Observability & Evaluation · Software component

SLO Monitor

Software componentObservability & EvaluationObservability & Evaluationarc:SLOMonitor

A software component that compares service indicators with thresholds and raises alerts before users notice degradation.

Responsibility. Alerts when indicators cross objectives.

Also known as: Alerting, Staging soak monitor, Data quality SLA monitor

Direct neighbourhood (hover for relationship types)

Relationships

is configured by structural

reads dependency

receives data from dynamic

Metrics Collector Ch1.7B Ch4.2

sends data to dynamic

Alert Manager Ch10.1

triggers dynamic

monitors assurance

Design guidance

SHOULD watch a new deployment over a soak period and trigger automatic rollback on any threshold violation.
SHOULD trigger a detailed profiling capture for the affected request pattern when p99 latency suddenly increases.
SHOULD flag breaches whenever P95 exceeds the SLA threshold rather than when the mean does (Ch8.1, Ref8.03).

Quantitative guidance

As stated by the sources; verify before use.

Example alerts: p95 latency > 200ms or failure rate > 1% (Ch1.7B).
Layered resilience targets 99.9% uptime (Ch2.8).
Staging soak thresholds: success rate > 95%, p95 latency < 8 s, error rate < 2%, memory stable (Ch4.2).
Example SLA targets: P95 <200ms, error rate <0.5% (Ch7.2).

Classification

Quality attributes: Reliability (ISO/IEC 25010 | NIST AI RMF: valid and reliable)
Risks mitigated: Undetected degradation from missing indexes or graph growth

Sources

Ch1.7B: T. Nguyen, "Relational Reasoning with Knowledge Graphs - Hybrid RAG+KG Integration," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.7B. ISBN: 9798244538229.
Ch2.8: T. Nguyen, "Error Handling and Resilience," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 2.8. ISBN: 9798244538229.
Ch3.6: T. Nguyen, "Trace Analysis and Execution Debugging," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 3.6. ISBN: 9798244538229.
Ch4.2: T. Nguyen, "Deployment and Scaling," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 4.2. ISBN: 9798244538229.
Ch4.4: T. Nguyen, "Performance Profiling and Optimization," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 4.4. ISBN: 9798244538229.
Ch6.4: T. Nguyen, "Data Quality Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 6.4. ISBN: 9798244538229.
Ch6.5: T. Nguyen, "Production RAG Systems," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 6.5. ISBN: 9798244538229.
Ch7.2: T. Nguyen, "Performance Optimization and Production Monitoring," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 7.2. ISBN: 9798244538229.
Ch8.1: T. Nguyen, "Latency Metrics," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 8.1. ISBN: 9798244538229.
Ch10.1: T. Nguyen, "Conversational UI," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 10.1. ISBN: 9798244538229.
Ref7.16: "Production Monitoring and Operations for Agentic AI," unpublished reference note (16-Production-Monitoring-Operations.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note
Ref8.03: "Agent Evaluation Frameworks and Metrics," unpublished reference note (03-Agent-Evaluation-Frameworks.md), Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam supplementary materials, 2026. unpublished note