Top 5 System Design Patterns for Software Architecture

Indispensable in software development, design patterns are like blueprints that can be used to address common challenges and achieve specific outcomes across various use cases. Design patterns have evolved to become industry standards for various areas of software development, often helping us avoid recurring problems during the design and implementation stages of projects. As it turns out, design patterns are also powerful tools in System Design.

I interviewed many skilled candidates in System Design Interviews across FAANG and beyond, however, I saw many skilled developers' interview performance suffer because they lacked sufficient knowledge of design patterns.

There are numerous System Design patterns, but today I want to help you start mastering design patterns by sharing the 5 patterns I believe are most important for System Designers and principle software engineers today.

Types of design patterns#

There are three main types of design patterns:

• Creational design patterns: These patterns abstract the instantiation process and help make a system independent of how its objects are created, composed, and represented. Examples include the Factory Method, Abstract Factory, and Singleton patterns.

• Structural design patterns: These patterns deal with the composition of classes and objects to form larger structures. They focus on relationships between objects. Examples include the Adapter, Bridge, and Decorator patterns.

• Behavioral design patterns: These patterns define how objects interact and communicate with each other. They address the collaboration and responsibilities of objects. Examples include the Observer, Strategy, and Command patterns.

Why are design patterns essential to System Design?#

While a designer can probably make simple systems without using some of the key patterns, doing so comes at a cost. Let’s briefly examine some reasons why they are used:

• Reusability: Design patterns provide reusable solutions to common problems, reducing the need to reinvent the wheel. Developers can leverage existing patterns, saving time and effort.

• Flexibility: Design patterns are designed to be adaptable. They can be tailored to specific requirements and contexts, allowing developers to build flexible and extensible systems.

• Communication: Design patterns establish a shared language among developers. By using well-known patterns, teams can effectively convey complex design ideas and collaborate seamlessly.

• Maintainability: Implementing design patterns often leads to more maintainable code. Patterns promote clear structure, making it easier to understand, modify, and extend software over time.

5 essential System Design Patterns#

Now that we know why we need them, let's get to know the essential patterns I mentioned (I'll expand more deeply on each pattern in the next section).

1. Microservices Architecture#

This particular pattern involves breaking down a large application into smaller, independent services that communicate over a network. Each microservice focuses on a specific business capability and can be developed, deployed, and scaled independently.
This pattern not only enhances scalability and flexibility, but also improves maintainability. It allows teams to work on different services simultaneously and reduces the impact of changes in one service on others.

2. Event-Driven Architecture#

In this frequently employed pattern, systems react promptly to events or messages, ensuring seamless functionality. Components communicate asynchronously through event production and consumption, often using a message broker or event bus. Using event-driven architecture boosts both responsiveness and scalability. The decoupling of components enables independent evolution and better handling of varying loads.

3. Layered Architecture (N-Tier Architecture)#

Layered Architecture organizes the system into distinct layers with specific responsibilities, such as presentation, business logic, and data access. Each layer interacts only with the layers directly adjacent to it.

A key benefit of this pattern is that it promotes the separation of concerns, making the system more modular, easier to understand, and maintain. It also facilitates testing and development by isolating changes to specific layers.

4. Client-Server Pattern#

This pattern splits the system into client and server parts. Clients demand services, and servers supply these services, often dealing with data processing and storage.

Because it establishes a clear division of tasks and consolidates control and data management on the server side, it effectively supports a wide array of applications, such as web and mobile apps.

5. Repository Pattern#

The Repository Pattern provides a centralized place for data access logic, abstracting the underlying data sources. It allows the separation of the business logic from the data access logic.

Using a repository enhances maintainability and testability by decoupling data access from business logic. It provides a consistent way to interact with data sources, facilitating changes in data storage strategies.

Why start with these patterns?#

These design patterns are crucial for principal engineers and system architects, allowing them to build systems that are robust, scalable, and maintainable.

• Scalability: Microservices and event-driven architectures enable systems to handle increasing loads and complex interactions efficiently.

• Maintainability: Layered and repository patterns promote clean separation of concerns, making the system easier to maintain and extend.

• Flexibility: The client-server pattern supports diverse client types and facilitates centralized management of business logic and data.

