Open feature library management

In an approach for managing an open feature library, a processor collects feature metadata from a data source, the feature metadata being data related to features for training a machine learning model. A processor builds a feature pipeline for the features based on the collected feature metadata. The feature pipeline may be a set of defined and active features. A processor executes the feature pipeline including computing the features. A processor executes a machine learning model using the computed features. A processor evaluates the features and corresponding model results.