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Microsoft Agent Framework → OpenObserve

Capture agent run latency, input metadata, output size, and error details for every Microsoft Agent Framework invocation. Microsoft Agent Framework is a Python SDK for building multi-agent AI workflows with support for multiple LLM providers. Instrumentation wraps each agent.run() call in an OpenTelemetry span exported to OpenObserve.

Prerequisites

  • Python 3.10+
  • An OpenObserve account (cloud or self-hosted)
  • Your OpenObserve organisation ID and Base64-encoded auth token
  • An OpenAI API key

Installation

pip install openobserve-telemetry-sdk agent-framework agent-framework-openai python-dotenv

Configuration

Create a .env file in your project root:

OPENOBSERVE_URL=https://api.openobserve.ai/
OPENOBSERVE_ORG=your_org_id
OPENOBSERVE_AUTH_TOKEN=Basic <your_base64_token>
OPENAI_API_KEY=your-openai-api-key

Instrumentation

Call openobserve_init() to set up the tracer provider, then wrap each agent.run() call in a manual span to capture input and output attributes.

from dotenv import load_dotenv
load_dotenv()

from openobserve import openobserve_init
openobserve_init(resource_attributes={"service.name": "microsoft-agent-framework"})

from opentelemetry import trace
import asyncio
import os
from agent_framework import Agent
from agent_framework_openai import OpenAIChatClient

tracer = trace.get_tracer(__name__)

client = OpenAIChatClient(api_key=os.environ["OPENAI_API_KEY"], model="gpt-4o-mini")
agent = Agent(client=client)

async def main():
    with tracer.start_as_current_span("agent_framework.run") as span:
        span.set_attribute("agent.input", "What is distributed tracing?")
        result = await agent.run("What is distributed tracing?")
        output = result.text if hasattr(result, "text") else str(result)
        span.set_attribute("agent.output_length", len(output))
        span.set_attribute("span_status", "OK")
    print(output)

asyncio.run(main())

What Gets Captured

Attribute Example Value
operation_name agent_framework.run
agent_input What is distributed tracing?
agent_output_length 2391
span_kind Internal
span_status OK on success, ERROR on failure
error_message Full error string on failed calls
service_name microsoft-agent-framework
duration End-to-end agent run latency in microseconds

Viewing Traces

  1. Log in to OpenObserve and navigate to Traces
  2. Filter by service_name = microsoft-agent-framework to see all agent runs
  3. Click any span to inspect agent_input, agent_output_length, and duration
  4. Filter by span_status = ERROR to find failed invocations and read error_message
  5. Sort by duration descending to identify the slowest agent calls

Microsoft Agent Framework traces in OpenObserve

Next Steps

With Microsoft Agent Framework instrumented, every agent run is recorded in OpenObserve. From here you can track latency per prompt type, monitor error rates, and set alerts when agent calls fail in production.

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