Putting machine learning models into production is difficult. It’s especially hard to do for a team that isn’t cross-function and doesn’t have strong ops or software engineering support. At Distil we used severless technology to deploy a Python-based machine learning system that let data scientists rapidly put models they trained into production for detecting automated threats on websites. This talk will discuss how we rapidly built this pipeline, what we learned and what we’d do differently in the future. We make hundreds of predictions per second and stream the results to hundreds of machines all without having to manage any machines or hardware.