BACKEND
APIs & DATABASES

Backend Developer Interview Questions: APIs, Databases & System Design

Master backend interviews with API design, database optimization, microservices, cloud architecture, and system scalability questions. Practice for Google, Amazon, Microsoft, and other top tech companies.

Backend Developer Interview Questions

1. How do you design a RESTful API?
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Expert Answer: RESTful API design follows REST principles: use HTTP methods correctly (GET, POST, PUT, DELETE), design resource-based URLs, return appropriate status codes, implement proper error handling, use JSON for data exchange, and ensure stateless communication.

Example: Design user management endpoints:

GET /api/users - List all users
GET /api/users/123 - Get specific user
POST /api/users - Create new user
PUT /api/users/123 - Update user
DELETE /api/users/123 - Delete user

Always use nouns for resources, not verbs. Implement proper status codes (200 for success, 404 for not found, 400 for bad request, 500 for server errors).
2. What is database indexing and when should you use it?
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Expert Answer: Database indexing creates a data structure that improves query performance by providing fast access paths to rows. Use indexes on columns frequently used in WHERE clauses, ORDER BY, and JOIN operations.

Example: "I implemented indexes on our e-commerce platform where product searches were slow. By adding composite indexes on (category, price) and full-text indexes on product descriptions, we reduced query time from 2 seconds to 50ms, improving user experience significantly. However, I balance this with write performance - too many indexes can slow down INSERT/UPDATE operations."
3. How do microservices differ from monolithic architecture?
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Expert Answer: Monolithic architecture is a single deployable unit with shared database and codebase, while microservices are independently deployable services with service-specific databases. Microservices offer better scalability and fault isolation but add complexity in communication and deployment.

Example: "I led the migration of our e-commerce platform from monolith to microservices. We split into User Service, Product Service, Order Service, and Payment Service. This allowed us to scale each service independently - we could scale the Product Service during sales events without affecting user authentication. However, we had to implement proper service discovery, API gateways, and distributed tracing to manage the increased complexity."
4. How do you handle database transactions and ACID properties?
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Expert Answer: ACID properties ensure database reliability: Atomicity (all operations succeed or fail together), Consistency (database remains valid), Isolation (concurrent transactions don't interfere), Durability (committed changes persist). Use transactions for operations that must complete as a unit.

Example: "In our banking system, money transfers required strict ACID compliance. I implemented database transactions using BEGIN/COMMIT/ROLLBACK to ensure that debiting one account and crediting another happened atomically. If any step failed, the entire transaction rolled back, preventing data inconsistency. I also implemented proper isolation levels to prevent race conditions during concurrent transfers."
5. How do you implement caching strategies?
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Expert Answer: Implement multiple caching layers: browser cache, CDN, application-level cache (Redis/Memcached), and database query cache. Choose appropriate cache patterns like cache-aside, write-through, or write-behind based on your use case.

Example: "I implemented Redis caching for our API responses. For frequently accessed user profiles, I used cache-aside pattern with 1-hour TTL. For product catalogs, I used write-through caching to ensure consistency. This reduced database load by 70% and improved response times from 500ms to 50ms. I also implemented cache warming for critical data during off-peak hours."
6. How do you design for scalability and high availability?
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Expert Answer: Design with horizontal scaling, load balancing, database replication, and fault tolerance. Implement circuit breakers, health checks, and graceful degradation. Use auto-scaling based on metrics like CPU, memory, and request rate.

Example: "I architected a system handling 1M+ daily users. Used load balancers to distribute traffic across multiple application instances, implemented master-slave database replication for read scaling, and deployed across multiple AWS availability zones. Added circuit breakers to prevent cascade failures and auto-scaling to handle traffic spikes. This achieved 99.9% uptime and seamlessly handled 5x traffic during product launches."
7. How do you implement authentication and authorization?
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Expert Answer: Implement JWT or OAuth for stateless authentication, use bcrypt for password hashing, implement role-based access control (RBAC), and secure API endpoints with proper middleware. Always use HTTPS and implement proper session management.

Example: "I implemented JWT-based authentication with refresh token rotation. Used bcrypt with salt rounds for password hashing, implemented role-based permissions (admin, editor, viewer), and created middleware to protect API routes. Added rate limiting to prevent brute force attacks and implemented OAuth integration for social login. This secured our API while maintaining good user experience with automatic token refresh."
8. How do you implement message queues and async processing?
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Expert Answer: Use message queues (Redis, RabbitMQ, AWS SQS) for decoupling services and handling async tasks. Implement proper error handling, dead letter queues, and monitoring. Design for idempotency and handle message ordering when required.

Example: "I implemented Redis Bull queues for email processing and image resizing. When users uploaded photos, the API immediately returned success while queuing the resize job. This improved user experience from 5-second waits to instant responses. Added job priorities, retry logic with exponential backoff, and dead letter queues for failed jobs. Also implemented job monitoring dashboard to track queue health and processing times."