oc new-app radanalyticsio/base-notebook \ -e JUPYTER_NOTEBOOK_PASSWORD=supersecret \ -e JUPYTER_NOTEBOOK_X_INCLUDE=https://radanalytics.io/assets/s3-source-example/s3-source-example.ipynb oc expose svc/base-notebook
Processing data stored in an external object store is a practical and popular way for an intelligent application to operate.
This is an example of the key pieces needed to connect your application to data in S3. It is presented as steps in a Jupyter notebook.
No architecture, this is a connectivity example.
Start a Jupyter notebook with,
oc new-app radanalyticsio/base-notebook \ -e JUPYTER_NOTEBOOK_PASSWORD=supersecret \ -e JUPYTER_NOTEBOOK_X_INCLUDE=https://radanalytics.io/assets/s3-source-example/s3-source-example.ipynb oc expose svc/base-notebook
From your OpenShift Console, go to the notebook’s web interface and
login with supersecret
.
Open the notebook and try out the example code.
No specific usage.
No specific expansion.
No video, follow the notebook steps.