The Modular Monolith Paradigm

When to Employ This Paradigm

• When you desire team autonomy similar to that of microservices, but without the operational overhead of a distributed system.
• When release velocity is slowed by tangled dependencies between internal modules.
• When a monolithic architecture is simpler to operate today, but there is a clear need to evolve toward a service-based model in the future.

Adoption Steps

1. Identify Modules: Define module boundaries that align with distinct business capabilities or Bounded Contexts from Domain-Driven Design.
2. Encapsulate Internals: Use language-level visibility modifiers (e.g., public/private), separate packages, or namespaces to hide the implementation details of each module.
3. Expose Public Contracts: Each module should expose its functionality through well-defined facades, APIs, or events. Forbid direct database table access or direct implementation calls between modules.
4. Enforce Architectural Fitness: Implement automated tests that fail the build if forbidden dependencies or package references are introduced between modules.
5. Plan for Evolution: Continuously track metrics such as change coupling and deployment scope to make informed decisions about if and when to split a module into a separate service.

Key Deliverables

• An Architecture Decision Record (ADR) that maps module boundaries and defines the rules for any shared code.
• Formal contract documentation (e.g., OpenAPI specs, event schemas) for every interaction point between modules.
• Automated dependency checks and dedicated CI/CD jobs for each module to enforce boundaries.

Risks & Mitigations

• Regression to a "Big Ball of Mud":
  • Mitigation: Without strict enforcement, module boundaries will inevitably erode. Treat any boundary violation as a build-breaking error and maintain a disciplined approach to code reviews.
• Shared Database Hotspots:
  • Mitigation: High contention on a shared database can become a bottleneck. Introduce clear schema ownership, use view-based access to restrict data visibility, or implement data replication strategies to reduce coupling.