Building Collaborative Microservices in Python with FastAPI and Pydantic

This article discusses building collaborative microservices in Python using the FastAPI framework. The author creates two microservices, Agent-A and Agent-B, that interact with each other in real-time. Agent-B is a service that reverses text, and Agent-A forwards the input to Agent-B and returns the reversed string. The article demonstrates how to extend this example with additional features such as logging, tracing, synchronous and asynchronous calls, error handling, authentication, and more. The article concludes that this pattern underpins many real-world distributed architectures and makes it a great learning foundation for building maintainable and scalable systems.

In the rapidly evolving landscape of software development, microservices have emerged as a powerful architectural pattern. This approach involves building distributed systems composed of small, specialized components that communicate seamlessly. This article delves into a practical example of building collaborative microservices using Python and the FastAPI framework.

The example involves two microservices, Agent-A and Agent-B, which interact in real-time. Agent-B is a service that reverses text, while Agent-A forwards input to Agent-B and returns the reversed string. Both services are built using FastAPI and leverage Pydantic for data validation.

Agent-B, the reverse service, is a minimal service that exposes a single endpoint to reverse a string. The code for Agent-B is straightforward and utilizes FastAPI and Pydantic for creating a simple API. Agent-A, on the other hand, acts as a forwarding service. It forwards the input text to Agent-B, receives the reversed string, and returns it as its response.

To run both services, the user can start Agent-B using the command `uvicorn agent_b:app --port 8001` and Agent-A using `uvicorn agent_a:app --port 8000`. The system can be tested using `curl` to send a request to Agent-A, which in turn interacts with Agent-B to reverse the text.

This example can be extended with additional features such as logging, tracing, error handling, and authentication. These features are crucial for building robust and scalable systems in a production environment.

The article concludes that this pattern of building microservices underpins many real-world distributed architectures. It provides a solid foundation for creating maintainable and scalable systems. By leveraging FastAPI and Python, developers can quickly build and deploy microservices that communicate effectively.

References:
[1] https://community.sap.com/t5/technology-blog-posts-by-sap/building-collaborative-microservices-in-python-with-fastapi-echo-amp/ba-p/14170025