Open Sourcing Feathr (https://engineering.linkedin.com/blog/2022/open-sourcing-fea...)

Feathr + Azure integration (https://azure.microsoft.com/en-us/blog/feathr-linkedin-s-fea...).

Tech talks on Feathr (https://www.youtube.com/watch?v=gZg01UKQMTY)

And its highlights include (more highlights are in github repo):

Battle tested in production for more than 6 years: LinkedIn has been using Feathr in production for over 6 years and have a dedicated team improving it.

Scalable with built-in optimizations: For example, based on some internal use case, Feathr can process billions of rows and PB scale data with built-in optimizations such as bloom filters and salted joins.

Rich support for point-in-time joins and aggregations: Feathr has high performant built-in operators designed for Feature Store, including time-based aggregation, sliding window joins, look-up features, all with point-in-time correctness.

Derived Features and centralized Feature Registry which encourage feature consumers to build features on existing features and encouraging feature reuse.

Happy to chat about it if anyone is interested in it!