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SAN and NAS virtualization

Keep pace with ever-increasing storage requirements without skipping a service level


After some years of false starts and false hopes, storage virtualization, also known as block virtualization, is finally proving its worth. All the major vendors have embraced it, most notably IBM, EMC, and HDS (Hitachi Data Systems); the solutions themselves have improved; and customers, typically large shops managing large SANs with intense data availability requirements, understand how to deploy it and where to get good ROI. No longer a technology in search of a problem, storage virtualization offers a way to address a wide range of storage management woes.


Storage virtualization creates an abstraction layer between host and physical storage that masks the idiosyncrasies of individual storage devices. When implemented in a SAN, it provides a single management point for all block-level storage. To put it simply, storage virtualization pools physical storage from multiple, heterogeneous network storage devices and presents a set of virtual storage volumes for hosts to use.

In addition to creating storage pools composed of physical disks from different arrays, storage virtualization provides a wide range of services, delivered in a consistent way. These stretch from basic volume management, including LUN (logical unit number) masking, concatenation, and volume grouping and striping, to data protection and disaster recovery functionality, including snapshots and mirroring. In short, virtualization solutions can be used as a central control point for enforcing storage management policies and achieving higher SLAs.

Perhaps the most important service enabled by block-level virtualization is nondisruptive data migration. For large organizations, moving data is a near-constant fact of life. As old equipment comes off lease and new gear is brought online, storage virtualization enables the migration of block-level data from one device to another without an outage. Storage administrators are free to perform routine maintenance or replace aging arrays without interfering with applications and users. Production systems keep chugging along.


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Virtualization can also help you achieve better storage utilization and faster provisioning. The laborious processes for provisioning LUNs and increasing capacity are greatly simplified — even automated — through virtualization. When provisioning takes 30 minutes instead of six hours and capacity can be reallocated almost on the fly, you can make much more efficient use of storage hardware. Some shops have increased their storage utilization from between 25 and 50 percent to more than 75 percent using storage virtualization technology.

Four architectural approaches
In a virtualized SAN fabric, there are four ways to deliver storage virtualization services: in-band appliances, out-of-band appliances, a hybrid approach called SPAID (Split Path Architecture for Intelligent Devices), and controller-based virtualization. Regardless of architecture, all storage virtualization solutions must do three essential things: maintain a map of virtual disks and physical storage, as well as other configuration metadata; execute commands for configuration changes and storage management tasks; and of course transmit data between hosts and storage. The four architectures differ in the way they handle these three separate paths or streams — the metadata, control, and data paths — in the I/O fabric. The differences hold implications for performance and scalability.

An in-band appliance processes the metadata, control, and data path information all in a single device. In other words, the metadata management and control functions share the data path. This represents a potential bottleneck in a busy SAN, because all host requests must flow through a single control point. In-band appliance vendors have addressed this potential scalability issue by adding advanced clustering and caching capabilities to their products. Many of these vendors can point to large enterprise SAN deployments that showcase their solution’s scalability and performance. Examples of the in-band approach include DataCore SANsymphony, FalconStor IPStor, and IBM SAN Volume Controller.

Steve Norall is a senior analyst for the Taneja Group.
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