Agent Observability with Distributed Tracing
You can’t improve what you can’t observe. Distributed Tracing for Agents captures the full journey of a request across agent steps, tool calls, LLM invocations, and external services — giving you end-to-end visibility into latency, errors, and behavior.
This is foundational for debugging and optimizing production agents.
As a dev, I instrument every agent with distributed tracing from the start.
Agent Observability Cheatsheet:
• Trace every step: User query → Agent thought → Tool/LLM call → Final output
• Add custom attributes: agent version, model, cost, trace context
• Tools: OpenTelemetry Jaeger/Tempo LangSmith/Phoenix dashboards
• Combine with metrics (latency, tokens, error rate) and structured logs
• Pro tip: Use consistent trace IDs across all services for full request visibility
How are you currently observing and tracing your production agents? Reply below 👇
Follow
@AiCamila_ for real-world production AI scaling tips.
#AgentObservability #DistributedTracing #AgenticAI #DevOps