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VMware Flings Update

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This has been a difficult week for all VMware employees due to the pending acquisition of VMware by Broadcom. Many VMware employees are still waiting to hear back from Broadcom about their employment status either before and/or after the planned acquisition close date. I wanted to provide this context before sharing a quick update regarding the VMware Flings program.

On Tuesday October 24th, VMware Fling authors was made aware that the VMware Flings site (flings.vmware.com) would be taken down and website would simply be redirected to developer.vmware.com/samples starting on Thursday October 26th.

The VMware Flings program was operated and run by VMware's Office of the CTO (OCTO) and while I do not have specifics on why it needed to go down, I tried my best to share out the news as broadly and as quickly as I could so that folks could at least grab what they needed. While the original notice mentioned the site would function up until 10/26 at 5pm PST, it looks VMware IT had already made the DNS changes and the redirect has already been propagated.

As of right now, I do not know the future of the VMware Flings program, but I did want to share a few updates since the site and its downloads are no longer available.

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How to setup Harbor registry on Synology

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With my recent exploration of GenAI and using a private ChatGPT solution with my own blog posts, I quickly realized in the space of AI/ML, the required software dependencies can take up a significant amount of storage, especially for a kubernetes/container-based deployment.

To give you an example, to deploy the private ChatGPT (h2ogpt) application using kubernetes, just the container image itself is a whopping 40GB+! ?

Unfourntately, this is not a one off scenario but a common theme when working in the AI/ML space that the size of the packages and drivers are extremely large even when using containers. I figure I should probably setup my own container registry instead of pulling directly from the Internet given the size of these images.

I already have a local Harbor instance running in a VM but with my Synology, I have been using it centralize a number of functions and that would be the ideal place to actually run Harbor. While you can run individual containers on the Synology as I have demonstrated HERE with GitLab, the Harbor installation processes relies on Docker Compose, which Synology does not natively support using the Synology DiskStation Manager (DSM) interface.

With a little bit of tinkering and trial/error, I was able to finally get Harbor running on my Synology and centralize all my storage needs including having my own container registry.

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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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