Introduction to Architecture Styles and Patterns as a Blueprint for Designing a System
Architecture styles and patterns play a significant role in software development, and it is a blueprint for designing a system that describes how components interact with each other to form a particular functionality. With so many architectural styles and patterns available today, it can take time to determine which approach best suits a specific project or system. So what are the variations in the concept of architectural styles and patterns? Which architecture approach is suitable for the project you are developing?
Before discussing the various variations of architectural approaches, it is imperative to know that architectural styles and patterns differ because these two terms are often used interchangeably but have different meanings.
Architecture Styles
This Architecture Style is a high-level strategy that provides an abstract framework for a family of systems. Architecture styles increase partitioning and encourage design reuse by often solving recurring problems.
Architecture styles can be themes or aesthetics that guide the design of buildings or homes—examples: Layered, Event-Driven, and Microservices.
Architecture Patterns
Architecture patterns have a more concrete and specific nature to address particular problems or modules within the system. They provide a structured solution to architectural concerns, outlining how components and interactions should organize for a particular functionality. Architecture patterns are similar to software design patterns but work at a higher level of abstraction. Examples are Model-View-Controller (MVC), Publish-Subscribe, and Serverless.
While architecture styles provide a broad framework and can see as a general philosophy of system design, architecture patterns are concrete solutions to specific design problems within this framework.
In other words, architecture styles describe the system's overall structure, while architecture patterns address specific design issues that may arise within this structure.
Now that you know the difference between architecture styles and patterns, here is a discussion of the patterns, principles, strengths, weaknesses, and implementations of 10 major architectural styles.
1. Layered Architecture Style
Layered architecture is one of the most common architectural patterns. It is often used for traditional web applications and enterprise applications.
Principle: This architectural style separates things into different layers. A typical example is a 3-tier architecture: presentation, business logic, and data storage layers.
Strengths: Easy to understand, test, and maintain; each layer can be developed and updated independently.
Weaknesses: It can cause performance overhead; changes that affect multiple layers can be challenging to implement.
The types of applications are web applications, enterprise applications.
The types of Antipatterns are Circular dependencies, skipping layers.
Layered (n-tier) pattern
The n-tier architecture divides the system into n layers, each with specific responsibilities. The most common division is into three layers: presentation, business logic, and data storage.
Layered (n-tier) Architecture Pattern
Clean / Onion Pattern
Clean Architecture, also known as Onion Architecture, is a software design philosophy emphasizing the separation of concerns within the system. It organizes software into concentric layers, with the domain model at the core, surrounded by application-specific layers. The outer layers depend on the inner layers, not vice versa, thus promoting high separation and isolation. It allows changes in infrastructure, UI, or external agencies to have minimal impact on the business logic. It is ideal for systems that require high maintenance, testing, and independence from external UIs, databases, or frameworks.
Clean / Onion Architecture Pattern
2. Component-Based Architecture Style
This style emphasizes the separation of concerns over the various functionality available throughout the software system.
Principle: This architecture style organizes the system as loosely coupled, reusable components.
Strengths: High level of reusability, flexibility, and maintainability.
Weaknesses: Complexity in managing components and their interactions.
Application: Web applications, desktop applications, distributed systems.
Antipatterns: Too large components, redundant components.
Object-oriented Pattern
This pattern is a paradigm based on "objects," which can contain both data and code: data in the form of fields (often called attributes) and regulation in the form of procedures (often called methods). It supports encapsulation, inheritance, and polymorphism, making designing, implementing, and maintaining complex systems easier.
Microkernel Pattern
This pattern separates the minimal functional core (microkernel) from extended functionality and customer-specific parts. The microkernel contains the core functionality, while the rest of the features are implemented as plugins to the microkernel. This allows the system to be extended easily without modifying the core.
Microkernel Architecture Pattern
Plugin Pattern
This pattern allows adding new functionality to an application by adding new modules or plugins. New modules are integrated into the application through a standard interface, which enables the application to be extended and customized. This pattern is commonly used in web browsers, media players, and content management systems.
3. Service-Oriented Architecture Style
This style designs software as a collection of services that communicate with each other. Each service stands alone and represents a specific business activity with a defined result.
Principle: SOA designs applications as a collection of services that communicate over a network.
Strengths: Flexibility, scalability, reusability, and loose coupling.
Weaknesses: Increased complexity, dependence on the network, and potential performance issues.
Applications: Enterprise systems, web services, microservices.
Antipatterns: Ignoring business needs, using SOA where it is not needed.
Service-Oriented Architecture Pattern (SOA)
This pattern designs software as a collection of separate services used in multiple systems. Each service in the SOA model is built to perform a specific business function, such as checking a customer's credit score, calculating payments, or processing mortgages. These services communicate with each other over a network to accomplish a specific activity, such as processing a mortgage application. SOA encourages reuse, as multiple applications and flexibility can use services, as services can be modified or replaced without affecting other services.
