Evaluating Nutanix’ original & unique implementation of Data Locality

Recently DeepStorage.net published a paper “Evaluating Data Locality” which was commissioned by VMware who have been critical of Nutanix ever since releasing VSAN.

The technology report preface includes strong language (below) broadly painting (data) locality as complicated and antithetical to modern storage. It is reasonable to expect that the report supports these claims with details of specific data locality implementations (such as those by Nutanix), but not a single real-life scenario is referenced. The author’s only responses to my enquiries  for the testing methodologies utilized was a tweet advising that the claim is only theoretical.

HowardBlogPreface

The report is clearly just an opinion piece without factual (at least not tested/validated) basis. Rather than reflect a rigorous examination of pros and cons of data locality, it appears the report may instead reflect a intention by sponsor VMware to create Fear, Uncertainty and Doubt (a.k.a FUD) around the Data Locality  capability that its own product lacks. The document certainly  does not highlight any advantages of VMware’s own product.The beauty of this kind of 3rd party commissioned report is it provides Nutanix with an opportunity to highlight the advantages of our platform’s capabilities  – which I will be doing in this (very) long post.

Nutanix implementation of Data locality is unique and, in my opinion, a significant advantage which explains why competitors lacking the same capabilities focus so much time/attention on trying to discredit it. In fact, I would go so far as to say the term “Data locality” is synonymous with Nutanix, at least in the context of hyper-converged infrastructure (HCI).

I contacted the author of the paper (Howard Marks) who stated:

“Of course not everything there was re: Nutanix implementation,” but the report is very similar to much of the competitive FUD that VMware uses in the field against Nutanix. This leads me to conclude Nutanix, especially being the market leader, is a significant if not the primary focus for the commissioning of this paper. While plenty of information is publicly available regarding Nutanix Data Locality such as the Nutanix bible and various blog articles such as “Data Locality & Why is important for vSphere DRS clusters” which date back to 2013, it’s common for competitors and analysts to get even the 101 level basics incorrect when it comes to the Nutanix implementation.

The report starts by talking about What (DeepStorage.net) mean by data locality. It stays very much at the 101 level, talking about reading data from a local device and avoiding network hops, which is only a small part of the advantage that Nutanix data locality provides.

WhatDoWeMeanByDataLocality

A few key points:

  1. Nutanix does not preferentially store a full copy of the data for each virtual machine on the local storage on the host where it runs.

Nutanix always writes new I/O to the local node, and replicas are distributed throughout the cluster. When a VM moves to another host, new data is again written locally and replicas distributed throughout the cluster.

This means for WRITE I/O, Nutanix Data Locality ensures consistent performance regardless of how many times and VM is moved around a cluster.

Data which is read cold is NOT localised!

For data which is read hot: If the read occurs remotely that 1MB extent is localised and one of the redundant replicas marked for deletion. This ensures subsequent reads for the read hot data are local and ensures there is only one penalty of traversing the network and requesting data from a remote node, however, large or small than penalty may be. Avoiding the penalty, put simply, is not a bad thing as even a 1% efficiency improvement adds up over time.

Virtual Disks (e.g.: VMDK, VHDX or VDISKS) are NEVER moved in their entirety from one node to another following a VM migration. This limitation applies not to Nutanix, but to VMware’s own VSAN where objects (up to 255Gb) need to be moved. Nutanix moves data at the much more granular scale of 1MB regardless of the size of the virtual disk.

Nutanix also does not, and has never done, STRICT LOCALITY as this would be very inefficient and limit the flexibility of a distributed platform. VMware VSAN, on the other hand, has a much more restrictive technique where one node hosts entire objects that almost never move, meaning the bulk of I/O is remote.

With  the release of AOS 4.5 in 2015, Nutanix delivered increased performance (especially from SATA tiers) from the distributed storage fabric by measuring latency for local vs remote and I/O where there is lower remote latency (e.g.: If the local drives are under heavy load) . This scenario is more likely with hybrid platforms.While all flash uptake is steadily rising, this capability makes hybrid a more performant/consistent platform for both new and existing deployments while protecting and maximising the investments already made by Nutanix customer base.

  1. VMs can migrate to any host in a Nutanix cluster, even where ZERO of the VMs’ data exists.

Nutanix data locality puts ZERO restrictions on where VMs can move within a cluster. VM’s can migrate to a host even if it has no local data. As mentioned earlier, Nutanix always writes new I/O to the local node which means subsequent reads (which are common for new data) are serviced locally. The system localizes remote reads only when they occur (at a 1MB granularity).

