Real-time anomaly detection in streaming data

Our platform processes over 10 million events per second. We need a system that can detect anomalies in real-time with minimal false positives. Requirements: - Sub-second detection latency - Less than 1% false positive rate - Ability to handle concept drift - Scalable horizontally - Support for multivariate time series We welcome both statistical and ML-based approaches.