An architectural pattern is the outline that allows you to express and define a structural schema for all kinds of software systems. It’s a reusable solution that provides a predefined set of subsystems, roles, and responsibilities, including the rules and roadmap for defining relationships among them. It helps you address various software engineering concerns such as performance limitations, high availability, minimizing business risk, etc.
Famous examples of architectural patterns are microservices, message bus, service requester/ consumer, MVC pattern, MVVM, microkernel, n-tier, domain-driven design components, and presentation-abstraction-control.
Features of Software Architecture Pattern:
Here are some more reasons why software architecture patterns are vital for any software application:
1. Defining Basic Characteristics of an Application:
Knowing each architecture’s characteristics, strengths, and weaknesses becomes important for choosing the right one to meet your business objectives. It has been observed that architecture patterns help in defining the basic characteristics and behaviors of an application. For instance, some architecture patterns can be naturally used for highly scalable applications, whereas others can be used for agile applications.
2. Maintaining Quality and Efficiency:
There is a high possibility that any application you build might face quality issues. According to your software development quality attributes, selecting an architecture pattern can help minimize the quality issues while simultaneously maintaining efficiency.
3. Providing Agility:
It is natural for software applications to undergo numerous modifications and iterations during software development and even after production. Therefore, planning a core software architecture beforehand provides agility to the application and makes future moderations effortless.
4. Problem Solving:
Prior planning and knowledge of a software architecture give a clear idea of how the application and its components will function. With an architecture in place, the developing team can adopt the best practices to resolve complex processes and solve any errors in the future.
5. Enhancing Productivity:
Irrespective of the skills and knowledge one has about a programming language, framework, or application, there has to be certain standardized principles. With an appropriate application pattern in place, the company can quickly grasp the project’s status. In addition, productivity rates improve the moment an architecture pattern is in place to make the project scope clear.
Types of Software Architecture Pattern:
1. Layered Pattern:
Layered Architecture Pattern, also known as n-tier architecture, describes an architectural pattern composed of several horizontal layers that function together as single unit of software.
layered architecture is classified into four distinct layers:
Presentation Layer – responsible for user interactions with the software system
Application/Business Layer – handles aspects related to accomplishing functional requirements
Domain Layer – responsible for algorithms, and programming components
Infrastructure/Persistence/Database Layer – responsible for handling data, databases
Usage:
Applications that are needed to be built quickly.
Enterprise applications that require traditional IT departments and processes.
Appropriate for teams with inexperienced developers and limited knowledge of architecture patterns.
Applications that require strict standards of maintainability and testability.
Limitations:
Unorganized source codes and modules with no definite roles can become a problem for the application.
Skipping previous layers to create tight coupling can lead to a logical mess full of complex interdependencies.
Basic modifications can require a complete redeployment of the application.
2. Event-driven pattern:
Event-driven Architecture Layer is made up of decoupled, single-purpose event processing components that asynchronously receive and process events. This pattern orchestrates the behavior around the production, detection, and consumption of all the events, along with the responses they evoke.
This diagram represents a common event-driven architecture design pattern, in which events feed actions in applications and repositories. The event is generated by some action, is fed through a connector or broker, then is processed, usually in a stream processing platform, and finally, a result is delivered to an application or repository.
The event-driven architectural style consists of two topologies
mediator and
broker.
A mediator is used when multiple steps are needed to be orchestrated within an event bus through a central mediator.
A broker is used to chain events together without using a central mediator.
Usage:
For applications where individual data blocks interact with only a few modules.
Helps with user interfaces.
Limitations:
Testing individual modules can only be done if they are independent, otherwise, they need to be tested in a fully functional system.
When several modules are handling the same events, error handling becomes challenging to structure.
Development of a system-wide data structure for events can become arduous if the events have different needs.
Maintaining a transaction-based mechanism for consistency can become complex with decoupled and independent modules.
3. Microkernel Pattern
This architecture pattern consists of two types of components – a core system and several plug-in modules. While the core system works on minimal functionality to keep the system operational, the plug-in modules are independent components with specialized processing.
