analyze each Tier (Phase 3) Fire wall Fire wall Load Balancer Web Servers Application Tier Database Tier Infrastructure Tier Validate Fix Optimize 14

  14. EJB - Latency Breakdown 15

  15. EJB - Throughput Distribution 16

  16. Re-run Baseline and Assess (Phase 4) • Quantify improvements • Deliver Executive and Detailed Reports 17

  17. Introducing ProTune • Validate performance • Optimize configuration • Verify alignment with business objectives 18

  18. Safe Deployment System™(SDS) Including Systematic Identification Problem Isolation Expert Recommendations WEB SERVERS LOADBALANCER APP SERVERS DB SERVERS NETWORK SECURITY Automated Improvements and Validation Overload Protection 19

  19. LOAD GENERATORS MONITOR MONITOR MONITOR MONITOR MONITOR MONITOR MONITOR How It Works • Mapped topology • Auto-Assigned monitoring • Business process emulation • System component validation • Problem detection • Recommended configuration • Automated checklist • Repeated validation • Audit trail CONSOLE 20

  20. Our Experience and Track Record • Over 3000 Optimization Engagements • Average Results (performance improvements): • ERP Systems – 100% • CRM Systems – 150% • Web andJ2EE – 400% • Complex C/S – 200% 21

  21. Electronic Ticketing System Improves Throughput by 10x… The Case • E-ticket system required throughput of 400 tickets/hr • Web-based application, Oracle database, SABRE system integration The Findings • Infrastructure Configurations: • Routers improperly configured, insufficient bandwidth, and insufficient file descriptors for Web Servers • Application Code Defects • Isolated JAVA code null pointer exception The Results • Increased system throughput by 10x from 270 to over 3000 transactions/hour …and booked over $1M per day with no down-time. 22

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