How to Determine If Your System Really Needs to Be Split into Microservices

Microservices have become popular and are used by large companies, but they double deployment complexity, make bug tracing harder, and can slow business iteration. The article argues that adopting microservices should be a deliberate decision based on concrete system pain points.

Typical Pain Points That May Justify Splitting

Coupled code causing widespread impact : Adding a new payment channel forces a full system retest because it’s unclear whether changes affect user or order modules, leading to larger regression scopes and slower releases.

Scaling difficulties : During peak sales, the order service experiences high load while user and content services remain idle. A monolith forces the entire system to be scaled, wasting resources, whereas microservices enable selective scaling.

Multiple teams sharing a single codebase : When Team A modifies a shared class, Team B’s features break, causing frequent merge conflicts and coordination overhead, indicating a strong signal for separation.

Diverse technology stacks : New features may be better written in Python while the existing system is Java‑based, or some modules need a newer framework version that others cannot adopt, creating friction in a monolithic setup.

If none of these issues are present, microservices likely add complexity without solving problems.

When Microservices Truly Shine

Microservices excel when multiple teams need to develop and release independently. For example, Team A owns the user service and Team B owns the order service; they can iterate and deploy without interfering with each other.

A simple rule: if the system does not require parallel development by multiple teams, many microservice benefits disappear.

Assessing Your Need for Microservices

The article proposes five quick questions:

System size : Is the codebase large enough and are module couplings hurting development efficiency?

Team size : Are there multiple teams that need to work on the same system concurrently?

Business scale : Is the current architecture actually hindering business growth rather than just looking inelegant?

Stability : Are domain boundaries clear and stable?

Operational capability : Does the team have the expertise to maintain the required infrastructure (Kubernetes, service registry, tracing, CI/CD pipelines, etc.)?

If most answers are “yes,” splitting into microservices is reasonable; otherwise, focusing on a well‑engineered monolith is more pragmatic.

Operational Overhead Considerations

Microservices shift complexity from the application layer to the infrastructure and operations layer. Teams need expertise in container orchestration, service discovery, distributed tracing, and robust CI/CD pipelines. Without such capabilities, adopting microservices can become a disaster.

Evolution Path

Many companies start with a monolith, let the business model stabilize, and gain clear domain boundaries before extracting the most volatile and well‑defined parts into independent services. This gradual evolution aligns with real‑world practices.

In summary, the best architecture is the one the team can comfortably manage; microservices should be adopted only when their benefits outweigh the added operational burden.