Did you know that every large-scale, successful enterprise software has one thing in common? This mascot ensures that the software is able to communicate well with its counterparts, survive load, scale resources, and never let the application go down.
Yes, you guessed it right. We are talking about software architecture patterns!
A software architecture lays down the basis for development. Thus, choosing the right architecture at the inception stage is important. It allows us to take the application to the next level as it moves towards success.
If you’re planning to build the next big thing in the software industry, then we recommend you to have a look at these top software architecture patterns that will ascertain that your product never fails to scale, communicate, and survive, even in the toughest of scenarios.
1. Layered Architecture Pattern
Layered architecture, also known as n-tier architecture is one of the most commonly used patterns for software development. The code in an n-tier pattern is arranged in layers. The data enters the system through the outermost layer (UI) and reaches the innermost layer (database). There are four layers in layered software architecture:
- Presentation layer (UI layer)
- Application layer (service layer)
- Business logic layer (domain layer)
- Data access layer (persistence layer)
There are at least three layers in a basic application: The presentation layer, which the user access through the GUI, the application layer that runs the business logic, and the data layer that stores and retrieves data. Since the layers are independent, it becomes easy to manage the infrastructure and thus build large-scale applications on it. Some of the popular and biggest software frameworks- Drupal, Express, Java EE are built using this architecture.
Caveats:
While building software using this architecture, remember that the code can become a mess if the roles and relationships are not clearly defined. In such an architecture, monolithic deployment is unavoidable, which means a small change in the code calls for application deployment.
2. Microservices Architecture Pattern
There are no heights to the growth of a software application. That is why it is important to ensure that a solution does not become inflexible and monolithic. A microservices architecture just ensures that.
Microservices is a modular architecture that divides software services into small, independent modules. Because the services are independent of each other, such architecture offers fault isolation capability, which means a fault in service will not affect another.
One of the best examples of software with such architecture is an eCommerce app where every individual process is a service. Search, recommendations to the shopper, payments. Everything is a service. Some of the tech giants such as Amazon, Netflix, Soundcloud use the microservices architecture to keep their solutions scalable and frequently updated.
Microservices architecture is best suited for an application if the development teams are spread out, or the business introduces frequent changes for the customers or the website/app has small components.
Caveats:
The architecture can’t be adopted for every application. This is because not every application has tasks that can be split into small, independent tasks. And for an application to adopt microservices, the services must be largely independent.
3. Service-Oriented Architecture Pattern
Service-Oriented Architecture (SOA) is an architectural style that structures an application as a collection of loosely coupled services. Services are self-contained, modular units that perform specific business functions and communicate with each other over a network. SOA promotes reusability, scalability, and flexibility by allowing services to be developed, deployed, and maintained independently.
SOA is often used in large enterprise systems where different departments or business units have distinct requirements. By encapsulating functionalities into services, organizations can achieve better maintainability, as changes to one service don't necessitate changes across the entire system.
Caveats:
Service Proliferation: Introducing too many services can lead to a highly distributed system, making it challenging to manage and monitor.
Coordination Complexity: Coordinating interactions between multiple services introduces complexity, and proper orchestration mechanisms are crucial.
ALSO READ: Microservices vs Service-Oriented Architecture (SOA)
4. Event-Driven Architecture Pattern
An event is used to capture, communicate, and process services in an event-driven architecture in a loosely coupled application. An event can be a significant state change or an update. For example, “an item purchased”, “a notification that the order is shipped”.
This architecture has three major components: Event Producers, Event Routers, and Event Consumers. The producers generate an event, the router filters and push the event to the consumers. In an event-driven architecture, the application services are loosely coupled, which means an application can scale and fail independently.
Caveats:
An event-driven architecture is highly adaptable for a dynamic and scalable development environment. However, testing can become complex in a modular environment if the modules are dependent on each other. Although testing individual modules is easy, verifying interactions between them is possible in a fully functional system. That is why an event-driven architecture is best suited for applications where the individual data blocks have to interact with only a few modules.
5. Serverless Architecture Pattern
Serverless architecture is a software design pattern wherein the application logic runs in an environment that is on the top of an Operating System and uses physical servers/virtual machines. The entire infrastructure-software, hardware, server is managed by the service provider. Other than this, serverless is a sought-after architecture amongst the developer community as it allows to scale-up or scale-down the resources, as the requirement strikes.
Caveats:
The serverless architecture comprises granular functions. Thus, managing several functions can get cumbersome, which, if go unattended can result in mini-monoliths.
ALSO READ: Benefits of Software Development using Serverless Architecture
6. Queue-based Architecture Pattern
In a queue-based architecture pattern, communication between different components or services occurs asynchronously through a central message queue. This design promotes flexibility and modularity as components interact without needing real-time connections.
