I read with interest a new paper from Xiotech that puts forward a new performance metric called the “Storage Value Index”. The Storage Value Index takes into consideration several key characteristics of an IO subsystem to give an overall numerical grade to determine the true value of your, or a proposed, IO subsystem. The basic formula for the Value Index is:
Storage Value Index = (TUC*IOPS*WY)/cost
Where:
TUC=Total usable capacity in Terabytes
IOPS=validated IOs per second (SPC-1 results for example)
WY=Warranty years (or years of paid maintenance if added to cost)
Cost=Cost of validated system
I found this to be an interesting metric except for one problem: it is only taking into consideration one side of the performance issue, IOPS. Why do I say this? Let’s look at some results from applying this metric to see where there may be issues with this value. Look at table 1 which uses values from the SPC website for its data source.
Table 1: Calculated Storage Value Indexes
From consideration of Storage Value Index (SVI) alone we would conclude from the results in Table 1 that the Fujitsu DX8400 would be the best IO subsystem because of its SVI of 35.4, followed by the Infortrend at 28.7 and so on. However this SVI is not giving us the entire performance picture. Notice that the systems with the lowest latency are being penalized by the ability of higher latency systems to add disks to increase IOPS.
In my work with Oracle tuning both prior to and during my tenure with Texas Memory Systems, my primary indication of IO subsystem problems is the read latency. Generally speaking the higher the IO latency the worse the system will perform. If you notice, the SVI doesn’t include anything dealing with latency. From queuing theory we know that IOPS and latency are not dependent on each other. To increase IOPS we can just add queues. I can have hundreds of thousands of IOPS and still have latencies in the 10-20 millisecond range just by adding disk drives to a system. So, it should be obvious if we want to take into consideration the true value if a system we must take into account the latency of that system at the measured IOPS value used in the SVI calculation. To this end I propose the latency adjusted SVI is a better measure as follows:
Adjusted Storage Value Index = (TUC*IOPS*WY)/(cost*L)
Where:
TUC=Total usable capacity in Terabytes
IOPS=validated IOs per second (SPC-1 results for example)
WY=Warranty years (or years of paid maintenance if added to cost)
Cost=Cost of validated system
L=Latency at measure IOPS level
Taking into account the latency now makes our results adjusted by both the throughput (IOPS) and the response time (latency) and gives a true Storage Value Index. Table 2 shows the results with this adjustment.
Table 2: Adjusted Storage Value Index
As you can see, by taking into account the final performance metric, latency, the results now give a better understanding of the complete IO subsystem.
In addition, the actual projected operating costs (floor space, electricity and cooling) for the warranty period should be added to the cost figures to get the true monetary cost of the systems to be compared. Unfortunately that information is not provided or easily obtainable.
References:
Xiotech White Paper: “Strategies for Measuring and Optimizing the Value of Your Storage Investments”, May, 2010
http://www.storageperformance.org/results/benchmark_results_spc1/#spc1
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