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The Challenge

LLM applications require specialized monitoring beyond traditional application metrics. RAG systems need retrieval-specific metrics, prompt flows require detailed tracing, and quality degradation must be detected before user impact. Existing monitoring solutions lacked LLM-specific capabilities.

Our Solution

We implemented a comprehensive observability stack using OpenTelemetry for standardized telemetry, RAG-specific metric design, prompt flow tracing, and real-time dashboards. The system includes automated quality checks, historical analysis capabilities, and intelligent alerting based on LLM-specific patterns.

Results

Reduced mean time to detection (MTTD) by 70%, achieved 100% observability coverage across all LLM applications, and improved alert accuracy to 95% (reducing false positives by 80%).

70%
Mttd Reduction
100%
Observability Coverage
95%
Alert Accuracy
80%
False Positive Reduction
50% faster
Incident Resolution Time

Measurement Period: 6 months post-deployment

Methodology: Monitoring metrics analysis and incident tracking

Time-to-Value

Total Duration: 7 weeks

  • Kickoff: Week 1
  • Architecture Review:
  • Build Complete:
  • Pilot Deployment:
  • Production Rollout: Week 7

Architecture & Scope

Components Deployed

  • OpenTelemetry instrumentation
  • RAG-specific metrics collector
  • Prompt flow tracer
  • Real-time dashboards (Grafana)
  • Automated quality check system
  • Historical analysis engine

Integration Points

  • OpenTelemetry SDK
  • Prometheus
  • Grafana
  • Alerting systems (PagerDuty/Slack)
  • All LLM applications
Architecture Diagram

Risk & Controls Implemented

Audit Trails

Complete observability data retention and audit logging

Permission Models

RBAC for monitoring data access

Evaluation Harnesses

Automated quality checks and anomaly detection

Compliance Controls

Observability aligned with audit and compliance requirements

Artifacts

Screenshots

Sample Outputs

Example monitoring dashboards and trace visualizations

Featured in

Advanced Large Language Model Operations

Springer Nature, March 2026

Chapter: Chapter 5: Monitoring and Observability of LLM Applications

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