Atla is an advanced observability platform designed specifically for AI agent monitoring and evaluation. This integration provides comprehensive insights into agent performance, automated quality assessment, and detailed analytics for production AI systems.

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Prerequisites

Install the Atla Insights SDK with Agno support: 
pip install "atla-insights"

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Configuration

Configure your API key as an environment variable: 
export ATLA_API_KEY="your_api_key_from_atla_dashboard"

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Example

from os import getenv
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools
from atla_insights import configure, instrument_agno

# Step 1: Configure Atla
configure(token=getenv("ATLA_API_KEY"))

# Step 2: Create your Agno agent
agent = Agent(
    name="Market Analysis Agent",
    model=OpenAIChat(id="gpt-4o-mini"),
    tools=[DuckDuckGoTools()],
    instructions="Provide professional market analysis with data-driven insights.",
    debug_mode=True,
)

# Step 3: Instrument and execute
with instrument_agno("openai"):
    response = agent.run("Retrieve the latest news about the stock market.")
    print(response.content)
Now go to the Atla dashboard and view the traces created by your agent. You can visualize the execution flow, monitor performance, and debug issues directly from the Atla dashboard.
atla-trace

Atla Agent run trace