How Cloudflare runs machine learning inference in microseconds

Cloudflare executes an array of security checks on servers spread across our global network. These checks are designed to block attacks and prevent malicious or unwanted traffic from reaching our customers’ servers. But every check carries a cost - some amount of computation, and therefore some amount of time must be spent evaluating every request we process. As we deploy new protections, the amount of time spent executing security checks increases.

Latency is a key metric on which CDNs are evaluated. Just as we optimize network latency by provisioning servers in close proximity to end users, we also optimize processing latency - which is the time spent processing a request before serving a response from cache or passing the request forward to the customers’ servers. Due to the scale of our network and the diversity of use-cases we serve, our edge software is subject to demanding specifications, both in terms of throughput and latency.

Cloudflare's bot management module is one suite of security checks which executes during the hot path of request processing. This module calculates a variety of bot signals and integrates directly with our front line servers, allowing us to customize behavior based on those signals. This module Continue reading