System Design Guide
Introduction
System design is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. A well-designed system is scalable, maintainable, reliable, and meets business goals.
This guide provides a comprehensive overview of system design, including a sample use case, architectural options, and decision-making criteria.
1. System Design Process Overview
- Requirement Gathering: Understand business needs, user requirements, and constraints.
- High-Level Architecture: Define the overall structure (monolith, microservices, etc.).
- Component Design: Break down into modules/services.
- Data Modeling: Design databases and data flow.
- Interface Design: Define APIs and user interfaces.
- Scalability & Reliability: Plan for growth and fault tolerance.
- Security & Compliance: Address authentication, authorization, and data protection.
- Deployment & Operations: Plan for CI/CD, monitoring, and maintenance.
2. Sample Use Case: Customer Portal
Scenario: Build a customer portal where users can:
- Submit applications
- Report issues
- Redeem rewards
Key Requirements
- User authentication and profile management
- Application submission workflow
- Issue tracking and support
- Reward redemption and tracking
- Admin dashboard for management
- Notifications (email/SMS)
- Scalability for growing user base
3. Architectural Approaches
A. Monolithic Architecture
- Description: All features are built into a single codebase and deployed as one unit.
- Pros:
- Simpler to develop and deploy initially
- Easier to test end-to-end
- Lower operational overhead for small teams
- Cons:
- Harder to scale individual features
- Codebase can become unwieldy as features grow
- Difficult to adopt new technologies for specific modules
- When to Choose:
- Small teams or MVPs
- Limited budget and time
- Low expected traffic
B. Bare Metal Deployment
- Description: Deploying the application directly on physical servers (no virtualization or containers).
- Pros:
- Maximum performance (no virtualization overhead)
- Full control over hardware and OS
- Cons:
- High upfront cost and maintenance
- Poor scalability and flexibility
- Slow to provision and recover from failures
- When to Choose:
- Specialized performance needs (e.g., high-frequency trading)
- Regulatory or legacy constraints
C. Microservices Architecture
- Description: Application is split into independent services (e.g., Auth, Application, Issues, Rewards), each with its own codebase and database.
- Pros:
- Independent scaling and deployment
- Technology diversity per service
- Fault isolation (failure in one service doesn’t bring down the whole system)
- Easier for large teams to work in parallel
- Cons:
- Higher operational complexity (orchestration, monitoring, networking)
- Requires robust DevOps and automation
- Distributed system challenges (consistency, latency)
- When to Choose:
- Large, growing teams
- Need for high scalability and availability
- Complex business domains
4. Decision-Making Criteria
| Criteria | Monolith | Bare Metal | Microservices |
|---|---|---|---|
| Team Size | Small | Any | Medium/Large |
| Time to Market | Fast | Slow | Medium |
| Scalability | Limited | Limited | High |
| Maintainability | Decreases w/size | Hard | High |
| Cost | Low (start) | High | Medium/High |
| Tech Flexibility | Low | Low | High |
| Fault Isolation | Low | Low | High |
| Operational Overhead | Low | High | High |
Recommendation: Start with a monolith for MVPs or small teams. Move to microservices as the system grows in complexity and scale. Bare metal is rarely recommended unless there are specific needs.
5. Example: Customer Portal Designs
Monolithic Example
- Single web app (e.g., Node.js, Django, ASP.NET)
- Single database (e.g., PostgreSQL)
- All features in one codebase
- Deployed on a VM or PaaS
Microservices Example
- Auth Service (user management, JWT)
- Application Service (handles submissions)
- Issue Service (tracks issues)
- Reward Service (manages rewards)
- API Gateway (routes requests)
- Separate databases per service
- Deployed on Kubernetes or cloud containers
6. Sample Decision Flow
- Prototype/MVP: Monolith for speed and simplicity
- Growth/Scale: Refactor to microservices for scalability and maintainability
- Special Needs: Consider bare metal only for unique performance or compliance requirements
7. Conclusion
System design is about making trade-offs. Choose the architecture that best fits your current needs, but design with future evolution in mind. Document decisions and revisit them as requirements change.