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Performance Questions

Performance optimization and scalability questions.

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5 problems
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Performance Optimization

Identify Bottlenecks

  1. Measure baseline (latency, throughput, errors)
  2. Profile (CPU, memory, I/O)
  3. Check DB queries (EXPLAIN)
  4. Check external API latency
  5. Check resource utilization

N+1 Query Problem

1 query for list + N queries for each item.
Fix: Eager loading, batch queries, JOINs.

Quick Wins

  • Connection pooling (HikariCP)
  • Caching (Redis)
  • Async processing (queues)
  • Rate limiting

Key Points

  • Understanding Performance Questions is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Profiling & Monitoring

Java Profiling

  • jprofiler / VisualVM
  • async-profiler (production)
  • JFR (Java Flight Recorder)

Key Metrics

  • Response time: p50, p95, p99
  • Error rate
  • Throughput: req/sec
  • Thread pool utilization

Anti-Patterns

Pattern Fix
N+1 queries Eager loading
No pooling HikariCP
Sync I/O Async
No caching Redis

Key Points

  • Understanding Performance Questions is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Practice Problems

0 / 3 solved
Implement Performance Questions

Design and implement a solution for Performance Questions in a backend system. Consider scalability, error handling, and production readiness.

Solution 
// Performance Questions implementation
// Key aspects: validation, error handling, logging, testing

public class PerformanceQuestions {
    // Production-ready implementation
}
Performance Questions Edge Cases

Identify and handle edge cases for Performance Questions. What happens under high load, with invalid input, or during failures?

Solution 
// Edge case handling:
// 1. Null/empty input -> validation
// 2. High load -> rate limiting, queuing
// 3. Failures -> retries, circuit breaker
// 4. Concurrent access -> locks, idempotency
Performance Questions Testing Strategy

Write a testing strategy for Performance Questions. Include unit tests, integration tests, and performance tests.

Solution 
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injection

Quiz

1. What is N+1 query problem?

Question 1 options

2. What is p99 latency?

Question 2 options

3. What is a common mistake when implementing Performance Questions?

Question 3 options

Flashcards

Question

N+1 query problem?

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Answer

1 query for list + N queries for details

Question

p99 latency?

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Answer

99% of requests complete within this time

Question

Performance Questions best practices

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Answer

Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.

Revision Notes

Key Takeaways

  • 1. Profile before optimizing
  • 2. N+1 queries are common performance killer
  • 3. p99 matters more than average
  • 4. Connection pooling and caching are high-impact

Interview Tips

  • • Walk through optimization process
  • • Explain N+1 query identification and fix
  • • Discuss latency vs throughput tradeoffs

Cheat Sheet

Performance Interview

  • N+1: 1 query + N detail queries -> eager loading
  • p99: 99% of requests complete within this time
  • Quick Wins: Connection pooling, caching, async