Real-time HTTP anomaly detection for always-online web platforms

Real-time HTTP anomaly detection for always-online web platforms targets a $8.0B = 200,000 mid-to-large web platforms x $40K ACV (application-layer security + runtime protection spend) total addressable market with medium saturation and a year-over-year growth rate of 15% (application security & runtime protection expanding with cloud adoption).

Key trends driving demand: Edge compute adoption -- pushing detection/mitigation closer to the request path reduces latency and enables inline defense.; Automated reconnaissance & bot sophistication -- increases demand for behavioral, real-time detection rather than static rules.; AI/ML for anomaly detection -- enables adaptive baselines and fewer false positives compared to signature-only approaches.; Shift to cloud-native architectures -- creates standardized integration points (sidecars, ingress controllers) for detectors..