Comparative Guide to Application Architectures with Spring Boot: Multi-Module, Hexagonal, and Microservices

Abstract

This article explores three common approaches to structuring applications with Spring Boot: multi-module projects, hexagonal architecture (ports and adapters), and microservices. It compares their main characteristics, advantages, and challenges across areas such as code organization, maintainability, testing, scalability, and deployment. The goal is to provide a clear and practical perspective to understand the key differences between these architectural styles, their motivations, and in which contexts they may be more suitable, without assuming that one is inherently better than the others. The intention is to support more informed design choices, considering both technical complexity and the context of the team and project. 

1. Introduction

In developing modern enterprise applications with Spring Boot, one of the key challenges is selecting an appropriate architecture that balances code organization, ease of maintenance, scalability, and technical complexity. As systems expand, it becomes increasingly important not just what features are implemented, but also how they are structured internally.

Common approaches to organizing applications in Spring Boot include multi-module projects, hexagonal architecture, and microservices. Each offers a different way of structuring code, defining responsibilities, and managing software evolution, and each is suited to different scenarios and needs.

This article aims to provide a comparative overview of these three approaches, highlighting their main features, advantages, and disadvantages. The goal is to offer a clear understanding of their differences and help determine which might be more appropriate depending on the project’s context.

2. Project Structure

2.1 Multi-Module (Modular Monolith)

A multi-module project is made up of a monolithic application divided into separate logical modules, usually under a common parent (such as the main POM in Maven or the root configuration in Gradle). Each module contains a related set of functionalities, like a web module, a services module, a persistence module, or modules organized by functional domains.

It is also common to include reusable or specialized modules, such as:

• Authentication and authorization modules (e.g., JWT, OAuth, role-based access).
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• Scheduled job modules (using Quartz, JobRunr, etc.).
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• Integration modules for external services (e.g., clients for AWS SES, Chime, S3, etc.).

Spring Boot supports this layout natively. The common modular-monolith approach involves one “application” module that depends on all others and produces a single fat-jar/war for deployment. However, you can designate several modules as Boot applications (each with its own main() and plugin). In that case, the build produces multiple executable artifacts, such as an API server, a background worker, and a CLI, all sharing the same core libraries but able to be deployed and scaled independently.

2.2 Hexagonal Architecture (Ports & Adapters)

Hexagonal architecture is a pattern for internal code organization (independent of whether the deployment is monolithic or distributed). It proposes separating the application's domain core from external concerns (databases, external services, user interface, etc.) through layers of ports and adapters. Structurally, it places the business logic (domain) at the center, surrounded by interfaces (ports) that define entry and exit points, and implementations of those interfaces on the outer layer (infrastructure adapters).

In a Spring Boot project, this is typically reflected in package separation or even independent modules. For example, a domain module (or package) containing pure entities and services, an application module for use cases, and infrastructure modules for persistence implementations, REST controllers, integrations, etc. The domain code should not depend on frameworks or external details, following the “dependency rule” (dependencies point inward toward the core). This leads to a project structured in concentric layers rather than strictly technical ones. The priority is to isolate the core logic and allow external concerns to plug in through interfaces.

Structurally, hexagonal architecture can coexist with a multi-module monolith (e.g., domain module, infrastructure module, etc.) or be applied within each microservice independently.

2.3 Microservices

A microservices-based system is structured as several independent Spring Boot applications, each running as a separate service. Instead of a single project, there are multiple projects (or at least multiple deployable modules). For example, one service for users, another for payments, another for inventory, and so on. Each microservice has its own codebase, business logic, and typically its own database or independent persistence layer.

They communicate with each other through network calls (REST, messaging, gRPC, etc.) and are deployed separately. Code organization, therefore, happens at two levels: internally, each microservice can follow a specific pattern (for example, hexagonal architecture or a traditional layered structure), and at the global level, the system is split by business context into multiple services. In Spring Boot, this usually means various Spring Boot applications running independently, often complemented by Spring Cloud for distributed configuration, service discovery, and more. This approach results in a modular structure at the deployment level: each module, or service, operates as an isolated application with its own lifecycle.

