A quick look at how I keep my project structured in a single repository—clean, accessible, and built to iterate fast.
We’ve all seen the architectural roadmaps trending on Twitter and LinkedIn. The moment someone talks about scaling a web application, the immediate advice thrown around is to split everything into independent microservices. Docker containers, Kubernetes clusters, separate APIs for every single feature—it looks beautiful on a system diagram.
But honestly? For a solo developer or an indie hacker just trying to launch an MVP, it feels like an absolute trap.
I’ve been mapping out the architecture for a platform I'm working on right now—a local service-matching web application designed to connect users with nearby artisans. The project needs all the standard foundations: user authentication, clean database routing, a manual payment flow, and a notification system to match workers with clients.
If I followed the trending tech advice, I’d be setting up multiple decoupled microservices right now. Instead, I’m keeping the entire stack highly centralized and building a single, solid monolith with a clean Express backend and MongoDB database.
Here is why I think the microservices obsession is killing solo productivity, and why keeping things monolithic is still king for shipping fast:
When you are the only person writing the code, your biggest enemy isn't system performance; it's context switching. Dealing with service-to-service communication, managing separate repositories, and orchestrating API gateways means you spend 70% of your time managing infrastructure and only 30% actually building features. With a monolithic structure, everything lives in one place. I can modify a database schema and update my routing files in seconds without deployment headaches.
Deploying a single, unified application to a cloud instance is straightforward. It's predictable, and the logging is entirely centralized. The moment you introduce microservices, you have to worry about distributed tracing. If a manual payment routing step fails, debugging across three different container logs to find out exactly where the connection dropped is a fast track to developer burnout.
Unless you are dealing with millions of concurrent requests from day one, your database and a well-optimized backend instance can handle the load just fine. Optimization should be a bridge you cross when you actually have the traffic to justify it, not a barrier you build for yourself before you even have your first active user.
I know a lot of devs swear by splitting things up early to prevent "spaghetti code" later on, but I feel like clean folder structure and strict coding discipline matter way more than physical separation of codebases.
Drop your thoughts below—I'd love to hear how you handle the architectural balance when shipping MVPs!
