If you design software architectures, you’re probably familiar with encountering the same goals and problems repeatedly. Luckily, architectural patterns provide reusable designs that address common situations. As Anand Butani explains:
“The architectural pattern captures the design structures of various systems and elements of software so that they can be reused. During the process of writing software code, developers encounter similar problems multiple times within a project, within the company, and within their careers. One way to address this is to create design patterns that give engineers a reusable way to solve these problems, allowing software engineers to achieve the same output structurally for a given project.”
Using architectural patterns in your software designs offers numerous advantages. They increase efficiency, productivity, and speed; optimize development costs; and improve planning, among other benefits.
In this article, we’ve rounded up 14 software architecture patterns by summarizing previous articles. Explore the various design patterns below and click the links to learn more about each one.
14 Software Architecture Patterns
Circuit Breaker Pattern
The circuit breaker pattern minimizes the impact of hazards by rerouting traffic to another service. While it enhances fault tolerance and accident prevention, it requires sophisticated testing and the use of an infrastructure-management technology like service mesh.
Client-Server Pattern
The client-server pattern is a peer-to-peer architecture consisting of a client that requests a service and a server that provides that service. Examples include banking, file sharing, email, and the World Wide Web. This pattern centralizes data and network peripherals, but the server can be expensive.
Command Query Responsibility Segregation (CQRS) Pattern
The CQRS pattern separates read and write activities when database queries occur more frequently than data changes. This approach provides greater stability, scalability, and performance but may increase costs due to the use of multiple database technologies.
Controller-Responder Pattern
The controller-responder pattern divides the architecture into two components: the controller, which handles data and distributes workloads, and the responder, which replicates data from the controller and generates results. While this pattern allows reading data from the responder without affecting the controller, a controller failure may result in data loss and require application restart.
Event Sourcing Pattern
The event sourcing pattern is suitable for applications that rely on real-time data. It continuously sends messages to a database, web server, log, or another target. This approach offers flexibility but demands a highly efficient and reliable network infrastructure to minimize latency.
Layered Pattern
The layered pattern is ideal for e-commerce, desktop, and similar applications with groups of subtasks executed in a specific order. While it enables quick application development, it can be challenging to split the layers later.
Microservices Pattern
The microservices pattern combines design patterns to create multiple services that work interdependently, forming a larger application. Smaller services facilitate easier updates, but the complexity requires greater architectural expertise to ensure everything functions correctly.
Model-View-Controller (MVC) Pattern
The MVC pattern divides an application into three components: the model, which contains data and main functionality; the view, which displays data and interacts with the user; and the controller, which handles user input and acts as the mediator between the model and the view. This pattern enables the generation of various views, but abstraction layers increase complexity.
Publish-Subscribe (Pub-Sub) Pattern
The pub-sub pattern publishes relevant messages to subscribers. While easy to configure, testing can be more challenging due to the asynchronous interactions between the publisher and the subscriber.
Saga Pattern
The saga pattern is used for transactions with multiple steps, such as travel reservation services. It enables loosely coupled, message-driven transactions to occur, but it requires extensive programming and can be complex to manage.
Sharding Pattern
The sharding pattern segments data in a database to speed up commands or queries. It ensures equal storage consumption across instances, but effective sharding management requires a skilled and experienced database administrator.
Static Content Hosting Pattern
The static content hosting pattern optimizes webpage loading time by storing static content separately from dynamic content. This approach is efficient for delivering content and media that rarely change, but it may result in data consistency issues and higher storage costs.
Strangler Pattern
The strangler pattern is useful when making incremental changes to a system. It involves placing the old system behind an intermediary to support gradual transformation, reducing risk compared to larger changes. However, meticulous attention to routing and network management, as well as a reliable rollback plan, is essential.
Throttling (Rate-Limiting) Pattern
The throttling pattern controls the rate at which data flows into a target. It is commonly used to prevent failure during distributed denial of service attacks or manage cloud infrastructure costs. Successful implementation requires robust redundancy mechanisms and is often used alongside the circuit breaker pattern to maintain service performance.
Summary
The next time you embark on a new software architecture project, consider incorporating these architectural design patterns to enhance your efficiency and effectiveness.
Working at the edge? Learn more about validated patterns.