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Optimize Oracle Applications Performance while Lowering Costs An Agilent Case Study

Optimize Oracle Applications Performance while Lowering Costs An Agilent Case Study. Presenters- Kevin Barry Kevin O’Malley OuterBay Technologies, Inc. Agenda. Introduction to Agilent Corporation The Data Growth Problem OuterBay ADM Suite The Agilent Solution Results & Benefits Q & A.

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Optimize Oracle Applications Performance while Lowering Costs An Agilent Case Study

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  1. Optimize Oracle Applications Performance while Lowering CostsAn Agilent Case Study Presenters- Kevin Barry Kevin O’Malley OuterBay Technologies, Inc.

  2. Agenda • Introduction to Agilent Corporation • The Data Growth Problem • OuterBay ADM Suite • The Agilent Solution • Results & Benefits • Q & A

  3. About Agilent • Global technology leader in communications, electronics, life sciences and chemical analysis • Revenue • $7 Billion in Revenues • Employees • 29,000 World Wide • Locations • Headquartered in Palo Alto, CA • 30 Facilities worldwide • Primary businesses • Test and Measurement • Automated Test • Semiconductor Products • Life Sciences and Chemical Analysis

  4. Agilent’s Oracle E-Business Environment • Oracle E-Business Suite 11i • Modules: Entire ERP Suite • Single global instance • Consistent, real-time view across all business units • Common business processes • HP Superdome (64 CPUs) • Go-live in July 2002 • Application OLTP production Data Growth • 92 GB/month • OLTP instance copied ~ 26 times for test/development • Growth expected to increase with additional plants coming online

  5. Agenda • Introduction to Agilent • The Data Growth Problem • OuterBay ADM Suite • The Agilent Solution • Results & Benefits • Q & A

  6. The Problem Performance issues in production • Strong relationship between DB size and OLTP / Batch performance Storage capacity required was explosive • Data growth was more than Oracle predicted • Total disk capacity requirements to exceed 26 TB in one year Business continuity challenges • Increase in backup and recovery times • Higher DR/HA costs

  7. 1300 Data Growth Impact 1200 Total Batch Run Time (Hrs/Month) Application Data 1100 Application Data (GB) 1000 900 800 700 600 Batch Run Time 500 400 Data Growth vs. Performance Application Data (GB)

  8. Data Growth Alternatives • Ask Oracle for assistance • Custom/in-house solution • Archive vendor search • Services engagement • Major project – year+ to deploy • Selected approach

  9. Agilent - Key Requirements • No disruption to the business • Uncompromised end-user reporting • No change to business processes • Guaranteed data and transaction integrity • Aggressive Data Retention Policies • True 24 x 7 Operations – Zero downtime allowed • Automation • Oracle Certification

  10. Agilent Selects OuterBay • Suite of proven solutions • Highly automated • Oracle certification • Online/transaction integrity • Experience • Ready to Implement

  11. Agenda • Introduction to Agilent • The Data Growth Problem • OuterBay ADM Suite • The Agilent Solution • Results & Benefits • Q & A

  12. Disaster Recovery Local Standby Disk Backup Reporting Encapsulated Archive Application Data Management Support & Projects Production Integration Test Unit Test Development Archive X(n) Parallel Initiatives Production Application Resource Monitor Policy & Configuration Console LiveArchive Instance Generator Developers Edition

  13. Application Transparency Encapsulated Archive Data Life Cycle Example Data Retention Policies 6 months-2Years 2-7 Years 7 – 25+ Years 3rd Party Reporting Tools Production History .XSD .XML • Active OLTP • Online • Sustained growth & perf. • Historical transactions • Online • Application dependent • Archive flat file • XML Query access • Open / Independent Storage Class High Cost High Availability Secondary Least Expensive

  14. Applications Resource Monitor • Discover areas of high and low data growth • Decision Support tool for data retention policies • Use across all instances and database applications DatabaseXtender

