Worker Pool
Manages a pool of goroutines to process tasks concurrently.
Understanding Worker Pool
The Worker Pool pattern manages a fixed set of goroutines (workers) that process tasks from a shared job channel. Instead of spawning unlimited goroutines — which can exhaust memory and overload resources — a worker pool bounds concurrency to N workers. In Go, this is implemented with a buffered jobs channel, a results channel, and N goroutines reading from the jobs channel. Each worker picks up a job, processes it, and sends the result back. This is one of Go\'s most important concurrency patterns, used for rate limiting, parallel processing, and resource management.
Key Concepts
- •Fixed worker count — a predetermined number of goroutines limits concurrency and prevents resource exhaustion
- •Jobs channel — a buffered channel feeds work items to workers — producers send, workers receive
- •Results channel — workers send completed results back through a separate channel for collection
- •Graceful shutdown — closing the jobs channel signals workers to finish current work and exit
When to Use
- • You need to process many tasks but want to limit concurrent goroutines
- • Resource constraints (DB connections, API rate limits) require bounded concurrency
- • You want predictable resource usage in production environments
- • Parallel processing of independent tasks with result collection
- • Each task is extremely fast and channel overhead dominates — a simple loop is better
- • You only have a few tasks — launching individual goroutines is simpler
- • