1. The Bar for Senior Backend Engineering Rounds
Backend interviews focus on how your services behave under high stress: when 50,000 requests hit simultaneously, how do you prevent connection pool starvation, memory bloat, and cascading database deadlocks?
2. High-Frequency Backend Interview Scenarios
Q1: How do you prevent Database Connection Pool Starvation?
Solution:
- Connection Pool Sizing: Set connection pools using PostgreSQL's formula
pool_size = (core_count * 2) + effective_spindle_countrather than setting arbitrary numbers like 1,000 connections. - Connection Multiplexing: Deploy PgBouncer in transaction-pooling mode to multiplex thousands of microservice clients into a pool of 50-100 real database connections.
- Strict Query Timeouts: Enforce
statement_timeout = 2000msso rogue queries abort before consuming pooled connections.
Q2: Optimistic Locking vs Pessimistic Locking: When to use which?
- Optimistic Locking (Version Column): Use in low-contention environments (e.g. updating profile details). Check
WHERE id = 1 AND version = 3; if affected rows = 0, retry. Zero database lock overhead. - Pessimistic Locking (
SELECT ... FOR UPDATE): Use in high-contention financial or ticket reservation systems (e.g. debiting wallet balances). Holds exclusive row locks until transaction commit.
Q3: What is the N+1 Query Problem and how do you resolve it?
Answer: Occurs when an ORM fetches 1 parent record and then executes N subsequent queries for child relationships. Fix using batch loading (e.g. GraphQL DataLoader) or SQL JOIN / IN (...) preloading.
3. Practice Backend STAR Answers with Vaylo AI
Speak your technical design answers directly into Vaylo AI STAR Voice Coach and receive instant scoring on depth, clarity, and architectural vocabulary.