Introduction
As software projects grow in complexity, recurring design challenges emerge. Architectural patterns offer general, reusable solutions to these common problems, enabling developers to tackle them effectively. By adhering to established patterns, teams can streamline development, enhance maintainability, and deliver higher-quality software solutions.
What is the architectural pattern?
The architectural pattern defines the high-level structure and organization of a software system. It outlines the fundamental components, their interactions, and the overall layout of the system. Let's break it down for better understanding.
Think of software architecture as the blueprint for a house. Just as a blueprint shows how different parts of a house fit together, software architecture also shows how different computer program modules interact. They're like ready-made templates that help programmers solve common problems efficiently.
Why do we need architectural patterns?
Some design problems occur regularly during the development of software and can make our software complex and bad if not considered at an early stage of development. Hence, a design pattern is a general repeatable solution to a commonly occurring problem in software design.
For programmers, these patterns are super handy. They make it easier to understand and work on a project because everyone follows the same plan. Adding new features becomes smoother, and fixing problems is quicker because you're using a proven method. From the client's side, it's a win too. These patterns mean projects are finished faster and cost less because developers aren't reinventing the wheel each time. Plus, since everything is well-organized from the start, there are fewer surprises along the way, which makes planning and budgeting easier.
Different types of architectural pattern
Each pattern has its characteristics and is suitable for different types of applications. Here are some of the most commonly used architecture patterns:
Model-View-Controller (MVC)
MVC divides the whole application into Model, View, and Controller.
- Model: It represents the data and business logic of the application. However, it lacks the logic that governs how data is presented to the user.
- View: It represents the user interface, i.e. displays the application data and interacts with the user.
- Controller: It handles the input from the user and acts as an intermediary between the model and the view, updating the model and updating the view.
Model-View-ViewModel (MVVM)
It is mainly used in XAML-based applications such as WPF and Xamarin.
- Model: It represents the data and business logic of the application.
- View: It represents the user interface.
- ViewModel: It acts as an intermediary between the view and the model, providing data-binding capabilities to synchronize the view with the underlying data model.
Layered Architecture
It promotes separation of concerns and modularity, making it easier to maintain and test applications.
- Presentation Layer: It handles user interaction and displays information to the user.
- Business Layer: It contains business logic and rules.
- Data Access Layer: It handles data persistence and retrieval operations.
Event-Driven Architecture (EDA)
It is commonly used in systems where responsiveness and scalability are critical, such as IoT applications and real-time analytics. In EDA, components communicate through events asynchronously, and events represent significant occurrences or state changes within the system. it enables loose coupling and scalability by allowing components to react to events without direct dependencies on each other.
Microservices Architecture
This architecture decomposes an application into a set of small, independent services that can be developed, deployed, and scaled independently. Each service in this architecture typically focuses on a specific business capability and communicates with other services via lightweight protocols like HTTP or messaging queues. It promotes scalability and agility but adds complexity in terms of managing distributed systems.
Service-Oriented Architecture (SOA)
This architecture organizes software components into services that are loosely coupled and interoperable. These services encapsulate business functionality and expose them via standardized interfaces like web services. It supports reusability, scalability, and flexibility by promoting modularization and interoperability.
Command Query Responsibility Segregation (CQRS)
This architecture separates the responsibility of handling commands (write operations that change the state of the system) from queries (read operations that retrieve data). This separation allows each side of the system to be optimized independently. By decoupling the read and write sides, developers can make changes to one side of the system without impacting the other. Implementing CQRS often requires additional infrastructure and technologies, such as separate databases or message queues for command processing.
- Repository Pattern: This architecture abstracts the data access logic away from the rest of the application, providing a clean separation between business logic and data access code. It centralizes data access logic in a single location, making it easier to manage and maintain. This pattern is commonly used in conjunction with other architectural patterns like MVC and MVVM.
- Clean Architecture: Clean Architecture emphasizes the separation of concerns and independence of frameworks and libraries. It consists of concentric layers, with the inner layers containing business logic and domain models and the outer layers containing frameworks and infrastructure details. It promotes testability, maintainability, and flexibility by enforcing boundaries between different parts of the system.
- Serverless Architecture: Serverless Architecture allows developers to build and run applications without managing servers or infrastructure. Applications are composed of small, stateless functions triggered by events and executed in response. Serverless architectures are highly scalable, cost-effective, and require minimal operational overhead.
- Pipeline Architecture: This architecture breaks down processing tasks into a series of stages, with each stage performing a specific operation on the data. Data flows through the pipeline from one stage to the next, with each stage adding value or transforming the data in some way. Pipeline architectures are commonly used in data processing systems, ETL (Extract, Transform, Load) processes, and message processing systems.
- Space-based Architecture: Space-based Architecture (also known as Tuple Space or Data Grid) is a distributed computing model where components communicate through a shared, distributed memory space. Components publish and subscribe to data stored in the shared space, allowing for loosely coupled and scalable systems. Space-based architectures are well-suited for applications requiring high scalability, fault tolerance, and real-time data processing.
Conclusion
Architectural patterns offer a systematic approach to solving recurring design challenges, empowering developers to create maintainable, efficient, and adaptable software systems. By using architectural patterns, development teams can standardize their practices, expedite project delivery, and mitigate risks associated with complex software projects.
Although all the architectural patterns are made to ease the task of development and provide various advantages, it is crucial to choose the right one for your project as choosing the wrong architecture may increase the complexity of the application.