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NVIDIA GPU with Dynamic DirectPath IO (Passthrough) to Tanzu Kubernetes Grid (TKG) Cluster using vSphere with Tanzu

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When provisioning a Tanzu Kubernetes Grid Cluster (TKC) using vSphere with Tanzu, you can easily request an NVIDIA GPU resource as part of the deployment, which can either be provided by NVIDIA vGPU or using PCIe passthrough with Dynamic DirectPath IO.

vGPU is great for those with a capable NVIDIA GPU, especially if the GPU will not be utilized 100% and you can share its resources amongst several VMs. However, if you do not have a capable GPU that supports vGPU, you can still provide you TKC workloads with a GPU resource using passthrough.


While playing with the Lenovo P3 Ultra, I unfortunately came to learn that NVIDIA RTX A5500 Laptop was NOT the same as an NVIDIA RTX A5500 🙁

Not ideal, but I guess NVIDIA did not want to add this additional device to their test matrix and hence their ESXi graphics drivers would not detect the GPU as vGPU capable. I knew that I could still use the NVIDIA GPU via passthrough but to my surprise, I just needed to get the NVIDIA drivers installed onto the TKC worker nodes.

That was much easier said than done as all the documentation that I could find on both VMware and NVIDIA website had detailed instructions for vGPU configuration but there was little to no documentation on how to use NVIDIA GPU in passthrough mode with vSphere with Tanzu. I came across a number of different NVIDIA solutions when it comes to k8s, but it was not very clear on which would be interoperable with vSphere with Tanzu and I eventually figured it out with the help pointing me in the right direction.

It was actually super easy, once you knew the exact steps! 😅

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How to download offline copy of the Tanzu Kubernetes releases (TKr) Content Library?

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As part of the setup for vSphere with Tanzu, a local vSphere Content Library needs be created to store the various Tanzu Kubernetes releases (TKr) which users typically synchronize from VMware's online TKr Content Library repository.


I typically recommend configuring the content library subscription to only download files when needed, rather than the entire library, which is currently over 200GB+.

After standing up another vSphere with Tanzu environment, I needed to download additional TKr images but I could not reuse my existing subscribed content library since it was configured on a different vCenter Server.

With the ability to host a custom vSphere Content Library on my Synology, I realized a better solution would be for me to simply download the full VMware TKr Content Library and host that locally on my network rather than re-downloading the same images each time I have a new deployment.

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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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