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Why I Switched: FastAPI vs. Spring Boot

From the JVM to Python: A personal journey in modern microservices development.

Dhruba Baishya
Dhruba Baishya
Software Engineer
Jan 24, 2026
6 min read

For years, I built microservices using Spring Boot. It’s a powerful framework, undeniably the industry standard for enterprise Java applications. But recently, I made the switch to FastAPI, and the difference in my daily development workflow has been transformative.

While Spring Boot is robust, FastAPI feels like a breath of fresh air. It’s not just about changing languages; it’s about a fundamental shift in how quickly and efficiently we can deliver value.

The Developer Experience Shift

# Effortless Bootstrapping

One of the first things I noticed was how incredibly easy it is to bootstrap a FastAPI project. With Spring Boot, even with the initializers, there’s a sense of "heavy lifting" right from the start. FastAPI is lightweight. You can get a robust, production-ready service up and running with minimal friction.

# Goodbye, Boilerplate

The reduction in boilerplate code is massive. In the Java world, we often find ourselves writing verbose configuration and glue code. FastAPI, leveraging modern Python features, allows me to express the same logic more concisely. Less code means less to maintain and fewer places for bugs to hide.

# Speed of Delivery

Because it’s Python, and because the framework gets out of the way, we end up creating valuable solutions at a much higher speed. The feedback loop is shorter. I can prototype, iterate, and deploy faster than I ever could with the JVM stack.

Tooling That Just Works

Dependency management in Python has evolved significantly. Using tools like uv provides a seamless experience that rivals, and in some ways exceeds, what I was used to with Maven or Gradle. It’s fast, reliable, and makes managing environments a breeze.

I’ve also found that building common libraries to share across microservices is much easier in this ecosystem. It simplifies our architecture and significantly reduces the effort needed to maintain shared logic, further speeding up development across the entire team.

The Microservices Context

"The reality is that most microservices we build today do not require heavy CPU workloads."

Personally, I have enjoyed building microservices using FastAPI. For the vast majority of I/O-bound network services—calling other APIs, querying databases—FastAPI is exceptionally performant.

If I had a specialized use case with heavy CPU computation, the JVM might still be the right tool. But for the typical microservice landscape, FastAPI hits the sweet spot of performance and developer joy.

Conclusion

Switching to FastAPI wasn't just about chasing a trend. It was a pragmatic choice for better productivity. The combination of Python's agility, FastAPI's modern design, and excellent tooling makes it a superior choice for building the next generation of our microservices.

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