Concurrency

Concurrency means handling multiple tasks at once. In backend development, it means processing multiple requests simultaneously.

Concurrency vs Parallelism

Concurrency (one core, switching):
Time --> [Task A][Task B][Task A][Task B][Task A]

Parallelism (multiple cores, simultaneously):
Core 1: [Task A][Task A][Task A]
Core 2: [Task B][Task B][Task B]

• Concurrency: Dealing with multiple things at once (structure)
• Parallelism: Doing multiple things at once (execution)

Concurrency in Backend

Request 1 --> Thread 1 --> Process --> Response
Request 2 --> Thread 2 --> Process --> Response  (simultaneously)
Request 3 --> Thread 3 --> Process --> Response

Challenges of Concurrency

1. Race Conditions — Two threads modifying shared data
2. Deadlocks — Threads waiting for each other forever
3. Thread Safety — Ensuring correct behavior with shared state
4. Resource Contention — Multiple threads competing for resources

Thread Safety Example

// NOT thread-safe
class Counter {
    private int count = 0;
    public void increment() {
        count++; // read-modify-write (race condition!)
    }
}

// Thread-safe
class Counter {
    private AtomicInteger count = new AtomicInteger(0);
    public void increment() {
        count.incrementAndGet(); // atomic operation
    }
}

Why Concurrency Matters

Modern servers handle thousands of concurrent requests:

• Each request processed by a different thread
• Shared resources (database connections, caches) need protection
• Correct synchronization prevents data corruption

Key Principles

1. Follow SOLID principles
2. Write clean, readable code
3. Test thoroughly
4. Document decisions
5. Monitor in production

Implementation

• Start simple, refactor as needed
• Use established patterns
• Consider trade-offs
• Review with peers

Continuous Improvement

• Learn from incidents
• Update documentation
• Share knowledge
• Mentor others

Key Points

• Understanding Concurrency 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