Code Search on Kubeflow
This demo implements End-to-End Code Search on Kubeflow.
NOTE: If using the JupyterHub Spawner on a Kubeflow cluster, use the Docker image
gcr.io/kubeflow-images-public/kubeflow-codelab-notebook which has baked all the pre-prequisites.
Kubeflow LatestThis notebook assumes a Kubeflow cluster is already deployed. See Getting Started with Kubeflow.
Ksonnet 0.12We use Ksonnet to write Kubernetes jobs in a declarative manner to be run on top of Kubeflow.
To get started, follow the instructions below.
NOTE: We will assume that the Kubeflow cluster is available at
kubeflow.example.com. Make sure
you replace this with the true FQDN of your Kubeflow cluster in any subsequent instructions.
Spawn a new JupyterLab instance inside the Kubeflow cluster by pointing your browser to https://kubeflow.example.com/hub and clicking "Start My Server".
In the Image text field, enter
gcr.io/kubeflow-images-public/kubeflow-codelab-notebook:v20180808-v0.2-22-gcfdcb12. This image contains all the pre-requisites needed for the demo.
Once spawned, you should be redirected to the Jupyter Notebooks UI.
Spawn a new Terminal and run
$ git clone --branch=master --depth=1 https://github.com/kubeflow/examples
This will create an examples folder. It is safe to close the terminal now.
Navigate back to the Jupyter Notebooks UI and navigate to
examples/code_search. Open the Jupyter notebook
code-search.ipynband follow it along.
This project derives from hamelsmu/code_search.