CRITICAL
AI Incident Detection & Alerting
Detecting anomalies in model behavior, output quality, error rates, and usage patterns in real time enables operations teams to identify and respond to AI-specific incidents before they impact users or violate SLAs. Traditional APM tools miss AI-specific failure modes like quality degradation, hallucination spikes, prompt injection attempts, and gradual drift that manifest as correctness issues rather than availability problems. When evaluating solutions, assess their ability to monitor both technical metrics (latency, errors, throughput) and quality metrics (relevance, accuracy, safety scores), customizable alert thresholds, incident classification and routing, integration with existing on-call workflows, and root cause analysis tooling.