Three key VDI storage challenges


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Challenge 2: Inefficient data protection

A second VDI storage challenge is data protection. Traditional arrays are notoriously inefficient in how they address backup, recovery and disaster recovery (DR) in a virtual desktop infrastructure, and outmoded data protection practices can exacerbate the situation. For example, many VDI users continue to back up using agent-based, third-party backup software running on VMs. Those backups are time consuming and resource intensive, and limit the number that can be done concurrently.

While some vendors have introduced copy-on-write VM snapshot capabilities to address these issues, many of the snapshot methods are constrained in terms of the space they consume and the length of time the snapshots can be retained. These limitations can compromise recovery point objectives (RPOs) and require manual management.

A handful of suppliers have developed solutions that provide efficient, rigorous and nondisruptive data protection for virtual desktops. These products share an important attribute: space efficiency. Nimble and HP both deliver VDI data protection capabilities that overcome the issues found in traditional methods. The vendors’ space economies are rooted in primary data storage optimization technologies such as thin provisioning and zero-copy clones, whose effects trickle down to secondary storage. Nimble’s in-line compression helps shrink this baseline even further.

Both Nimble and HP

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then enable highly efficient, point-in-time snapshots that internally share unchanged blocks. These thin snapshot technologies reduce capacity needs by upwards of 90% over traditional backup methods, and allow users to retain hundreds, and even thousands, of snapshots concurrently; in addition, backup windows can be reduced to a matter of seconds. The lightweight snapshots can easily and efficiently be wide-area network (WAN)-replicated to a remote site for DR purposes. Recovery is streamlined from hours to minutes because the restore can be based on a recent thin snapshot.

This was first published in February 2012

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