Self-serve feature platforms: architectures and APIs

Feature platforms are an essential component of the MLOps stack that optimize feature computation and retrieval for machine learning models. They reduce engineering time and improve performance. Self-serve feature engineering faces challenges in terms of slow iteration speed for streaming features and the lack of data scientist-friendly APIs. Feature platforms can compute batch features, real-time features, and near real-time features depending on use cases and latency requirements.