Defensive AI Security & Governance› Agent Observability›An Observability Reference Architecture: Sampling, Cost, Privacy, and the Feedback Loop

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Agent Observability

1The Observability Gap: Why Traditional APM Fails on Non-Deterministic AI SystemsResearch
2The Pillars for AI: Traces, Metrics, and Evals as First-Class TelemetryResearch
3Semantic Telemetry: Capturing Reasoning, Tool Calls, and Decision Provenance with OpenTelemetry GenAIResearch
4Detecting Regressions Without Ground Truth: Reference-Free Evals and Drift SignalsResearch
5An Observability Reference Architecture: Sampling, Cost, Privacy, and the Feedback LoopResearch

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Murali Chillakuru

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An Observability Reference Architecture: Sampling, Cost, Privacy, and the Feedback Loop

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