python VS kind

One option is to use list_namespace(), as described in https://github.com/kubernetes-client/python/blob/master/kubernetes/docs/CoreV1Api.md

I have checked the python version == 2.7 and pip freeze - ipaddress==1.0.22, urllib3==1.24.1 and websocket-client==0.54.0 are the versions which satisfy the requirement - as mentioned here: https://github.com/kubernetes-client/python/blob/master/README.md#hostname-doesnt-matchfollowed the issue on this thread - https://github.com/kubernetes-client/python/issues/36 - not much help.

kubectl apply -f class.yamlkubectl apply -f rbac.yamlkubectl apply -f deployment-arm.yaml I want to use the kubernetes-client written in python to replace it. My current code, loads the there yaml files (using pyyaml), edits them a bit, inserts into a file and use the command line kubectl to execute those three commands. Some of the code:

In the Kubernetes Python client code it's called "klass":

https://github.com/kubernetes-client/python/blob/1a0cb469528e6b2bdeb3eb2c06945f1c22303dfd/kubernetes/client/api_client.py#L266

and in Apache ecosystem it's called clazz:

https://github.com/search?q=org%3Aapache+clazz&type=code

Just thought it was amusing and wanted to share

One way is to use configmap lock https://github.com/kubernetes-client/python/tree/master/kubernetes/base/leaderelection

I'm having trouble connecting to the kubernetes python client even though I'm following the examples here in the api.

As you can imagine, that's a lot of functions to choose from, luckily all of them are listed in docs and you can click on any one of them to get an example of its usage.

I spent more than 8 hours wrestling with Kubernetes image credential provider plugins before finally stumbling upon the real solution. If you think this is as simple as dropping a config into Kind or Minikube think again. It doesn’t work that way, and I’d rather save you the wasted time I went through.

Kind (Kubernetes in Docker)

Yes, tools like Minikube, kind, and k3s create single-node clusters for development and testing. However, production Kubernetes is designed for distributed environments. Single-node deployments forfeit high availability, scalability, and fault tolerance benefits that justify Kubernetes complexity.

I needed a test bed for dumping all my wacky tools, horrible spaghetti code, and other OSS nonsense. Yes, I could use kind (https://kind.sigs.k8s.io/) on my own computer, but that would defeat some of the purpose of the things I'm doing: testing production-like environments, testing multi-node cluster things, testing for longer-term viability etc. Kind could probably do all these things, but where's the fun in that? ;)

Alternative: You may use minikube or kind if you prefer.

For the sake of simplicity l’ll show how to spin up two K8s clusters with kind, and use them in this demo.

Kubernetes KIND - Local Kubernetes development

Kind

Last step is starting the Kubernetes cluster. As I mentioned HariKube is transparent for Kubernetes, it works with Kubernetes out of the box, but supporting of large datasets requires recompiling Kubernetes API-Server and Controller-Manager. You can follow the guide how to do it here, but for simplicity in this tutorial we use Kind with vanilla Kubernetes.

For the installation of the ToolHive Operator, we’ve assumed there is already a Kubernetes cluster available with an Ingress controller. We have used Kind for this post as it is simple to set up, free and easy to use.