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It is just not enough these days to have storage virtualization for the sake of storage virtualization. Pooling heterogeneous resources and migrating data from point A to point B while the application is up and running is great, but businesses really need complete solutions -- solutions that provision storage more efficiently as well as virtualize, protect, migrate, dedupe, encrypt, replicate, recover and archive any data source in real time via policy.



There is a definite need for a simple, yet comprehensive, solution that enables a more efficient IT infrastructure and leverages existing assets, policies and procedures, all while reducing the overall costs. This requires building an optimized suite of integrated data services on a common platform.

This holistic approach is called the "optimized data services" (ODS) utility. An ODS utility enables physical abstraction and flexible data movement by virtualizing existing datasets, storage and servers between compute and storage elements. Once virtualized, this allows the creation of policies that enforce specific service levels for explicit or pooled datasets. Physical constraints, such as volumes in the same array, or SAN versus non-SAN, or storage network-attached devices or hosts, should not hinder the grouping of data elements for consistency or recovery purposes.

The overall administrative burden is reduced, providing an element of automation to the design through the thin provisioning capabilities for enhancing storage utilization thast the ODS solution enables. Additionally, capacity expansion for running applications can occur in real time and on demand by the compute resources in question. Recovery time objectives (RTO) and recovery point objectives (RPO) are achievable at minimal costs based not on budget constraints, but by the service level agreement (SLA) policy applied to the application. This unique capability can only be achieved if the solution also automatically applies efficiency in data storage and movement. Such effciency is accomplished through de-duplication and sub-block-level monitoring of all stored data to ensure only unique data is stored and replicated.

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