Policy-based data management in ILM

Computer Technology Review, August, 2004 by Mike Palermo

Information Lifecycle Manage-ment is a concept that has caught the attention of business users, integrators, and IT departments alike--all looking for ways to manage critical digital assets and growing data volumes.

Business users look to ILM to meet regulatory requirements for data retention and access, or otherwise manage critical business data over its lifetime.

IT hopes that ILM technologies will reduce storage costs and administration by automating the placement, retention, and protection of data using appropriate storage resources.

A comprehensive ILM solution should address both the business user's content-specific goals and IT's underlying data management requirements. Much of the industry's focus has been on content-layer applications, which are some of the first "ILM solutions" to hit the market. But when considering architectures and solutions for ILM, it's important to not lose sight of ILM's potential to reduce managed storage costs by automating data management aligned with that data's value.

Aligning Storage With the Changing Value of Data

Like any other business asset, the value of data changes over time. Infrequently accessed data is typically less valuable to a business than the data used in today's operations. Yet many companies treat both types of data the same by storing them on the same expensive, high-performance disk resources.

Recent data retention regulations modify some data's gradual depreciation by adding regulatory value to the data for fixed time periods. In a regulated environment, data that is older and infrequently accessed has a significant value if required for an audit several years down the road. However, it may not require the performance of high-speed disks. The day after its regulatory period expires, the value of the data may decline dramatically. Some organizations may even decide that the best business decision is to delete the data at that point in time.

By aligning storage cost, capacity, and performance with the changing data value over time, organizations can improve storage efficiency. But manually tracking and moving data is prohibitively expensive and error prone, and can offset any cost advantages of using less expensive storage. What's needed is the ability to automatically locate and protect data according to business values--policy-based data management.

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Two Essential Layers of ILM

As a system for managing both the assessment of data value and the actual disposition of digital assets, ILM is comprised of two different technology layers:

* A content-aware layer looks at the content of files and uses that information to approximate the value of the data. Examples include e-mail archiving and image management systems.

* A policy-based data management layer moves and maintains the data on different storage resources based on the storage cost, access, and security characteristics.

These layers work together to create a comprehensive ILM solution. By focusing exclusively on the content layer, you risk losing the data management benefits of ILM.

Dangers of Neglecting the Data Management Layer

ILM is still an evolving market segment. Many early entrants focus primarily on the content layer: classifying and managing e-mail messages, documents, or images. These solutions offer only a rudimentary system for data management, capable of moving objects between a restricted number of dedicated storage resources. For example, an e-mail messaging solution might specify that e-mails more than 60 days old from user Smith must be moved from a given disk volume to a specific tape library.

Although implementing a package like this seems like a quick and easy way to start achieving benefits of ILM, there are long-term drawbacks to this approach. Because the content-layer is application-aware, most organizations will eventually implement multiple ILM solutions across different applications and content areas. If each ILM application has its own dedicated silo of storage, key benefits of ILM are lost.

Buying, deploying and managing distinct islands of storage increases storage hard ware and management costs--something IT is trying to avoid in times of growing data volumes.

When a specific content-layer application manages the storage, it's difficult to switch ILM vendors, add a new storage supplier, use a new computing platform, or take advantage of other technology advances. Companies using dedicated storage risk locking into that supplier for the life of the data.

To reduce costs for data management, storage acquisition (while maintaining flexibility) it's best to create a unified storage environment that can support multiple applications. You'll want to start by creating a policy-based data management environment as a foundation for multiple content-layer applications.

What Makes a Policy-Based Data Management Foundation?

To support a wide range of content-layer applications, the data management layer must provide:

* Unified storage

* Automated data access, protection and retention, based on customized policies