A functional feature store is necessary, but a production-ready one must also perform efficiently under load and scale effectively as data volumes and request rates increase. This chapter addresses the practical aspects of ensuring your feature store meets these operational requirements.

We will cover methods for systematically evaluating performance through benchmarking. You'll learn techniques to minimize online feature retrieval latency and to scale offline feature computation tasks for large datasets. Additionally, we examine strategies for optimizing storage usage, managing operational costs, designing for high availability and disaster recovery, and conducting capacity planning and load testing to prepare for future demands.