1. Introduction
In the ever-evolving realm of technology, software architecture plays a pivotal role in shaping the digital landscape. From the advent of monolithic structures to the rise of microservices and beyond, each architectural shift has brought about transformative waves of innovation. Today, we stand on the precipice of yet another epoch in software development, where modern software architectures – when used correctly – provide unprecedented levels of scalability, flexibility, and efficiency for digital applications.
In this article, we explore some of the latest advancements in modern software architecture that impact the way digital applications are designed, built, and deployed. As computing power increases, the demand for faster, highly adaptable software also intensifies. This is why we recommend that developers, architects, and tech enthusiasts understand these architectural paradigms.
2. Implementation Patterns
One of the concepts that is heavily used for large systems that need to scale fast is Event Sourcing. Event Sourcing is a pattern with an intrinsic characteristic: the traceability of the operations and data changes. The central pillar of this pattern is the Event Store. Each action executed inside a system using event sourcing generates at least one event that is stored and broadcasted into the system, potentially triggering other actions and data changes.
When using event sourcing the current state of the application can be determined by replaying the events in the store, so the event store represents the “source of truth” for the data in the system.
However, the event store is accompanied by datasets or projections representing the state of the application for different use cases in the system. Although this pattern is appropriate for some systems, specific criteria must be met before using it. The most important ones are:
– Consistency and real-time updates to the views are not mandatory
– Eventual consistency must be acceptable for the target system
Event Sourcing usually goes hand in hand with another pattern: CQRS – Command and Query Request Segregation. CQRS allows the separation of concerns relative to the data manipulation operations. The Commands are responsible for triggering the data change in the system and the Queries are responsible for retrieving the data from the system through the materialized views or projections, which allows for faster response time of the aggregated data.
The benefits of CQRS come mostly from the fast response time for queries given the fact that the data is already aggregated to a certain degree and the load on the data source is minimized.
3. Application-level architecture
These patterns are important for keeping the data flow consistency and structure for the software system. In practice these patterns are not used as standalone components, but they are integrated in a specific architecture.
At application level, models like Hexagonal Architecture, Onion Architecture, or Clean Architecture are usually being considered.
Although they have different names, they are similar in purpose, reducing the coupling between the components of an application and obtaining an application that is easy to change and maintain. These architectures mainly rely on the Dependency Inversion Principle and Domain Driven Design principles. The business logic, the application model and the abstractions for the external dependencies are defined as the “Core” of the application. So, the “Core” will use the abstractions for implementing the logic without having to care about the actual implementation of the details.
Chronologically, the Hexagonal Architecture was the first model proposed in 2005 by Alistair Cockburn, then Jeffrey Palermo came up with the Onion Architecture in 2008, and then, in 2012, Robert C. Martin, brought the Clean Architecture which unifies the previous proposals, as well as other concepts, like Use Case Driven approach for software development.
So, in a way, Clean Architecture is positioned as an evolution of the Hexagonal Architecture and the Onion Architecture. This does not mean that Clean Architecture is the “silver bullet” and the others should be disregarded.
Usually, the decision on which type of architecture is best to use at application-level is influenced by the system-level architecture and the experience of the people involved in the development of the application.
4. System Level Architecture
At system-level, there are systems where the entire functionality is implemented through a single executable unit; this would be a Monolith Architecture.
In other cases, the functionality is distributed across multiple executable units, and other approaches are being considered:
– Service Oriented Architecture (SOA), with Microservices being a particular application of SOA
– Micro-Apps / Micro-System Architecture
Each of these approaches has advantages and disadvantages, some of which are covered in the following paragraphs.
4.1 Monolith Architecture
Main advantages of Monolithic Architectures:
Simplicity: they are simpler to develop and maintain compared to distributed systems; the entire system is contained within a single codebase. This is why it is easier to understand, debug, and test. Considering there is only one unit to deploy, the deployment process is simplified as well.
Performance: when evaluating at a small scale, monolithic architectures offer a better performance compared to distributed architectures because there is no overhead of inter-service communication or network latency. Function calls within the monolith are faster since they occur within the same process.
Development Productivity: developers have a single codebase to work with, which simplifies development and reduces the complexity of coordinating multiple services. It allows for faster development iterations, as changes can be made within the monolith without affecting other services.
Easier Data Management: data management is often simpler since there is typically one central database or data store. Maintaining data consistency and enforcing data integrity is straightforward, as there are no distributed data sources to synchronize.
Cost-Effectiveness: Monolithic architectures can be more cost-effective for smaller applications or startups with limited resources. The development, deployment, and maintenance costs are generally lower compared to managing a distributed system with multiple services.
