Getting error while running workflow on kubernetes

Hi,

I’m using minikube to run kubernetes in local system and trying to run workflow defined in demos/sklearn-pipe/sklearn-project.ipynb but getting the below error message.

Jupyter Cell:

artifact_path = path.abspath('./pipe/{{workflow.uid}}')

run_id = skproj.run(
    'main',
    arguments={}, 
    artifact_path=artifact_path, 
    dirty=True)

Error message: MaxRetryError: HTTPConnectionPool(host='ml-pipeline.default.svc.cluster.local', port=8888): Max retries exceeded with url: /apis/v1beta1/experiments (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fea36705a90>: Failed to establish a new connection: [Errno -2] Name or service not known'))

I have followed the instructions mentioned in below readme file https://github.com/mlrun/mlrun/blob/master/hack/local/README.md

Can anyone help me in resolving the error?

[ghost]

for issue 1 try (if you followed the instructions):

from mlrun.platforms import mount_pvc
fn.apply(mount_pvc("nfsvol", "nfsvol", "/home/joyan/data"))

[yaronha]

@narendra36 you should set both DEFAULT_DOCKER_REGISTRY (url, e.g. https://index.docker.io/v1/) and DEFAULT_DOCKER_SECRET (k8s secret name, in the same namespace), another way is to set the registry per function, add this method to your function object fn.build_config(image='target/image:tag', secret='my_docker')