You are here. The art of HCI performance testing

At some point potential Hyper-converged infrastructure (HCI) users want to know – “How fast does this thing go?”.  The real question is “how do we measure that?”.

The simplest test is to run a single VM, with a single disk and issue a single IO at a time.  We see often see this sort of test in bake-offs, and such a test does answer an important question – “what’s the lowest possible response time I can expect from the storage”.

However, this test only gives a single data point.  Since nobody purchases a HCI cluster to run a single VM,  we also need to know what happens when multiple VMs are run at the same time.  This is a much more difficult test to conduct, and many end-users lack access and experience with tools that can give the full picture.

In the example below, the single VM, single vdisk, single IO result is at the very far left of the chart.  Since it’s impossible to read I will tell you that the result is about 2,500 IOPS at ~400 microseconds.  (in fact we know that if the IOPS are 2,500 the response time MUST be 400 microseconds 1/2,500 == .0004 seconds)

However with a single VM, the cluster is mostly idle, and has capacity to do much more work.   In this X-Ray test I add another worker VM doing the exact same workload pattern to every node in the cluster every 5 minutes.

By the time we reach the end of the test, the total IOPS have increased to around 600,000 and the response time only increased by an additional 400 microseconds.

In other words the cluster was able to achieve 240X the amount of work measured by the single VM on a single node with only a 2X increase in response time, which is still less than 1ms.


The overall result is counter-intuitive, because the rate of change in IOPS (240X) is way out of line with the increase in response time (2X).  The single VM test is using only a fraction of the cluster capacity.

When comparing  HCI clusters to traditional storage arrays – you should expect the traditional array to outperform the cluster at the far left of the chart, but as work scales up the latent capacity of the HCI cluster is able to provide huge amounts of IO with very low response times.

You can run this test yourself by adding this custom workload to X-Ray

HCI Performance testing made easy (Part 1)

In this short series I will describe how to perform performance an resiliency tests on a HCI cluster using X-ray.

X-Ray can do the following for the performance tester.

  • Model IO workloads using standard fio format
  • Create VMs based on user-specified criteria (CPUs, Memory, Number & Size of disks)
  • Provision the VMs  to a HCI cluster (Nutanix AHV, ESXi, Hyper-V)
  • Execute the workloads
  • Display and store the results

In particular X-Ray give the additional benefits that most workload generators do not

  • Specify and deploy workloads with different IO patterns and characteristics
    • Most workload generators create a uniform workload on all workers
  • Execute and terminate sub-workloads on a user-specified timeline
    • e.g. Begin workload 1 then introduce workload 2 and measure the interference
  • Introduce failure scenarios and measure the impact to performance

Here’s a video of X-Ray in action, I export an existing X-Ray test, edit it to create a new test, upload and execute the test.

 

The files are in my X-ray GitHub

Storage Bus Speeds 2018

Storage bus speeds with example storage endpoints.

Bus Lanes End-Point Theoretical Bandwidth (MB/s) Note
SAS-3 1 HBA <-> Single SATA Drive 600 SAS3<->SATA 6Gbit
SAS-3 1 HBA <-> Single SAS Drive 1200 SAS3<->SAS3 12Gbit
SAS-3 4 HBA <-> SAS/SATA Fanout 4800 4 Lane HBA to Breakout (6 SSD)[2]
SAS-3 8 HBA <-> SAS/SATA Fanout 8400 8 Lane HBA to Breakout (12 SSD)[1]
PCIe-3 1 N/A 1000 Single Lane PCIe3
PCIe-3 4 PCIe <-> SAS HBA or NVMe 4000 Enough for Single NVMe
PCIe-3 8 PICe <-> SAS HBA or NVMe 8000 Enough for SAS-3 4 Lanes
PCIe-3 40 PCIe Bus <-> Processor Socket 40000 Xeon Direct conect to PCIe Bus

 

Notes


All figures here are the theoretical maximums for the busses using rough/easy calculations for bits/s<->bytes/s. Enough to figure out where the throughput bottlenecks are likely to be in a storage system.

  1. SATA devices contain a single SAS/SATA port (connection), and even when they are connected to a SAS3 HBA, the SATA protocol limits each SSD device to ~600MB/s (single port, 6Gbit)
  2. SAS devices may be dual ported (two connections to the device from the HBA(s)) – each with a 12Gbit connection giving a potential bandwidth of 2x12Gbit == 2.4Gbyte/s (roughly) per SSD device.
  3. An NVMe device directly attached to the PCIe bus has access to a bandwidth of 4GB/s by using 4 PCIe lanes – or 8GB/s using 8 PCIe lanes.  On current Xeon processors, a single socket attaches to 40 PCIe lanes directly (see diagram below) for a total bandwidth of 40GB/s per socket.

  • I first started down the road of finally coming to grips with all the different busses and lane types after reading this excellent LSI paper.  I omitted the SAS-2 figures from this article since modern systems use SAS-3 exclusively.
LSI SAS PCI Bottlenecks

 

Intel Processor & PCI connections