What to cover in a system design interview?

A system design interview is an open-ended interview where you are asked to design the architecture of a large-scale system. The focus is on evaluating your understanding of scalability, efficiency, and trade-offs when designing real-world systems. Here’s what you should cover during a system design interview:

1. Clarifying Requirements

• Ask Clarifying Questions: Understand the key functionality and constraints of the system. It's essential to clarify requirements, such as:
  • Expected user base (how many users, read/write ratio).
  • Latency and performance expectations.
  • Consistency, availability, and partition tolerance requirements (CAP theorem).
  • Data storage needs (volume, structure).
• Example: For a system like Twitter, clarify the functionality around posting tweets, following users, and newsfeed generation.

2. High-Level Architecture

• System Components: Break down the system into key components like clients, servers, databases, and load balancers. Sketch out a high-level architecture showing how data flows between these components.
  • Client-server architecture
  • Load balancers for distributing traffic
  • API gateways to manage different services
  • Databases (SQL or NoSQL, depending on the use case)

3. Data Storage and Database Design

• Database Choices: Decide whether to use SQL (relational) or NoSQL (non-relational) databases based on the system’s requirements.

  • For structured data (e.g., a financial system), you might choose SQL (e.g., MySQL, PostgreSQL).
  • For large, unstructured data (e.g., social media posts, logs), NoSQL options like MongoDB or Cassandra might be better.

• Sharding and Partitioning: Discuss how you would scale your database using sharding (horizontal partitioning) or partitioning strategies to distribute data across multiple servers.

4. Caching and Optimization

• Caching Layers: Use caches (e.g., Redis, Memcached) to store frequently accessed data in memory, reducing load on the database and improving performance.
  • Example: In a newsfeed system, you can cache popular feeds to reduce database queries.

5. Load Balancing and Scalability

• Load Balancers: Discuss how you will distribute incoming traffic across multiple servers to handle high user demand. Tools like Nginx or AWS Elastic Load Balancer are common choices.
• Horizontal vs. Vertical Scaling:
  • Horizontal scaling: Adding more machines.
  • Vertical scaling: Increasing the power (CPU, memory) of a single machine.
• Auto-scaling: Implementing systems that can scale automatically based on demand (e.g., using cloud providers like AWS or Google Cloud).

6. Handling Failures and Fault Tolerance

• Redundancy: Design your system to handle failures gracefully. Discuss:
  • Replication: Replicating data across different servers or data centers to ensure that the system remains available even if some parts fail.
  • Backup Systems: Using backup databases or hot/cold standbys in case of failure.
  • Fault tolerance: Explain how your system can continue to operate under partial failures (e.g., using circuit breakers, retries, fallbacks).

7. Security and Privacy

• Data Security: Address security measures, such as:
  • Authentication and Authorization: Implement OAuth, JWT, or Role-Based Access Control (RBAC) for securing APIs.
  • Data Encryption: Encrypt data both in transit (using HTTPS) and at rest.
  • Rate Limiting: Prevent abuse by controlling the rate at which requests are processed.

8. APIs and Microservices

• API Design: Define how different components of the system interact via RESTful or GraphQL APIs. Explain the versioning strategy, error handling, and pagination for APIs.
• Microservices Architecture: Discuss the potential use of microservices for breaking the system into smaller, loosely-coupled services, allowing independent development and scaling.

9. Monitoring and Maintenance

• Monitoring Tools: Use tools like Prometheus or Grafana to track system health, performance metrics, and logs.
• Logging: Implement structured logging (e.g., with ELK Stack) to track errors and system behavior.

10. Trade-offs and Justifications

• Justify Your Design: Every design decision involves trade-offs, such as choosing between consistency and availability (CAP theorem), or between performance and cost.
  • Explain why you chose certain technologies or architectural patterns based on the system’s requirements and constraints.

Example Scenario: Designing a URL Shortener

• Clarify requirements: High availability, low latency, ability to handle millions of URLs.
• High-level architecture: A system with API gateways, load balancers, and database clusters.
• Data storage: Use a NoSQL database like Cassandra to store billions of records, and implement consistent hashing for sharding.
• Caching: Cache frequently accessed URLs with Redis.
• Security: Implement rate-limiting to prevent abuse.

Resources for System Design Interview Prep

To dive deeper into system design interview prep, you can use resources like Grokking the System Design Interview, which offers step-by-step explanations and examples of how to tackle common system design problems.