Tuesday, May 20, 2014

Cloudy I/O Performance - Deciphering IOPS in IaaS (Part 1 of 2)

Note: This is part 1 of a 2 part post. Part 2 can be found here.


Disk performance scaling options in the public cloud seem limited (particularly in Azure as of this writing), but there are ways to increase your IOPS in IaaS solutions. To add to the performance problem, transactional costs of running application tests can be not only time consuming but expensive. To tune your storage performance reliably you will need a fast, consistent way to test different configurations. This article will cover that methodology and lead into a results/guidance article for Azure (but applicable to others) IaaS storage performance.

We'll be doing this testing on Windows, but you could also easily do this on Linux and the results that I'll be sharing are just as applicable there. To accomplish this testing we'll be using the following tools:

Let's begin!


We will proceed in the following order:
  1. Analyze Workload
  2. Create Test Scenarios
  3. Collect and Analyze Results (Mainly in Part 2)
  4. Findings (In Part 2)


If you plan on emulating my tests you'll need to have access to the following:
  • Microsoft Windows Azure account (note this methodology will worth with EC2 or any other platform including standard hardware/on-prem VMs)
  • IaaS VM Configured. A medium size is recommended for testing 4 disks or fewer to limit the available memory. More on that below.
  • Administrator access to your VM.
  • Your workload is in fact disk I/O bound. If you're not sure of that you may want to start with this article.
  • Awareness that you will incur additional storage transaction costs by running these tests.

Analysis/Create Workload

Note: If you're just trying to get a general sense for your VM I/O performance capability, you don't need to collect data for a custom access specification. IOMeter includes several tests you can use so skip to the "Install IOMeter..." section below.

The first thing we need to do is create our workload. By using IOMeter we can develop custom access patterns that model common workloads and have the tool and workloads installed and configured in minutes on any machine. There is nearly endless information on this topic, so I won't attempt to create a definitive source here. For details on how to configure and use IOMeter, see the following videos/articles:

 To create an accurate workload you will need a good understanding of the access pattern of your application. If you don't have that information you can use a tool like Perfmon to do analysis on a fully configured platform. The following counters will be of interest when creating your access specification:

  • Physical or Logical Disk: Average Disk Bytes per Read
  • Physical or Logical Disk: Average Disk Bytes per Write
  • Physical or Logical Disk: Disk Read Bytes/sec
  • Physical or Logical Disk: Disk Write Bytes/sec
  • Physical or Logical Disk: Disk Reads/sec
  • Physical or Logical Disk: Disk Writes/sec

For further information, see this excellent Technet Article.

By collecting this data during the access pattern you wish to emulate you can accurately estimate (with one caveat) the information needed to create the IOMeter access specification. That caveat is determining the sequential vs. random access pattern of the platform since Perfmon analysis will reveal the rest. To determine that, you'll need an understanding of how the platform stores and accesses/writes data. In my case I'm tuning my VM for Splunk, which uses a Map/Reduce functionality that has a highly sequential read/write pattern. If you are unsure of your access pattern then err on the side of configuring for mostly random access (90% or so) since it is generally more common and demanding of the underlying storage subsystem. 

Install IOMeter and Config Access Specification

The following actions can be done on your target testing platform or a different machine to stage settings. We'll be saving our settings for quick use later.

  1. Download and install IOMeter on your server. There are a series of ways to stage files on any VM, but if you're looking for a quick way in the Microsoft ecosystem check out my Onedrive/Azure post.

  2. Open IOMeter as administrator.

  3. Under "Topology" configure your workers. Each worker represents one thread generating I/O. By default it will create one per CPU thread available, but in most cases you will only want one worker per process you are emulating. In my case I'm assuming one large query at a time (and we'll scale from there), so I'll be testing with one worker. If you are unsure stick to one worker and you can move up from there when you become more familiar.

