Observability & Evaluation · Software component
Failure Correlation Analyzer
Software componentObservability & EvaluationObservability & Evaluationarc:FailureCorrelationAnalyzer
An analysis component that correlates failure occurrences with time of day, concurrent load, input type and resource state to reveal the conditions under which intermittent failures cluster.
Responsibility. Identifies the operating conditions with which failures correlate.
Also known as: Intermittent failure analysis, Load/temporal correlation analysis, Metric correlation analysis
Relationships
reads dependency
Design guidance
- SHOULD record concurrent workload counts in traces so failure rates can be correlated with load.
Quantitative guidance
As stated by the sources; verify before use.
- Test (10 concurrent workflows) 98% success vs production (50+) 92%; 8% of 500 daily workflows failed (Ch8.2A).
- Latency 3.2 s at 10 concurrent workflows vs 8.7 s at 50 (2.7x for 5x load) due to shared-state lock contention (Ch8.2A).
- Failures clustered 9 AM-5 PM peak hours before fixes and were uniform afterwards (Ch8.2A).
- Checks failure correlation by time, load, input type and resource state; correlation > 0.7 treated as a strong pattern (Ref8.07).
Classification
- Patterns
- Correlation analysis
- Quality attributes
- Maintainability (ISO/IEC 25010)
- Risks mitigated
- Load-dependent failures invisible in low-concurrency testing
Sources
- Ch8.2A: T. Nguyen, "Error Rates and Reliability," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 8.2A. ISBN: 9798244538229.
- Ch10.4: T. Nguyen, "Human-in-the-Loop," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.4. ISBN: 9798244538229.
- Ref8.07: "Agent Health Checks and Diagnostics," unpublished reference note (07-Agent-Health-Checks-Diagnostics.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note