Hi, There're some challenges bringing a model inside notebook to a production environment. Many many organizations, the most common practice I see today is something like
1. Data scientist develop a model in a data science notebook. 2. SW engineer rewrites the model, to meet the production requirements. In other words, data scientists do not have self-service capability. And the organization is spending a lot of time for reimplementing model for production. I tried to identify the gaps between data science notebook and production environment, and what can possibly address them. So models that created by data scientists in the notebook can go production with minimum efforts. I made a proposal to solve this problem. Please review and comment. Any ideas and feedbacks are welcome. You can make a modification if needed. https://docs.google.com/document/d/1YA6q8W9yO8a88xzLDYs9zv_fKu2_cnB58rmQbakxi1I/edit?usp=sharing This document is linked from https://issues.apache.org/jira/browse/ZEPPELIN-3994 Thanks, moon
