Nutanix X-Ray Benchmarking tool – Extended Node Failure Scenario

In the first part of this series, I introduced Nutanix X-Ray benchmarking tool which has been designed very differently to traditional benchmarking tools as the performance of the app is the control and the variable is the platform,not the other way around.

In the second part, I showed how Nutanix AHV & AOS could maintain the performance while utilising snapshots to achieve the type of recovery point objective (RPO) that is expected in production environments, especially with business critical workloads whereas a leading hypervisor and SDS platform could not.

In this part, I will cover the Extended Node Failure Scenario in X-Ray and again compare Nutanix AOS/AHV and a leading hypervisor and SDS platform in another real world scenario.

Let’s start by reviewing what the description of the X-ray Extended node failure scenario.


I really like that X-ray has a scenario which shows a simulated node failure as this is bound to happen regardless of the platform you choose, and with hyperconverged platforms the impact of a node failure is arguably higher than traditional 3-tier as the nodes contain some data which needs to be recovered.

As such, it is critical before choosing a HCI platform to understand how it behaves in a failure scenario which is exactly what this scenario demonstrates.


Here we can see the impact on the performance of the surviving VMs following the power being disconnected via the out of band management interface.

The Nutanix AOS/AHV platform continues to run at a very steady rate, virtually without impact to the VMs. On the other hand we see that after 1 hour the other platform has a high impact with significant degradation.

This clearly shows the Acropolis Distributed Storage Fabric (ADSF) to be a superior platform from a resiliency perspective, which should be a primary consideration when choosing a platform for any production environment.

Back in 2014, I highlighted the Problems with RAID and Object Based Storage for data protection and in a follow up post I discussed how Nutanix Acropolis Distributed Storage Fabric (ADSF) compares with traditional SAN/NAS RAID and hyper-converged solutions using Object storage for data protection.

The above results clearly demonstrate the problems I discussed back in 2014 are still applicable to even the most recent versions of a leading hypervisor and SDS platform. This is because the problem is the underlying architecture and bolting on new features is at best masking the constraints of the original architectural decision which has proven to be significantly flawed.

This scenario clearly demonstrates the criticality of looking beyond peak performance numbers and conducting a thorough evaluation of a platform prior to purchase as well as comprehensive operational verification prior to moving any platform into production.

Related Articles:

Nutanix X-Ray Benchmarking tool Part 1 – Introduction

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

Nutanix X-Ray Benchmarking tool – Snapshot Impact Scenario

In the first part of this series, I introduced Nutanix X-Ray benchmarking tool which has been designed very differently to traditional benchmarking tools as the performance of the app is the control and the variable is the platform,not the other way around.

This is done by generating realistic IO patterns (e.g.: Not 100% 4k read) and then performing functions against the platform to see how the control (the VM application performance) is impacted by the underlying platforms functionality.

A great example of this is performing snapshots as the first step in a space efficient backup solution.

X-Ray has a built in test which generates an OLTP workload which is ran for 8 hours which for an all flash platform generates 6000 IOPS across the database and 400 IOPS for the logs. The scenario is detailed in the X-Ray report shown below.


The Snapshot impact scenario is then ran against multiple platforms and using the Analysis functionality within X-ray. we can generate a report which overlays the results from multiple platforms.

The below example is GA Acropolis Hypervisor (AHV) on AOS 5.1.1 verses a leading hypervisor and SDS platform showing the snapshot impact scenario.


Each of the red lines indicate a snapshot and what we observe is the performance of both platforms remains consistent until the 10th snapshot (shown below) where the Nutanix platform continues without impact and the leading hypervisor and SDS platform starts degrading significantly.


In the real world, customers use the intelligent features of storage, SDS or hyper-converged platforms but rarely test how this functionality works prior to purchasing. This is because it’s difficult and time consuming to do so.

Nutanix X-Ray tool makes the process of validating a platforms performance under real world scenarios a quick and easy process and provides automatically generated reports where accurate comparisons can be made.

What this example shows is that while both platforms could achieve the required performance without snapshots, only Nutanix AHV & AOS could maintain the performance while utilising snapshots to achieve the type of recovery point objective (RPO) that is expected in production environments, especially with business critical workloads.

As part of the Nutanix Solutions and Performance engineering organisation, I can tell you that the focus for Nutanix is real world performance, using data reduction, leveraging snapshots, mixing workloads and testing a large scale.

In upcoming posts I will show more examples of X-Ray test scenarios as well as comparisons between GA Acropolis Hypervisor (AHV) & AOS 5.1.1 verses a leading hypervisor and SDS platform.

Related Articles:

Nutanix X-Ray Benchmarking tool Part 1 – Introduction

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

Dare2Compare Part 6 : Nutanix data efficiency stats can’t be found

If you’ve not read Parts 1 through 5, we have already proven several claims by HPE Simplivity regarding Nutanix to be false, as well as explored the misleading way in which HPE SVT promote data efficiency.

We continue with Part 6 where we will discuss HPE’s claim that “Nutanix data efficiency stats are stealthier than a ninja”. (below)

While HPE’s claim is an attempt to create Fear, Uncertainty and Doubt (FUD), HPE are partially correct in that we (Nutanix) have done a very poor job of promoting the arguably market leading data efficiency that Nutanix provides.

