Kubeflow-kale :- How to integrate kubeflow-kale extension to run pipelines on a seperate standalone cluster of Kubeflow pipelines

Question

I am currently trying to use the kubeflow kale jupyter extension on my local jupyterlab server without Kubernetes and kubeflow installed and trying to run my code pipeline on GCP AI pipeline server or any other Cloud Kubeflow pipeline server. I am able to do it through kubeflow pipeline SDK(As it has a feature to add hostname details). But when trying to achieve through the kubeflow-kale extension it does not work. As I am aware we need to provide the hostname of the Kubeflow pipeline server which I was not able to add on kubeflow-kale UI extension drop-down fields. I have explored a lot of kubeflow-kale materials and blogs but was not able to find the solution. Almost all the blogs and material about Kubeflow-kale implementation has been done on the Kubeflow hosted notebook server

Can anyone help me with the following doubts about Kubeflow-kale:-

1. Kubeflow-kale is only supported for kubeflow hosted notebook server?
2. If No, How can we provide the option to run the pipeline on a remote Server like GCP AI Pipelines?

Answer 1

Spending time last one yar with Kubeflow wand echo system what I realize is following:

1. Kubeflow-kale is open sourced however not completely free, there are issues running the kubeflow-kale on latest version, we have reported issues on github for the same, it works with Arrikito however Arrikito is licensed

2. You should be able to install kale locally step by step as mentioned in their documentation, however I have not tried it

3. If you are looking for pipeline editor Elyra is much better choice - free and they are adding support for other pipelines like TFX etc.