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Windows solves this problem using Volume Shadow Copy Service (VSS). A backup system that's about to create a snapshot of a volume simply needs to communicate its intention to VSS. (To do this, it must be capable of being a VSS requestor.) VSS then provides the requestor a list of applications for which it requires VSS intervention prior to taking snapshots. The requestor then communicates with each application's VSS writer. Once an application has been prepared for the snapshot, the requestor asks VSS to create the snapshot. VSS then informs the VSS snapshot provider to create the snapshot. (The snapshot provider can be Windows itself, or a storage or virtualization system like those discussed earlier.) Once the snapshot has been successfully created, the requestor can inform the supported applications (via its VSS writer) that they have been backed up, which allows them to do things like truncate their transaction logs.
Unfortunately, VSS functionality (or any meaningful equivalent) doesn't exist for Unix- or Linux-based operating systems. So if you plan to use snapshots with Unix systems, you'll need to use an application that can accomplish the same steps, or you'll have to write a script that communicates directly with the applications.
Restoring snapshot data
There are a number of ways to do restores with near-CDP systems. The most common
is to make the historical versions of files available as a subdirectory underneath the originating directory. When a previous version of a file is needed, a user can simply point their file browser to the appropriate directory, locate the file, and then copy and paste it.
Another type of restore happens when a user is looking for a file and isn't quite sure where or when it was last seen. This type of restore is very easy to do in traditional backup products because they have a database that tracks the location of all files and all versions of those files. However, most near-CDP storage systems don't have similar capability. It's one reason why many companies use their traditional backup product to configure, schedule and report on their near-CDP backups. Depending on the capabilities of your backup product, it can create a catalog of all snapshots it's controlling, allowing you to search this catalog during restores.
The most valuable type of restore a near-CDP system can perform is when you lose an entire volume or a directory containing the virtual disk volumes that comprise a virtual machine (VM). While in most cases it must be performed manually, it's a relatively simple process to point NFS or CIFS clients to a different server, or to mount a VM from a different location. This is when a near-CDP system truly pays for itself because it allows you to perform this "restore" in a few moments, rather than several hours. Once the problem with the production volume has been corrected, you can do a reverse restore from the backup system to the primary system and revert back to the primary system once that restore has been completed. After you've done this type of restore once, you won't want to go back to the "old days."
Finally, it's critical to monitor and report on the success/failure of your near-CDP backups. This functionality may be provided by your storage vendor, but it's most likely provided by your backup software vendor and their partners. This is another reason why you should consider controlling your near-CDP backups via your backup software product, even if all it's doing is acting as a traffic cop. Having all your backup functionality in one place is a good thing.
Don't embark on a near-CDP backup project hastily. Check out your vendor's capabilities and perform a proof-of-concept test before signing any purchase orders. And make sure all the good things about your current backup system -- centralized scheduling, cataloging, monitoring and reporting -- don't disappear when you deploy your shiny new near-CDP system.
BIO: W. Curtis Preston is an executive editor in TechTarget's Storage Media Group and an independent backup expert. Curtis has worked extensively with data deduplication and other data reduction systems.
This was first published in January 2011