Kubeflow notebook servers

 We can use Kubeflow to start a Jupyter notebook server in a namespace, where we can run experimental code; we can start the notebook by clicking the Notebook Server tab in the user interface and selecting NEW SERVER

We can then specify parameters, such as which container to run(which could include the TensorFlow container we examined earlier in our discussion of Kocker), and how many resources to allocate.

You can also specify a Persistent Volumn(PV) to store data that remains even if the notebook server is turned off, and special resources such as GPUs.

Once started, if you have specified a container with TensorFlow resources, you cna begin running models in the notebook server.