Confluera Real-time Threat Storyboarding is a cloud-native threat detection and investigation platform that uses behavioral analytics and ML-powered anomaly detection to identify suspicious host and network behaviors in real time. The platform is built on a patented Continuous Attack Graph technology using T-DAG (Transactional Directed Acyclic Graph) concepts. It models execution activity across infrastructure as causally linked graphs, which are continuously ranked by the degree of suspicious behavior. Core workflow: 1. Workload and cloud infrastructure telemetry are causally stitched into infrastructure-wide activity sequences. 2. Security signals from native detections and third-party tools are applied to those sequences. 3. Attack chains are automatically prioritized based on cumulative risk scoring. 4. Context-sensitive response actions are surfaced to evict attackers and remove backdoors. The platform tracks adversary lateral movement across hosts and containers in real time, including east-west movements. It is designed to detect slow-moving, low-and-slow attacks by maintaining causal event chains even across long dormant periods (minutes to months). Security signals from threat intelligence feeds and third-party security tools are fused into threat storyboards, reducing false positives and surfacing weak signals that would otherwise be lost. Remediation recommendations are automatically generated and kept current based on live, active entities in the attack graph. The platform claims a 10x reduction in alerts and is designed to handle high-throughput telemetry streams across tens of thousands of workloads.