Monolithic Architecture: From Classic to Modular Patterns

Monolithic architecture defines a software development model in which the entire system is built and deployed as a single, coherent, and self-contained execution unit. Business logic, access interfaces, and data persistence mechanisms all run within a single computational process or unified runtime environment.

Choosing a monolithic architecture represents a deliberate architectural decision aimed at minimising operational complexity and optimising intra-system communication — a conscious trade-off between code management, network latency, and infrastructure overhead.

The monolith retains high relevance in modern software engineering due to its performance advantages. Function calls within the same memory space execute in nanoseconds, completely eliminating serialisation costs and network latency that are characteristic of distributed architecture. Furthermore, using a single database resource enables ACID-consistent transactions without complex coordination patterns such as sagas or two-phase commit.

A critical element of architectural analysis is clearly distinguishing a monolith from the anti-pattern known as the "Big Ball of Mud". The concept of a monolith describes a physical boundary of deployment and execution. "Big Ball of Mud" refers to the absence of logical structure, chaotic coupling of components, and lack of encapsulation within the code. A correctly designed monolith can maintain a clear separation of concerns and a high level of maintainability while remaining a single deployable artifact.

Classic Monolith

The classic monolith is characterised by tightly coupled components within a single codebase and shared computational resources and database. The application forms a unified structure in which a change to any part of the code requires recompiling, retesting, and redeploying the entire system.

The structure of a classic monolithic application is traditionally based on horizontal (layered) decomposition. The presentation layer handles the user interface, exposes API endpoints, and performs initial request validation. The business logic layer contains domain rules, processing logic, and data flow coordination. The data access (or persistence) layer manages object-relational mapping, database queries, and interaction with persistent storage.

Code organisation groups files by their technical role rather than domain belonging. Dedicated directories for controllers, services, and repositories create a structure in which logic from different business areas is mixed within the same namespaces.

• Advantages: low initial entry threshold, no network latency in internal communication, simple local development environment, easy end-to-end testing.
• Disadvantages: limited ability to scale specific parts of the application, longer build and deployment times as code grows, high blast radius (single point of failure where a fault in one module can take down the entire process).
• Common failure mode: architectural erosion where presentation-layer calls bypass business logic and directly access the database.

Monolith First

The "Monolith First" strategy involves starting the construction of every new system with a monolithic architecture before any decisions are made to split it into distributed services.

Starting with a monolith is justified by project realities in which domain boundaries at an early stage of product development are unclear and subject to frequent change. Premature decomposition into microservices risks creating a so-called distributed monolith that combines network latency with tight logical coupling. A monolith enables cheap and fast refactoring of module boundaries within a single codebase by modifying package structures, without changing network interfaces and communication protocols.

This approach works well for MVPs, startups, and projects with limited operational and personnel budgets. Its main advantage is the rapid delivery of business value, team focus on domain logic rather than infrastructure, and flexibility in shaping the data model. The primary risk is a lack of architectural discipline, which can lead to a monolith that fails to meet modularity standards and makes later decomposition impossible.

Micro Monolith

Micro Monolith is an architectural pattern that represents a compromise between decomposition into small services and the deployment simplicity of a monolith. Its core premise is to keep hardware, software, and data close together in one place while maintaining strict physical or file-level isolation of individual components.

In this approach the application in the development environment is organised as a collection of small, specialised projects or files corresponding to separate business responsibilities — such as search, product catalogue, or payment handling. Each component has defined API endpoints or communication interfaces. During the build process these components are merged and deployed as a single executable project.

Responsibility boundaries are defined at the source file or mini-project level, with each managing its own slice of logic. System scaling is achieved by installing the full artifact on new server instances, while the application router or API gateway directs traffic on a given instance only to the selected active endpoints.

The advantages of Micro Monolith are high code readability, ease of localising bugs, and the elimination of network complexity and container orchestration. The downside is that the entire system must be redeployed when a single file changes, and potentially uneven server resource utilisation. The difference from a classic monolith lies in the construction: the classic monolith mixes logic within shared application layers, whereas Micro Monolith emphasises module autonomy at the code and API interface level, treating the monolith purely as a packaging and runtime mechanism.

Modular Monolith (Modulith)

Modular Monolith (Modulith) is an architectural style in which the application is built and deployed as a single process unit, but its internal architecture has been divided into independent, well-encapsulated business modules.