This DeepStorage.net criticism of data locality is not at all applicable to Nutanix’s data locality implementation. The report highlights some weaknesses of vendors who have quite frankly just adopted the data locality terminology without the underlying architecture of the leading Enterprise Cloud platform from Nutanix.

Let’s look at the next section, “Data locality’s promoted advantages”.

DataLocalityPromotedAdvantages

A few key points:

  1. Nutanix does not claim data locality is the only way to deliver the performance modern datacenters demand.

Nutanix Acropolis distributed storage fabric (ADSF) understands where reads and writes are occurring and how to most intelligently place data and when locality will benefit and when a workload demands more I/O than a single node can provide.

Nutanix released Acropolis Block Services (ABS) in 2016 which allows virtual or physical workloads to enjoy scale out performance using all nodes in a Nutanix cluster. In the case of a physical server, no data locality is available, but if the workload is a VM, some data locality is possible which takes some overhead off the network to maximise the available bandwidth for remote I/O to occur with minimal contention.

The below tweet shows a physical server connected to a 4 node cluster using 4 active paths, then the same physical server expanding automatically to 8 paths when the cluster was expanded to 8 nodes.

ABS can be used with VMs running on Nutanix as well where the I/O requirements are so high that a single controller becomes a bottleneck. These use cases are extremely rare these days, but Nutanix has a (very) good solution for these scenarios while allowing all other VMs to benefit from data locality as ABS is used on a per server (VM or physical) basis.

This is a very good example of Nutanix having multiple solutions for different workloads and use cases as well as being the first to market with these capabilities.

  1. As I mentioned earlier, Nutanix always writes new I/O to the local node, and replicas are distributed throughout the cluster.

Why am I bringing this up for the third (!!) time? This is such a key point because writing locally ensures “a significant fraction of write I/ Os will also go to the local media.” as per the DeepStorage.net report.

This fraction is 50% for Resiliency Factor 2 (RF2) and 33% for Resiliency Factor 3 (RF3).

This means for RF2 results in a 50% less chance of the network or a remote node being a bottleneck to the I/O being written and acknowledged and, of course, 33% for RF3. It also means less unnecessary network utilization and potential contention.

The next section (rightly) talks about “Reduced network traffic”.

ReducedNetworkTraffic

A few key points on reduced network traffic.

  1. The report confirms that reduced network traffic is an indisputable advantage

The report and Nutanix agree, reduced network traffic is a good thing. But what advantages does reducing network utilization provide with these super fast 10/25/40 and even 100Gb networks?

A few examples come to mind when hearing critics talk about data locality. For example, critics also claim that the network is not a bottleneck for storage and latencies are very low these days. Even if this were 100% true, it doesn’t take into account the networking requirements of the virtual machine and the applications. If an app is driving any reasonable level of I/O it’s typically because users are accessing the service being provided by that/those VMs.

So the less I/O (unnecessarily) used for remote storage I/O, the MORE available bandwidth and the LOWER contention there is for actual virtual machine/user traffic. Keep in mind contention can occur without network links being 100% utilised.

A second example is when remote I/O occurs it means that two nodes are involved in the I/O path, as opposed to one. The CPU for Node 1 is in a wait state while waiting for Node 2 to respond. This is a simple example of remote I/O (or a lack of data locality) having higher overheads from a (In-kernel or VM based) storage controller CPU perspective.

The final example is an economic one. If a customer uses a solution like Nutanix then the requirement to upgrade from 10Gb networking to 25/40/100Gb networking is significantly reduced. In the past, it was common that I would design virtualisation solutions using SAN/NAS which required 4 x 10GB NICs (2 for VM traffic and 2 for IP Storage traffic), or 2 x 10GB for VM traffic and 2 x 8GB FC HBAs for storage traffic.

Since joining Nutanix in 2013, I have seen only a handful of customers who required more than 2 x 10Gb for VM and storage traffic, and this has been in large part due to data locality. For context, I have focused on business critical applications the entire 4+ years I’ve been with Nutanix so the workloads customers are running are the same, or in many cases larger, than the ones which have required 4 x 10Gb NICs in the past.

The next section covers DeepStorage.net thoughts on “The downside to data locality”.

TheDownsideToDataLocality

A few key points on the downside to data locality.

