ML Ops Platform at Cloudflare

We've been relying on ML and AI for our core services like Web Application Firewall (WAF) since the early days of Cloudflare. Through this journey, we've learned many lessons about running AI deployments at scale, and all the tooling and processes necessary. We recently launched Workers AI to help abstract a lot of that away for inference, giving developers an easy way to leverage powerful models with just a few lines of code. In this post, we’re going to explore some of the lessons we’ve learned on the other side of the ML equation: training.

Cloudflare has extensive experience training models and using them to improve our products. A constantly-evolving ML model drives the WAF attack score that helps protect our customers from malicious payloads. Another evolving model power bot management product to catch and prevent bot attacks on our customers. Our customer support is augmented by data science. We build machine learning to identify threats with our global network. To top it all off, Cloudflare is delivering machine learning at unprecedented scale across our network.

Each of these products, along with many others, has elevated ML models — including experimentation, training, and deployment — to a crucial position within Continue reading