Back to Ecosystem Pulse
OperationsReference
multi-agent-observability-opentelemetry
by chrisipanaque
OpenTelemetry reference for tracing and metrics in LangGraph multi-agent systems
Python
Updated Jul 19, 2026
Share:
Overview
Implements OpenTelemetry patterns for multi-agent LLM systems to capture distributed traces, metrics, and logs. Provides a reference implementation that instruments LangGraph-based agent orchestration and demonstrates how to correlate agent-to-agent calls across services. Includes example instrumentation hooks and trace/span conventions tailored to agent workflows.
Why It Matters
As agents coordinate and delegate, observability becomes essential to assess reliability and build agent track records. This reference shows how to surface traces and metrics that become trust signals for agent-to-agent evaluation and continuous monitoring. Until you can reliably trace interactions and failures, you can't compute meaningful reputation or diagnose delegation failures in multi-agent deployments.
Best For
Engineers instrumenting LangGraph agent orchestrations who need a practical pattern for distributed tracing and telemetry.
Use Cases
- Instrument LangGraph orchestrations to correlate agent-to-agent calls with distributed traces
- Expose metrics and failure signals to support agent reliability and continuous evaluation
- Create reproducible telemetry patterns to build agent track records for reputation systems
Works With
langgraphopentelemetrypython
Topics
agent-orchestrationagent-tracingai-observabilitydistributed-tracingenterprise-aiinstrumentationlanggraphllm-observabilitymetricsmonitoring+7 more
Keywords
multi-agent observabilityopentelemetryagent-tracinglanggraph