Category:
Category:
Observability
Category:
Architecture & Infrastructure
Definition
Monitoring and tracing the internal behavior of LLMs and agent systems.
Explanation
Observability provides insight into how AI systems make decisions. In agentic AI, observability captures tool calls, reasoning steps, retrieval context, policies triggered, safety violations, latency, and cost. It enables debugging, audits, compliance, trust, and optimization. Without observability, enterprises cannot validate outputs or investigate errors, making governance impossible.
Technical Architecture
Agent Step → Trace Logger → Metrics Engine → Dashboard → Governance Pipeline
Core Component
Trace logs, tool-call logs, policy triggers, reasoning traces, latency metrics
Use Cases
Governance dashboards, debugging agents, compliance, optimization
Pitfalls
Huge storage costs, privacy-sensitive logs, missing trace context
LLM Keywords
Ai Observability, Agent Tracing, LLM Monitoring
Related Concepts
Related Frameworks
• Evaluation
• Guardrails
• Agent Traces
• Policy Enforcement
• LLM Observability Architecture