The Storage Economist

Quite often while discussing cost-reduction, we draw a simple x-y graph that depicts:

• Flat, or nearly flat IT budgets, year over year
• Increasing demand for storage (and VM apps) capacity, usually at a 30-50% growth-rate year-to-year
• The requirement to drive down unit costs to allow the growth-rate, given a flat budget

We tend not to question the growth-rate, right? It is what it is. IT does not seem to have control around how many new apps, systems, or user data requirements emerge each year, and we must simply react to the demand. I see a change required in some of these assumptions about IT being able to curb or challenge real-growth-rate. At a minimum, we can begin to distinguish physical from logical growth.

For many IT shops, capacity growth in the storage space has a come-and-ask-for-it mentality. We don’t throw data away anymore, and the price of a disk is cheap enough to keep all data and to keep it online all the time. This kid-in-a-candy store mentality is unsustainable for the near future. Global recession fears, local austerity initiatives, capital preservation, and protection cash are all real requirements in today’s IT environments. The growth-rate of structured data was noted to be 30% per year in the next few years (see IDC: State of File-Based Storage Use in Organizations: Results from IDC’s 2011 Trends in File-Based Storage Survey, doc #228824, June 2011) and unstructured tends to be around 60% y/y.

Part of the problem with curbing storage appetites is that IT planners and storage architects don’t always have good visibility from the business or apps regarding the growth-rate needed to support the business. There are new projects on the horizon for:

• Big data project
• New apps and systems, like VDI
• Change in direction relative to market trends
• Planned and unplanned spikes (opportunities or risks) to be satisfied
• New legislation or consumption patterns that radically change demand
• Cloud, and all things related to the cloud

Most planners tend to look back at the past few years to understand history in order to predict the future. This is always safe, but often insufficient.

Another tactic is to employ storage architecture elements that are more accommodating to unknown demands. Having some of these technologies in place may not change the unpredictable nature of the growth, but it can soften the impact on the bare-metal requirements needed to support logical/virtual growth:

• Thin provisioned volumes
• Virtualization of arrays, volumes, machines
• Compression
• De-duplication
• Archiving of stale data

These above examples can help deliver a different physical capacity growth, while at the same time, presenting to the consumer a logical view of capacity that can meet the business or data demands.

In my next post, I will review some of these roadmap or step-down options available within the storage architecture. These tactics may not impact the outward demand for high-growth storage, but they can reduce the on-the-floor infrastructure and investments required to present a logical presentation of high-growth capacity.