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Defining measures
What is an IOPS Really?
Many articles have explored the performance aspects of filesystems, storage systems, and storage devices. Classically, performance results are reported with statements such as Peak throughput is x MBps or Peak IOPS is x . However, what does "IOPS" really mean and how is it defined?
Typically, an IOP is an I/O operation, wherein data is either read or written to the filesystem and subsequently the storage device, although other IOPs exist that don't strictly include a read or write I/O operation (more on that later).
The number of input/output operations per second (IOPS) sounds simple enough, but the term has no hard standard definition. For example, what I/O functions are used during IOPS testing? If the I/O functions involve reading or writing data, how much data is used for a read or write?
Despite not having a precise definition, IOPS is a very important storage performance measure for applications. Think about the serial portion of Amdahl's Law, which typically includes I/O. Getting data to and from the storage device as quickly as possible affects application performance and scalability. With the large number of cores in today's systems, either several applications run at the same time – all possibly performing I/O – or a running application uses a large number of processes, all possibly performing I/O. Storage performance is under even more pressure.
IOPS Specifics
The IOPS acronym implies that more I/O operations per second is better than fewer. The larger the IOPS, the better the storage performance. As a consequence, an important aspect of measuring IOPS is the size of the data used in the I/O function. (I use the terminology of the networking world and refer to this as the "payload size.") Does the I/O operation involve just a single byte or does it involve 1MiB, 1GiB, 1TiB?
Most of the time, IOPS are reported as a plain
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