Nutanix X-Ray Benchmarking tool – Introduction

I’ve been excited to write about X-ray for a while now, but I’ve not had the time. But the opportunity has presented itself where I could kill two birds with one stone and do some performance comparisons between Nutanix AHV Turbo Mode and other platforms on the same underlying hardware, so what better time to review X-ray as part of this process.

So for those of you who have not heard of X-Ray, it wouldn’t be unreasonable to assume it’s just another benchmarking tool to further muddy the waters when comparing different platforms.

However X-Ray takes a different approach, to quote Paul Updike who is part of Nutanix Technical Marketing Engineering:

Normally performance is your test variable and you measure the effect on the system. X-ray is upside down, performance of an app in a VM is the control and our test variable is the system. We measure the effect on the control.

So if all you want is “hero numbers” you’ve come to the wrong place, although  X-Ray does have a peak performance micro-benchmark test built-in, it’s far from real world in comparison to the other tests within X-ray.

The X-Ray virtual appliance is recommended to be ran on a cluster which is not the target for the testing, such as a management cluster. But for those environments where this additional hardware may not be available, it can also be deployed on VirtualBox or VMware Workstation on your PC or laptop.

Also if you have an Intel NUC, you could deploy Nutanix Community Edition (CE) and run X-Ray on CE which is based on AHV.

In addition to the different approach X-ray takes to benchmarking, I like that X-ray performs fully automated testing across multiple hypervisors including ESXi, AHV as well as different underlying storage. This helps ensure consistent and fair comparisons between platforms, or even comparisons between Nutanix node types if you decide to compare model types before making a purchasing decision.

X-ray has several built in tests which are focused not just on outright performance, but on how a system functions and performs during node failure/s, with snapshots as well as during rolling upgrades.

The reason Nutanix took this approach is because it is much more real world than simply firing up I/O meter with lots of outstanding I/O with a 100% random 4k read. In the real world, customers performance upgrades (hopefully regularly to take advantage of new functionality and performance!), hardware does fail when we can least afford it and using space efficient snapshots as part of an overall backup strategy makes a lot of sense.

Now let’s take a look at the X-Ray interface starting with an overview:


X-Ray is designed to be similar to PRISM to keep that great Nutanix look and feel. The tool is very simple to use with three sections being Tests, Analyses and Targets.

To get started is very quick/easy, just open the “Targets” view (shown below) and select “New Target”.


In the “Create Target” popup, you simply, provide a name for the target e.g.: “Nutanix NX-3460 Cluster AHV”, select the Manager type, being either vCenter for ESXi environments or PRISM for AHV.

Then select the cluster type, being Nutanix (i.e.: A Nutanix NX, Dell XC, Lenovo HX or HPE/Cisco software only) OR “Non-Nutanix” which is for comparisons with platforms not running Nutanix AOS such as VMware vSAN.


For VMware environments, you then provide the vCenter details and regardless of the hardware type or platform, you supply the out of band management (e.g.: IPMI) details. The out of band management details allow X-ray to perform simulated hardware failure tests which are critical to any product evaluation and pre-production operational verification testing.

X-Ray then allows you to select the cluster, container (or datastore) and networking (e.g.: Port Group) to be used for the testing.


X-ray then discovers the nodes (e.g.: ESXi Hosts) and allows you to add nodes and confirm the IPMI type to ensure maximum compatibility.


Now hit “Save” and you’re good to go! Pretty simple right?

Now to run a test, simply click the test you want to run and select “Add to Queue”.


The beauty of this is X-ray allows you to queue as many tests as you want and leave the system to run the tests, say overnight or over a weekend without requiring you to monitor them and start tests one by one.

In between tests the target systems are cleaned up (i.e.: data and VMs deleted) to ensure consistent / fair results even when running test packages one after another.

Once a test has been ran, you can view the results in the X-Ray GUI (as shown below):


You can also generate a PDF report for individual tests or perform analysis between two tests including of different platforms:


The above results show and overlay between two platforms, the first being AHV (although it’s incorrectly named Turbo mode when it was ran using non Turbo mode AOS version 5.1.1). As we can see, AHV even without turbo mode was more consistent than the other platform.