  1. Deepstorage.net is not talking about Nutanix Data Locality

As I mentioned at the start of this article, by DeepStorage.net definition, it is not talking about Nutanix unique implementation of data locality. It is referring to other products in the HCI market trying to emulate Nutanix.

  1. I agree with the article that other vendors’ object based implementations are inefficient.

In short, the other vendors claiming to have data locality don’t really have data locality per se. Their use of data locality refers to limitations of fairly rudimentary file systems / object stores. This strategy is doubtlessly designed to try and elevate their products into conversations where Nutanix is widely considered the market leader due to many unique capabilities like Data Locality implementation.

The next section is “I/O concentration”.

IOconcentration

A few key points on I/O concentration.

  1. Again, Deepstorage.net is not talking about Nutanix Data Locality

Nutanix distributed storage fabric does not use flash devices as “cache” per se like VSAN,

  1. I agree with the article that distributing data across nodes reduces the potential for I/O hotspots.

This is, in fact, exactly what Nutanix does in real time, based on fitness values (patent pending) which takes into account capacity utilization and performance of each individual node and drive. So Nutanix keeps Write I/O local, and proactively (in the write path) ensures that replicas are placed in the optimal place to minimise potential hotspots. This also ensures subsequent reads can be done locally in the vast majority of cases.

The next section covers “Constraints on VM placement / movement & load balancing”.

ConstraintsonVMplacement

A few key points on I/O concentration.

  1. None of the constraints highlighted are applicable to Nutanix.Nutanix does, however, have another unique capability which ensures data locality maximization without any overheads so onto point 2 :)
  2. Nutanix Acropolis Hypervisor (AHV) automatically places VMs powering on or recovering from a HA event onto the node with the most local data.

This is what we refer to as “restoring locality” which is done in the most lightweight way possible by moving the VM and not the data!

This capability is not  new; it’s been built into AHV since day 1 and the below tweet shows what it looks like from the Nutanix PRISM UI.

This function minimizes the chance of data needing to be “localised”.

  1. What the article refers to is an HCI product which is similar to HA pairs where VMs can only run on two nodes where the data is located, which is why DRS being disabled or Manual is recommended.

In reality, this isn’t data locality, it’s just a basic product which has very limited scalability. One of the many issues with this type of product is that a single node failure creates a significant risk and cannot be recovered without hardware replacement.

Nutanix, on the other hand, can restore the resiliency and even tolerate subsequent failures without failed hardware (such as SSD/HDD or even entire nodes) being replaced.

I recently wrote a series of posts after HPE decided to start a campaign of FUD against Nutanix with #HPEDare2Compare. One article in the series specifically covers the resiliency of the Nutanix platform in depth so I encourage you to take a look at that post and the rest of the series.

The next section covers “Data Locality limits VM Migration”.

DataLocalityLimitsVMMigration

A few key points on Data Locality limiting VM Migration.

  1. As previously mentioned, VM’s can migrate to ANY node in a Nutanix cluster, without restriction AND without bulk data movement.

To recap, For data which is never accessed, it is NEVER moved! Only data which is read/overwrite hot is localised and is done so at a 1MB granularity.

Virtual Disks (e.g.: VMDK, VHDX or VDISKS) are NEVER moved in their entirety from one node to another following a VM migration.

Now if you believe the network is not a bottleneck, then this granular localisation is not a problem. But think about it this way; The network is used the same amount of time if a remote read is localised or not, so what’s the problem with localising? The problem is actually not localising the data as subsequent reads hit the network unnecessarily adding some overhead, even if it’s minimal.

  1. If data locality results in data being spread over multiple nodes, how is this worse than a platform without data locality that allows vDisks to “spill” over to other nodes?

The simple answer is “spilling” over between nodes (i.e.: What VSAN does) is at best a band-aid to try and address the fact that VSAN is not a distributed file system. ADSF, on the other hand, is a distributed storage fabric and distributes replicas across the entire cluster by design. This is also done in real time based on the fitness values (patent pending) which takes into account capacity utilization and performance of each individual node and drive.

  1. New micro-services don’t know the underlying storage, and cannot migrate VMs or containers to where the data is located.

Well, lucky Nutanix has a solution for that. The next generation hypervisor (AHV) places VMs automatically on the node with the most local data.

