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A Perfect Blend of Replication and Disk-Based Backup


Note: This is part one of a two-part series. Part two, which will explain how IBM Tivoli Continuous Data Protection is best used, will appear in the December issue of AIX EXTRA.

The computer-backup world is going through some exciting innovations. A few years ago, we started hearing about disk-based backup, which helped improve overall backup performance (faster backups, faster restores). Customers would also often use some type of replication as a style of data protection. IBM Tivoli Continuous Data (CDP) is somewhat of a blend of those two approaches. Specifically:

  • CDP continually captures all changes (akin to replication)
  • CDP tags (versioning) objects so that they can be specifically rolled back to a particular time

While disk-based backup offers faster backup and restore times, it does nothing to help with higher recovery-point objectives; that is, the backup interval is still typically once per day. CDP provides nearly infinite recover points so that any change can be recovered. This is proving to be of huge interest to all computer users, from corporate IT administrators down to individual home users.

Taxonomy

The three main types of CDP all have merits for various situations and customer needs: block-based, file-based and application-based.

Let's start by examining block-based solutions. They're transparent; applications need not know that they're present. Most block-based solutions are "in fabric" (in the SAN fabric) and thus also work without regard to the type of server or storage. Quite simply, they see every block write go across the storage network and logically keep a time-ordered cache of those writes. Some solutions are quite sophisticated in their management of that cache, such that they can instantly present a view of disk/LUN at any time represented in their cache (versus having to re-assemble or roll through transactions in a costly manner).

Block solutions excel at capturing the data transparently and presenting a view of a past point in time, but sometimes require additional work on the part of the application or user in order to make use of that historical view. For example, imagine a database application that's constantly streaming I/O to a storage element. Rolling back to a view at some arbitrary time that wasn't synchronized with a database or quiesce point would likely mean that the database would have to perform its own crash recovery from that time view. Often, block-CDP solutions will support a tagging operation that allows the CDP device to tag specific times that are matched with application-side quiescing to allow for discrete recovery points. In between those discrete points, the solution will provide useful views, but perhaps at the expense of an application re-sync of some sort.

The potential benefits of a block-based solution are a high-application transparency; there's no negative performance effect on the application; and it's typically agnostic of hardware and platforms.

Chris Stakutis is a data-storage industry inventor and technologist with IBM. Chris can be reached at chris.stakutis@us.ibm.com.



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