“Simplicity is the ultimate sophistication.” — Leonardo da Vinci
The Importance of Patterns in Engineering: Finding the Right Balance
Patterns in software engineering are often described as the building blocks for solving common problems. They provide a proven approach to designing systems that are scalable, maintainable, and efficient. However, as with any tool, patterns need to be applied thoughtfully. Overusing them can lead to overengineering, while under using them can result in fragile and unmaintainable systems.
In this post, we’ll explore the importance of using patterns in engineering, look at some modern patterns for cloud-based stacks with web and mobile front ends, and discuss when it’s better to avoid patterns altogether to avoid overengineering.
Why Use Patterns in Engineering?
At its core, a design pattern offers a structured solution to recurring problems within a system. Here are a few reasons why patterns are crucial in modern software engineering:
- Proven Solutions: Patterns encapsulate years of industry experience, offering tried-and-true solutions for common challenges. They reduce the risk of errors by leveraging what has already been proven to work.
- Maintainability: A well-implemented pattern makes systems easier to maintain and extend. Future engineers can recognize the pattern in use, making the code easier to understand and modify.
- Scalability: Modern engineering, especially with cloud and distributed systems, requires handling massive scale. Patterns like microservices or event-driven architecture allow systems to scale without major refactoring.
- Consistency: Patterns enforce consistency across teams and projects, improving collaboration and reducing the learning curve when bringing new developers on board.
However, patterns aren’t without their drawbacks. Applying them inappropriately or over-engineering a solution can lead to unnecessary complexity.
Modern Patterns for Cloud-Based Stacks with Web and Mobile Front Ends
Let’s break down some modern patterns for various parts of a tech stack that involves cloud backends and both web and mobile front ends.
- Backend: Microservices Architecture
- Microservices have become a dominant architectural pattern for cloud backends. In this approach, the system is broken into small, independent services that communicate over APIs. Each service handles a specific business function and can be scaled independently.
- When to Use: If your system needs to handle large amounts of traffic or requires independent scaling of various components (e.g., payment processing, user management), microservices are an ideal choice. This pattern also shines when different teams work on different parts of the system.
- When to Avoid: For smaller applications or when complexity outweighs the benefits. Microservices introduce additional overhead with deployment, monitoring, and inter-service communication.
- Microservices have become a dominant architectural pattern for cloud backends. In this approach, the system is broken into small, independent services that communicate over APIs. Each service handles a specific business function and can be scaled independently.
- Backend: Serverless Architectures
- Serverless computing allows developers to write and deploy code without managing underlying servers. AWS Lambda and Azure Functions are popular examples.
- When to Use: Serverless is great for event-driven applications like real-time notifications, background processing, or when you expect unpredictable traffic spikes. It’s also useful for rapid development and deployment with reduced operational overhead.
- When to Avoid: When you need long-running processes or low-latency, high-performance computing. Serverless may introduce cold-start latency and is harder to debug for complex workflows.
- Serverless computing allows developers to write and deploy code without managing underlying servers. AWS Lambda and Azure Functions are popular examples.
- Backend: CQRS (Command Query Responsibility Segregation)
- CQRS separates the responsibility for reading and writing data. Commands handle changes to the system (e.g., creating an order), while queries handle data retrieval (e.g., fetching order status).
- When to Use: This pattern excels in systems with high read and write loads that require different optimization strategies for each. For instance, in e-commerce applications, reads might need to be optimized for speed, while writes ensure strong consistency.
- When to Avoid: In simpler applications where separating reads and writes introduces unnecessary complexity and duplication of effort.
- CQRS separates the responsibility for reading and writing data. Commands handle changes to the system (e.g., creating an order), while queries handle data retrieval (e.g., fetching order status).
- Web Front End: Component-Based UI (React, Vue, Angular)
- Component-based architecture is the gold standard for building modern web front ends. Frameworks like React, Vue, and Angular allow developers to build reusable, independent components that encapsulate both logic and presentation.
- When to Use: If you’re building a dynamic, interactive web application with reusable UI elements (e.g., dashboards, data-driven interfaces).
- When to Avoid: For static websites or simple content pages. Component-based architectures can add unnecessary overhead when server-side rendering or static site generators (SSG) like Next.js or Gatsby would suffice.
- Component-based architecture is the gold standard for building modern web front ends. Frameworks like React, Vue, and Angular allow developers to build reusable, independent components that encapsulate both logic and presentation.
- Mobile Front End: BLoC and MVVM Patterns (Flutter, SwiftUI)
- For mobile development, patterns like BLoC (Business Logic Component) in Flutter or MVVM (Model-View-ViewModel) in SwiftUI help structure code by separating concerns. These patterns make it easier to manage complex state and update the UI accordingly.
- When to Use: In mobile applications where data-binding and separation of concerns lead to better maintainability, particularly for apps that need to handle complex states (e.g., streaming apps, multi-page form apps).
- When to Avoid: In simple mobile apps, especially prototypes or MVPs, where the additional abstraction layer might slow down development without adding much value.
- For mobile development, patterns like BLoC (Business Logic Component) in Flutter or MVVM (Model-View-ViewModel) in SwiftUI help structure code by separating concerns. These patterns make it easier to manage complex state and update the UI accordingly.
When Not to Use Patterns: Avoiding Overengineering
While patterns bring a lot of value, applying them when they’re not needed can lead to overengineering. Here’s how to avoid that:
- Understand the Problem First: Don’t reach for a pattern just because it’s popular or new. Assess the problem and understand whether a simple solution could work before introducing additional complexity.
- Avoid Premature Optimization: It’s tempting to design for scale or flexibility before it’s necessary, but this can backfire. Build for today’s requirements and only optimize for future needs when they arise. For example, starting with a monolith and breaking it into microservices as the need arises can be more efficient.
- Keep It Simple: If you find yourself explaining your system architecture with too much complexity, it might be a sign that you’ve over-applied patterns. Simple, straightforward solutions that are easy to reason about are often better in the long run.
- Look Out for Pattern Soup: This happens when multiple patterns are applied in the same project without a clear need, leading to confusion, high maintenance costs, and slowed development speed.
Wrapping up…Patterns Are Tools, Not Rules
Patterns are essential to building modern, scalable, and maintainable systems, but they are tools to be applied wisely. Just as you wouldn’t use a hammer to fix every problem, not every project or part of a stack needs a formal pattern. Understanding when to use them—and when to avoid them—will help you build systems that strike the right balance between simplicity, scalability, and maintainability.
When in doubt, remember: the best architecture is the one that solves your current problems without over complicating future ones.
