Summary
Awesome! You may not have realized it yet, but in this chapter, you learned how to architect and implement a very complex machine learning system that could rival existing image-generation services you see out there. The concepts we showed here are essential and are at the heart of all the distributed systems you could imagine, whether they are designed to run machine learning models, extraction pipelines, or math computations. By using modern tools such as FastAPI and Dramatiq, you’ll be able to implement this kind of architecture in a short time with a minimum amount of code, leading to a very quick and robust result.
We’re near the end of our journey. Before letting you live your own adventures with FastAPI, we’ll study one last important aspect when building data science applications: logging and monitoring.
