Test System and Methodology
Our approach to storage testing targets long-term performance with a high level of granularity. Many testing methods record peak and average measurements during the test period. These average values give a basic understanding of performance, but fall short in providing the clearest view possible of I/O QoS (Quality of Service).
While under load, all storage solutions deliver variable levels of performance. 'Average' results do little to indicate performance variability experienced during actual deployment. The degree of variability is especially pertinent, as many applications can hang or lag as they wait for I/O requests to complete. While this fluctuation is normal, the degree of variability is what separates enterprise storage solutions from typical client-side hardware.
Providing ongoing measurements from our workloads with one-second reporting intervals illustrates product differentiation in relation to I/O QoS. Scatter charts give readers a basic understanding of I/O latency distribution without directly observing numerous graphs. This testing methodology illustrates performance variability, and includes average measurements during the measurement window.
IOPS data that ignores latency is useless. Consistent latency is the goal of every storage solution, and measurements such as Maximum Latency only illuminate the single longest I/O received during testing. This can be misleading, as a single 'outlying I/O' can skew the view of an otherwise superb solution. Standard Deviation measurements consider latency distribution, but do not always effectively illustrate I/O distribution with enough granularity to provide a clear picture of system performance. We utilize high-granularity I/O latency charts to illuminate performance during our test runs, and our IOPS to Latency measurements highlight IOPS performance at specific latency points.
Our testing regimen follows SNIA principles to ensure consistent, repeatable testing, and utilizes multithreaded workloads found in typical production environments. We measure power consumption during precondition runs. This provides measurements in time-based fashion, with results every second, to illuminate the behavior of power consumption in steady state conditions. We also present IOPS-to-watts measurements to highlight efficiency.
This evaluation features SSDs of varying capacity, and overprovisioning variations require consideration during performance and power consumption analyses. The Toshiba HK3R2 sample has 960GB of user-addressable capacity, the Micron M500DC features 800GB of capacity, and the Samsung 845DC EVO and Intel DC S3500 models are 480GB. The SSDs are tested over their full LBA range to highlight performance at maximum utilization. The first page of results will provide the 'key' to understanding and interpreting our test methodology.
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