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Building custom Tanzu Kubernetes Releases (TKR) for vSphere with Tanzu

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Right before going on PTO, I caught this really interesting tweet from my buddy Robert Guske that we now support building your own custom Tanzu Kubernetes Releases (TKR), the Kubernetes software distributions that is signed and supported by VMware, which is typically provided by VMware through the online TKR Content Library.

While there are already a number of existing customizations that can be applied when deploying a Tanzu Kubernetes Workload Cluster (TKC), there may still be certain VM configurations that you would like to add, which is simply not possible today. In some of the customer requests, it can be as simple as changing the default size of the primary disk for a TKR, which is statically configured today as 20GB.

With this and many other use cases, it is nice to see that we now finally provide customers with a supported method to build their own custom TKR that might include additional customizations that is required by their organization for use with vSphere with Tanzu.

I recently got a chance to play with the new vSphere Tanzu Kubernetes Grid Image Builder tool, which is also an open source project from VMware and leverages the existing Kubernetes Image Builder, which I have also used before (see this blog post HERE for more details). While getting started, it took me a few tries but I eventually got it working after speaking with the Developers as I ran into a few issues.

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Create Windows 11 Virtual Appliance using Tiny 11 with only 2GB memory

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I recently came to learn about a really cool project called Tiny 11 which is a stripped down version of Windows 11 Pro 22H2 that can run with just 2GB of memory and 8GB of storage. While you would probably not use this for production workloads, it could be interesting for those with homelabs and can even for demo purposes.

Disclaimer: Tiny 11 is not an official project from Microsoft, use at your own risk. If you are interested in creating an optimized Windows 10 or 11 image, you can also check out these VMware resources here and here to produce a similiar size image using official Microsoft tools and images.

UPDATE (02/16/23) - There is now an Arm version for Tiny 11, which is great for anyone using the ESXi-Arm Fling and the technique in this blog post would also apply.

After performing a manual installation of Tiny 11, I thought it would be neat if I could build a Virtual Appliance (OVA) for Tiny 11 and also add custom OVF properties, which would allow anyone to customize the OS further without having to rely on any external tooling.

In fact, I had demonstrated this concept back in 2019 using Windows Server 2016 in this blog post and I figure it should be easy enough to also do the same for Tiny 11 or even standard Windows 11! With a bit of trial/error, I was indeed able to create a simple Tiny 11 OVA that includes the following OVF properties as shown in the screenshot below.


My initial goal was to fully automate the building of a Tiny 11 OVA with custom OVF properties using Packer. However, after many attempts, I was not able to figure out the correct autoattended.xml configuration and decided on a semi-manual approach which is detailed in the instructions below. If anyone is able to figure out how to get Tiny 11 installed via Packer, then I may revisit this topic and automate the remainder of the setup.

Note: The instructions below are not specific to Tiny 11 in any way and is also applicable to standard Windows 10 or 11 image.

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vSphere with Tanzu using Intel Arc GPU

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After successfully passing through the new Intel Arc 750/770 GPU to both a Linux and Windows VM running on ESXi, which also includes keyboard/mouse access and video output to an external monitor, I wanted to see if our vSphere with Tanzu solution could also take advantage of the new Intel Arc GPU?


The answer is absolutely YES! 😀

In vSphere 7.0 Update 3 MP01 and later, vSphere with Tanzu introduced the support for adding a Dynamic DirectPath I/O device to a VM that is provisioned using the VM Service Operator. Before we can take advantage of the new Dynamic DirectPath I/O feature, we first need to create a new custom VM Class definition that maps to our Intel Arc GPU.

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