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How to bootstrap vSAN Express Storage Architecture (ESA) on unsupported hardware?

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I was recently chatting with a fellow colleague who asked an interesting question about the memory overhead between running vSAN Original Storage Architecture (OSA) versus the new vSAN Express Storage Architecture (ESA) from a VMware Homelab perspective. I honestly did not know the answer as I am only using vSAN OSA for my personal homelab. I was curious myself, especially its implicationn on small form factor (SFF) systems which typically max at out 64GB of memory.

Today, vSAN ESA is only officially supported when using vSAN ESA Ready Nodes which are all listed in the vSAN ESA HCL and the minimum amount of memory is 512GB. For the best possible experience and supported configurations, customers should only use approved vSAN ESA hardware and the use of any other systems will not yield the same benefits nor outcomes. As an aside, a fantastic resource for all things vSAN ESA can be found on the vSAN ESA TechZone page, which I highly recommend bookmarking as there is a lot of in-depth technical resources and collateral.

Disclaimer: This is not officially supported by VMware and is purely for educational purposes, use at your own risk.

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Configure NSX-T Edge to run on AMD Ryzen CPU

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The vast majority of VMware Homelabs is still Intel-based today but I have been seeing a slow rise of AMD-based kits being adopted, especially with AMD's desktop line of CPUs known as Ryzen. One of the considerations on whether you could use an AMD processor was whether you were planning to deploy NSX-T and in earlier releases, only Intel was supported as the NSX-T Edge required support for Data Plane Development Kit (DPDK) and this was only supported with Intel-based processors.

With the latest NSX-T 3.0 release, AMD-based processors are now supported and per the release notes, the following CPUs can be used:

  • AMD EPYC 7xx1 Series (Naples)
  • AMD EPYC 3000 Embedded Family and newer
  • AMD EPYC 7xx2 Series (Rome)

You will notice that only AMD's server line of CPUs known as EPYC are currently supported, which makes sense for running Production workloads. If you attempt to deploy an NSX-T Edge Node running on a non-EPYC platform, you will get an error message stating the CPU is not supported and I figured this was probably due to the lack of DPDK support in the consumer CPUs.

Yesterday, in our internal "Homelab" Slack channel, I came across an interesting tidbit from Andrea Spagnolo, a Sr. Field Engineer in our Cloud Native Business Unit who shared a pretty neat trick on how to get latest NSX-T 3.0 release to work with a Ryzen-based CPU.

Disclaimer: This is not officially supported by VMware. The behaviors described here can change in the future

First off, I want to thank Andrea for sharing but also credit to Beniamino Guarnaschelli and his blog post here which actually gave Andrea the idea to take a closer look as he was trying to get this setup in his own personal homelab.

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Deploying a minimal vSphere with Kubernetes environment

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A very useful property of automation is the ability to experiment. After creating my vSphere 7 with Kubernetes Automation Lab Deployment Script, I wanted to see what was the minimal footprint in terms of the physical resources but also the underlying components that would be required to allow me to still a fully functional vSphere with Kubernetes environment.

Before diving in, let me give you the usual disclaimer 😉

Disclaimer: This is not officially supported by VMware and you can potentially run into issues if you deviate from the official requirements which the default deployment script adheres to out of the box.

In terms of the physical resources, you will need a system that can provision up to 8 vCPU (this can be further reduced, see Additional Resource Reduction section below), 92GB memory and 1TB of storage (thin provisioned).


which translates to following configuration within the script:

  • 1 x Nested ESXi VM with 4 vCPU and 36GB memory
  • 1 x VCSA with 2 vCPU and 12GB memory
  • 1 x NSX-T Unified Appliance with 4 vCPU and 12GB memory
  • 1 x NSX-T Edge with 8 vCPU and 12GB memory

Note: You can probably reduce memory footprint of the ESXi VM further depending on your usage and the VCSA is using the default values for "Tiny", so you can probably trim the memory down a bit more.

Another benefit to this solution is by reducing the number of ESXi VMs required, it also speeds up the deployment and in just 35 minutes, you can have the complete infrastructure fully stood up and configured to try out vSphere with Kubernetes!


The other trick that I leveraged to reduce the amount of resources is by changing the default number of Supervisor Control Plane VMs required for enabling vSphere with Kubernetes. By default, three of these VMs are deployed as part of setting up the Supervisor Cluster, however I found a way to tell the Workload Control Plane (WCP) to only deploy two 🙂


This minimal deployment of vSphere with Kubernetes has already been incorporated into my vSphere with Kubernetes deployment script, but it does require altering several specific settings. You can find the instructions below.

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