Service-Oriented Architecture Architecture Pattern (SOA)
Broker Pattern
In the Broker architecture pattern, system components are communicated through a broker entity. The broker coordinates communication, such as forwarding requests and sending results and exceptions. This pattern structures distributed software systems with discrete components interacting with remote service calls.
Microservice Pattern
This pattern designs a software application as a series of small services, each running within its process and communicating with a lightweight mechanism, usually HTTP. These services are built around business capabilities and can be used independently by fully automated deployment engines. This pattern enables fast, frequent, and reliable delivery of complex applications.
Microservice Architecture Pattern
Serverless (Function as a Service or FaaS) Pattern
In this pattern, applications are built and run in a cloud environment without considering servers. The cloud provider dynamically manages the allocation of machine resources, and developers can focus only on individual functions in their application code. This pattern is ideal for scalable and event-driven applications.
4. Distributed System Architecture Style
This style refers to a system in which components residing in networked computers communicate and coordinate their actions by sending messages. The members interact with each other to achieve a common goal.
Principle: This architecture involves multiple systems working together over a network to appear as a single system to the end user.
Strengths: Scalability, fault tolerance, and resource sharing.
Weaknesses: Increased complexity, network dependency, and issues related to data consistency.
Applications: Distributed databases, cloud computing, telecommunication networks.
Antipatterns: Does not consider network failures, ignores data consistency challenges.
Space-Based Pattern
This pattern, known as Tuple Space or Cloud Architecture, is designed to avoid a single point of failure or performance bottleneck by evenly distributing services and resources across multiple servers. This pattern is ideal for high-volume, mission-critical applications that require 100% uptime and horizontal scalability, such as financial trading systems or online gaming platforms.
Space-Based Architecture Pattern
Peer-to-Peer (P2P) Pattern
In this pattern, each participant (peer) in the network acts as both a client and a server, and the network nodes communicate directly without needing a central server. This pattern is used in applications that require distributed computing or resource sharing, such as file-sharing networks or blockchain technology.
Peer-to-Peer (P2P) Architecture Pattern
5. Domain-Driven Architecture Style
This style focuses on the core domain and domain logic, basing the design on the business domain model. This style emphasizes collaboration between technical experts and domain experts to iteratively refine accurate and effective models for solving business problems.
Principle: Focuses on the core domain and domain logic and bases the design on the domain model.
Strengths: Improves understanding of complex business domains and encourages communication between technical and business teams.
Weaknesses: Can be overwhelming for simple domains and requires deep understanding.
Application: Complex business systems, enterprise software.
Antipatterns: Ignores ubiquitous language and does not involve domain experts.
Hexagonal (Ports & Adapters) Pattern
This pattern allows applications to be equally driven by users, programs, automated tests or batch scripts, and to be developed and tested separately from the devices and databases they run on. This pattern separates the business logic of the software from outside concerns, which are driven by ports and adapters. This pattern is ideal for applications that need to be decoupled from their software environment, so that they can adapt to new environments.
Hexagonal (Ports & Adapters) Architecture Pattern
Domain-Driven Design Pattern
This pattern is a software development approach for complex requirements by linking the implementation with an evolving model. It involves a close relationship between the performance and the current model, with a constant iteration cycle on both. DDD is ideal for complex systems with rich and intricate business rules or procedures where the domain constantly changes.
Domain-Driven Design Architecture Pattern
6. Event-Driven Architecture Style
Event-driven architecture is a software architecture and model for application design. With event-driven systems, the capture, communication, processing and persistence of events is the core structure of the solution.
Principles: This architecture style is driven by events such as user actions, sensor outputs, or messages from other programs.
Strengths: Highly scalable, loose coupling, encourages real-time or near-real-time information flow.
Weaknesses: Increased complexity due to asynchronous programming can make maintenance and debugging difficult.
Applications: GUI applications, real-time analysis, complex event processing.
Antipatterns: Disregard for event order, lack of event durability.
Event-Driven Pattern
Event-Driven Architecture is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. It is also highly adaptable and can be used for both small applications and large complex systems.
Event-Driven Architecture Pattern
Pub-Sub Pattern
This is a messaging pattern where the message's sender, the publisher, does not program the message to be sent directly to a specific recipient, known as the subscriber. Instead, published statements are characterized into topics without knowing which subscribers, if any, may exist. Similarly, subscribers express interest in one or more issues and receive only messages of interest without knowing who the publishers are, if any. This pattern is widely used in asynchronous systems to separate the processes that generate events from those that consume them, thus allowing for greater scalability and control.
7. Separation of Concern Architecture Style
Separation of concern is a design principle for dividing a computer program into different parts, each addressing an other problem.
Principle: Different areas of functionality are handled by separate and independent parts of a system.
Strengths: Improves understanding, reduces complexity, promotes modularity and parallel development.
Weaknesses: It can increase complexity due to interface management and requires more communication between modules.
Applicability: Almost all types of software systems.
Antipatterns: Mixing issues, lack of clear module boundaries.