Deeper into the essential patterns #

Microservices Architecture#

Microservices Architecture is an architectural style that structures an application as a collection of small, autonomous services modeled around a business domain. Each service is self-contained and implements a single business capability.

Key characteristics#

Here are the key characteristics, benefits, and challenges of the Microservices Architecture:

Service independence#

Each microservice operates independently and encapsulates a specific business function or process. Services communicate with each other through well-defined APIs, often over HTTP/REST or messaging protocols.

Decentralized data management#

Each microservice has its own database, allowing it to be decoupled from other services. This promotes autonomy and minimizes the risk of a single point of failure.

Continuous delivery and deployment#

Microservices support continuous integration and continuous deployment (CI/CD) practices. Each service can be developed, tested, and deployed independently.

Polyglot persistence and polyglot programming#

Teams can choose different technologies, programming languages, and databases that best fit the specific needs of each service.

Scalability#

Microservices can be scaled independently, allowing for efficient resource utilization and tailored scaling strategies based on the needs of each service.

Microservices architecture promotes the development of scalable, flexible, and maintainable applications by breaking down the monolithic structure into smaller, manageable services. While it offers significant advantages, it also introduces new complexities that require careful planning and robust infrastructure to manage effectively. This architecture is particularly valuable for large, dynamic applications where rapid development and deployment are essential.

Event-Driven Architecture#

Event-Driven Architecture (EDA) is a design pattern that enables systems to respond to events or changes in state. It decouples the components of a system, allowing them to communicate through events rather than direct calls. This architecture is highly scalable, flexible, and responsive, making it ideal for applications that need to handle a high volume of real-time data and interactions. Here are its key aspects:

Key characteristics#

Events as primary entities#

Events are the primary means of communication between components. An event is a significant change in state, such as a user action, a sensor reading, or a transaction completion.

Producers and consumers#

Event producers are components that generate events when something significant happens (e.g., a user clicks a button, a temperature sensor detects a change).

Event consumers are components that react to events, performing actions such as updating data, triggering workflows, or sending notifications.

Event channels#

Events are transmitted through channels, which can be implemented using messaging systems like Apache Kafka, RabbitMQ, or Amazon SNS. These channels ensure that events are delivered to interested consumers.

Asynchronous communication#

Components communicate asynchronously, meaning the event producer does not wait for the consumer to process the event. This decoupling improves system performance and scalability.

Event processing models#

Event stream processing is when events are processed in real-time as they occur.

Event sourcing is when all changes in the state are stored as a sequence of events, allowing the state to be reconstructed by replaying events.

EDA provides a robust framework for building scalable, flexible, and responsive systems. By decoupling components and enabling asynchronous communication through events, EDA can efficiently handle complex real-time interactions and large volumes of data. However, it requires careful design and management to address the challenges associated with event handling, consistency, and monitoring.

Layered Architecture (N-Tier Architecture)#

The Layered Architecture pattern, also known as the N-Tier architecture, is a design pattern that organizes the system into a set of layers, each with distinct responsibilities and functionalities. This separation of concerns promotes modularity, ease of maintenance, and scalability.

Here is an overview of the layered pattern:

Presentation layer#

Role#

The topmost layer is responsible for handling the user interface and user experience. It communicates with the user, receiving input and displaying output.

Components#

Web pages, desktop applications, mobile apps, and UI frameworks

Application layer (Service layer)#

Role#

It manages the application’s logic and controls the flow of data between the presentation and data layers. It processes user inputs received from the presentation layer and invokes business logic.

Components#

Application services, controllers, and workflow engines

Business logic layer (Domain layer)#

Role#

It contains the core functionality of the application, implementing the business rules and logic. It ensures that the data passed between the other layers is processed according to the business requirements.

Components#

Business rules, domain models, and business services

Data access layer (Persistence layer)#

Role#

It handles the interaction with the database or any other storage mechanism. It provides a way to retrieve, store, and update data, abstracting the underlying data access technology.

Components#

Data repositories, Data Access Objects (DAOs), and database connections

Database layer#

Role#

The bottommost layer is responsible for actual data storage. It stores the application’s data in a structured way, allowing efficient querying and transaction management.

Components#

Relational databases, NoSQL databases, file systems, and data storage services

Overall, the layered pattern is a widely used architectural pattern that provides a clear structure and separation of concerns, making it easier to develop, maintain, and scale complex applications.

