Resources And Memory Management

Resource and Memory Management Principles

Universal Resource Management Rules

1. Always Clean Up Resources

Resources requiring cleanup:

• Files, network connections, database connections
• Locks, semaphores, mutexes
• Memory allocations (in manual-memory languages)
• OS handles, GPU resources

Clean up in ALL paths:

• Success path: Normal completion
• Error path: Exception thrown, error returned
• Early return path: Guard clauses, validation failures

Use language-appropriate patterns:

• Go: defer statements
• Rust: Drop trait (RAII)
• Python: context managers (with statement)
• TypeScript: try/finally
• Java: try-with-resources

2. Timeout All I/O Operations

Why timeout:

• Network requests can hang indefinitely
• Prevents resource exhaustion (connections, threads)
• Provides predictable failure behavior

Timeout recommendations:

• Network requests: 30s default, shorter (5-10s) for interactive
• Database queries: 10s default, configure per query complexity
• File operations: Usually fast, but timeout on network filesystems
• Message queue operations: Configurable, avoid indefinite blocking

3. Pool Expensive Resources

Resources to pool:

• Database connections: Pool size 5-20 per app instance
• HTTP connections: Reuse with keep-alive
• Thread pools: Size based on CPU count (CPU-bound) or I/O wait (I/O-bound)

Benefits:

• Reduces latency (no connection setup overhead)
• Limits resource consumption (cap on max connections)
• Improves throughput (reuse vs create new)

Connection Pool Best Practices:

• Minimum connections: 5 (ensures pool is warm)
• Maximum connections: 20-50 (prevents overwhelming database)
• Idle timeout: Close connections idle >5-10 minutes
• Validation: Test connections before use (avoid broken connections)
• Monitoring: Track utilization, wait times, timeout rates

4. Avoid Resource Leaks

What is a leak:

• Acquire resource (open file, allocate memory, get connection)
• Never release it (forget to close, exception prevents cleanup)
• Eventually exhaust system resources (OOM, max connections, file descriptors)

Detection:

• Monitor open file descriptors, connection counts, memory usage over time
• Run long-duration tests, verify resource counts stay stable
• Use leak detection tools (valgrind, ASan, heap profilers)

Prevention:

• Use language patterns that guarantee cleanup (RAII, defer, context managers)
• Never rely on manual cleanup alone (use language features)

5. Handle Backpressure

Problem: Producer faster than consumer

• Queue grows unbounded → memory exhaustion
• System becomes unresponsive under load

Solutions:

• Bounded queues: Fixed size, block or reject when full
• Rate limiting: Limit incoming request rate
• Flow control: Consumer signals producer to slow down
• Circuit breakers: Stop accepting requests when overwhelmed
• Drop/reject: Fail fast when overloaded (better than crashing)

Memory Management by Language Type

Garbage Collected (Go, Java, Python, JavaScript, C#):

• Memory automatically freed by GC
• Still must release non-memory resources (files, connections, locks)
• Be aware of GC pauses in latency-sensitive applications
• Profile memory usage to find leaks (retained references preventing GC)

Manual Memory Management (C, C++):

• Explicit malloc/free or new/delete
• Use RAII pattern in C++ (Resource Acquisition Is Initialization)
• Avoid manual management in modern C++ (use smart pointers: unique_ptr, shared_ptr)

Ownership-Based (Rust):

• Compiler enforces memory safety at compile time
• No GC pauses, no manual management
• Ownership rules prevent leaks and use-after-free automatically
• Use reference counting (Arc, Rc) for shared ownership

Related Principles

• Concurrency and Threading Mandate @.claude/rules/concurrency-and-threading-mandate.md
• Concurrency and Threading Principles @.claude/skills/concurrency-and-threading-principles/SKILL.md
• Error Handling Principles @.claude/rules/error-handling-principles.md - Resource cleanup in error paths