If we take a business application’s perspective, the core system can be defined as general business logic without the custom code for special cases, special rules, or complex conditional processes. On the other hand, the plug-in modules are meant to enhance the core system in order to produce additional business capabilities.
Usage:
Applications that have a clear segmentation between basic routines and higher-order rules.
Applications that have a fixed set of core routines and dynamic set of rule that needs frequent updates.
Limitations:
The plugins must have good handshaking code so that the microkernel is aware of the plugin installation and is ready to work.
Changing a microkernel is almost impossible if there are multiple plugins dependent on it.
It is difficult to choose the right granularity for the kernel function in advance and more complex at a later stage
4. Microservice Pattern
Microservices architecture pattern is seen as a viable alternative to monolithic applications and service-oriented architectures. The components are deployed as separate units through an effective, streamlined delivery pipeline. The pattern’s benefits are enhanced scalability and a high degree of decoupling within the application.
Owing to its decoupled and independent characteristics, the components are accessed through a remote access protocol. Moreover, the same components can be separately developed, deployed, and tested without interdependency on any other service component.
Usage:
Businesses and web applications that require rapid development.
Websites with small components, data centers with well-defined boundaries, and remote teams globally.
Limitations:
Designing the right level of granularity for a service component is always a challenge.
All applications do not include tasks that can be split into independent units.
Performance can be affected because of tasks being spread across different microservices.
5. Space-Based Pattern
The concept of tuple space – the idea of distributed shared memory is the basis of the name of this architecture. The space-based pattern comprises two primary components – a processing unit and a virtualized middleware.
The processing unit contains portions of application components, including web-based components and backend business logic. While smaller web applications could be deployed in a single processing unit, the larger applications could split the application functionality into multiple processing units to avoid functional collapse. Furthermore, the virtualized-middleware component contains elements that control various aspects of data synchronization and request handling. They can be custom-written or can be purchased as third-party products.
Usage:
Applications and software systems that function with a large user base and a constant load of requests.
Applications that are supposed to address scalability and concurrency issues.
Limitations:
It is a complex task to cache the data for speed without disturbing multiple copies.
6. Client-Server Pattern
A client-server architecture pattern is described as a distributed application structure having two main components – a client and a server. This architecture facilitates the communication between the client and the server, which may or may not be under the same network. A client requests specific resources to be fetched from the server, which might be in the form of data, content, services, files, etc. The server identifies the requests made and responds to the client appropriately by sending over the requested resources.
The functionality of this architecture is highly flexible as a single server can serve multiple clients, or a single client can use multiple servers. The servers can be classified by the services or resources they provide, irrespective of how they perform.
Usage:
Applications like emails, online banking services, the World Wide Web, network printing, file sharing applications, gaming apps, etc.
Applications that focus on real-time services like telecommunication apps are built with a distributed application structure.
Applications that require controlled access and offer multiple services for a large number of distributed clients.
An application with centralized resources and services that has to be distributed over multiple servers.
Limitations:
Incompatible server capacity can slow down, causing a performance bottleneck.
Servers are usually prone to a single point of failure.
Changing the pattern is a complex and expensive process.
Server maintenance can be a demanding and expensive task.
7. Master-Slave Pattern
Imagine a single database receiving multiple similar requests at the same time. Naturally, processing every single request at the same time can complicate and slow down the application process. A solution to this problem is a master-slave architecture pattern that functions with the master database launching multiple slave components to process those requests quickly.
As the title suggests, the master-slave architecture pattern can be pictured as a master distributing tasks to its slaves. Once the slave components finish their tasks, the distributed tasks are compiled by the master and displayed as the result.
This pattern is well-suited for applications that can be divided into smaller segments for executing similar requests. An appropriate example would be a database application that requires heavy multitasking as its vital component.
Usage:
Development of Operating Systems that may require a multiprocessors compatible architecture.
Advanced applications where larger services have to be decomposed into smaller components.
