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ILM: Panacea or Proprietary Poison?

How ILM Works

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Using an access-frequency counter is a much better method for discovering stale data than using the "date last modified" attribute assigned to the data by the server OS. A lot of data is touched but never changes, referenced but never rewritten. Even the "date last accessed" parameter that OS vendors have begun to capture doesn't effectively identify data that's ready for the archive: There's a difference between data accessed once since the last time you checked and data accessed 100 times. "Date last accessed" lacks the granularity of a true access-frequency counter, like the one they had in the mainframe shop.

The ILM engine, using data characteristics and access frequencies, moves data from platform to platform under the aegis of well-defined migration policies. In addition, the ILM engine considers the capabilities, costs and location of the underlying storage infrastructure, integrating these characteristics into policy definitions so data lands on the storage gear providing the best price-performance mix.

The old formula still holds true: Access to data once written to disk falls by 30 percent within a week and by 90 percent within a month. So why store infrequently accessed or updated data on your most expensive gear? The vendors say ILM will solve the problem of storage oversubscription with underutilization once and for all.

To help you assess the vendors' claims for yourself, we asked 16 companies for their definitions of ILM and for descriptions of their products. Our objective was to create a compendium of definitions and perspectives that serves as a one-stop reference to ILM offerings.

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