The Microservices Migration: When to Split the Monolith

In the engineering world, "monolith" has become a dirty word, while "microservices" are touted as the ultimate solution to all scaling problems. The reality, as always, is far more nuanced.

At Arosa, we frequently advise clients who are struggling with monolithic codebases. However, we often find that jumping straight into a microservices architecture is the wrong move.

In Defense of the Monolith

A monolithic architecture—where all business logic is contained in a single deployable unit—is highly cohesive. It is easy to debug, easy to test end-to-end, and straightforward to deploy. For startups finding product-market fit, a well-structured monolith is almost always the right choice.

The problem arises when the engineering team grows. When 50 developers are trying to commit code to the same repository simultaneously, deployment pipelines slow to a crawl, and a bug in the billing module accidentally takes down the user login system.

When to Make the Leap

You shouldn't split a monolith just because you have a lot of traffic (you can often just scale the monolith horizontally). You should split it when:

1. Organizational Scaling: You need independent teams to deploy code autonomously without coordinating with the entire company.
2. Disparate Resource Requirements: The video processing module requires heavy GPU usage, while the authentication module requires high memory. Splitting them allows you to provision hardware optimally.
3. Fault Isolation: A memory leak in a secondary feature shouldn't crash the core product.

The Strangler Fig Pattern

If you decide to migrate, never attempt a "big bang" rewrite.

Instead, use the Strangler Fig pattern. Identify a single, highly cohesive domain within the monolith. Extract it into an independent service. Route traffic to the new service via an API Gateway. Repeat this process until the monolith has been entirely "strangled" by the new microservices ecosystem.

Microservices aren't a silver bullet—they trade code complexity for operational complexity. Ensure your DevOps infrastructure is ready before taking the plunge.