  1. On Nutanix, Data Locality is never random. Because ALL write I/O goes to the node running the VM or container.

So for the emerging market of microservices/containers, etc, Nutanix ADSF is the perfect platform as any new data is written locally (optimally) no matter where the instance starts up in the cluster. If that workload only runs for a short time, or moves between hosts several times, it gets the maximum data locality with no additional overhead as locality for new data is achieved in the write path and on by default.

  1. Static VMs do not require enough capacity on the local node on Nutanix

Back in 2015 this was a perceived problem, but it has in reality never been a problem thanks to ADSF being a truly distributed storage fabric. I wrote the article “What if my VMs storage exceeds the capacity of a Nutanix node?” which covers off this point in detail for those of you who are interested. In short, this is not a problem at all for Nutanix.

For example, in a 100 node cluster one VM running on Node 1 can use all the capacity of the 100 node cluster and this is automatically balanced in real time as discussed earlier by the fitness values (patent pending). This balancing avoids a situation where virtual disks are “spilled” onto new nodes/drives because the distribution of replicas is done at the time of writing the IO.

The next section covers “Data Locality and metadata clones”.

DataLocalityandMetadataClones

One key point on Data Locality and Metadata clones.

  1. Nutanix allows the customer making the metadata clones to chose between maximum performance or maximum capacity savings.

Nutanix shadow clones, which are typically used for VDI golden images as the article mentioned, can also provide maximum data locality and therefore performance for metadata clones when they, for whatever reason, have spread across a large number of nodes (which I don’t see typically, but i’ll address the scenario all the same).

If customers want/need maximum performance, Shadow Clones provide the solution. If  the environment warrants maximum capacity savings, then Nutanix can simply cache read hot data in the content cache on the nodes running the MySQL VMs which also provides a reasonable level of data locality without the capacity overheads of making an entire copy, in this scenario, five times.

I can’t stress enough, remote read I/O is not a problem for Nutanix, it’s just not as optimal as local I/O.

This tweet says it all, and is a phase I coined back at VMworld 2013 which I tweeted out today.

Network utilization or remote I/O on Nutanix, will be in the worst, and most unlikely, case equal to VSAN, but because data locality writes new data locality, all write I/O will be local, making it more efficient than VSAN and other HCI products.

The next section covers “Deduplication”.

DataDedupe

A few key points on Data Locality and Dedupliciation.

  1. Deduplication is the most overrated storage feature!

Deduplication does not, despite popular belief, solve world hunger or typically reduce your real datacenter storage requirements by 10x or even 5x regardless of vendor. I discuss this importaint topic in The truth about Storage Data efficiency ratios and Dare2Compare Part 1 : HPE/Simplivity’s 10:1 data reduction HyperGuarantee Explained.

For VDI, metadata clones save SO much capacity that even if you keep an entire copy of the dataset on EVERY NODE, you still need a minimal amount of flash per node. e.g.: If you use Shadow clones with even 400GB per node of cloned data (unlikely but let just use this for an example), even a single 800GB SSD which are very affordable these days would have you well covered.

So I’m moving on from VDI as it’s all but a non issue in the real world.

Moving onto server workloads, firstly many datasets do not achieve significant deduplication ratios and other datasets such as database workloads suffer significant performance implications of being deduped due to the fact sequential I/O streams frequently having to be served as random due to deduplication.

In my experience, customers running mission critical workloads such as SQL, SAP and Oracle do not want deduplication, and therefore opt to turn it off or just avoid platforms not allowing dedupe to be turned off (yes platforms like this exist even in 2017!!).

But I have to concede, deduplication on a distributed file system such as ADSF which does global dedupe and especially on platforms like VSAN which do dedupe on a per disk group basis (which can be a smaller dedupe domain than a node), are not as capacity efficient as a centralised SAN. But the pros of Nutanix and ADSF far outweigh the minimal difference in deduplication efficiency which is insignificant in the real world.

  1. Nutanix does not “need” a local copy and can/does access remote replicas

In short, Nutanix can work with no data locality or 100% data locality. The more locality the better, but in the WORST case, Nutanix has the same network overheads/latency as a SAN does in the BEST case. I cover of this in my younger/fatter days in this VMworldTV interview from 2013 (From 2:44 onward).

The next section covers “Erasure Coding”.

ErasureCodingDataLocality

One key point on Data Locality and Erasure Coding.

  1. It’s not a conflict, it’s a choice between capacity efficiency and performance.

Erasure coding (EC-X) has been a capability of ADSF since 2015 and its uptake has been steadily growing over the past two years. The best thing about Nutanix data reduction capabilities is the ability to turn on/off features per vDisk. Even within a single VM, multiple different data reduction features and combinations can be used to maximise performance and data reduction/efficiency.

In general, the primary use cases for Erasure coding which I detailed in “What’s .NEXT 2015 – Erasure Coding” is write cold data, such as

  1. File Servers
  2. Backup
  3. Archive
  4. Email
  5. Logging
  6. Video
  7. Audio

Data Locality is designed to reduce overheads and optimise performance. Erasure Coding still writes locally and if/when data meets the criteria for striping (meaning the data is write cold for 7 days), then the Erasure Coding will take effect as a low priority background task.

Customers get all the performance of RF2/RF3 along with data locality. Erasure coding is striped only when the data qualifies as write cold. Once striped, there is reduced level of data locality due to the striping of data across nodes, however, by the time data is striped, it is unlikely that maximum performance will be a realistic concern or even noticible.

With that said, in the WORST case, Nutanix has the same network overheads/latency as VSAN or a traditional SAN does in the BEST case.

It should be clear by this stage that the data locality report tries to find every possible corner case to make data locality sound like a bad thing. Although many points are valid for other platforms lacking the unique data locality capabilities that Nutanix customers enjoy, not a single point has any merit in regard to real-world Nutanix scenarios.

Next up we talk “Data Locality and offline resources”.

DataLocalityOfflineResources

A few key points on Data Locality and Offline Resources.

  1. As data locality is not central to Nutanix performance, if VMs do not for any reason have a high percentage of data locality, we’re not worse off than VSAN, and we’re better off than a SAN in any case.

Nutanix performance is excellent without locality; data locality just makes things better and does so with minimal overhead. In other words, the pros far outweigh the cons.

In the failure scenario the article described, Nutanix will still benefit from a more optimal write path as one replica is always written locally even directly after a HA event. Nutanix’s ability to rebuild data is, as the report states, a many-to-many architecture.

For example, if a VSAN node fails, the second copy of an object is solely read from ONE node and written to another ONE node. Should a single Nutanix node fail, EVERY NODE in the cluster participates in the rebuild making the recovery time faster. And the rebuild has a low impact due to the “many hands make light work” approach.

Importantly, data does not have to be recovered to any specific location/node, so ADSF uses the fitness values discussed earlier to place data intelligently for both performance and capacity to ensure an optimal storage fabric.

And FINALLY, the conclusions!

Conclusions

Some final thoughts:

  1. The closer we look at data locality the less attractive it looks?

When talking about other platforms, I would agree because they don’t truly have data locality. The points raised in this post clearly show the report is almost entirely not applicable to Nutanix, with the exception of the insignificant (in the real world) efficiency reductions when using Deduplication and Erasure Coding with distributed platforms (which is much more applicable to VMware VSAN than Nutanix as previously mentioned).

The part which I find the most amusing is that while VMware commissioned the article, the only valid (yet insignificant) points around data reduction which have some impact on Nutanix, have higher impacts on VSAN which has a much less efficient (per disk group as opposed to global) deduplication.

  1. “We [DeepStorage.net] believe that users would be better served by the consistent performance of an all-flash system rather than gaming the performance of a hybrid system with data locality.”

Comparing all flash to hybrid is apples and oranges, but the point about consistent performance is reasonable. Data locality (as explained earlier) ensures the write path remains consistent even after a VM migrates as one replica is always written locally and the other replica/s distributed across the cluster. So for consistency, especially for write performance (which is much more intensive than read), data locality is the way to go!

Related Articles:

  1. Being called out on Exchange performance & scale. Close (well not really), but no cigar.

What’s .NEXT 2017 – AHV Turbo Mode

Back in 2015 I wrote a series titled “Why Nutanix Acropolis Hypervisor (AHV) is the next generation hypervisor” which covered off many reasons why AHV was and would become a force to be reckoned with.

In short, AHV is the only purpose built hypervisor for hyper-converged infrastructure (HCI) and it has continued to evolve in terms of functionality and maturity while becoming a popular choice for customers.

How popular you ask? Nutanix officially reported 23% adoption as a percentage of nodes sold in our recent third quarter fiscal year 2017 financial highlights.

Over the last couple of years I have personally worked with numerous customers who have adopted AHV especially when it comes to business critical applications such as MS SQL, MS Exchange.

One such example is Shinsegae who is a major retailer running 50,000 MS Exchange mailboxes on Nutanix using AHV as the hypervisor. Shinsegae also runs MS SQL workloads on the same platform which has now become the standard platform for all workloads.

This is just one example of AHV proven in the field and at scale to have the functionality, resiliency and performance to support business critical workloads.

But at Nutanix we’re always striving to deliver more value to our customers, and one area where there is a lot of confusion and misinformation is around the efficiency of the storage I/O path for Nutanix.

The Nutanix Controller VM (CVM) runs on top of multiple hypervisors and delivers excellent performance, but there is always room for improvement. With our extensive experience with in-kernel and virtual machine based storage solutions, we quickly learned that the biggest bottleneck is the hypervisor itself.

Next2017TraditionalHypervisorBottleneck

With technology such as NVMe becoming mainstream and 3D XPoint not far behind, we looked for a way to give customers the best value from these premium storage technologies.

That’s where AHV Turbo mode comes into play.

Next2017AHVTurboMode

AHV Turbo mode is a highly optimised I/O path (shortened and widened) between the User VM (UVM) and Nutanix stargate (I/O engine).

These optimisation have been achieved by moving the I/O path in-kernel.

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Just kidding! In-kernel being better for performance is just a myth, Nutanix has achieved major performance improvements by doing the heavy lifting of the I/O data path in User Space, which is the opposite of the much hyped “In-kernel”.

The below diagram show the UVM’s I/O path now goes via Frodo (a.k.a Turbo Mode) which runs in User Space (not In-kernel) and onto stargate within the Controller VM).

Next2017FrodoDatapath2

Another benefit of AHV and Turbo mode is that it eliminates the requirement for administrators to configure multiple PVSCSI adapters and spread virtual disks across those controllers. When adding virtual disks to an AHV virtual machine, disks automatically benefit from Nutanix SCSI and block multi-queue ensuring enhanced I/O performance for both reads and writes.

The multi-queue I/O flow is handled by multiple frodo threads (Turbo mode) threads and passed onto stargate.

Next2017FrodoUpdated

As the above diagram shows, Nutanix with Turbo mode eliminates the bottlenecks associated with legacy hypervisors, one such example is VMFS datastores which required VAAI Atomic Test and Set (ATS) to minimise the impact of locking when the numbers of VMs per datastore increased (e.g. >25). With AHV and Turbo mode, every vdisk has always had it’s own queue (not one per datastore or container) but frodo enhances this by adding a per-vcpu queue at the virtual controller level.

How much performance improvement you ask? Well I ran a quick test which showed amazing performance improvements even on a more than four year old IVB NX3450 which only has 2 x SATA SSDs per node and with the memory read cache disabled (i.e.: No reads from RAM).

A quick summary of the findings were:

  1. 25% lower CPU usage for the similar sequential write performance (2929MBps vs 2964MBps)
  2. 27.5% higher sequential read performance (9512MBps vs 7207MBps)
  3. A 62.52% increase in random read IOPS (510121 vs 261265)
  4. A 33.75% increase in random write IOPS (336326 vs 239193)

So with Turbo Mode, Nutanix is using less CPU and RAM to drive higher IOPS & throughput and doing so in user space.

Intel published “Code Sample: Hello World with Storage Performance Development Kit and NVMe Driver” which states “When comparing the SPDK userspace NVMe driver to an approach using the Linux Kernel, the overhead latency is up to 10x lower”.

This is just one of many examples which shows userspace is clearly not the bottleneck that some people/vendors have tried to claim with the “in-kernel” is faster nonsense I have previously written about.

With Turbo mode, AHV is the highest performance (throughput / IOPS) and lowest latency hypervisor supported by Nutanix!

But wait there’s more! Not only is AHV now the highest performing hypervisor, it’s also used by our largest customer who has more than 1750 nodes running 100% AHV!

Next20171650Nodes

Dare2Compare Part 7 : HPE provides superior performance to Nutanix

In part 4, we covered off a series of failure scenarios and how the HPE/SVT product responds and the same scenarios and how Nutanix responds which clearly proved HPEs claim of having superior resiliency than Nutanix to be false and I would argue even highlighted how much more resilient the Nutanix platform is.

Now in part 7, I will address two false claims (below) that Nutanix has lower performance to HPE SVT and that Nutanix doesn’t post performance results.

Tweet #1 – HPE Simplivity 380 provides superior performance than Nutanix

Problem number 1 with HPE’s claim: Their URL is dead… so we cannot review what scenario/s they are claiming HPE/SVT is higher performing.