  4. Under "Disk Targets" select the disk you wish to test. This can change in later runs so if the disk you want to test isn't present here select a placeholder.
  5. Under "Disk Targets" configure your "Maximum Disk Size". This configures the size of your test file in sectors, which are considered to be 512 bytes each. To lessen the impact of OS caching you need to ensure this value exceeds the amount of RAM present on the machine to be tested. In my case I'll be testing on a 6GB RAM machine with a (approx) 7.5GB file, so I've configured it for 15000000 sectors. (15000000 sectors * 512 bytes per sector=7,680,000,000 bytes)  To do this quickly take your total desired size (in bytes!) and divide it by 512. (If you aren't certain you got it right, check the size iobw.tst file created at the root of your target drive after the first test is complete)

  6. Testing T: With a 4.5GB Test File

  7. Under "Disk Targets" configure your maximum outstanding I/O. This varies depending on access spec and OS, but I've had consistent (with real application access) results testing with 16 maximum outstanding I/O on windows. 
  8. Under "Test Setup" configure your "Ramp Up Time" and "Run Time". Ramp up need only be about 20 seconds for most scenarios and run time is best between 1 and 10 minutes. My results are based on (many per config) 5 minute tests. 
  9. Under "Access Specification" select your access spec. There is far too much to get into here; either select one or many existing access specifications that suit you needs ("4k 75% read" is a good start if you don't care) or create your own based on your findings from the Analysis/Create workload section. For the purposes of my test I made a "_Splunk" access spec with the following characteristics ascertained from my earlier performance testing:
    1. Transfer Request Size: 32kB (NOTE: My access spec may not reflect yours. Most won't be this large)
    2. Percent Read/Write Distribution: 53% Write/47% Read (NOTE: My access spec may not reflect yours. Most specs won't be this write heavy)
    3. Percent Random/Sequential Distribution: 75% Sequential/25% Random (NOTE: My access spec may not reflect yours. Most specs won't be this sequential)

  10. Add your access specification to the list of queued tests if you haven't done so already (removing all others).

  11. Click the disk icon to save the settings to an ICF file. This file will save all your settings including custom access specifications if applicable. Since this file is what you'll use to shortcut future testing, save it somewhere easy to transfer to other VMs such as OneDrive, Dropbox, SpiderOak, etc.

Run the Test

After setting up or loading your test settings, all you need do is click the green flag to start the test and then select where you would like to save the results. Make sure you don't overwrite any previous results and give the file a meaningful name so you remember what this test represents later, i.e. "results_3disk_1_StorAcct_Striped_32k_sectors_noCache_run1.csv" or similar. 

The test will run for the configured time and then you will be able to run additional tests or analyze results. Since the output is in CSV format, the natural place to look at this data is Excel. When IOMeter starts for the first time on a given disk it needs to create the test file. This will take quite awhile in both Amazon EC2 and Azure. (15 mins for my 7.5G for example) I believe this is due to the way space is allocated on the backend storage. Once this is created, however, you can run subsequent tests on the same volume without needing to wait for the test file to be created. Once the run is done I recommend running several more to ensure your tests aren't subject to wild performance swings. More on analysis in part 2 of this article.

How Much Will This Cost?

Since you're charged by transaction I'm sure you will be wondering how much this will cost. Let's break down your above baseline (system running) cost in Azure:

IOPS are currently capped at 500 for standard tier machines (300 for basic). Storage transactions are currently $0.01 per 100,000. (halved on 3/14/14) For every 5 minute test per disk you access you will then execute a maximum of 150,000 transactions. As a one time per configuration cost, you will need to build the test file which will be (test file size/volume sector size) transactions. For example, a 7.5 Gib test file will be approximately 1,875,000 transactions assuming a default 4kb sector size. (7,500,000,000/4000)

Test transactions + creation transactions = 2 million or so IOPS, or $0.20 @ .01 per 100,000. So... not much. The amount is generally trivial on Amazon EC2 as well. While this methodology will save you some in transaction costs, the main savings will be in time & labor. (which is usually our real cost anyhow!)

Further Optimization

Once you are comfortable with this process I would advise doing the following to further optimize this process. After doing so you may be able to automate the whole routine!

  • Create standard Perfmon counter sets for disk access and save/import them as a template
  • Script the Perfmon analysis with PowerShell
  • Create or download IOMeter templates for common access routines and include them with your set.
  • Script the installation and running of IOMeter, including multiple runs and uploading results to a common location. Easy to do with PowerShell and refer to the IOMeter manual for command line options (page 75 or so).
  • Package up all your assets with a custom installer and put it in an easy to get location. (mmmm... Chocolatey)
  • If you want angry followers and think digital bits are out there to be wasted, auto tweet your results! (maybe not this)

In Closing

I/O testing in the cloud is certainly feasible but requires a little extra discipline. With several access specifications in your toolkit you can conquer most performance problems quickly. What to do if your cloud platform doesn't provide your desired IOPS? Coming up in part 2!

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