Optimize Oracle Applications Performance while Lowering Costs An Agilent Case Study

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

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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. - PowerPoint PPT Presentation

Transcript of Optimize Oracle Applications Performance while Lowering Costs An Agilent Case Study

Page 1: Optimize Oracle Applications Performance while Lowering Costs An Agilent Case Study

Optimize Oracle Applications Performance while Lowering Costs

An Agilent Case Study

Presenters-Kevin BarryKevin O’MalleyOuterBay Technologies, Inc.

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Agenda

• Introduction to Agilent Corporation

• The Data Growth Problem

• OuterBay ADM Suite

• The Agilent Solution

• Results & Benefits

• Q & A

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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

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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

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Agenda

• Introduction to Agilent

• The Data Growth Problem

• OuterBay ADM Suite

• The Agilent Solution

• Results & Benefits

• Q & A

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The Problem

Performance issues in productionStrong relationship between DB size and OLTP / Batch

performance

Storage capacity required was explosiveData growth was more than Oracle predictedTotal disk capacity requirements to exceed 26 TB in one

year

Business continuity challengesIncrease in backup and recovery timesHigher DR/HA costs

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Data Growth vs. PerformanceA

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Data Growth Alternatives

• Ask Oracle for assistance

• Custom/in-house solution

• Archive vendor search

Services engagement

Major project – year+ to deploy

Selected approach

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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

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Agilent Selects OuterBay

• Suite of proven solutions

• Highly automated

• Oracle certification

• Online/transaction integrity

• Experience

• Ready to Implement

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Agenda

• Introduction to Agilent

• The Data Growth Problem

• OuterBay ADM Suite

• The Agilent Solution

• Results & Benefits

• Q & A

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Support & ProjectsProduction

Disaster Recovery

Local Standby

Disk Backup

Reporting

Production

Integration Test

Unit Test

Development

X(n)Parallel Initiatives

Application Resource Monitor

LiveArchive Instance Generator

Archive

Developers Edition

Policy & Configuration Console

EncapsulatedArchive

Application Data Management

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Encapsulated Archive

ProductionHistory

Data Retention Policies

Application Transparency

• Active OLTP • Online • Sustained growth & perf.

• Historical transactions• Online• Application dependent

6 months-2 Years 2-7 Years 7 – 25+ Years

.XSD.XML

• Archive flat file• XML Query access• Open / Independent

Storage Class

High CostHigh Availability

Secondary Least Expensive

3rd Party Reporting Tools

Data Life Cycle Example

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DatabaseXtender

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

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Data Growth Analysis

• Identify active vs. inactive data• Build data relocation into the business

process• Implement based on predictable

storage requirements

125

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Space(GB)

TTERelocation

RelocationRelocation

Relocation

Jan2002

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Eligible

Eligible Forecast

Ineligible

Ineligible Forecast

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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

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OuterBay Platform

Active Repository

LiveArchive

Encapsulated Archive

Application ResourceMonitor

Instance Generator

Developer Edition

mkelly
smaller
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Agenda

• Introduction to Agilent

• The Data Growth Problem

• OuterBay ADM Suite

• The Agilent Solution

• Results & Benefits

• Q & A

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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

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Agilent Approach – Instance Generator

Test and Development Environments

Dev

Training

Patch• Create fully functional

subset databases for

development, test, UAT,

training, and demo

• Policies selected by time

Policy Sets

ProductionOLTP Copy

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Agilent Approach - LiveArchive

Archive Module Data Retention in Production Archiving Frequency

Inventory 2 Months + Current Month Monthly

Cost History 2 Months + Current Month Monthly

WIP 2 Months + Current Month Monthly

Supplier Schedules 2 Months + Current Month Monthly

AP/Procurement 2-3 Months after PO gets finally closed Monthly

Cash Management 6 Months + Current Month Monthly

GL 12+2 Months of adjustment period, after a period is permanently closed

Monthly

Quote Expired Quotes, older than 9 months will get deleted

Monthly

Workflow Delete workflows older than 15 days as part of regular Oracle workflow purge

Monthly

Best Practices in Data Retention Policies

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Agenda

• Introduction to Agilent

• The Data Growth Problem

• OuterBay ADM Suite

• The Agilent Solution

• Results & Benefits

• Q & A

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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

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The Results

• Defer investments in hardware upgrades

• Decrease TCO for E-Business Suite

• Minimal user impact/end user training

Expected Benefits

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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

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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

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Phase II Tuning

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Pick Selection List Generation

Business Benefits Example: Shipping

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Agilent Approach

• 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

Lessons Learned – Implementation Project

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

- Naresh Shanker, Agilent