Scaling: The scaling for monolith architecture is simple to achieve when talking about vertical scaling, which can be acceptable when the system is being used inside a company. However, when talking about millions of users, the scaling becomes complicated for monolith systems.
It’s important to note that the advantages of monolithic architecture come with trade-offs. As the system grows in complexity, or requires high scalability, modularity, or fault isolation, other architectural styles might be a better fit for its implementation. The choice of architecture depends on the specific requirements and characteristics of the system being developed.
The main disadvantages of the Monolith Architecture are:
Lack of Modularity: Monolithic architectures tend to lack modularity and can become increasingly difficult to maintain and extend over time. Changes in one part of the system may have unintended consequences on other parts, making it harder to isolate and manage dependencies. This disadvantage is resolved to some extent by using a Modular Monolith approach.
Limited Scalability: Scaling a monolithic application is simple up to a point where the vertical scaling is just not enough to keep up with the usage of the system. Horizontal scaling of a monolith system can be complex and expensive because the entire system needs to be scaled, instead of scaling only the parts of the system that are under stress.
Technology lock-in: All the components in the system will use the same technology and development framework. The system evolves in time, but it is complicated to make sure that the new developed components are up to date with the latest technology changes and advances, because the changes in a component dependency affect the entire system.
Lack of Agility: The interdependencies within the monolith can make it harder to adopt agile development practices, such as independent deployment of features or rapid iteration.
Single Point of Failure: Monolithic architectures have a single codebase, which means that a failure in one part of the system can potentially bring down the entire application. This lack of fault isolation can impact overall system reliability and availability.
4.2 Service Oriented Architecture
The Service Oriented Architecture on the other hand brings certain advantages:
Loose Coupling: Functionalities are encapsulated within individual services. These services can be developed, deployed, and maintained independently, leading to loose coupling between components. This modularity allows for easier scalability, maintainability, and extensibility of the system.
Service Reusability: when designed correctly the services will be reusable across multiple applications or systems. By exposing well-defined interfaces, services can be leveraged by different client applications, reducing redundancy, and promoting code sharing. This reusability helps in achieving better development efficiency and consistency across the organization.
Interoperability and Integration: The use of standardized protocols and data formats for communication between services makes the services accessible to other systems that might need to integrate. Interoperability is promoted, allowing services to be developed using different technologies and platforms while still being able to communicate and interact seamlessly.
Flexibility: Considering that the functionality is implemented in multiple services, new services can be added, or existing services modified without impacting the entire system, allowing for incremental updates and continuous improvement. A new code base can be easily kept up to date with technological advances without having a negative impact on the development of the system overall.
Scalability: Having a system composed of multiple services, it is possible for each service to be scaled independently based on demand. Services can be distributed across different nodes, enabling horizontal scaling to handle increased workloads, leading to a better performance compared to a monolith under high loads.
Although it might seem that the Service Oriented Architecture resolves the problems of the Monoliths it must be considered that this architecture also has its disadvantages, which in some cases are not acceptable.
Some of the significant disadvantages of the Service Oriented Architecture include:
Increased Complexity: Compared to monolithic architectures, additional complexities are introduced. The management of services, orchestration, and service discovery mechanisms adds a layer of complexity that needs to be properly designed, implemented, and maintained. This complexity can impact development efforts and overall system understanding.
Performance Overhead: To achieve overall system functionality in a SOA, the services include a communication component and usually the actual communication done over the network. The use of standardized protocols and message formats, such as XML or JSON, can add processing and serialization/deserialization overhead. Additionally, network latency and the need for synchronous communication between services can impact overall system performance, however if the system is designed properly, this communication overhead will be compensated by the scalability of the individual services.
Integration Challenges: Integrating disparate services and ensuring smooth interoperability can be challenging. Services developed by different teams or organizations may have variations in standards, protocols, or data formats, leading to integration difficulties. Achieving seamless communication and data consistency across services may require additional effort and coordination.
Governance Complexity: Managing many services within SOA requires effective governance practices. Establishing and enforcing standards, policies, and guidelines for service development, deployment, and versioning can be complex and time-consuming. Without proper governance, there is a risk of service proliferation, inconsistency, and potential conflicts.
Distributed System Challenges: Ensuring reliability, fault tolerance, and consistency in distributed environments can be more challenging compared to monolithic architectures. Handling failures, managing distributed transactions, and dealing with eventual consistency require careful design and implementation.
Overemphasis on Reusability: While service reusability is an advantage of SOA, the pursuit of maximum reusability can lead to overly complex and generic services that may not align perfectly with the specific needs of each consuming application. Striking the right balance between reusability and application-specific requirements can be a challenge.
