Design Principles and Key Characteristics in System Design

When we talk about system design, two terms often come up together – design principles and key characteristics.

They sound similar, but they describe different layers of thinking in how we build scalable, reliable, and efficient systems.

What are Design Principles?

Design principles are the core guidelines or philosophies that architects follow when designing any system.

They are not tied to specific technologies or metrics – they are ways of thinking that help ensure your design meets both current and future needs.

Think of them as rules of good architecture – the “why” behind every design choice:

1 Scalability

Definition: The ability of a system to handle increased loads – be it more users, data, or transactions – without sacrificing performance. A scalable system can expand its resources (either vertically or horizontally) without significant degradation in performance or requiring a complete redesign.

It can be done by various ways:

• Horizontal scaling: Adding more machines or instances to distribute the load.
• Vertical scaling: Enhancing the capacity of a single machine, by adding resources (CPU, RAM, storage).
• Elastic Scaling: The ability to scale up or down automatically based on demand, often used in cloud environments.

Example: A social media platform must scale to accommodate millions of users worldwide, with growing data storage and processing needs.

Analogy:

A highway that can add more lanes to handle more traffic without slowing down.

2 Reliability

Definition: It is the system's ability to operate continuously without failure and recover from failures quickly. A reliable system must be designed with fault tolerance, redundancy, and error-handling mechanisms to ensure high availability.

It can be done through various ways:

• Robust error handling.
• Minimal downtime and quick recovery from failures.

Analogy:

A car that starts every morning, even in very cold weather.

3 Availability

Definition: The degree to which a system remains operational and accessible when needed. It is represented in 9's for example, 99.90% percent availability means downtime of some hours per year.

Key Points:

• Use of redundant components.
• Failover mechanisms to ensure continuous service even during partial system outages.

4 Efficiency

Definition: How efficiently a system processes tasks under various loads.

It is primarily measured by:

• Latency: Delay in getting the first response.
• Throughput: Number of operations handled in a given time.

5 Maintainability

Definition: It refers to how easy it is to update, fix, and improve the system over time. Systems with good maintainability are modular, well-documented, and have clear separation of concerns, making it easier for engineers to make changes without breaking other parts of the system.

Modularity: Breaking down a system into independent, reusable modules or components.

Loose Coupling: Minimizing dependencies between components to make them easier to modify and test.

Code Readability and Documentation: Clear, well-commented code and detailed design documentation help future developers maintain the system.

Example: A content management system (CMS) should allow developers to easily add new features or update existing ones without disrupting the overall functionality.

6 Performance (Latency & Throughput)

The system processes requests and delivers responses efficiently.

What it means:

• Latency: The time taken to complete a single operation (e.g., time to load a page).
• Throughput: The number of operations performed in a unit of time (e.g., requests processed per second).

How you measure it:

P95/P99 latency (the latency experienced by 95% or 99% of requests), and queries per second (QPS).

Analogy:

A fast-food restaurant that serves individual customers quickly (low latency) and can serve a long line without slowing down (high throughput).