Applications processing raw data stored in different servers over a distributed network.
Web browsers that follow multithreading to increase its responsiveness.
Limitations:
Failure of the master component can lead to a loss of data with no backup over the slave components.
Dependencies within the system can lead to a failure of the slave components.
There can be an increase in overhead costs due to the isolated nature of the slave components.
8. Pipe-Filter Pattern
A pipe-filter architecture pattern processes a stream of data in a unidirectional flow where components are referred to as filters, and pipes are those which connect these filters. The chain of processing data takes place where the pipes transmit data to the filters, and the result of one filter becomes the input for the next filter. The function of this architecture is to break down significant components/processes into independent and multiple components that can be processed simultaneously.
The pipe-filter pattern is best suited for applications that process data in a stream using web services and can create simple sequences to complex structures. Compilers can be considered a fitting example having this architecture pattern since each filter performs lexical analysis, parsing, semantic analysis, and code generation.
Usage:
It can be used for applications facilitating a simple, one-way data processing and transformation.
Applications using tools like Electronic Data Interchange and External Dynamic List.
Development of data compilers used for error-checking and syntax analysis.
To perform advanced operations in Operating Systems like UNIX, where the output and input of programs are connected in a sequence.
Limitations:
There can be a loss of data in between filters if the infrastructure design is not reliable.
The slowest filter limits the performance and efficiency of the entire architecture.
During transmission between filters, the data-transformation overhead costs might increase.
The continuous transformational character of the architecture makes it less user-friendly for interactional systems.
9. Broker Pattern
A broker pattern is used for structuring distributed systems with decoupled components. By invoking remote services, components can interact with others in broker architecture patterns. Also, the broker is responsible for all the coordination and communication among the components.
Clients, servers, and brokers are three major components of the broker pattern. Generally, a broker will have access to all the services and characteristics related to a particular server. When clients request a service from the broker, the broker redirects them to a suitable service category for further process.
Usage:
Used in message broker softwares such as Apache ActiveMQ, Apache Kafka, RabbitMQ, and JBoss Messaging.
For structuring distributed systems that have decoupled components.
Limitations:
Shallow fault tolerance capacity.
Requires standardization of service description.
The hidden layer may decrease software performance.
Higher latency and requires more effort in deployment.
10. Peer-to-Peer Pattern
In the peer-to-peer architectural pattern, individual components are called peers. A peer can act as a client, a server, or both and change its role dynamically over time. As a client, a peer can request service from other peers, and as a server, a peer can provide services to other peers. The significant difference between peer-to-peer and client-server architecture is that each computer on the network has considerable authority and the absence of a centralized server. Its capacity increases as more and more computers join the network.
There are three models of unstructured P2P architecture pattern:
Pure P2P
Hybrid P2P
Centralized P2P
Usage:
File-sharing networks such as Gnutella and G2.
Cryptocurrency-based products such as Bitcoin and Blockchain.
Multimedia products such as P2PTV and PDTP.
Limitations:
No guarantee of high-quality service.
Achieving robust security is challenging.
Performance depends on the number of nodes connected to the network.
No way to backup files or folders.
Might need a specific interface to read the file.
Advantages of using Software Architecture Pattern:
Some of the advantages of using an architecture pattern are the following:
Architecture defines the model of the software, how it will function, and defines the problems you might encounter when it comes to implementation. As a result, these patterns make it easier to make decisions and manage change to get better estimates of the time and cost of a project.
Provide a proven reusable solution for known problems and is built on a tried and tested design experience
Huge cost saving opportunity and reduction in risk if a software architecture is used
Higher quality standards are achieved because the pattern results in a highly testable and traceable development process
Disadvantages of using Software Architecture Pattern:
Some of the disadvantages of using an architecture pattern include:
A poorly selected software design pattern increases the total cost and duration of a development project because the proposed software product has to be adapted to the selected pattern
Innovative and cutting edge solutions will commonly not have a suitable architecture pattern available
Can result in an overly complicated software product due to the selection of an inappropriate architecture pattern
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