In fact, several colleagues and I created a feature request to properly report in a clear and detailed way, the ADSF data efficiencies and I am pleased to say these changes were included as part of the recent AOS 5.1 release.

Now what Nutanix users see in PRISM “Storage” view is (as shown below):

  1. A Capacity optimization overview
  2. Data reduction ratio which is made up of deduplication, compression and erasure coding savings*.
  3. Data reduction savings which is a total GB/TB/PB value from data reduction
  4. An Overall Efficiency ratio which is a combination of Data Reduction, Cloning and Thin Provisioning

*Metadata copies/snapshops/pointers etc are not included in the deduplication value as they are not deduplication.

The resulting summary is very clear and easy to understand so customers can see what efficiencies are from data reduction, and which savings (which typically form by far the largest “efficiency”) come from Cloning and thin provisioning.


One major item which will be included in an upcoming release is zero suppression. Zero suppression is a capability which has been in Nutanix Distributed Storage Fabric since Day 1 and it avoids unnecessarily storing zeros, instead storing metadata which achieves the same outcome but is much higher performance and uses much less capacity.

Nutanix snapshots or pointer based copies (depending on how you refer to them) are also not included in the overall efficiency number, however these will also be included as a seperate line item in a future release as we aim to be very clear regarding what data efficiencies a customer is achieving with Nutanix.

Some vendors recommend Eager Zero Thick (EZT) VMDKs on vSphere, and then deduplicate the zeros which artificially increases the deduplication ratio. Nutanix does not do this as it’s inefficient to create more data to deduplicate when you can simply avoid writing the data in the first place. However we do plan to report the savings from Zero suppression as a seperate line item as it is a value our platform provides.

For a more detailed view, Nutanix customers can dive down into the storage,Diagram view where admins can view of each containers data efficiency breakdown (as shown below).


As we can see, Nutanix is very transparent showing what data reduction features are enabled, what ratio is being achieved, the total, used, reserved and even Thick Provisioned storage with an effective free based on physical multiplied by data reduction ratio and an overall efficiency value.

Now that we’ve covered off how Nutanix measures and reports on data reduction/efficiency, I’d like to highlight a critical factor when discussing data reduction/efficiency and that is that data efficiency is totally dependant on the individual customers data. For the same dataset, the difference between vendors with the same capabilities, e.g.: Deduplication, Compression and Erasure Coding (EC-X) are unlikely to be vastly different (or better put, change a business outcome one way or another) despite what each vendor will say about their implementation of such technologies.

In short: The biggest factor in the achieved data reduction is not the vendor, it’s the customer data.

With that said, if you’re comparing HPE SVT and Nutanix, then there is a pretty major delta between the two products in terms of capabilities and that is because Nutanix supports Erasure Coding (EC-X) and HPE SVT does not.

As a result, Nutanix has a major advantage as Erasure Coding in the Nutanix Acropolis Distributed Storage Fabric (ADSF) is complimentory to both deduplication and compression.

Unlike Compression and Deduplication, Erasure Coding can provide savings (or another way to look at it would be lower data redundancy overheads) regardless of the data type.

So where Deduplication and Compression will get minimal/no savings for data such as Video files, Erasure Coding still provides savings so the delta between Nutanix and HPE SVT will only increase in Nutanix favour the less the customer data will dedupe and/or compress.

HPE SVT on the other hand has a RAID (RAID 6 being N-2 usable or RAID 60 being N-4 usable) overhead and on top of that, use replication (2 copies / 50% usable) for an usable capacity (of raw) of well below 50% depending on the number of drives per node.

Nutanix, using RF2 and EC-X provides between 50% (minimum) and 80% (maximum) usable capacity of RAW and with RF3 (N+2) between 33% (minimum) and 66% (maximum) usable excluding the benefits of compression and deduplication.

The next major factor in data efficiency ratios is how they are measured!

In Part 1 I have already covered how misleading HPE SVT’s 10:1 efficiency guarantee is, and this is a great example of why it can be difficult to compare apples/apples between vendors. Nutanix on the other hand does not measure data efficiency in the same misleading manner.

In Summary:

  1. Nutanix AOS 5.1 has comprehensive data reduction/efficiency reporting within the PRISM HTML GUI
  2. Nutanix data reduction capabilities exceed that of HPE SVT as both products have Dedupe and Compression, but Erasure Coding (EC-X) is only supported on Nutanix
  3. All data reduction capabilities on Nutanix are complimentory, so Dedupe , Compression and Erasure Coding can all work together to maximise savings.
  4. Erasure Coding provides data reduction even for data which is not compressible or dedupeable
  5. Nutanix data efficiency stats are easily visible in the PRISM GUI and are much more detailed than HPE SVT

Return to the Dare2Compare Index:

But wait, there’s more!

As far as data reduction results are concerned, they are all over twitter and a simple search comes up with many examples. The first one being my favorite. Not because of the data reduction ratio itself but because it shows one of the major values of a 100% software solution where a simple software upgrade (which is one-click rolling, non-disruptive) provided the customer a significantly higher data reduction ratio. So basically, the customer got more capacity for free!

Note: None of the below show the latest data efficiency reporting capabilities from AOS 5.1.

Here are a few other examples which I found using this Twitter search: