Peak performance vs Real World – Exchange on Nutanix Acropolis Hypervisor (AHV)

I wrote a post in April 2015 titled “Peak Performance vs Real World Performance” which discusses how benchmarks are not realistic and the performance shown in benchmarks can rarely be reproduced with real workloads. It has been one of my most popular posts, and I have had overwhelmingly positive feedback, with only a select few still pushing unrealistic peak performance benchmarks as being of value to customers.

I thought I would whip up a post showing an example of benchmarks vs real world performance requirements using MS Exchange Jetstress on Nutanix.

The below is a screen shot from Nutanix PRISM HTML based GUI showing a Virtual Machines Read/Write IOPS , bandwidth and latency during a MS Exchange Jetstress benchmark.

JetstressAHV20160105

The screen shot shows ~4000 Read IOPS and ~4000 Write IOPS at a latency of 1.59ms.

But what does the above really tell us and what does it mean to a customer?

I’ve been quoted as saying “Benchmarks are of little value without context specific to customer requirements!” and I stand by this statement.

Let’s now look at an example of a real customers requirement:

The below is from the Exchange server role requirements calculator and it is a screen shot from the Role requirements tab which shows an estimate of the IOPS required for the Databases and Logs for a single Exchange instance.

ExchangeIOexample

It shows the required IOPS being 536 for the databases and 115 for the logs.

Note: The sizing calculator was for an environment supporting 20000 mailboxes across 3 mailbox servers. As such, the above IO requirements are for ~6666 users.

So now that we have done the MS Exchange solution sizing (shown above is just the storage performance requirements), we understand the requirement to be around 651 mixed Read/Write IOPS per mailbox VM. We can then take a benchmark such as Jetstress and validate that the solution has sufficient storage performance.

To require the ~8000 IOPS the Jetstress test showed, we would need to scale up each Exchange instances to support have a much larger number of users and have each user send/receive 500 emails per day to reach this requirement.

8kJetstressIOPS

But in scaling up each Exchange instance to reach the peak IOPS that even this 3 year old generation Nutanix node can deliver we would vastly exceed the compute sizing recommendations for Exchange 2013 (being 24vCPUs and 96GB RAM) as shown by the calculator below.

ScaleUpExchange

As we can see, for an Exchange instance to require those peak IOPS, we would have to size the Mailbox server VMs with more than 10x the recommended vCPUs (24) and 15x the RAM (96GB). This shows that peak IOPS which can be achieved are not relevant in the real world.

In fact, Exchange generally does not require more than 1000 IOPS. Typically its requires much less, as my earlier example shows. So peak performance numbers are of little/no value as they can’t (and more importantly don’t need to be) reproduced in the real world.

With a tool like Jetstress we can configure a precise Mailbox profiles and test only what you require. If the solution can produce more IOPS than what you need (such as in this example), that’s fine for headroom, but in this day and age where Nutanix allows you to quickly and easily scale (Compute/Storage performance & capacity), I recommend designing for what you need in the foreseeable future (by this I mean 6-12 months) and scale if/when required.

What a benchmark does help you understand is how much headroom a solution has over and above your requirements which can help choose a solution to support mixed workloads, BUT the benchmark would need to be re-ran concurrently with suitable benchmarks for all other applications you intend on mixing to see how the solution behaves with mixed workloads.

As such, single application peak performance benchmarks are almost never valuable (to customers) unless your planning to run application specific silos. I strongly recommend anyone considering implementing an application specific silo, read the following article: Enterprise Architecture & Avoiding tunnel vision.

And… if you’re planning to run application specific silos and/or scaling up workloads to the point they need crazy IOPS, then you’re increasing the size of your failure domains, CAPEX and OPEX which is only doing yourself (or your customer) a disservice. But that’s a topic for another day.

I hope this example shows how real world requirements and performance is vastly different to what a benchmark shows and why peak performance benchmarks should be taken with a grain of salt.

I’ve always said the focus should be on gathering requirements and delivering on business outcomes, not focusing on performance which is typically only a very small part of a solution that delivers a successful business outcome.

Summary:

When sizing an MS Exchange solution on Nutanix, IOPS is not a constraining factor even for large scale deployments. The most common constraining factor is the Microsoft recommended compute maximums being 24 vCPUs and 96GB RAM, which is the same constraint regardless of if you run on Nutanix, or any other virtual / physical platform.

Related Articles:

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).

bugatti-veyron-super-sport-

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.

bugatti-veyron-super-sport_100315491_l

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.

veyron-tires-2-thumb-550x336

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.

bugatti-veyron-wallpaper-7

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.

heavy-traffic-beirut-saidaonline

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.

Summary:

  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).