Here are some of the most common software architectural patterns observed :
| 1 | Circuit breaker | This pattern minimizes the effects of a hazard by rerouting traffic to another service. While it helps make systems more fault tolerant to prevent accidents, it also requires sophisticated testing and using an infrastructure-management technology like service mesh. |
| 2 | Client- Server | This pattern is a peer-to-peer architecture that is comprised of a client, which requests a service, and a server, which provides the the service. Examples include banking, file sharing, email, and the World Wide Web. One advantage of this pattern is that data and network peripherals are centrally managed, however, the server is expensive. |
| 3 | CQRS | The command query responsibility segregation (CQRS) pattern handles the situation where database queries happen more often than the data changes. It separates read and write activities to provide greater stability, scalability, and performance, but it requires more database technologies and therefore may increase costs. |
| 4 | Controller – Responder | Also known as master-slave architecture, pattern divides the architecture into two components: The controller handles the data and distributes workloads, and the responder replicates data from the controller and generates results. One advantage is that you can read data from the responder without affecting the data in the controller, but if the controller fails, you may lose data and need to restart the application. |
| 5 | Event Sourcing | This pattern is good for applications that use real-time data. It sends a continuous stream of messages to a database, web server, log, or another target. It’s very flexible but demands a highly efficient and reliable network infrastructure to minimize latency. |
| 6 | Layered | This pattern is good for e-commerce, desktop, and other applications that include groups of subtasks that execute in a specific order. The layered pattern makes it easy to write applications quickly, but a disadvantage is that it can be hard to split up the layers later. Read more … |
| 7 | Microservices | This pattern combines design patterns to create multiple services that work interdependently to create a larger application. Because each application is small, it’s easier to update them when needed, but the complexity means you need greater architectural expertise to make everything work correctly. Read more … |
| 8 | MVC | This pattern divides an application into three components. The model contains the application’s data and main functionality; the view displays data and interacts with the user; and the controller handles user input and acts as the mediator between the model and the view. This pattern enables the application to generate various views, but its layers of abstraction increase complexity. Read More … |
| 9 | Publish – Subscribe | This pattern sends (publishes) relevant messages to places that have subscribed to a topic. It’s easy to configure but more challenging to test because interactions between the publisher and the subscriber are asynchoronous. Read More… |
| 10 | Saga | This pattern is used for transactions with multiple steps, such as travel reservation services. A “saga” includes the various steps that must happen for the transaction to complete. This pattern enables transactions (ideally with five or fewer steps) to happen in loosely coupled, message-driven environments, but it requires a lot of programming and can be complex to manage. Read more.. |
| 11 | Sharding | This pattern segments data in a database to speed commands or queries. It ensures storage is consumed equally across instances but demands a skilled and experienced database administrator to manage sharding effectively. Read More.. |
| 12 | Static content hosting | This pattern is used to optimize webpage loading time. It stores static content (information that doesn’t change often, like an author’s bio or an MP3 file) separately from dynamic content (like stock prices). It’s very efficient for delivering content and media that doesn’t change often, but downsides include data consistency and higher storage costs. |
| 13 | Strangler | This pattern is used when you’re making incremental changes to a system. It places the old system behind an intermediary to support incremental transformation, which reduces risk compared to making larger changes. However, you need to pay close attention to routing and network management and make sure you have a rollback plan in place in case things go wrong. Read More.. |
| 14 | Throttling | Also known as rate limiting pattern, this pattern controls how fast data flows into a target. It’s often used to prevent failure during a distributed denial of service attack or to manage cloud infrastructure costs. To use this pattern successfully, you need good redundancy mechanisms in place, and it’s often used alongside the circuit breaker pattern to maintain service performance. Read More.. |