Error Tracking
Also called: Exception Tracking
The process of capturing, recording, aggregating, and monitoring errors and exceptions generated by an AI system to support debugging, reliability, and operational visibility.
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Related terms
The practice of recording application, model, and system events to support debugging, monitoring, troubleshooting, and operational analysis.
Failure AnalysisThe process of investigating errors, failures, or unexpected behavior in an AI system to identify root causes, assess their impact, and implement corrective or preventive actions.
Application MonitoringThe practice of collecting and analyzing telemetry from applications to track performance, availability, errors, and overall operational health.
AlertingThe process of automatically notifying users or systems when predefined conditions, thresholds, or anomalies indicate potential issues requiring attention.
Error RecoveryThe process by which an AI system detects execution failures, handles exceptions, and restores normal operation through retries, fallbacks, alternative actions, or corrective procedures.