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3. Maintainability and Scalability

3.1 Multi-Module (Modular Monolith)

Dividing a complex application into smaller modules improves code organization and maintainability. Each module focuses on a single responsibility, making it easier to understand and modify parts of the system without affecting others. Structuring the project into separate modules, each with a specific functionality, allows for better management, reuse, and maintainability in complex applications.

Teams can work in parallel on different modules with fewer conflicts. However, in the end, it is still a monolith: all modules are deployed together. This means scalability at the level of individual components is limited. You cannot scale a specific module independently, only the entire application. Still, a well-modularized monolith can scale horizontally by replicating the whole application, for example, through multiple load-balanced instances.

In terms of maintainability, a modular monolith avoids the complexity of a distributed system, making it generally easier to debug and less prone to inconsistencies. If the boundaries between modules are well defined, the risk of a “big ball of mud” (tangled code) is reduced, and modules can be refactored or extracted more easily in the future.

3.2 Hexagonal Architecture (Ports & Adapters)

Hexagonal architecture is specifically designed to improve long-term maintainability. Enforcing a strict separation of concerns ensures that changes in one part of the application (for example, changing the database or modifying business logic) have minimal impact on other parts. For instance, it is possible to replace an adapter (such as switching from an SQL database to NoSQL, or from REST to messaging) without touching the business core, since the core depends only on interfaces. This promotes software evolution and reduces the risk of introducing bugs by isolating changes. It also facilitates unit and integration testing: the domain can be tested in isolation by substituting adapters with mocks, thanks to the decoupling from external dependencies.

In terms of scalability, hexagonal architecture does not inherently make an application distributed, but it does support evolutionary scalability. It becomes easier to add new features or even scale specific components externally because the design allows multiple implementations for a given port. For example, two different data sources can be handled simultaneously. Some authors argue that this internal modularity also helps scale functionality by allowing new capabilities to be added without breaking existing ones. It can also prepare the ground for a transition to microservices if some modules are eventually separated physically.

Hexagonal architecture encourages clean, localized changes, which improve maintainability and make it easier for teams to evolve the system over time. It also provides a solid foundation for scaling functionality in a structured way. Still, runtime scalability depends mainly on the system's deployment model, whether it's monolithic or distributed.

3.3 Microservices

The division into microservices provides clear benefits in terms of scalability and some degree of development autonomy, although it introduces challenges for overall maintainability. From a scalability perspective, microservices allow selective scaling of the most heavily loaded parts of the system. If a specific service reaches its capacity limit, additional instances of that microservice can be deployed quickly to distribute the load, without needing to scale the entire application.

This provides flexibility for growth. Each service can be sized, replicated, and deployed independently based on demand. Additionally, different teams can work on separate services and deploy them without waiting for a global release cycle, which speeds up the delivery of new features. Regarding maintainability, at first glance, each microservice is simpler, with a smaller and more focused codebase, which makes it easier to understand and test in isolation.

It is also easier to isolate and fix failures in individual services without impacting the rest of the system. If something goes wrong, it is possible to roll back the deployment of a single service. This suggests that maintaining each microservice individually can be straightforward. However, complexity does not disappear; it is simply shifted to the system as a whole.

With dozens of services, maintaining consistency, monitoring, compatible versions, and reliable communication between them becomes a significant challenge. Microservices architecture does not reduce complexity, but it makes it more visible and manageable by breaking it into smaller pieces. This means that maintainability at a macro level can suffer if API contracts, centralized configuration, and service coordination are not properly managed.

4. Advantages and Disadvantages

4.1 Multi-Module (Modular Monolith)

4.1.1 Advantages

• Modularity and organization: Enables large applications to be modularized into smaller, more manageable components, improving system understanding. Encourages code reuse and clear separation of concerns. Each module can be developed and tested in isolation to some extent, keeping the codebase more organized.
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• Local maintainability: Since everything resides in a single codebase, cross-cutting changes (such as global refactors) and comprehensive testing are easier to perform. There is no network latency between parts of the system, which simplifies debugging by keeping the entire trace in one place.
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• Efficient internal performance: Calls between modules are simply in-memory method calls (or invocations within the same process), which leads to better performance compared to invoking remote services. A well-optimized monolith can make better use of modern hardware resources by avoiding the overhead of serialization and network communication.

