resource-management

Go Concurrency Patterns Series: ← Rate Limiter | Series Overview | Actor Model → What is the Semaphore Pattern? A semaphore is a synchronization primitive that maintains a count of available resources and controls access to them. It allows a specified number of goroutines to access a resource concurrently while blocking others until resources become available. Types: Binary Semaphore: Acts like a mutex (0 or 1) Counting Semaphore: Allows N concurrent accesses Weighted Semaphore: Resources have different weights/costs Real-World Use Cases Connection Pools: Limit database/HTTP connections Resource Management: Control access to limited resources Download Managers: Limit concurrent downloads API Rate Limiting: Control concurrent API calls Worker Pools: Limit concurrent workers Memory Management: Control memory-intensive operations Basic Semaphore Implementation package main import ( "context" "fmt" "sync" "time" ) // Semaphore implements a counting semaphore type Semaphore struct { ch chan struct{} } // NewSemaphore creates a new semaphore with given capacity func NewSemaphore(capacity int) *Semaphore { return &Semaphore{ ch: make(chan struct{}, capacity), } } // Acquire acquires a resource from the semaphore func (s *Semaphore) Acquire() { s....

Go Concurrency Patterns Series: ← Request/Response | Series Overview | Mutex Patterns → What is the Worker Pool Pattern? The Worker Pool pattern manages a fixed number of worker goroutines that process jobs from a shared queue. This pattern is essential for controlling resource usage, preventing system overload, and ensuring predictable performance under varying loads. Key Components: Job Queue: Channel containing work to be processed Worker Pool: Fixed number of worker goroutines Result Channel: Optional channel for collecting results Dispatcher: Coordinates job distribution to workers Real-World Use Cases Image Processing: Resize/compress images with limited CPU cores Database Operations: Limit concurrent database connections API Rate Limiting: Control outbound API call rates File Processing: Process files with bounded I/O operations Web Scraping: Limit concurrent HTTP requests Background Jobs: Process queued tasks with resource limits Basic Worker Pool Implementation package main import ( "fmt" "math/rand" "sync" "time" ) // Job represents work to be processed type Job struct { ID int Data interface{} } // Result represents the outcome of processing a job type Result struct { JobID int Output interface{} Error error } // WorkerPool manages a pool of workers type WorkerPool struct { workerCount int jobQueue chan Job resultQueue chan Result quit chan bool wg sync....