How Lyft Built an ML Platform That Serves Millions of Predictions Per Second

Lyft built LyftLearn Serving, a machine learning platform that handles millions of predictions per second for ride-sharing operations like pricing, fraud detection, and driver incentives. The company replaced its monolithic system with a microservices architecture that generates independent services for each team, allowing them to use different ML libraries and deploy independently. Using a configuration generator, ML engineers can quickly create functional microservices through a simple setup process, while automated self-testing ensures models continue working correctly as the system evolves.