Tiered storage: Heterogeneous vs. homogeneous


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Heterogeneous tiered storage

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In this approach, different technologies are used at each tier. Equipment costs are low, but moving data between tiers can be problematic.

Tiered storage is one of those topics I'm hearing a lot about lately. But actually moving to a tiered storage strategy can be tricky. How do you architect your solution? And how do you move data as its value changes?

When most people think of storage tiers, they think of the same thing: Different types of storage arrays at different price points that are designated to hold different classes of data. Imagine an infrastructure that contains the components as shown in "Heterogeneous tiered storage" on this page. This mythical company has four tiers of storage in use from four different vendors. Such a strategy has been proposed by many, and it makes some sense. The tiers are divided according to technical functionality, price and service levels.

If there's a benefit to mixing enterprise, midrange and internal storage, there's also clearly an underlying problem: How can you move data between tiers when the requirements for that data change? For example, the data collected in a lab might become business critical once a product based on it is developed. Moving to a different storage system usually requires a complete migration project, including both downtime and substantial risk of failure. What if there was a simple way to add data mobility to a tiered storage environment?

Virtualization products seem to answer this question, but few organizations have been willing to deploy them. Volume management products such as Veritas Volume Manager can help, too. But what if data migration wasn't required at all?

Homogeneous tiered storage
By varying protection of volumes within an enterprise array, you can achieve a more manageable storage architecture. Initial equipment costs may be higher than with the heterogeneous approach.

Tiering data on a single array
A single array strategy would be viable if you could adjust parameters of the storage within the array to meet different requirements. Some of these parameters include RAID protection (availability), replication (recoverability) and cost. Many arrays have the ability to replicate data, and some can vary the level of RAID protection. Different RAID levels yield different levels of availability and recoverability of data, and they are important to the cost factor as well.

A single enterprise-class array can easily scale to hold tens or even hundreds of terabytes of data, and can service dozens of hosts over a SAN. High-end arrays could hold the majority of a company's data, but the challenge of reducing costs remains. Lately, more businesses are considering creating different classes of storage and price points within a single array by varying the level of RAID protection, mirroring, replication and even drive types. And at least one vendor is bringing a specialty array to market to service this need.

The simplest way to vary the class of service is simply to turn off the features that enterprise arrays are known for. This is actually the standard practice for most organizations, whether or not they realize it. High-value data might have multiple internal point-in-time copies or business-continuance volumes (BCVs), while lower-value data does not. Similarly, only a small portion of an array's contents is normally replicated off site for disaster recovery purposes. These two methods create de facto tiers of service at vastly different price points than the nonmirrored or nonreplicated data in the same array.

Replication is expensive. The bandwidth to replicate a terabyte of storage out of state for one year could easily cost more than all of the hardware involved. So varying the replication of data is a sensible way to implement storage tiers. BCVs can also get costly if there are too many in use, and there's often a large part of enterprise storage set aside for use as BCVs even if they are never used. But turning off these features just brings ridiculously high prices down to simply expensive.

This was first published in December 2003

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