In this installment of the series, the author explores the development of Python-based microservices using Couchbase, focusing on performance and scalability. The text discusses the implementation of a User Profile service in Python, initially utilizing a "full code" approach with Python’s HTTPServer class, and later transitioning to FastAPI for improved performance through asynchronous programming. The article highlights considerations for processing request paths efficiently and securing the microservice with a Bearer Token. The service is containerized using Kubernetes for testing with different implementations, including a Node.js version for comparison. The Node.js implementation demonstrated superior performance in terms of latency, but the Python versions, particularly with FastAPI, showed effective scalability. The text concludes by acknowledging Python’s suitability for moderate load services, while suggesting Node.js for high-scale, low-latency applications, emphasizing Couchbase's compatibility with multiple languages and frameworks.