💻Technical Questions
Q1What is the difference between REST and GraphQL?
💡REST: multiple endpoints, fixed response shape. GraphQL: single endpoint, client specifies fields, reduces over/under-fetching. Trade-offs in caching, versioning, complexity.
Q2Design a rate limiter for an API. What algorithm would you use?
💡Token bucket vs leaky bucket vs sliding window counter. Storage (in-memory vs Redis for distributed). Race conditions. Implementation complexity.
Q3How does database indexing work? When do indexes slow down writes?
💡B-tree structure, how reads use index, write amplification on insert/update/delete. Index selectivity. Covering indexes. Multi-column index column order.
Q4What is database sharding and when would you use it?
💡Horizontal partitioning by shard key. Problems: cross-shard queries, hot shards, rebalancing. Alternatives: read replicas, caching, vertical scaling.
Q5Explain ACID properties in databases.
💡Atomicity, Consistency, Isolation (levels: read uncommitted, committed, repeatable read, serializable), Durability. How distributed systems relax ACID (BASE).
Q6What is the difference between optimistic and pessimistic locking?
💡Optimistic: check-and-update, conflicts detected at commit. Pessimistic: lock before read. Trade-offs in concurrency, throughput, deadlock risk.
Q7How do message queues work and when would you use them?
💡Decoupling producers/consumers, async processing, retry logic. Kafka vs RabbitMQ vs SQS trade-offs. Dead letter queues, consumer groups, at-least-once delivery.
🧠Behavioral Questions
B1Tell me about the most challenging API you designed. What trade-offs did you make?
💡REST vs GraphQL, versioning strategy, authentication, rate limiting, error handling design. Show you've thought about the API consumer's experience.
B2Describe a production incident you were involved in. What was your role?
💡Walk through detection, triage, fix, communication, and post-mortem. What would you do differently? Show ownership.
🎯Situational Questions
S1Your API endpoint responds in 5+ seconds under normal load. How do you investigate and fix?
💡APM tools (New Relic, Datadog), database query profiling (EXPLAIN ANALYZE), N+1 query detection, caching opportunities, async processing, connection pool tuning.
S2You need to migrate a live database table with 100M rows without downtime. How do you approach it?
💡Dual-write pattern, shadow table, gradual cutover, feature flags, rollback strategy. Never lock the table — use online schema change tools.
Must-Know Topics
- ✓REST API Design
- ✓SQL & NoSQL Databases
- ✓Caching (Redis, Memcached)
- ✓Message Queues (Kafka, RabbitMQ)
- ✓Docker & Kubernetes
- ✓System Design (scalability, availability)
- ✓Authentication (JWT, OAuth)
- ✓Microservices Architecture
Common Interview Mistakes to Avoid
- ✗Not considering authentication/authorization in API design
- ✗Ignoring database query performance (N+1 problems)
- ✗Over-engineering with microservices for simple use cases
- ✗Not handling idempotency in payment or write APIs
- ✗Forgetting to design for failure (retries, timeouts, circuit breakers)
Frequently Asked Questions
What languages are most common in backend developer interviews?▼
Java (Spring Boot), Python (Django/FastAPI), and Node.js (Express) are the most common in India. Go is growing rapidly, especially at infrastructure-heavy companies. The interviewer typically lets you choose your language.
How deep is system design tested in backend interviews?▼
For senior roles (4+ years), system design is typically 1–2 rounds covering scalability, availability, and database design. For junior roles, expect high-level design questions. Focus on: designing URL shorteners, notification systems, rate limiters, and caches.
Do backend developers need to know frontend in interviews?▼
Not deeply, but familiarity helps for full-stack questions. Most backend interviews are backend-focused: APIs, databases, concurrency, system design. Some companies (early-stage startups) may expect full-stack flexibility.
Is microservices architecture tested in interviews?▼
Yes, at 3+ years of experience. Common questions: when to break a monolith, service discovery, distributed transactions (saga pattern), inter-service communication (gRPC vs REST), and observability in distributed systems.
What database concepts are most important for backend interviews?▼
Indexing (B-tree, how indexes work), ACID properties, isolation levels, query optimization (EXPLAIN), database normalization, and when to use NoSQL vs SQL. Knowing how one database (PostgreSQL or MySQL) in depth beats knowing many databases superficially.
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