This notebook shows how to compile and run a simple Kubeflow pipeline using Jupyter notebooks and Google Cloud Storage. The pipeline is very simple, and is a helpful starting point for people new to Kubeflow.
This pipeline requires you to setup a notebook server in the Kubeflow UI. After you are setup, upload this notebook and then run it in the notebook server.
This pipeline requires a GCS bucket. If you haven't already, create a GCS bucket to run the notebook. Make sure to create the storage bucket in the same project that you are running Kubeflow on to have the proper permissions by default. You can also create a GCS bucket by running gsutil mb -p <project_name> gs://<bucket_name>.
In order to run this pipeline, make sure to upload the notebook to your notebook server in the Kubeflow UI. You can clone this repo in the Jupyter notebook server by connecting to the notebook server and then selecting New > Terminal. In the terminal type git clone https://github.com/kubeflow/examples.git.