Distributed Tracing
An observability technique that tracks requests as they flow across multiple distributed services to measure latency, diagnose failures, and analyze system behavior.
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Related terms
The practice of monitoring, tracing, and analyzing AI systems to understand their behavior, performance, reliability, and operational health in production.
Application MonitoringThe practice of collecting and analyzing telemetry from applications to track performance, availability, errors, and overall operational health.
LoggingThe practice of recording application, model, and system events to support debugging, monitoring, troubleshooting, and operational analysis.
Metrics CollectionThe process of gathering quantitative measurements from AI systems and applications to track performance, reliability, usage, and operational health.
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.