Client-Server Pattern#

The Client-Server Pattern is a fundamental architectural design pattern in software engineering, characterized by the separation of concerns between client and server entities. Here are the key aspects and benefits of the Client-Server Pattern.

Structure#

Client#

The client, typically a front-end application that interacts with the user, is a requester of services. It sends requests to the server and processes responses.

Server#

The server is a provider of services and is usually a back-end system that processes client requests, performs necessary computations or data retrieval, and sends back responses.

Key characteristics#

Separation of concerns#

The client and server are distinct entities with clear roles. The client focuses on the user interface and user interactions, while the server handles data processing, storage, and business logic.

Communication#

Communication between the client and server typically occurs over a network using standardized protocols such as HTTP, TCP/IP, or WebSocket.

Request-response model#

The interaction follows a request-response model where the client sends a request to the server, the server processes the request, and then the server sends back a response to the client.

The client-server pattern is foundational in modern computing, underpinning many of the applications and services we use daily. It provides a robust framework for building distributed systems that are scalable, maintainable, and capable of supporting a wide range of client devices and interfaces.

The Repository Pattern#

This pattern was presented by Hieatt and Mee in Fowler's book: Patterns of Enterprise Application Architecture. By implementing a collection-like interface, the repository pattern facilitates communication between the domain and data mapping layers in software design.

Here’s a quick look at the key characteristics of the Repository Pattern.

Key characteristics#

How it works#

Acting as an in-memory domain object collection, the repository facilitates communication between the domain and data mapping layers. Clients use a declarative approach to build query specifications and then submit them to the repository to be satisfied.

The repository enables the seamless addition and removal of objects through its encapsulated mapping code. A repository is a conceptual entity that encapsulates objects stored in a data store and the corresponding operations, offering an object-oriented perspective on the persistence layer.

The repository pattern is a complex pattern that incorporates various other patterns. Despite the extensive machinery working in the background, the repository provides a user-friendly interface. To retrieve specific objects from a query, clients generate a criteria object that outlines their desired characteristics.

From the perspective of code using a repository, it looks like a straightforward collection of domain objects in memory. The repository hides the fact that it does not directly store the domain objects from the client code. It’s important for code utilizing a repository to understand that this seemingly small object collection could actually correspond to a product table containing hundreds of thousands of records.

Non-relational databases#

The repository is versatile in its ability to use different object sources, even beyond relational databases, through the use of specialized strategy objects for data mapping. This makes it particularly valuable in systems with multiple database schemas or sources for domain objects, as well as in testing scenarios where speed is important, and the use of only in-memory objects is preferred.

Code readability#

Utilizing repositories can enhance code readability and clarity in query-heavy implementations. For instance, a browser-based system with numerous query pages requires an efficient method to process HttpRequest objects into query results. Converting the HttpRequest into a criteria object is usually a straightforward task for the handler code, often happening automatically or with little hassle.

Abstraction of data access#

The pattern abstracts the data access layer, providing a clean interface to the business logic layer. This means the business logic does not need to know the specifics of how data is stored or retrieved.

Centralized data access logic#

All data access operations are centralized in the repository, which encapsulates the logic required to query, insert, update, and delete data.

Separation of concerns#

The business logic is decoupled from data access logic, promoting a separation of concerns. This makes the system more modular and easier to maintain.

Consistency in data access#

The repository pattern provides a consistent API for data access, ensuring that all parts of the application interact with the data source in a uniform way.

The Repository Pattern is a powerful tool for managing data access in a structured and maintainable way. By centralizing and abstracting data access logic, it promotes separation of concerns, enhances testability, and provides flexibility in how data is stored and retrieved. However, it should be used judiciously to avoid unnecessary complexity, particularly in simpler applications.

Mastering design patterns#

I hope this blog gave you a good launch into design patterns in System Design. Since there are numerous patterns that are used for System Design, I have only touched the tip of the iceberg here.

Of course, just knowing design patterns is not enough to ace System Design interview questions. You must exercise critical thinking to choose the appropriate pattern for your scenario. To truly master design patterns, you'll need to get good at choosing the optimal patterns for a specific scenario — and this just takes time and practice. Happy learning!