What are the key components to consider in a distributed system design?

1. Load Balancing
2. Caching
3. Database Sharding
4. Message Queues
5. Service Discovery
6. Monitoring and Logging
7. Content Delivery Networks (CDNs)
8. Replication and Consistency

Explain the time and space complexity of QuickSort.

• Time Complexity:
  • Average case: O(n log n)
  • Worst case: O(n²) (rare, occurs with poor pivot selection)
• Space Complexity:
  • O(log n) due to the recursive call stack
• QuickSort is often preferred for its excellent average-case performance and in-place sorting capability.

What strategies can you employ to manage technical debt effectively?

1. Regular code reviews
2. Refactoring sprints
3. Setting aside time for improvements in each sprint
4. Maintaining a technical debt backlog
5. Educating stakeholders about the importance of addressing technical debt
6. Implementing automated testing and continuous integration
7. Establishing coding standards and best practices

Describe techniques for scaling a database to handle increased load.

1. Vertical scaling (upgrading hardware)
2. Horizontal scaling (sharding)
3. Read replicas for distributing read operations
4. Caching frequently accessed data
5. Denormalization for read-heavy workloads
6. Implementing a database proxy
7. Using NoSQL databases for specific use cases
8. Partitioning data by functionality

Compare and contrast microservices and monolithic architectures.

Microservices:

• Pros: Scalability, technology diversity, easier deployment
• Cons: Complexity, network latency, data consistency challenges

Monolithic:

• Pros: Simplicity, easier debugging, data consistency
• Cons: Scaling difficulties, technology lock-in, slower deployment

Choice depends on project size, team structure, and scalability needs.

What are the key principles of writing clean, maintainable code?

1. DRY (Don't Repeat Yourself)
2. SOLID principles
3. Writing self-documenting code
4. Consistent naming conventions
5. Keeping functions and classes small and focused
6. Writing unit tests
7. Code comments for complex logic
8. Regular refactoring
9. Version control best practices
10. Code reviews

How would you design a system for high availability and fault tolerance?

1. Implement redundancy at all levels (servers, data centers)
2. Use load balancers to distribute traffic
3. Implement circuit breakers for failing services
4. Design for graceful degradation
5. Use asynchronous processing where possible
6. Implement proper monitoring and alerting
7. Regular disaster recovery drills
8. Use distributed databases with replication
9. Implement auto-scaling for traffic spikes
10. Use containerization for consistent environments