Chapter 15: Continuous Evaluation & Monitoring¶

Continuous evaluation & automated red teaming animation

Figure: Continuous Evaluation & Monitoring in action (animated)

Overview¶

Telemetry Everywhere: Instrument agents with granular logging and real-time metrics.

Continuous Evaluation in Production¶

Building trustworthy AI doesn't stop at deployment—it requires ongoing vigilance:

Automated Monitoring: Continuous quality and safety checks on production traffic
Drift Detection: Alert when model behavior changes over time
A/B Testing: Compare system versions with real user interactions
Feedback Integration: Capture user corrections and satisfaction signals
Automated Red Teaming: Ongoing adversarial testing with PyRIT

Azure AI Foundry Monitoring¶

Azure provides comprehensive continuous evaluation capabilities:

Application Insights: Real-time telemetry for every AI interaction
Azure Monitor: Alerts and dashboards for operational metrics
Evaluation Pipelines: Scheduled batch evaluations on production data
PyRIT Integration: Automated red team scanning in Azure AI Foundry

Continuous evaluation transforms AI from a "deploy and hope" model to a "measure and improve" model. With Azure's monitoring stack and GitHub Actions for CI/CD, you can catch issues before users do.

Resources and Further Reading¶

Online Resources¶

🌐 Azure Monitor
🌐 Continuously Monitor Your AI Applications
🌐 Continuously Evaluate Your AI Applications

Next Steps¶

Continue your learning journey:

← Chapter 14 | Chapter 16 →

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