Is Your ‘Distributed Monolith’ Undermining Microservice Benefits?

Why a Distributed Monolith Is Problematic

Many teams attempt to migrate from a monolith to microservices by simply splitting codebases and databases, but end up with a distributed monolith that retains monolithic drawbacks while adding network overhead.

Typical Transformation Steps

Identify business domains, split storage, define service boundaries.

Refactor code to replace internal service calls with remote calls (e.g., Dubbo, Feign).

These steps bring apparent benefits such as separate repositories, independent CI/CD pipelines, and isolated databases.

Hidden Drawbacks

Are the services truly independent, or do they require extensive coordination of synchronous interfaces?

Is each deployment truly autonomous, or must multiple services be released together?

Does a failure in one service still cascade and affect many functionalities?

Despite the perceived advantages, development efficiency may suffer: startup time increases from minutes to tens of minutes, and developers must run multiple services simultaneously.

The transformation often results in higher failure rates because internal calls become remote, introducing network I/O and increasing the probability of faults with each additional synchronous call.

Root Causes of a Failed Migration

Unreasonable domain splitting leading to excessive synchronous remote calls. Proper domain understanding and reducing synchronous interactions—favoring asynchronous messaging and selective data redundancy—are essential for low coupling.

Rudimentary implementation without distributed safeguards . Teams frequently omit rate limiting, degradation, and circuit‑breaker strategies, leaving services vulnerable to cascading failures.

Without careful domain modeling and protective mechanisms, the system’s stability degrades, and the promised microservice benefits become negligible.

Before embarking on a microservice overhaul, assess whether your organization faces these issues and consider more thoughtful decomposition and resilience patterns.