CAPV: Addressing Node Provisioning Issues Due to an Invalid State of ETCD

I recently ran into a strange scenario on a Kubernetes cluster after a sudden and unexpected crash it had experienced due to an issue in the underlying vSphere environment. In this case, the cluster was a TKG cluster (in fact, it happened to be the TKG management cluster), however, the same situation could have occurred on any cluster managed by Cluster API Provider vSphere (CAPV).

I have seen clusters unexpectedly crash many times before and most of the time, they successfully went back online when all nodes were up and running. In this case, however, some of the nodes could not boot properly, and Cluster API started attempting their reconciliation.

TKG 2.3: Fixing the Prometheus Data Source in the Grafana Package

With the release of TKG 2.3, the Grafana package was finally updated from version 7.5.x to 9.5.1. If you have deployed the new Grafana package (9.5.1+vmware.2-tkg.1) or upgraded your existing one to this version, you may have run into error messages in your Grafana dashboards.

For example, in the TKG Kubernetes cluster monitoring default dashboard, you may have run into the Failed to call resource error when opening the dashboard and noticed that a lot of the data is missing.

TKG: Updating Pinniped Configuration and Addressing Common Issues

Most of the TKG engagements I’ve been involved in included Pinniped for Kubernetes authentication. On many occasions, I have seen issues where the configuration provided to Pinniped was incorrect or partially incorrect. For example, common issues may be related to the LDAPS integration. Many environments I have seen utilize Active Directory as the authentication source, and Pinniped requires the LDAPS certificate, username, and password, which are often specified incorrectly. Since this configuration is not validated during the deployment, you end up with an invalid state of Pinniped on your management cluster.

Streamlining and Customizing Windows Image Builder for TKG

Tanzu Kubernetes Grid (TKG) is one of the few platforms providing out-of-the-box support and streamlined deployment of Windows Kubernetes clusters. VMware is actively investing in this area and constantly improving the support and capabilities around Windows on Kubernetes.

Unlike Linux-based clusters, for which VMware provides pre-packaged base OS images (typically based on Ubuntu and Photon OS), VMware cannot offer Windows pre-packaged images, primarily due to licensing restrictions, I suppose. Therefore, building your own Windows base OS image is one of the prerequisites for deploying a TKG Windows workload cluster. Fortunately, VMware leverages the upstream Image Builder project - a fantastic collection of cross-provider Kubernetes virtual machine image-building utilities intended to simplify and streamline the creation of base OS images for Kubernetes.

Tanzu Kubernetes Grid GPU Integration

I recently had to demonstrate Tanzu Kubernetes Grid and its GPU integration capabilities. Developing a good use case and assembling the demo required some preliminary research.

During my research, I reached out to Jay Vyas, staff engineer at VMware, SIG Windows lead for Kubernetes, a Kubernetes legend, and an awesome guy in general. :) For those who don’t know Jay, he is also one of the authors of the fantastic book Core Kubernetes (look it up!).

Getting Started with Carvel ytt - Real-World Examples

Over the years of working with Tanzu Kubernetes Grid (TKG), one tool has stood out as a game-changer for resource customization: Carvel’s ytt. Whether tailoring cluster manifests, customizing TKG packages, or addressing unique deployment requirements, ytt has consistently been a fundamental part of the workflow. Its flexibility, power, and declarative approach make it an essential tool for anyone working deeply with Kubernetes in a TKG ecosystem.

But what exactly is ytt? Short for YAML Templating Tool, ytt is part of the Carvel suite of tools designed for Kubernetes resource management. It provides a powerful, programmable approach to templating YAML configurations by combining straightforward data values, overlays, and scripting capabilities. Unlike many traditional templating tools, ytt prioritizes structure and intent, making it easier to maintain, validate, and debug configurations—particularly in complex, large-scale Kubernetes environments.

Harbor Registry – Automating LDAP/S Configuration – Part 2

This post continues our two-part series on automating LDAP configuration for Harbor Registry. In the previous post, we demonstrated how to achieve this using Ansible, running externally. However, external automation has its challenges, such as firewall restrictions or limited API access in some cases/environments.

Note: make sure you review the previous post as it provides a lot of additional background and clarifications on this process, LDAPS configuration, and more.

Here, we explore an alternative approach using Terraform, running the automation directly inside the Kubernetes cluster hosting Harbor. This method leverages native Kubernetes scheduling capabilities for running the configuration job in a fully declarative approach and does not require any network access to Harbor from the machine running the job.