John-Lin/Kubeflow.md

## Kubeflow.md

      
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              Kubeflow.md
            
          
    Deploy Kubeflow on Minikube

Install minikube

Please see How to Minikube
Running a minikube with 4CPUs and 8GB memory

$ minikube start --cpus 4 --memory 8192
If you want to use the vm driver with hyperkit
$ minikube start --vm-driver=hyperkit --cpus 4 --memory 8192
Deploy Kubeflow

$ git clone git@github.com:google/kubeflow.git
$ cd kubeflow
$ kubectl apply -f components/ -R
# Wait until all pod are getting running state. (6-7 mins)
Get the URL for the notebook.
$ minikube service tf-hub-lb --url
or access JupyterHub on http://localhost:8000 by
$ kubectl port-forward tf-hub-0 8000:8000
User Login

input any username and password will login
Basic notebook with scipy in JupyterHub

Spawner options

Image : jupyter/scipy-notebook (jupyterhub version MUST be at least 0.8.1)
CPU: 200m (could be more)
Memory: 256Mi (could be more)
Extra Resource Limits: (leave it empty)
than press the Spawn button
##Tensorflow wit notebook in JupyterHub
Spawner options

Image : gcr.io/kubeflow/tensorflow-notebook-cpu
CPU: 300m (almost run out of quota in 4 CPU minikube)
Memory: 1.5Gi (could be more)
Extra Resource Limits: (leave it empty)
than press the Spawn button
Running a tensorflow example

See Neural Network Example
You may get this message, python3.5 still works. but we are in 3.6 wait until google fixed this issue. We could just ignore.
/home/raju/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6
See  tensorflow/tensorflow#14182
CPU/Mem resource monitoring on K8S

$ kubectl describe node