  15. TTE 125 100 75 50 25 0 Relocation Relocation Relocation Relocation Space (GB) Jan 2002 May 2002 Sep 2002 Jan 2003 May 2003 Sep 2003 Jan 2004 May 2004 Sep 2004 Jan 2005 May 2005 Sep 2005 Eligible Eligible Forecast Ineligible Ineligible Forecast Data Growth Analysis • Identify active vs. inactive data • Build data relocation into the business process • Implement based on predictable storage requirements

  16. Key Features • Combined View Reporting – native reports/queries • Data Growth and Process Monitoring • Data Parity Support • Database Reorganization Support • Online Operations (users stay on the system) • Concurrent Manager integration (or 3rd party scheduling tools) • Fully Recoverable/Restartable • Full audit trail – repository-based • Reload Support

  17. OuterBay Platform LiveArchive Encapsulated Archive Application Resource Monitor Active Repository Instance Generator Developer Edition

  18. Agenda • Introduction to Agilent • The Data Growth Problem • OuterBay ADM Suite • The Agilent Solution • Results & Benefits • Q & A

  19. Agilent Approach • Test and Development Environments • OuterBay Instance Generator: Relationally intact subsetting • 11 Modules implemented • INV, COST, WIP, AP/PO, GL, AR, Quotes, Workflow, Cash Mgmt, Order Mgmt, Cycle Count • Production Environment • OuterBay LiveArchive: Online Archiving • 9 Modules implemented • INV, COST, WIP, AP/PO, GL, Quotes, Workflow, Cash Mgmt, Supplier Schedules Two-tiered Solution

  20. Agilent Approach – Instance Generator Test and Development Environments • Create fully functional subset databases for development, test, UAT, training, and demo • Policies selected by time Patch Policy Sets Production OLTP Copy Training Dev

  21. Agilent Approach - LiveArchive Best Practices in Data Retention Policies

  22. Agenda • Introduction to Agilent • The Data Growth Problem • OuterBay ADM Suite • The Agilent Solution • Results & Benefits • Q & A

  23. The Results • $ Savings for Storage • Subsets for Test, Dev, and Training = 30% of Production • 500 GB from 1.8 TB • Current usage • Patch, Training • Planned usage • 11.5.10 Upgrade testing: 10+ copies • IT Process Streamlined • 17% reduction in subset creation times Delivered by Instance Generator

  24. The Results • Defer investments in hardware upgrades • Decrease TCO for E-Business Suite • Minimal user impact/end user training Expected Benefits

  25. The Results • $ Savings for Storage: 2.5% of total 2005 IT budget • Number of rows archived = ~ 500 Million • 500 GB in storage savings in Production • Total storage savings = 13 TB • Agilent can now defer disk spending for 1 year • Related Savings • HA, Backup & Recovery Delivered by OuterBay LiveArchive

  26. The Results • Data growth management  stable, predictable performance management • Take guesswork out of capacity planning • Free up resources for business initiatives • Accelerate critical business processes Unexpected Benefits

  27. Performance Benefits Total Batch Run Time (Hrs/Month) Data Growth Impact Application Data (GB) Phase II Tuning Sustained Predictable Performance LiveArchive Phase I Tuning

  28. Sustained Predictable Performance Business Benefits Example: Shipping Pick Selection List Generation Total Batch Run Time (Hrs/Month) Average Run time (Min)

  29. Sustained Predictable Performance Business Benefits Example: OM Order Import Total Batch Run Time (Hrs/Month) Average Run time (Min)

  30. Sustained Predictable Performance Business Benefits Example: AP Payables Approval Total Batch Run Time (Hrs/Month) Average Run time (Min)

  31. Agilent Approach Lessons Learned – Implementation Project • You can NEVER START THIS TOO EARLY!!! • Set the plan by largest “wins” first and get buy-off immediately • Get message out that data is NOT being purged; just relocated • Users retain transparent access and combined reporting • Engage key business groups early, establish as a critical business project: Finance, Audit, etc… • Strong team work between IT and Business teams required • Incremental rollout enabled the project team to • Refine process • Enforce accountability

  32. “OuterBay Software has provided Agilent with a long-term positive business impact with an extraordinary, immediate ROI !” • Naresh Shanker, Agilent

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