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Can we get some context with IOPS and other metrics?

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Storage I/O trends

Server, storage and IO metrics that matter need context

There is an old saying that the best I/O (Input/Output) is the one that you do not have to do.

In the meantime, let’s get a side of some context with  them IOPS from  vendors, marketers and their pundits who are tossing them around for server,  storage and IO metrics  that matter.

 

Expanding the conversation, the need for more context

The good news is that people are beginning to discuss  storage beyond space capacity and cost per GByte, TByte or PByte for both DRAM  or nand flash Solid  State Devices (SSD), Hard  Disk Drives (HDD)  along with Hybrid  HDD (HHDD)  and Solid State Hybrid  Drive (SSHD) based solutions. This applies to traditional enterprise or SMB IT  data center with physical, virtual or cloud based infrastructures.

hdd and ssd iops

 

This is good because it expands the conversation beyond just  cost for space capacity into other aspects including performance (IOPS, latency,  bandwidth) for various workload scenarios along with availability, energy  effective and management.

Adding a side of context

The catch is that IOPS while part of the equation are  just one aspect of performance and by themselves without context, may have  little meaning if not misleading in some situations.

 

Granted it can be entertaining, fun to talk about or  simply make good press copy for a million IOPS. IOPS vary in size depending on  the type of work being done, not to mention reads or writes, random and  sequential which also have a bearing on data throughout or bandwidth (Mbytes  per second) along with response time.

 

However, are those million IOP's applicable to your  environment or needs?

 

Likewise, what do those million or more IOPS represent about type of work being done? For example, are they small 64 byte or large  64 Kbyte sized, random or sequential, cached reads or lazy writes (deferred or  buffered) on a SSD or HDD?

 

How about the response time or latency for achieving them  IOPS?

 

In other words, what is the context of those metrics and why  do they matter?

 

storage i/o iops
Click on image to view more metrics that matter including IOP's for HDD and SSD's

 

Metrics that matter give context for example IO sizes  closer to what your real needs are, reads and writes, mixed workloads, random  or sequential, sustained or bursty, in other words, real world reflective.

 

As with any benchmark take  them with a grain (or more) of salt, they key is use them as an indicator then  align to your needs. The tool or technology should work for you, not the other  way around.

 

Here are some examples of context that can be added to  help make IOP's and other metrics matter:

  • What is the IOP size, are they 512 byte (or  smaller) vs. 4K bytes (or larger)?
  • Are they reads, writes, random, sequential or  mixed and what percentage?
  • How was the storage configured including RAID,  replication, erasure or dispersal codes?
  • Then there is the latency or response time and  IO queue depths for the given number of IOPS.
  • Let us not forget if the storage systems (and  servers) were busy with other work or not.
  • If there is a cost per IOP, is that list price  or discount (hint, if discount start negotiations from there)
  • What was the number of threads or workers, along  with how many servers?
  • What tool was used, its configuration, as well  as raw or cooked (aka file system) IO?
  • Was the IOP's number with one worker or multiple  workers on a single or multiple servers?
  • Did the IOP's number come from a single storage  system or total of multiple systems?
  • Fast storage needs fast serves and networks,  what was their configuration?
  • Was the performance a short burst, or long  sustained period?
  • What was the size of the test data used; did it  all fit into cache?
  • Were short  stroking for IOPS or long stroking for bandwidth techniques used?
  • Data  footprint reduction (DFR)  techniques (thin provisioned, compression or dedupe) used?
  • Were write data committed synchronously to  storage, or deferred (aka lazy writes used)?

 

The above are just a sampling and not all may be relevant  to your particular needs, however they help to put IOP's into more contexts.  Another consideration around IOPS are the configuration of the environment,  from an actual running application using some measurement tool, or are they  generated from a workload tool such as IOmeter, IOrate,  VDbench among others.

 

Sure, there are more contexts and information that would  be interesting as well, however learning to walk before running will help  prevent falling down.

 

Storage I/O trends

Does size or age of vendors make a difference when it  comes to context?

Some vendors are doing a good job of going for out of  this world record-setting marketing hero numbers.

 

Meanwhile other vendors are doing a good job of adding  context to their IOP or response time or bandwidth among other metrics that  matter. There is a mix of startup and established that give context with  their IOP's or other metrics, likewise size or age does not seem to matter for  those who lack context.

 

Some vendors may not offer metrics or information  publicly, so fine, go under NDA to learn more and see if the results are  applicable to your environments.

 

Likewise, if they do not want to provide the context,  then ask some tough yet fair questions to decide if their solution is applicable  for your needs.

 

Storage I/O trends

Putting this all into context

What this means is let us start putting and asking for metrics  that matter such as IOP's with context.

 

If you have a great IOP metric, if you want it to matter  than include some context such as what size (e.g. 4K, 8K, 16K, 32K, etc.),  percentage of reads vs. writes, latency or response time, random or sequential.

 

IMHO the most interesting or applicable metrics that  matter are those relevant to your environment and application. For example if  your main application that needs SSD does about 75% reads (random) and 25%  writes (sequential) with an average size of 32K, while fun to hear about, how  relevant is a million 64 byte read IOPS? Likewise when looking at IOPS, pay  attention to the latency, particular if SSD or performance is your main  concern.

 

Get in the habit of asking or telling vendors or their  surrogates to provide some context with them metrics if you want them to  matter.

 

So how about some context around them IOP's (or latency  and bandwidth or availability for that matter)?

 

Ok, nuff said (for now).

Cheers gs


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