9 Backend Questions Every Big Tech Companies Asks

1. How do you ensure the scalability of a backend system?

• Explanation: Discuss approaches such as horizontal and vertical scaling, load balancing, and the use of microservices. Explain the importance of stateless services, distributed data stores, and caching mechanisms.

2. What are the main differences between SQL and NoSQL databases?

• Explanation: SQL databases (e.g., MySQL, PostgreSQL) are relational, support ACID transactions, and use structured query language. NoSQL databases (e.g., MongoDB, Cassandra) are non-relational, designed for flexible schemas, and often provide eventual consistency. Use cases for each type based on the nature of the application and data requirements.

3. What is REST, and how does it differ from GraphQL?

• Explanation: REST (Representational State Transfer) is an architectural style for designing networked applications, using standard HTTP methods and URLs. GraphQL is a query language for APIs that allows clients to request specific data and aggregate responses from multiple sources. Discuss the advantages and trade-offs of each, such as REST's simplicity and GraphQL's flexibility.

4. How do you manage and store user authentication tokens securely?

• Explanation: Discuss the use of JWT (JSON Web Tokens) and secure storage practices like Http Only cookies or secure local storage. Explain the importance of using HTTPS, token expiration, and refreshing mechanisms. Mention techniques for handling token revocation and invalidation.

5. What are the key principles of designing a resilient and fault-tolerant system?

• Explanation: Cover concepts like redundancy, failover strategies, circuit breakers, and graceful degradation. Explain the use of monitoring, alerting, and automated recovery mechanisms to detect and respond to failures.

6. Can you explain the concept of eventual consistency in distributed systems?

• Explanation: Eventual consistency is a consistency model where updates to a distributed system will propagate to all nodes, but not immediately. Discuss scenarios where eventual consistency is acceptable, such as in large-scale distributed databases. Mention trade-offs between immediate consistency and availability.

7. What are some common caching strategies you use to improve performance?

• Explanation: Discuss different caching strategies like in-memory caching (e.g., Redis, Memcached), database query caching, and CDN (Content Delivery Network) caching. Explain cache invalidation strategies, cache eviction policies, and the importance of balancing cache size with data freshness.

8. How do you approach database indexing to optimize query performance?

• Explanation: Describe how indexes work and their impact on read and write operations. Discuss different types of indexes (e.g., B-tree, hash, full-text) and when to use them. Explain the importance of analyzing query patterns and avoiding over-indexing.

9. What is CI/CD, and how does it benefit the development and deployment process?

• Explanation: CI (Continuous Integration) involves automatically building and testing code changes as they are committed.CD (Continuous Deployment/Delivery) involves automatically deploying code changes to staging or production environments. Discuss the benefits of CI/CD, such as faster release cycles, early detection of issues, and improved collaboration.

These questions cover a range of foundational knowledge and practical skills essential for backend engineering. A good backend engineer should be comfortable discussing these topics and demonstrating a deep understanding of each.