In the era of hyper-scale architectures, the microservice pattern has become the default for many engineering teams. However, after a decade of building systems, I’ve realized that the rush to microservices often introduces more problems than it solves.

The Cost of Distribution

When you split a monolith, you trade in-process function calls for network boundaries. This introduces:

  1. Network Latency: What used to take nanoseconds now takes milliseconds.
  2. Failure Modes: You now have to handle partial failures, network partitions, and cascading timeouts.
  3. Observability Overhead: Tracing a request across 10 services requires significant investment in distributed tracing tooling.

When to Actually Split

A system should be broken apart not for technical vanity, but for organizational scaling or distinct resource requirements:

  • Organizational: When multiple teams are stepping on each other’s toes deploying the monolith.
  • Resource Asymmetry: When one small part of the application requires massive CPU/Memory scaling independently of the rest.

If you don’t have these problems, focus on modularizing your monolith instead. Clean boundaries inside a single binary are vastly underrated.