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Search Results for: Tanzu Kubernetes Grid

Troubleshooting tips for configuring vSphere with Kubernetes

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With more and more folks trying out the new vSphere with Kubernetes capability, I have seen an uptick in questions both internally and externally around the initial setup of the infrastructure required for vSphere with Kubernetes but also during the configuration of a vSphere Cluster for Workload Management.

One of the most common question is why are there no vSphere Clusters listed or why a specific vSphere Cluster is showing up as Incompatible? There are a number of reasons that this can occur including vCenter Server not being able to communicate with NSX-T Manager to retrieve the list of NSX pre-checks which would cause the list to either be empty or listed as incompatible. Not having proper time sync between vCenter Server and NSX-T which can also manifest in a similar behavior among other infrastructure issues.


Having ran into some of these issues myself when developing my automation script, I figure it might be useful to share some of the troubleshooting tips I have used when trying to figure out what is going on whether that is during the initial setup or actually deploying workloads using vSphere with Kubernetes.

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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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Useful Interactive Terminal and Graphical UI Tools for Kubernetes

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I recently ran an internal hands-on workshop where I demonstrated to our field, marketing, support and engineering on just how easy it is to deploy and manage Tanzu Kubernetes Grid (TKG) Clusters running on VMware Cloud on AWS. While developing the lab which has been several weeks in the making, I did not want to assume everyone was familiar with Kubernetes (K8s) and as part of the workshop, I thought it would be useful to include some additional utilities that would provide a better lab experience for those that are just getting started in their K8s journey.

I included tools like bat, kube-ps1 and Octant as an example and the weekend before the workshop, I came to learn about a really neat terminal-based UI tool called kubelive and I knew I had to include that in the workshop. Interestingly, after the workshop, several folks shared with me that they had not heard of this tool either and others on Twitter had the same feedback. Given the level of interests with K8s in the VMware community, especially with the launch of vSphere with Kubernetes (Project Pacific), I thought it might be useful to share some of the terminal-based and graphical UI tools that I had been evaluating and learning about.

As of writing this blog post, my current two favorites is Octant for a graphical-based UI (browser) Headlamp Radar for a graphical based UI and K9s for a terminal-based UI.

Radar

In 2026, this is my current go to k8s-based visualization, which you can read more about HERE.

Headlamp

I noticed that many of the graphical tools listed below are no longer being developed as of Nov 2025. While doing a quick search to see what are the latest options in 2025, I came across Headlamp which looks to fit my need quite well. It is a desktop application that you can download and use for free and after importing your kubeconfig file, you can start interacting with the system. While I could have used K9s, I was looking for something more interactive and I found it be pretty easy to use after a few minutes and allowed me to quickly clean up some failed deployments with just a few clicks. Depending on your needs, you might still opt for a CLI-based tool like K9s or kubectl, but for those looking for something graphical, this might be one to consider.

Octant

Octant is a browser-based UI aimed at application developers giving them visibility into how their application is running. I also think this tool can really benefit anyone using K8s, especially if you forget the various options to kubectl to inspect your K8s Cluster and/or workloads. Octant is also a VMware Open Source project and it is supported on Windows, Mac and Linux (including ARM) and runs locally on a system that has access to a K8S Cluster. After installing Octant, just type octant and it will start listening on localhost:7777 and you just launch your web browser to access the UI.

One thing I really like about Octant is how easy it is to switch context between different K8s Cluster with a simple drop down along with namespace filtering which is quite helpful in narrowing down a specific deployments, usually for informational or troubleshooting purposes.


Most of my workflows generally involves a specific K8s pod and the Resource View tab is super handy to give me a quick overview of the different resources that is associated whether that is a deployment, secret, service, etc.


The YAML tab beats using cat and bat, especially for really large and complex deployments and you can search right in the browser.
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