Component-Based Monoliths: The Architecture Pattern More Teams Should Consider

Software architecture trends come and go.

Over the last decade, microservices have become the default answer to many architectural challenges. Teams often move from monolithic applications to dozens or hundreds of independently deployable services in pursuit of scalability, agility, and team autonomy.

Sometimes this is the right decision.

But sometimes the operational cost of microservices outweighs their benefits.

After working with large-scale financial systems, I've become increasingly interested in a different architectural approach: the Component-Based Monolith.

How Many Teams End Up With Microservices

Many systems start life as a modular monolith.

A single codebase contains multiple business components such as:

• Accounts

• Balances

• FX

• Payments

• Reporting

Each component owns a specific business capability while sharing a common deployment unit.

This approach aligns well with the Common Closure Principle (CCP):

Components that change together should be packaged together.

As systems grow, pressure often emerges to split these components into independent microservices.

The reasoning is usually sound:

• Independent release cycles

• Separate ownership

• Smaller deployment units

• Reduced coupling between business domains

These goals align with principles such as:

• REP (Reuse/Release Equivalence Principle)

• CRP (Common Reuse Principle)

On paper, everything looks better.

In practice, things can become more complicated.

The Hidden Cost of Microservices

Imagine a system split into 50 microservices.

Each service has:

• Its own repository

• Its own CI/CD pipeline

• Its own deployment process

• Its own monitoring configuration

• Its own release management

Now imagine all 50 services depend on:

• Spring Boot

• Logging frameworks

• Security libraries

• Database drivers

• Internal shared libraries

A security update arrives.

A framework upgrade is required.

A dependency reaches end-of-life.

Suddenly every service needs attention.

Instead of one upgrade effort, the organization now has 50 upgrade efforts.

The architecture has unintentionally created a large number of reasons to change.

This is where another important principle enters the discussion.

The Stable Dependencies Principle

The Stable Dependencies Principle (SDP) states:

Depend in the direction of stability.

The practical interpretation is simple:

The dependency structure of your system has a direct impact on your maintenance costs.

When many services share the same dependencies, every dependency upgrade creates work across the entire platform.

The more distributed the architecture becomes, the more expensive these renovations become.

This cost is often underestimated during initial architecture discussions.

Teams focus heavily on deployment independence.

They spend less time calculating long-term maintenance overhead.