Metaflow has been used in production at Netflix since early 2018. The core Metaflow was open-sourced in December 2019. Some features of Metaflow are not available in open-source yet but we may open-source them later if there is sufficient external interest. These features are listed below.

Please click the link and comment / thumbs-up the corresponding GitHub issue if you want to see the feature open-sourced.

Support for R Lang

​Metaflow in the R language. Provide an idiomatic R API which uses the Python library as the backend (Github issue)

Support deployments to a production DAG scheduler

Netflix uses an internal DAG scheduler to orchestrate most modeling and ETL pipelines in production. Metaflow flows can be deployed to the production scheduler with a single command. A similar integration could be provided e.g. for AWS Step Functions (Github issue)

Support for hosting models as a micro-service

An easy-to-use Function-as-a-Service -style microservice hosting platform for artifacts (e.g. models) produced by Metaflow runs (Github issue)

Metaflow DataFrame

Support in-memory processing of large data sets (Github issue)​

MetaflowBot

A Slack bot for Metaflow. Use it to ask questions about past runs (Github issue)