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What You’ll Learn

In this guide, you’ll learn how to:
  • Set up a Fiddler application for monitoring Google ADK agents
  • Install and configure the Fiddler ADK SDK
  • Instrument ADK agents with automatic telemetry
  • Run a multi-turn agent with tool calls
  • Verify monitoring is working correctly
Time to complete: ~10 minutes

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Prerequisites

Before you begin, ensure you have:
  • Fiddler Account: An active account with access to create applications
  • Python 3.10+: Verify your version: 
    python --version
  • Fiddler ADK SDK: Install the SDK: 
    # Using uv (recommended)
uv add fiddler-adk

# Or using pip
pip install fiddler-adk
  • Google Gemini Access: Either a Gemini API key or Vertex AI credentials: 
    # Option A: Gemini API key
export GOOGLE_API_KEY=<your-gemini-api-key>

# Option B: Vertex AI
export GOOGLE_GENAI_USE_VERTEXAI=1
export GOOGLE_CLOUD_PROJECT=<your-gcp-project>
export GOOGLE_CLOUD_LOCATION=us-central1
If you prefer using a notebook, download it directly from GitHub or open it in Google Colab to get started.
1

Create a Fiddler Application

First, create a dedicated application in Fiddler to receive your agent traces.
  1. Sign in to your Fiddler instance
  2. Navigate to GenAI Applications in the left sidebar
  3. Click Add Application
  4. Enter the application details:
    • Name: google-adk-monitoring
    • Project: Select a project from the dropdown or press Enter to create a new one
  5. Click Create and copy the Application UUID (you’ll need this for configuration)
2

Configure Credentials

Set up the required credentials. You need your Fiddler API key (from Settings) and the Application UUID from Step 1.Instructions for generating your API key can be found in the Access guide.
# Fiddler credentials
export FIDDLER_URL="https://your-fiddler-instance.com"
export FIDDLER_API_KEY="<your-fiddler-api-key>"
export FIDDLER_APPLICATION_ID="<application-uuid-from-step-1>"

# Google Gemini credentials (choose one)
export GOOGLE_API_KEY="<your-gemini-api-key>"
# or for Vertex AI:
# export GOOGLE_GENAI_USE_VERTEXAI=1
# export GOOGLE_CLOUD_PROJECT="<your-gcp-project>"
Tip: Save these in a .env file and load with python-dotenv for easy reuse.
3

Set Up Instrumentation

Add two lines to your application to enable Fiddler monitoring:
import os
from fiddler_otel import FiddlerClient
from fiddler_adk import GoogleADKInstrumentor

# Initialize Fiddler client
client = FiddlerClient(
    api_key=os.environ["FIDDLER_API_KEY"],
    application_id=os.environ["FIDDLER_APPLICATION_ID"],
    url=os.environ["FIDDLER_URL"],
)

# Enable automatic instrumentation
GoogleADKInstrumentor(client).instrument()
That’s it. All ADK agents created after this point are automatically traced.
4

Create and Run Your Agent

Create an ADK agent with tools and run it:
import asyncio
from google.adk.agents.llm_agent import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.genai import types


# Define a tool
def get_weather(city: str) -> dict:
    """Get current weather for a city."""
    return {"city": city, "temp_f": 72, "condition": "sunny"}


# Create agent
agent = Agent(
    model="gemini-2.5-flash",
    name="weather_agent",
    description="A helpful weather assistant",
    instruction="You help users check the weather. Be brief.",
    tools=[get_weather],
)


async def main():
    session_service = InMemorySessionService()
    runner = Runner(
        agent=agent, app_name="demo", session_service=session_service
    )
    session = await session_service.create_session(
        app_name="demo", user_id="user1"
    )

    # Send a message
    message = types.Content(
        role="user",
        parts=[types.Part(text="What's the weather in San Francisco?")],
    )

    async for event in runner.run_async(
        user_id="user1", session_id=session.id, new_message=message
    ):
        if hasattr(event, "content") and event.content:
            parts = getattr(event.content, "parts", []) or []
            text = "".join(
                p.text for p in parts if getattr(p, "text", None)
            )
            if text:
                print(f"Agent: {text}")

    # Flush traces before exit
    client.force_flush(timeout_millis=5000)


asyncio.run(main())
5

Verify Monitoring in Fiddler

After running your agent:
  1. Navigate to your Fiddler instance
  2. Open the GenAI Applications page
  3. Click on your application (google-adk-monitoring)
  4. Open the Trace Explorer
You should see a trace tree with:
  • Agent span (invoke_agent) - the agent execution
  • LLM span (call_llm) - the Gemini API call with input/output
  • Tool span (execute_tool get_weather) - the tool call with arguments and response
Each LLM span shows the user’s question, the model’s response, system instructions, and token usage.

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Troubleshooting

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No Traces Appearing

  • Verify client.force_flush() is called before the process exits
  • Check for 401 errors in logs (wrong API key)
  • Ensure the Application UUID matches an existing GenAI Application

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Gemini API Errors

  • Verify GOOGLE_API_KEY or Vertex AI credentials are set
  • For Vertex AI, ensure gcloud auth application-default login has been run

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Configuration Options

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Supported Models

Any Gemini model supported by Google ADK:
  • gemini-2.5-flash, gemini-2.5-pro
  • gemini-2.0-flash
  • gemini-1.5-flash, gemini-1.5-pro

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Supported ADK Versions

  • google-adk >= 1.34.2 (both 1.x and 2.x lines)
  • opentelemetry-api >= 1.37.0

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Next Steps