Due to the enormous cost of selecting and migrating to a completely new primary storage infrastructure, most organizations try to wring every last drop of functionality out of their storage resources. That's one reason why most storage deployments are viewed as five-year investments.
Yet with corporate data growing at geometric rates, the notion of deploying a platform that can scale out for such a long time -- not to mention the idea you can plan that far into the future accurately -- is becoming a joke. Many "long-term" storage investments have hit the wall much earlier than anticipated, incurring uncomfortable trips to the corner office. Hey, didn't you say those big, expensive hunks of hardware were going to last?
Face it -- upgrading your storage infrastructure is going to happen more often than you'd like. But at least server virtualization has dramatically decreased the pain involved in making a midstream migration from one storage platform to another or of running more than one system in parallel. The truth is your ability to predict your future needs is more difficult than ever. In fact, you'll probably be wrong -- and that's OK.
The old approach
Most enterprise SANs are built around a controller and disk-shelf architecture. Typically, the controller resources are sized based on the total amount of host I/O required on the front end and the amount of disk resources addressed on the back end.
In these types of platforms, an unexpected spike in the number of disk resources required might mean replacing the controllers while continuing to leverage the same disk. Fortunately, most vendors that use this kind of architecture make controller upgrades relatively easy -- sometimes not even incurring downtime.
In many cases, upgrading previous-generation technology simply to avoid the hassle of migrating was a key factor in deciding whether to extend the life of an existing platform.
The emerging reality
That poor trade-off need not persist in environments where server virtualization has been aggressively employed. In such environments, the data migration process has become almost easy. Once the new storage has been set up in parallel with the old, it's just a matter of a few mouse clicks to start moving virtual machines from one platform to the other, often without introducing any perceptible service interruption.
This new ease of shuffling data opens the door to new storage planning concepts. Instead of planning for and buying a primary storage platform that will take the organization through the next five or six years, many organizations find that planning to run a consistent rotation of two different systems in parallel is more desirable -- and offers the ability to expand while retaining the value of the initial long-term investment.
In this approach, storage purchases are still made with the full intention that they last five years; the difference is that they aren't intended to scale through five years of growth. Instead, somewhere around year three of that window, additional investment into the first platform stops, and a second, smaller deployment of a current-generation primary storage platform is made in parallel. That system then absorbs organic growth through the next two years, often fielding more demanding applications that can take advantage of improvements made between the generations.
Then, as the first platform reaches its end of life, the second is expanded to completely take over for it and the first system is retired. A year later when the second platform reaches its three-year midlife, the cycle continues and a new storage platform is introduced to absorb organic growth through its end of life, and so on.