4.1.2 Disadvantages

• Growing size and complexity: Over time, even with modularization, a monolith can become very large. If modular boundaries are not enforced with discipline, responsibilities may become entangled, leading to tight coupling. A small change requires redeploying the entire application, and in large teams, the monolith can become a bottleneck for frequent delivery.
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• Limited component-level scalability: It is not possible to scale individual modules independently. To handle increased load in a specific functionality, the entire monolith must be scaled, consuming more resources than necessary for underused parts.
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• Coupled reliability: Since all modules run within the same process, a critical failure (for example, an unhandled exception crashing the JVM) will affect the whole application. Similarly, long-running or resource-intensive operations in one module (such as a batch job triggering garbage collection) can degrade overall performance.

4.2 Hexagonal Architecture (Ports & Adapters)

4.2.1 Advantages

• High maintainability and flexibility: Separating business logic from other concerns makes the code easier to maintain and understand. Infrastructure or integration changes (for example, switching databases, web frameworks, or messaging providers) do not affect the business core as long as the ports (interfaces) are preserved. This reduces the risk of side effects from changes in other layers.
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• Technological independence: The core of the application is independent of external technical details. For example, domain logic can run without a web server or a real database, using mocked adapters. This independence facilitates technology migrations and testing. The application can support multiple technologies at its edges without requiring changes to the core (for instance, numerous types of clients or various databases).
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• Improved testing and quality: Due to the high level of decoupling, writing unit and integration tests is easier. The central business logic can be tested in isolation by injecting fake adapters, which leads to more robust test suites.
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• Reusability and extensibility: Hexagonal architecture, by defining clear contracts (ports), promotes reusing business logic across different contexts. For example, the same core can be invoked by a REST API, a batch processor, or a command-line interface without duplicating logic. You just need to implement new adapters that connect to the appropriate port.
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• Foundation for scaling or refactoring: If migrating to microservices or another architecture in the future, having implemented the hexagonal design helps identify autonomous business components. In fact, it is compatible with DDD (Domain-Driven Design) and can be combined with a modular monolith, serving as a foundation for eventually splitting modules into services. Many companies (Netflix, for instance) have used hexagonal design as a basis before moving toward service-based architectures, keeping the business logic isolated in each part.

4.2.2 Disadvantages

• Additional complexity: Implementing a hexagonal architecture introduces an extra layer of abstraction. It requires more layers and interfaces than a traditional layered design, which results in writing more boilerplate code. This increases the initial complexity of the project. For straightforward projects or prototypes, defining ports and adapters might be excessive when a standard architecture would suffice.
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• Learning curve and design effort: Adopting hexagonal architecture properly requires the team to understand the pattern well and have some experience in software design. The initial design phase is more involved and takes more time to identify the right ports, domain boundaries, and how to split responsibilities.
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• No strict guide for physical organization: Hexagonal architecture defines principles (inward dependencies, separation of adapters) but does not prescribe a fixed folder or module structure. This provides flexibility but can lead to inconsistencies. Two teams might structure hexagonal projects differently, for example, organizing adapters by technology vs. by use case. Without clear conventions, code can become scattered, or adapters might improperly depend on one another, breaking isolation. In other words, maintaining architectural purity requires ongoing discipline; otherwise, over time, the separation may erode, and unwanted dependencies can emerge.
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• Invisible benefit for the client: Many advantages of hexagonal architecture are internal (maintainability, flexibility), but from the end-user perspective, the application behaves the same. This makes it harder to justify to non-technical stakeholders in early stages, especially since initial feature delivery may be slower due to the added design and code structure overhead.

