System Design Principles

Scalability

Ability to handle growth in users, data, or traffic without performance degradation.

Reliability

System continues to work correctly even when failures occur.

Maintainability

Code is easy to understand, modify, and extend over time.

Performance

System responds quickly and uses resources efficiently.

Design Process

1. Requirements Gathering

• Functional requirements (what the system does)
• Non-functional requirements (performance, scalability, reliability)
• Constraints (budget, timeline, technology choices)

2. Capacity Estimation

• Traffic estimates (requests per second)
• Storage estimates (data volume and growth)
• Memory and CPU requirements

3. System Interface Design

• API design and contracts
• Data formats and protocols
• User interface considerations

4. Data Model Design

• Database schema and relationships
• Data partitioning strategies
• Caching and indexing decisions

5. Detailed Design

• Component architecture
• Data flow diagrams
• Failure mode analysis

Key Concepts

CAP Theorem

Consistency, Availability, Partition Tolerance - pick two.

ACID vs BASE

• ACID: Strong consistency (traditional databases)
• BASE: Basic availability, soft state, eventual consistency

Horizontal vs Vertical Scaling

• Vertical: Add more power to existing servers
• Horizontal: Add more servers to distribute load

Common System Designs

URL Shortener

• Hash function for URL shortening
• Database for mapping storage
• Redirect service for lookups

Social Media Feed

• Fan-out on write vs read
• Timeline generation strategies
• Push vs pull mechanisms

E-commerce Platform

• Product catalog and search
• Shopping cart and checkout
• Inventory management
• Payment processing

Chat Application

• Real-time messaging architecture
• Message persistence and retrieval
• Presence indicators
• Group chat management

Performance Optimization

Database Optimization

• Query optimization and indexing
• Connection pooling
• Read replicas and sharding

Caching Strategies

• Application-level caching
• Database query caching
• CDN for static assets

Asynchronous Processing

• Message queues for background jobs
• Event-driven architecture
• Batch processing for bulk operations

Monitoring & Alerting

Key Metrics

• Response time and throughput
• Error rates and availability
• Resource utilization (CPU, memory, disk)
• Business metrics (conversion rates, user engagement)

Alerting Strategy

• Define service level objectives (SLOs)
• Set up alerts for critical failures
• Implement gradual escalation
• Automate incident response

Security Considerations

Defense in Depth

• Multiple layers of security controls
• Zero trust architecture
• Principle of least privilege

Common Threats

• Injection attacks (SQL, XSS, CSRF)
• Authentication bypass
• Data breaches and leakage
• DDoS attacks

Security Best Practices

• Input validation and sanitization
• Secure communication (HTTPS/TLS)
• Regular security audits and penetration testing
• Incident response planning