Each module in a modular monolith is responsible for a specific domain area and has full ownership of its own logic and data. Boundaries between modules are enforced at the code level. Communication between modules may only occur through the module's explicitly defined public API or through an internal, in-memory event bus mechanism. Direct references to internal classes of one module from outside it are prohibited.

Data isolation in a modular monolith requires each module to have exclusive ownership of its own portion of the data model. In practice this means using separate database schemas or strict table separation. SQL queries joining tables belonging to different modules are not allowed; access to another module's data must go through its public API.

The advantages of a modular monolith are high cohesion, low coupling, zero network latency, the ability for multiple teams to work in parallel, and ease of eventual service extraction. The downside is the need to maintain strict architectural discipline and the constraints of a single runtime environment. Modularity concerns the logical organisation of code, while deployment remains simple — the application is packaged into one executable and runs as a single process.

Comparing the Approaches

The data shows important second-order dependencies. The classic monolith offers the lowest start-up cost, but as the codebase grows, the cost of introducing changes rises exponentially because of uncontrolled dependencies. Monolith First optimises time-to-market, provided the system gradually transitions toward a modular structure. Micro Monolith shifts the organisational burden from layers to isolated source files, removing network overhead while preserving clarity. Modular Monolith requires the highest design investment up front, but delivers the lowest long-term maintenance cost and the simplest path for system evolution.

Common Problems in Monolithic Architecture

Monolithic systems are subject to natural processes of structural degradation if their development is not controlled by architectural rules.

Another issue is missing module boundaries and the anti-pattern of sharing everything. Using the same domain objects, utility classes, or data models across all layers leads to a situation where changing the structure of one table forces modifications throughout the entire application. This is accompanied by the loss of clear code ownership — in a large, shapeless codebase no team feels responsible for the quality of individual components.

These systems also suffer from accumulating technical debt, manifested through lengthening compilation times, slow automated test execution, and difficulty updating external libraries. At the execution level there is also the problem of excessive component dependency: an unhandled error or memory leak in a subordinate module can bring down the entire production process.

How to Design a Good Monolith

Designing a durable and evolution-ready monolith requires implementing strict engineering principles at the level of code organisation and data modelling.

The architecture must be grounded in the principle of Separation of Concerns and strive for High Cohesion with Low Coupling. Code should be organised vertically around business domains, not horizontally around technical layers.

Encapsulation and clear module boundaries form the structural foundation. Each module should expose only its public API to the outside world, hiding implementation details, service classes, and persistence models. The Dependency Inversion Principle should be applied to manage interactions — basing communication on interfaces and abstractions.

Maintaining the adopted principles requires automated testing of architectural boundaries. Implementing dependency tests at the compilation level automatically blocks attempts to make illegal imports of internal classes and protects the application from degradation.

When to Choose Each Approach

The decision to choose a specific variant of monolithic architecture must be based on a multi-criteria analysis of business, organisational, and technical requirements.

• Classic Monolith: simple applications with predictable logic (mainly CRUD-class systems), built by small teams, where infrastructure costs must be minimised and anticipated traffic scale is low.
• Monolith First: new products, startups, and innovative projects where domain boundaries are not fully formed. Enables rapid validation of market hypotheses without incurring distributed infrastructure costs.
• Micro Monolith: medium-scale projects where the team wants single-artifact deployment simplicity but requires clear code separation at the level of independent files or components. Suitable for teams with limited operational and DevOps competencies.
• Modular Monolith: complex enterprise-class systems with rich domain logic, built by multiple development teams. Optimal when the application requires high in-memory processing performance, full transactional consistency, and preparation for eventual decomposition into microservices.

The main decision criteria for an IT architect are: complexity of the business domain and maturity of its boundaries; structure, size, and maturity of engineering teams; maturity of operational processes and availability of DevOps resources; requirements for communication latency and transactional consistency.

Summary

Monolithic architecture is a fully legitimate and efficient design pattern in modern software engineering. Contemporary development methodology is moving away from viewing the monolith as an outdated solution, positioning it instead as a deliberate infrastructure choice.

The key to successful monolithic systems is their internal modularity. The quality and durability of software is not determined by the number of deployed containers or processes, but by discipline in enforcing logical boundaries, encapsulation, and data ownership. A modular monolith makes it possible to obtain the organisational benefits attributed to distributed systems while eliminating their network and operational overhead.

The fundamental engineering principle remains the pursuit of simplicity. Architectural simplicity should always be a direct design goal — achieved by eliminating unnecessary layers and communication nodes — not an accidental by-product of the software creation process.