Considering Microservices as a particular implementation of SOA, some of the specific elements include:
Size and Granularity: the focus is on small, self-contained services that are responsible for specific business capabilities. Each microservice is typically developed, deployed, and scaled independently, which often have their own dedicated data storage.
Data duplication: Because each microservice has its own storage, some data must be duplicated and kept coordinated with other microservices.
Deployment: they are designed for independent deployment and scalability.
Organizing: microservices are typically owned by small, cross-functional teams, and each team is responsible for the development, deployment, and maintenance of their respective microservices. This organizational structure enables autonomy and faster development cycles.
4.3 Micro-App Architecture
Micro-App architecture is an approach that combines the benefits of microservices with the concept of user-centric applications.
User-Centric Focus: Micro-App architecture places a strong emphasis on designing applications around specific user needs or user journeys. By breaking down the application into smaller, focused micro-apps, each micro-app can be tailored to address a specific user requirement, providing a more personalized and intuitive user experience.
Modular and Scalable: Similar to microservices, micro-apps are designed to be modular and loosely coupled. Each micro-app focuses on a specific functionality or feature, allowing for easier development, deployment, and scalability. Micro-apps can be developed, updated, and scaled independently, enabling faster iterations, and reducing the impact of changes on the overall system.
Rapid Development and Deployment: With micro-app architecture, development teams can work on individual micro-apps independently, reducing the complexity and dependencies typically associated with monolithic applications. This enables faster development cycles, quicker time to market, and easier deployment of new features or updates to specific micro-apps without impacting the entire application.
Improved Reusability: Micro-app architecture encourages the development of reusable components or services that can be leveraged across multiple micro-apps. This promotes code reuse, reduces duplication of efforts, and improves overall development efficiency. Reusable components can be developed, tested, and maintained independently, enhancing productivity and consistency across the organization.
Flexibility and Adaptability: Micro-app architecture enables flexibility and adaptability by allowing the application to evolve incrementally. New micro-apps can be added, or existing micro-apps modified or replaced without disrupting the entire system.
Enhanced User Experience: By breaking down the application into smaller, specialized micro-apps, the user experience can be improved. Micro-apps can be designed to be lightweight, focused, and optimized for specific user interactions, resulting in faster loading times, reduced complexity, and a more intuitive user interface.
Of course, the Micro-App architecture has its own disadvantages which are partially inherited from the microservice similarities. Some of these disadvantages include:
Increased Complexity: They can introduce additional complexity compared to traditional monolithic or even microservices-based architectures. Coordinating and managing multiple micro-apps, their interactions, and the overall user experience can be challenging. The increased number of components and services may require more sophisticated governance and monitoring mechanisms.
Communication and Integration Overhead: Micro-App architecture relies on communication and integration between different micro-apps to provide a cohesive user experience. This introduces potential latency and overhead due to the need for inter-micro-app communication. Proper coordination, versioning, and compatibility management are necessary to ensure smooth integration between micro-apps.
Distributed State Management: As the application logic is distributed across multiple micro-apps, managing the shared state, and ensuring consistency can become more complex. Synchronizing data and maintaining data integrity across different micro-apps may require additional effort and careful design.
Operational Complexity: Deploying and managing a larger number of micro-apps can increase operational complexity. Each micro-app needs to be individually deployed, monitored, scaled, and maintained. This requires appropriate infrastructure, automation, and monitoring tools to ensure efficient management and troubleshooting.
Governance and Versioning: Managing the lifecycle, versioning, and compatibility of multiple micro-apps can be complex. Changes in one micro-app may require coordination and compatibility checks with other micro-apps that depend on it. Proper governance practices, versioning strategies, and backward compatibility measures need to be in place to ensure smooth evolution and avoid compatibility issues.
It is important to note that the disadvantages mentioned above are not inherent to Micro-App architecture itself but are considerations that need to be addressed during the design and implementation process. With careful planning, proper architectural choices, and effective governance, these challenges can be mitigated.
5. Conclusions
When considering modern architecture approaches in software development, there are multiple levels at which the architecture must be detailed. For system-level architectures, there are different options that can be used to build modern solutions.
The choice for an architecture or another must be made in a pragmatic manner based on facts, taking into consideration advantages and disadvantages applied to the particular situation for which the software system is being designed for. There is no such thing as “one size fits all” in software development.
Choosing an architecture based only on buzzwords and so-called state-of-the-art concepts, without taking into consideration the aspects discussed above, will lead to higher probability of having features that are not actually required, or even worse, take a toll on the overall system performance.
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