MVVC Pattern
This pattern facilitates the separation of graphical user interface development from business logic or back-end development. MVVC view controllers are responsible for exposing data objects from the model so that those objects are easily managed and presented. This pattern is widely used in broad areas of user interaction such as desktop and mobile applications.
MVP Pattern
This is a derivative of the model-view-controller (MVC) architecture pattern. In MVP, the renderer assumes functionality as an "intermediary." The model and view are entirely separate and communicate with each other only through the presenter. MVP is an excellent architecture for modern web applications because it allows easier automated unit testing and provides a clean structure for the project.
Model-View-Presenter Architecture Pattern
8. Interpreter Architecture Style
An interpreter pattern is a design pattern that specifies how to evaluate sentences in a language. The basic idea is to have a class for each symbol (terminal or nonterminal) in a specialized computer language.
Principle: Program instructions are executed directly without being converted into machine language.
Strengths: Easier to debug and test, more flexible.
Weaknesses: Slower than compiled languages, requires more resources.
Applications: Scripting languages, some high-level programming languages.
Antipattern: Using an interpreter where performance is critical.
Interpreter Architecture Pattern
Interpreter Pattern
This design pattern specifies how to evaluate sentences in a language. The basic idea is to have a class for each symbol (terminal or nonterminal) in a specialized computer language. The syntax tree of a sentence in a language is an example of a composite pattern and is used to evaluate (interpret) sentences for clients. These patterns are used in compilers and translators for programming languages, in regular expression engines, and in processing and analyzing structured text data.
9. Concurrency Architecture Style
Concurrency is a system property in which multiple independent tasks are executed at the same time.
Principle: Different parts of a program are executed independently, possibly simultaneously.
Strengths: Can improve performance significantly, especially on multi-core systems.
Weaknesses: Designing and debugging problems with race conditions and deadlocks can be tricky.
Application: Real-time systems, high-performance computing, web servers.
Antipatterns: Ignores potential concurrency issues and does not correctly synchronize shared resources.
Orchestration Pattern
A controller ('orchestrator') controls service interaction in this pattern. It defines the business logic's control flow and ensures everything happens as ordered. This pattern is typically used in complex business processes where you must coordinate multiple services and want centralized control.
Orchestration Architecture Pattern
Choreography Pattern
This pattern implements a service system where each service works independently and interacts with other services through events. There is no central orchestrator. Instead, each service knows what to do next. This pattern is used when you want to create a decentralized, highly decoupled system that allows for greater flexibility and scalability.
Choreography Architecture Pattern
Primary-Secondary Pattern
This pattern consists of two types of components: Primary and Secondary. The primary feature distributes the work among identical secondary members and computes the final result from the results returned by the secondary machines. This pattern is used in parallel computing to perform faster computations by dividing an enormous computational task among multiple processors.
Pipeline/Pipe-Filter Pattern
This pattern involves a chain of processing elements (processes, threads, coroutines, etc.) organized so that the output of one piece is the input of the next. The idea is to break down tasks that perform complex processing into separate elements that can be reused. This pattern is used in Unix and Unix-like operating systems for the pipelining command.
10. Data-Centric Architecture
This style focuses on how data is organized and transformed. This style is often used in systems that process large amounts of data, perform complex calculations, or must have high scalability.
Principle: The database is at the center of the architecture, and all interactions occur through the database.
Strengths: Can provide data consistency, integrity, and reliability.
Weaknesses: Can create data bottlenecks and potential scalability issues.
Application: Many enterprise applications, CRM systems, and ERP systems.
Antipatterns: Ignores potential data bottlenecks, and does not consider data scalability.
Command Query Responsibility Segregation (CQRS) Pattern
This pattern separates read and write operations for data storage. It allows scaling read and write workloads independently and optimizing them separately. This pattern is ideal for applications with a high difference between read and write loads.
Command Query Responsibility Segregation (CQRS) Architecture Pattern
Event-Sourcing Pattern
This programming technique models the state changes that an application makes as an immutable sequence or "log" of events. Instead of modifying the existing state of the application, event sourcing involves storing the events that triggered the state change. This pattern is used in systems that need to know the circumstances that caused the current state, such as auditing systems or real-time collaborative applications.
Kappa Pattern
This tool is a software architecture pattern. Rather than using a relational DB like SQL or a key-value store like Cassandra, the canonical data stored in a Kappa Architecture system is an immutable log. This pattern is used in real-time data processing systems.
Lambda Pattern
This data processing architecture uses batch and stream processing methods to handle large amounts of data. This pattern provides a robust system that is tolerant of hardware failures and human errors. This pattern is used in big data processing tasks.
Conclusion
Understanding architecture styles and architecture patterns is essential for a software developer or architect. These styles and practices provide a way to communicate, document, and explore design alternatives. They also offer solutions to common problems, save time and effort, and result in more robust and maintainable systems. However, this is just the tip of the iceberg. Many more styles and patterns are out there, and new ones are constantly developing.
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