To create a PDF report, simply use the “Actions” drop down menu and select “Create Report”.XrayCreateReport

The report will create a report which covers off details about X-ray, the Target cluster/s, the scenario being tested and the test results.


It will show simple results such as if the test passed (i.e.: Completed the required tasks) and things like test duration as shown below:


X-Ray also provides built-in tests for mixed workloads, which is much more realistic than testing peak performance for point (or siloed) solutions which are become more and more rare these days. XrayMixedWorkloads

X-Ray’s built in tests are also auto scaling based on the cluster size of the target and allow tuning of the scenario. For example, in the VDI simulator scenario, Task, Knowledge or Power Users can be selected.


X-Ray provides a tool which is free of charge, multi-hypervisor, multi-platform (including non-HCI) which is easy to use for proof of concepts, product comparisons as well as real world, operational verification.

I am working with the X-ray team to develop new built in test scenarios to simulate real world scenarios for business critical applications as well as to allow customers and 3rd parties to validate the benefits of functionality such as data locality.

The following is a series of posts covering Nutanix AHV Turbo Mode performance/functionality comparisons with other products.

Nutanix X-Ray Benchmarking tool Part 2 -Snapshot Impact Scenario

Nutanix X-Ray Benchmarking tool Part 3 – Extended Node Failure Scenario

Peak Performance vs Real World Performance

In this post I will be discussing Real World Performance of Storage solutions compared to peak performance. To make my point I will be using some car analogies which will hopefully assist in getting my point across.

Starting with the Bugatti Veyron Super Sport (below). This car has a W16 engine with 4 turbochargers and produces 1183BHP (~880kW) and has a top speed (peak performance) of 267MPH (431KPH).


The Veyron achieved the world record 267MPH at Volkswagen’s Ehra-Lessien test track in Germany. The test track has a 5.6 mile long straight. This is one of the very few places on earth where the Veyron can actually achieve its peak performance.

Now for the Veyron to achieve the 267MPH, not only do you need a 5.6 mile long straight, but the Veyron’s rear spoiler must NOT be deployed. Now rear spoilers provide down-force to keep stability so having the spoiler down means the car has a reduced ability to for example take corners.


In addition to requiring a 5.6 mile long straight, the rear spoiler being down, the Veyron can also only maintain its top speed (Peak performance) for 12 minutes before the Veyron’s 26.4-gallon fuel tank will be emptied, which is lucky because the Veyron’s specially designed tyres only last 15mins at >250MHP.


So in reality, while the Bugatti Veyron is one of (if not the fastest) production car in the world, even when you have all your ducks in a row, you can still only achieve its peak performance for a very short period of time (in this example <12 mins) and with several constraints such as reduced ability to corner (due to reduced aerodynamics from the spoiler being down).

Now what about Fuel Economy? The Veyron is rated as follows:

City Driving: 29 L/100 km; 9.6 mpg

Highway Driving: 17 L/100 km; 17 mpg

Top Speed: 78 L/100 km; 3.6 mpg

As you can see, vastly different figures depending on how the Veyron is being used.

There are numerous other factors which can limit the Veyron’s performance, such as weather. For example if the test track is wet, or has strong head winds, the Veyron would not be able to perform at its peak.


So while the Veyron can achieve the 267MPH, In the real world, its average (or Real World) performance will be much lower and will vary significantly from owner to owner.

At this stage you’re probably asking “What has this got to do with Storage”?

A Storage solution, be it a SAN/NAS or Hyper-Converged, all can be configured and benchmarked to achieve really impressive Peak Performance (IOPS) much like the Veyron.

But these “Peak Performance” numbers can rarely (if at all) be achieved with “Real World” workloads, especially over an extended duration.

To quote two great guys in the Storage industry (Vaughn Stewart & Chad Sakac):

Absolute performance more often than not, is NOT the only design consideration.

I couldn’t agree with this more. The storage vendors are to blame by advertising unrealistic IOPS numbers based on 4K 100% read and now customers expect the same number of IOPS from SQL or Oracle.

The MPG of the Veyron is like the number of IOPS a Storage array can achieve. It Depends on how the Car or Storage Array is used! The car will get higher MPG if used only on the highway just like a Storage Array will get higher IOPS if only used for one I/O profile.