HPEBrokenURL

Before we discuss Nutanix performance, HPE have repeatably made further claims that Nutanix does not post performance results and have further complained there are no 3rd party published performance testing results.

One recent example of these claim is shown below which states: “I know you don’t publish performance results”

Nutanix does in fact publish performance data, which is validated by:

  • 3rd parties partners/vendors such as Microsoft and LoginVSI
  • Independant 3rd parties such as Enterprise Storage Group (ESG) and;
  • Internally created material

The following is a few examples of published performance data.

  1. Nutanix Citrix XenDesktop Validated by LoginVSI

In fairness to HPE, this is a recent example so let’s take a look at Nutanix track record with LoginVSI.

LoginVSIBenchmarks

Here we can see six examples dating back to Jan 2013 where Nutanix has made performance results with LoginVSI available.

2. Nutanix Reference Architecture: Citrix Validated Solution for Nutanix

This was a jointly developed solution between Citrix and Nutanix and was the first of it’s kind globally and was made available in 2014.

3. Microsoft Exchange Solution Reviewed Program (ESRP) – Storage

Nutanix has for many years been working with business critical applications such as MS Exchange and has published two ESRP solutions.

The first is for 24,000 Users on Hyper-V and the second is for 30k Users on AHV.

NutanixESRPScreenshot

Interestingly, while HPE/SVT have a reference architecture for MS Exchange, they do not have an ESRP for the platform and this is because they cannot provide a supportable configuration due to lack of multi-protocol support.

Nutanix on the other hand has Microsoft supportable configurations for ESXi, Hyper-V and AHV.

4. ESG Performance Analysis: Nutanix Hyperconverged Infrastructure

This report is an example of a 3rd party who has validated performance data for VDI, MS SQL and MS Exchange.

As we can clearly see with the above examples, Nutanix does and has for a long time provided publicly available performance data from many sources including independant 3rd parties.

Moving onto the topic of Nutanix vs HPE/SVT performance, I feel it’s importaint to first review my thoughts on this topic in detail in an article I wrote back in 2015 titled: Peak performance vs real world performance.

In short, I can get any two products and make one look better than the other by simply designing tests which highlight strengths or weaknesses of either product. This is why many vendors have a clause in the EULA preventing publishing of performance data without written permission.

One of the most importaint factors when it comes to performance is sizing. An incorrectly sized environment will likely not perform within acceptable levels, and this goes for any product on the market.

For next generation platforms like Nutanix, customers are protected from under-sizing because of the platforms ability to scale by adding additional nodes. In 2016 I wrote the post titled “Scale out performance testing with Nutanix Storage Only Nodes” which shows how adding additional storage only nodes to a Nutanix cluster increased IOPS by approx 2x while lowering read and write latency.

What is more impressive than the excellent performance improvements is this was done without any changes to the configuration of the cluster or virtual machines.

The same test performed on HPE/SVT and other SDS/HCI products cannot double the IOPS or decrease read/write latency as the SVT platform is not a distributed storage fabric.

Here in lies a major advantage to Nutanix. In the event Nutanix performance was no longer sufficient, or another platform was higher performance, say per node, then Nutanix can (if/when required) scale performance without rip/replace or reconfiguration to meet almost any performance requirement. The performance per node is not a limiting factor for Nutanix like it is with HPE/SVT and other platforms.

What about performance for customers who are maximising the ROI from existing physical servers using Acropolis Block Services. The benefits just keep coming. A server connected using ABS will improve its IOPS, latency and throughput when additional nodes are added to the Nutanix cluster automatically as the Acropolis Distributed Storage Fabric (ADSF) increases the number of paths dynamically so all Controller VMs in the cluster service ABS traffic as shown in the tweet below.

As such, regardless of if workloads are virtual or physical, when using Nutanix, performance can always be improved non-disruptively and without compromising the resiliency of the cluster by simply adding nodes (which BTW is a one click operation).

Summary:

  1. Nutanix has been publishing performance results through independant 3rd parties and partners for many years.
  2. Nutanix has validated solutions from Microsoft, LoginVSI and Citrix to name a few.
  3. Nutanix performance can scale well beyond HPE/SVT for both virtual and physical workloads
  4. Nutanix provides validated performance data across multiple hypervisors
  5. HPE/SVT have provided no evidence, scenarios or references to SVT being a higher performance platform.

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