In this architecture, components act as either producers or consumers. Producers generate messages and enqueue them into the message queue, while consumers dequeue messages from the queue for processing. The message queue serves as a temporary storage, ensuring that messages are not lost even if the sender and receiver components operate at different speeds or experience temporary failures.
One significant advantage of this approach is the decoupling of components. They remain independent, requiring only a shared understanding of the message format. As a result, changes in one component's implementation do not directly impact others.
Moreover, as the system grows, additional instances of components can be introduced to handle increased workloads. The message queue plays a crucial role in load balancing by distributing messages evenly among the available instances.
Caveats:
Ensuring message order can be challenging, especially when multiple producers and consumers are involved. Some scenarios may demand strict message ordering, necessitating additional considerations in the system design.
Additionally, the system's complexity increases with the introduction of a message queue. Proper error handling, monitoring, and management of message queues become essential to maintain system robustness.
7. Client-Server Architecture Pattern
The client-server architecture is a fundamental model in software development where an application is split into two primary components: the client and the server.
The client, representing the user interface, is responsible for presenting information to the end user and collecting their input. Clients can take various forms, such as desktop applications, mobile apps, or web browsers. When a user initiates an action or request, the client sends a corresponding request to the server.
On the other hand, the server holds the central repository of resources, manages data, and performs various services. It processes incoming requests from clients, executes the necessary operations, and sends back the results. Servers handle tasks related to business logic, data storage, and application functionality.
Communication between the client and server occurs over a network. The client sends requests to the server, and the server responds with the requested data or performs the specified operations. This communication is often based on a request-response paradigm, where clients request services or data, and servers fulfill those requests.
One of the key features of the client-server architecture is decoupling. The client and server components operate independently, and changes to one can be made without affecting the other, as long as the agreed-upon communication protocol is maintained.
Common examples of the client-server architecture include web applications, where the browser serves as the client and the server hosts the application logic and data. Similarly, in database systems, the client application interacts with the database server to retrieve or update data.
Caveats:
Network Dependency: Dependency on network communication can introduce latency.
Scaling Considerations: Scaling may require additional infrastructure, and load balancing strategies are crucial.
8. Pipe-Filter Architecture Pattern
In a pipe-filter architecture, filters are independent components that process input data and produce output. Pipes connect these filters, allowing the flow of data from one filter to the next. Each filter performs a specific task, and the combination of filters in the pipeline achieves the overall system functionality.
This modular design fosters reusability, as filters can be developed and tested independently. It also facilitates maintenance and updates, as modifications to one filter do not necessarily impact others in the pipeline. The architecture is well-suited for scenarios where the processing of data involves multiple discrete steps.
Caveats:
Performance Bottlenecks: Inefficient filter implementations or dependencies between filters may hinder system efficiency.
Design Complexity: Careful design is needed to avoid performance bottlenecks and maintain an efficient flow of data.
9. Space-based Architecture Pattern
The space-based architecture is meant to avoid functional collapse by dividing processing and storage load between multiple servers. In this architecture, the applications are composed of self-sufficient units called Processing Units. Since these units are independent of each other, it allows the application to scale as the demand strikes.
The Space-based architecture is closely related to Shared Nothing architecture which is distributed computing architecture and is known to address scalability issues (and is used by Google, Amazon, etc.). This software architecture is suitable for applications that have a large user-base, have a constant load of requests, and are supposed to address scalability & concurrency issues.
Caveats:
For a space-based architecture, it is difficult to build proficiency to cache the data for speed without corrupting the copies.
10. Peer-to-Peer Architecture Pattern
In a peer-to-peer architecture, each peer is capable of initiating requests and providing services to other peers. The decentralized nature of the architecture eliminates the need for a central server, promoting autonomy and scalability. Peers can collaborate directly, sharing resources, information, or services without relying on intermediaries.
This architecture is often employed in file-sharing systems, collaborative networks, and certain types of communication applications. It is well-suited for scenarios where a centralized authority is impractical or where resilience to node failures is essential.
Caveats:
Coordination and Synchronization: Coordinating actions and synchronizing data among peers can be challenging.
Security Concerns: Ensuring consistency and security in a decentralized environment can be complex.
Choosing the Right Software Architecture:
There is a lot that goes into selecting the right software architecture for the upcoming project. Reliability, performance, security, usability, availability are some of the basics that should be considered while selecting a software architecture. Other than that, defining the futuristic scope of the solution is important.
If a technical aid is required to finalize the right architecture for your project, our software architects can be approached. Our team would assess the project and related factors to recommend the right software architecture.