As the IO size and profile of workloads like SQL & Oracle are vastly different than the peak performance benchmarks using 4K 100% Read IOPS, expecting the same IOPS number for the benchmark and SQL/Oracle is as unrealistic as expecting the Veyron to do 267MPH in heavy traffic.


But like I said, Its the storage vendors fault for failing to educate customers on real world performance so many customers have the impression that peak IOPS is a good measurement, and as a result customers regularly waste time comparing Peak Performance of Vendor A and Vendor B, instead of focusing on their requirements and Real World performance.

In the real world, (at least in the vast majority of cases) customers don’t have dedicated storage solutions for one application where peak performance can be achieved, let alone sustained for any meaningful length of time.

Customers generally run numerous mixed workloads on their storage solutions, everything from Active Directory, DNS , DHCP etc which has low capacity/IOPS requirements , Database, Email and Application servers which may have higher capacity/IOPS requirements to achieve and backup with are low IOPS but high capacity.

Each of these workloads have different IO profiles and depending on storage architecture may share storage controllers / SSDs / HDDs / storage networking all of which can result in congestion / contention which leads to reduced performance.

Before you start considering what vendors storage solution is best, you need to first understand (and document) your requirements along with a success criteria which you can validate storage solutions against.

If your requirements are for example:

  • Host 10TB of Exchange Mailboxes for 2000 users (~400 random Read/Write 32-64k IOPS)
  • Host 20TB Windows DFS solution
  • Host 50TB of Backups
  • Support 1TB active working set SQL Database
  • Host 10TB of misc low IO random workload
  • Have Per VM snapshot / backup / replication capabilities

Then there is no point having (or testing) a solution for 100k Random Read 4k IOPS, as your requirement may be less than 10K IOPS of varying sizes and profile.

Consider this:

If the storage solution/s your considering can achieve the 10K IOPS with the I/O profile of your workloads and can be easily scaled, then a solution able to achieve 20K IOPS day 1, is of little/no advantage to a solution which can achieve 12K IOPS since 10K IOPS is all that you need.

Now if your Constraints are:

  • 12RU rack space
  • 4kw Power
  • $200k

Anything that’s larger than 12RU, uses more than 4Kw of Power or costs more than $200k is not something you should spend your time looking at / benchmarking etc since its not something you can purchase.

So to quote Vaughn and Chad again, “Don’t perform Absurd Testing”. absurdtesting

In my opinion, customers should value their own time enough not to waste time doing a proof of concepts (PoCs) on multiple different products when in reality only 2 meet your requirements.

An example of Absurd testing would be taking a Toyota Corolla on a test drive to a drag strip and testing its 1/4 mile performance when you plan to use the car to pick-up the shopping and drop the kids off at school.

school crossingcarshopping

Its equally as Absurd to test 100% Random Read 4k IOPS or consider/test/compare a storage solutions <insert your favourite feature here> when its not required or applicable to your use case.


  1. Peak performance is rarely a significant factor for a storage solution.
  2. Understand and document you’re storage requirements / constraints before considering products.
  3. Create a viability/success criteria when considering storage which validates the solution meets you’re requirements within the constraints.
  4. Do not waste time performing absurd testing of “Peak performance” or “features” which are not required/applicable.
  5. Only conduct Proof of Concepts on solutions:
    1. Where no evidence exists on the solutions capability for your use case/s.
    2. Which fall within your constraints (Cost, Size , Power , Cooling etc).
    3. Which on paper meet/exceed your requirements!
    4. Where you have a documented PoC plan with a detailed success criteria!
  6. As long as the solution your considering can quickly, easily and non-disruptively scale, there is no need to oversize day 1.
    1. If the solution your considering CANT quickly, easily and non-disruptively scale, then its probably not worth considering.
  7. The performance of a storage solution can be impacted by many factors such as compute, network  and applications.
  8. When Benchmarking, do so with tests which simulate the workload/s you plan to run, not “hero” style 100% read 4k (to achieve peak IOPS numbers) or 100% read 256k (to achieve high throughput numbers).