Databricks created MLflow in 2018 as an open source platform for the management of machine learning lifecycles. The platform was created in response to the complicated process of machine learning model development. Unlike traditional software development, machine learning models must not only track code versions, but versions of data sets, model parameters, and algorithms. Because of this, the variables that must be tracked and managed can grow exponentially. 

MLflow prevents the process from overwhelming scientists, educators, developers, and other users by providing a platform to fully manage end-to-end machine learning development lifecycle, which includes everything from data prep, deployment, experiment tracking, creating reproducible runs, model sharing, and collaboration.

Matei Zaharia, the original creator of Apache Spark and creator of MLflow, said of his platform, “MLflow has become the open source standard for machine learning platforms because of the community of contributors, which consists of hundreds of engineers from over a hundred companies. ” Zaharia concludes with, “Machine learning is transforming all major industries and driving billions of decisions in retail, finance, and health care. Our move to contribute MLflow to the Linux Foundation is an invitation to the machine learning community to  incorporate the best practices for ML engineering into a standard platform that is open, collaborative, and end-to-end.“
The Linux Foundation will create a vendor neutral home that includes an open governance model to aid in the broadening of MLflow adoption.

To date, MFflow has been downloaded over 2 million times per month and enjoys over 200 contributors. 

Original announcement: https://www.linuxfoundation.org/press-release/2020/06/the-mlflow-project-joins-linux-foundation/