AWS Strands Integration

Updated on Aug 14, 2026

Use this integration when your AWS Strands application is implemented in Python.

Setup

1. Install SDK

bash

pip install progress-observability

2. Instrument your app

python

Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY")
)

3. Complete example

python

import os
from dotenv import load_dotenv
from strands import Agent, tool
from strands.models.openai import OpenAIModel
from progress.observability import Observability

load_dotenv()

# LLM INSTRUMENTATION
Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY")
)

model = OpenAIModel(
  client_args={"api_key": os.getenv("OPENAI_API_KEY")},
  model_id="gpt-4o-mini"
)


@tool
def get_weather(location: str) -> str:
 """Get the weather for a given location."""
 return f"The weather in {location} is cloudy with a high of 15°C."


agent = Agent(
  name="weather_agent_strands",
  model=model,
  tools=[get_weather],
  system_prompt="You are a helpful AI assistant.",
  callback_handler=None
)

result = agent("What's the weather in Paris?")

Observability.shutdown()

Avoiding duplicate spans

When using Observability.instrument() with AWS Strands and an OpenAI-compatible model, each model call may be captured twice — once by the Strands native tracing hooks (StrandsInstrumentor) and once by the lower-level OpenAI client patch (OpenAIInstrumentor). This doubles reported token usage and cost.

To fix it, block the redundant instrumentor:

python

from progress.observability.enums import ObservabilityInstruments

Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY"),
    block_instruments={ObservabilityInstruments.OPENAI},
)