4.3 Microservices

4.3.1 Advantages

• Independent deployment and fault isolation: Each microservice is an autonomous unit that can be deployed or updated without impacting the others. This brings great agility: new versions or patches for a service can go to production immediately, without having to coordinate a significant release. Additionally, a problem in one service (for example, crashing due to an unhandled exception) does not bring down the entire system. Only the affected functionality is impacted. A small services architecture increases overall system reliability, as failures are not catastrophic. Other services continue to function and, if well designed, can mitigate the temporary absence of the failed one.
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• Granular and efficient scalability: This is the main reason to adopt microservices. Each service can be scaled individually according to its specific demands, instead of scaling the entire system. This enables better use of resources, allowing high-load services to scale independently while low-traffic services remain lightweight.
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• Development agility (small teams): Microservices promote the formation of autonomous teams aligned with specific business contexts. Each team works with minimal coordination with others and can deliver end-to-end features (from database to API) within its own service. This supports shorter release cycles. Atlassian, for instance, reported that with microservices, they moved from weekly deployments to several per day.
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• Technological flexibility: Since services are isolated, each one can be implemented using different technologies if needed (for example, one in Java with Spring Boot, another in Node.js), although this is not mandatory. Even when staying within Spring Boot, there is freedom to configure different data stores (one can use MySQL, another MongoDB, another a message queue), depending on what suits each use case best. This controlled heterogeneity allows choosing the optimal tool for each microservice without forcing that choice on the entire system.
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• Long-term maintainability of subsystems: Each microservice is relatively simple. With smaller codebases, it becomes easier over time to refactor or rewrite a complete service without affecting the rest. If a service becomes obsolete or too complex, it can be replaced independently. This isolation also helps with testing. It is feasible to run exhaustive tests for a service in a controlled environment. Similarly, observability can be more focused (logs, metrics, and traces by service), making it easier to pinpoint bottlenecks in specific parts of the system.

4.3.2 Disadvantages

• System-wide complexity: A microservices-based architecture introduces significantly more complexity than a monolith. Teams must manage inter-service communication (latency, network failures, data serialization, API compatibility), deployment orchestration, distributed configuration, and service discovery. Atlassian warns that moving from a few monoliths to many microservices leads to “unwanted complexity” and makes it harder to maintain delivery speed and confidence. Without strict governance, development can easily become chaotic, with many teams deploying services independently and making it difficult to understand how all the pieces fit together.
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• Infrastructure and operational costs: Running microservices adds overhead in multiple areas. Each new service consumes resources (memory, CPU for separate Spring Boot JVMs or containers), and requires its own CI/CD pipeline, monitoring, and logging. This increases the cost of testing, deploying, hosting, and observing each service. For small projects, these costs are often unjustifiable. In many cases, a well-structured monolith uses fewer total resources than an equivalent number of microservices performing the same tasks.
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• Increased organizational overhead: Although microservices allow independent teams, the organization as a whole must coordinate service versions and dependencies. The DevOps effort becomes significantly higher to automate deployments, scaling, and monitoring of so many components. Inter-team communication must also increase to agree on service contracts and avoid misunderstandings. Atlassian points out that another layer of coordination and collaboration is introduced when multiple teams must align their updates and interfaces.
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• Performance and latency: While microservices offer scalability, each remote call between services is much slower than an in-memory method call in a monolith. JSON (or other formats) serialization, HTTP/TCP transport, and related processing add latency per request. In applications requiring low latency or a high number of synchronous interactions between components, microservices can become a bottleneck. In fact, latency between services is a serious challenge in systems demanding real-time responses (e.g., high-frequency financial trading).
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• Data consistency and transactions: In a monolith, a database transaction can span multiple operations across modules atomically. With microservices, where each service typically owns its own database, distributed transactions are complex to implement. Eventual consistency via asynchronous messaging is often used instead. This forces a rethinking of business workflows to tolerate delayed consistency, which is not always trivial. Additional compensating logic is required to handle failures midway through a process.

Conclusion

Each approach fits a particular context. A multi-module monolith provides development simplicity with some degree of modular structure, making it suitable for starting projects in Spring Boot and for many medium-sized enterprise applications that do not require fine-grained scalability. Hexagonal architecture introduces solid internal design principles that enhance maintainability and facilitate long-term evolution, regardless of whether the deployment is monolithic or service-based.

Microservices, in turn, offer a scalable and flexible solution for large-scale systems or environments that demand continuous delivery and autonomous teams, but they come with significantly higher complexity and infrastructure requirements. There is no universal solution: in real-world Spring Boot projects, it is advisable to assess both present and future needs (team size, expected traffic, delivery pace, fault tolerance, etc.) and consider combining architectural strategies.

A common approach is to start with a modular monolith that follows a hexagonal architecture to ensure sound design, and extract microservices only when the system has grown enough and service boundaries are well-defined. This strategy allows early development speed without compromising scalability in the long term.