Fastly Next-Gen WAF
52 Case Studies
A Fastly Next-Gen WAF Case Study
DoorDash, a last-mile logistics platform operating in more than 1,200 cities across the U.S. and Canada, was struggling with scaling security: their homebrew Splunk plus AWS WAF approach required constant rules maintenance as customer traffic grew. To gain better visibility and protection without that operational burden, DoorDash turned to Signal Sciences (now part of Fastly).
Signal Sciences deployed in minutes and delivered superior visibility, detection and blocking with no false positives. By using Signal Sciences’ Power Rules, traffic-source signals and APIs to integrate with custom tooling, DoorDash more effectively blocked bots and business-logic attacks and eliminated the heavy rules maintenance they faced with AWS WAF.