#googlekubernetesengine — Public Fediverse posts

Google launches Kubernetes AI Conformance program to prepare clusters for machine learning

https://fed.brid.gy/r/https://nerds.xyz/2026/04/kubernetes-ai-conformance/

Google launches Kubernetes AI Conformance program to prepare clusters for machine learning

https://web.brid.gy/r/https://nerds.xyz/2026/04/kubernetes-ai-conformance/

Google launches Kubernetes AI Conformance program to prepare clusters for machine learning

https://web.brid.gy/r/https://nerds.xyz/2026/04/kubernetes-ai-conformance/

Google launches Kubernetes AI Conformance program to prepare clusters for machine learning

https://fed.brid.gy/r/https://nerds.xyz/2026/04/kubernetes-ai-conformance/

Google launches Kubernetes AI Conformance program to prepare clusters for machine learning

https://web.brid.gy/r/https://nerds.xyz/2026/04/kubernetes-ai-conformance/

I’m working on #Kubernetes these days. Recently, I wrote a series on how one could design a full-fledged testing pipeline targeting #GoogleKubernetesEngine. The second part mentions creating a #GKE instance in the context of a GitHub workflow. In this post, I want to assess #Crossplane by creating such an instance.

https://blog.frankel.ch/feet-wet-crossplane/

I’m continuing my series on running the test suite for each PR on #Kubernetes. In the previous post, I laid the groundwork for our learning journey.

This week, I will raise the ante:

* Create and configure a #GoogleKubernetesEngine instance
* Create a Kubernetes manifest for the app, with #Kustomize for customization
* Allow the #GitHub workflow to use the #GKE instance
* Build the Docker image and store it in the GitHub Docker repo
* Finally, run the end-to-end test

https://blog.frankel.ch/pr-testing-kubernetes/2/