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Grid Economics for the Data CenterRex WangVP Product Marketing, Oracle

The following is intended to outline our general product direction. It is intended for information

purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any

material, code, or functionality, and should not be relied upon in making purchasing decisions.The development, release, and timing of any

features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

The Traditional Data Center

Dedicated Stacks

Middleware

Database

Storage

• Dedicated silos are inefficient

• Sized for peak load

• Constrained performance

• Difficult to scale

• Expensive to manage

Grid Computing Virtualizes and Pools IT Resources

What is Grid Computing?Grid computing is a technology architecture that virtualizes and pools IT resources, such as compute power, storage and network capacity into a set of shared services that can be distributed and re-distributed as needed

Oracle Grid Computing in All Tiers

Middleware• Application Grid

• WebLogic Server• Coherence In-Memory Data Grid• JRockit Real Time• Tuxedo

Database• In-Memory Database Cache• Real Application Clusters

Storage• Automatic Storage Management• Exadata Storage Server• HP Oracle Database Machine

Infrastructure• Oracle VM

Management• Oracle Enterprise Manager Grid Control

Most complete, open and integrated grid computing architecture in the industry

Virtualization and Clustering Are Complementary

Consolidation With Grid Computing

Server A Server B Server C Server D

Application A Application B Application C Application D

Workload Avg Utilization<20%

Applications A, B, C, D, E

NetWorkload

Avg Utilization70%

Freed capacity to deploy elsewhere

Consolidate withOracle Grid Computing

• Take advantage of complementary workload peaks

• Higher utilization rates and efficiency

• Lower CapEx & OpEx

• Green footprint

Oracle Shared Instance

Server E

Application E

Server A Server B Server C Server D Server E

Scale Out With Grid Computing

Applications A, B, C, D, E

NetWorkload

If utilization too high,increase capacity

• Pay-as-you-go scale-out

• Smaller machines running at higher utilization

• Revolutionary capacity planning• Avoid upfront CapEx and ongoing

OpEx• Take advantage of advances in

hardware price-performance and energy efficiency

• World-class clustering at all levels of the stack: middleware, database, storage

Oracle Shared Instance

Server A Server B Server C Server D

• Add/Remove nodes to the cluster dynamically

• Scale linearly to hundreds of nodes

• Performance through parallelization

Scale out withOracle Grid Computing

Quality of Service with Grid Computing

Applications A, B, C, D, E

NetWorkload

• Deliver consistent, high Quality of Service

• Reliability through redundancy

• Predictable performance at any scale

• High availability – every application gets HA

Oracle Shared Instance

Server A Server B Server C Server D

• Load balancing

• Active-Active configuration

• Failover

• Disaster recovery

• Rolling upgrades

Quality of Service withOracle Grid Computing

Server E

AR APHR

AR

HR

AP

Resource (CPU)

Web

J2EE

DB

PROVISIONING + WORKLOAD MANAGEMENT + AVAILABILITY

Storage

APAR HR Sales Sales Sales BI BI

PROVISIONING + WORKLOAD MANAGEMENT + AVAILABILITY

Response Time Objectives

IMDBCache

IMDBCache

IMDBCache

Agile Operations with Grid Computing

Grid Economics for the Data Center

Virtualization and clustering enable consolidation

Pay-as-you-go scale-out

High Quality of Service

Automated grid management

Lower CapEx & OpEx

Avoid upfront CapEx & OpEx

Avoid lost user productivity

Raise IT staff efficiency