Data Life Cycle Management

Other than temporary data that is generated as an intermediate step in data processing, most data has a lifecycle that needs to be managed in order to yield the most benefit from it. This lifecycle is comprised of four phases: online production, nearline reference, backup/restore staging, and offline archive. Each phase places different requirements on storage in terms of availability (i.e. access latency and throughput) and cost (of media, transport, environmental overhead, etc.) As such, data is typically moved from one storage system to another as it moves from one phase of the lifecycle to the next. Often, the data is also replicated within a lifecycle phase.

Historically, online data is stored on disks and offline data is stored on tapes. This has worked well for relatively small amounts of locally stored data. Consistently growing data volumes and the need to access all kinds of data over the network have driven the need for lower cost, disk-based storage systems to meet the needs of two phases of the data management lifecycle — nearline reference and backup/restore staging.

Unfortunately, customized solutions to meet these needs also bring adverse effects, such as vendor-specific data management software. The lack of integration between solutions increases complexity and the management overhead of both the storage system and the data movement. As a result, IT organizations are struggling to manage the data lifecycle with their limited budgets and human resources.

In addition, many IT organizations today are challenged with moving online and nearline data to offline tape backup and archive. The requirement for 24x7 application uptime dramatically shrinks the “backup window”. Many IT organizations cannot afford the complexity and cost of FC-SAN-based tape library solutions. As a result, much of the data in many enterprises is not backed up regularly, if at all. Even for the data that is backed up, the latency of restoring data from tape is usually long.

To address the needs for cost effective, simple and scalable data lifecycle management, Intransa has developed a new architecture that forms the foundation of an intelligent IP SAN. The StorStac architecture is designed to heavily leverage the learning curve and economies-of-scale of state-of-the-art, standards-based, networking (IP/Ethernet), distributed computing and disk (e.g. ATA & S-ATA) technologies. By moving the storage provisioning and management intelligence from the application hosts into the network, StorStac provides a platform for deploying various storage services, including data migration and replication. This frees up the application host CPU to serve the applications, enables consolidation of backup/restore resources (i.e. servers, tape libraries, software), and streamlines data migration from online to offline storage.

Intransa’s new Storage Grid system is a second-generation iSCSI-enabled, networked storage solution that implements the StorStac architecture. This solution offers low cost, block-level, networked storage that can be deployed anywhere on the IP network and managed centrally. The enterprise-class features, such as fail-over and load balancing, support the high-availability needs of online data. The policy-based virtual volume management and dynamic volume expansion capabilities, in conjunction with Intransa’s inexpensive disk storage pool, simplify capacity management and improve capacity utilization for online, nearline, and backup/restore staging applications. Intransa’s snapshot capability allows many point-in-time virtual copies of data, representing days and weeks of data, thereby obviating the need to incrementally backup to tape on a daily basis.

The strength of the StorStac architecture allows an Intransa Storage Grid system to form the basis for networked storage services to encompass all phases of the data management lifecycle, including online (such as remote mirroring and replication), nearline (large, distributed storage) and backup/restore staging. It also enables IT organizations to tap into the existing network and system management knowledge base, thus minimizing the total cost of ownership of a scalable, networked storage infrastructure.

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