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|Utilization can be a matter of perspective|
From the host side, all of the storage on the array that is allocated for it is the pool of raw storage available. In the context of the array, that would be considered just one pool of used storage. You may vastly overestimate utilization if you don't go beyond host statistics.
Room for improvement
Fundamentally, utilization is a question of balancing the usage of a storage resource with the need to maintain a buffer for growth. If all growth was planned, just-in-time provisioning would allow storage resources to be added only when needed, and near 100% utilization would be possible. But budgeting and purchasing cycles, installation time and continual growth conspire to require a buffer of unused storage. For this reason, most managers overspecify storage requirements by 20% to 50%.
In many cases, buffers are specified all the way up the chain, from the database administrator through the storage manager. Let's say an application requires 10GB of storage. If everyone includes a 50% buffer for growth, the DBA will ask for 15GB, the systems administrator for 22.5GB and the storage administrator will buy 34GB. This will yield a true utilization rate of just 30%.
While no rule of thumb will fit all situations, a 20% buffer should suffice for many systems. This should provide adequate time to provision more storage, but if your purchasing timeframe is longer than a few months, a much larger buffer may be required. In our example, a 20% buffer gives us just over 17GB of storage purchased, yielding 58% utilization.
One of the less obvious benefits of a shared utility model for storage (December 2002 Integration, "End to end management in sight") is a reduction of the amount of storage required to provide a growth buffer for unexpected requests. Most systems won't experience sudden growth, and the average rate for a number of systems will be more even and predictable. If a large storage environment is shared by a number of applications, a smaller buffer can be maintained, improving overall utilization dramatically.
A smooth and regular process of adding new space to a shared SAN can also reduce the planning timeframe. Most dedicated storage is specified for the life of an application, which can lead to tremendous waste in both disk space and dollars. "Buying storage in advance is wasteful," demonstrates the cost differences between purchasing decisions. The center two columns compare buying four years of storage at today's prices and waiting to buy each year's requirement at the current prices. Although both cases end up with 310GB of storage after four years, annual purchasing saves more than 30% of the cost.
This effect is magnified if the growth projections are incorrect. Many application managers aren't sure how much space they'll need in three years' time, so they overspecify to be on the safe side. In our example, slowing the growth to just 20GB per year saves an additional 2% over annual purchasing. But annual forecasting could also allow the storage manager to reduce the buffer to 20% after the first year, drastically reducing the amount of storage purchased and increasing the cost savings to 40%.
You may also be able to improve file system utilization by focusing on buffer requirements for individual hosts and file systems. On database servers, file systems often don't need to be expanded because new file systems will be created for new data files. Therefore, database filesystems can be filled to almost 100% without concern. Similarly, many hosts won't experience much data growth, so their buffers can be reduced.
The most effective way to improve storage utilization for servers with external storage is to simply to connect them to a shared SAN. A true SAN (as opposed to a system of dedicated storage using FC) allows unused storage to be reallocated to more needy systems dynamically. Growth is averaged across many systems, enabling frequent forecasting and provisioning. A true shared SAN managed as an internal utility can result in tremendous utilization improvements and cost savings.
This was first published in February 2003