In order to improve the usability of FADI when deployed for Machine Learning / Data Science projects, a support for Seldon should be added.
Seldon is an open source project for packaging machine learning models and scoring them. It hides such models behind a REST API, and build Docker containers for deploying them.
From the user's point of view, Seldon is essentially a tool for converting source code into containers, making it "easier and faster to deploy your machine learning models and experiments at scale on Kubernetes". Related advanced features are also provided. In particular, performances metrics are generated by Seldon
Is your feature request related to a problem? Please describe.
No, it's a suggestion for an extension improving the functional coverage of FADI instances.
Describe the solution you'd like
Helm charts should be added to FADI, in order to be able to deploy and exploit an instance of Seldon.
Ideally we would want an example documentation like we have for BinderHub with a concrete use case and shiny screenshots, maybe we can combine both in an integrated example (also MLFlow?).
In order to improve the usability of FADI when deployed for Machine Learning / Data Science projects, a support for Seldon should be added.
Seldon is an open source project for packaging machine learning models and scoring them. It hides such models behind a REST API, and build Docker containers for deploying them.
From the user's point of view, Seldon is essentially a tool for converting source code into containers, making it "easier and faster to deploy your machine learning models and experiments at scale on Kubernetes". Related advanced features are also provided. In particular, performances metrics are generated by Seldon
Is your feature request related to a problem? Please describe. No, it's a suggestion for an extension improving the functional coverage of FADI instances.
Describe the solution you'd like Helm charts should be added to FADI, in order to be able to deploy and exploit an instance of Seldon.
Describe alternatives you've considered None.
Additional context N/A