Why Your “Distributed Monolith” Is Still a Single Point of Failure

In a recent group chat about microservices, the term “distributed monolith” was coined to describe a situation where a company attempts a microservice transformation but ends up with a system that looks like microservices on the surface while still behaving like a monolith, often performing worse.

Why a Distributed Monolith Is Bad

Typical migration steps include defining business domains, splitting storage, and converting internal service calls to remote calls (e.g., Dubbo or Feign). This yields benefits such as separate codebases, independent CI/CD pipelines, and isolated databases.

However, the transformation often fails to achieve true microservice goals. Questions arise:

Are the codebases truly independent, or do many synchronous interfaces still require coordination?

Is each service’s release truly autonomous, or must multiple services be released together?

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

Even though the application appears split, developers may face longer startup times (e.g., from 3 minutes to 30 minutes) and need to run multiple services simultaneously, reducing development efficiency.

Moreover, the perceived benefits can be offset by increased instability: remote calls introduce network I/O, raising the failure rate of each interaction and thus the overall system failure probability.

The Root Causes of a Misguided Migration

Two main factors contribute to the problem:

Unreasonable domain splitting that creates excessive synchronous remote calls. Proper domain modeling and reducing synchronous calls—favoring asynchronous messaging and selective data redundancy—are essential for lower coupling and better stability.

Rudimentary implementation lacking distributed protection mechanisms such as provider-side rate limiting, consumer-side degradation, and circuit breaking. Without these safeguards, the added complexity of remote dependencies degrades system reliability.

Addressing these issues requires thoughtful domain decomposition and robust protective patterns to prevent the distributed monolith from becoming a more fragile system than the original monolith.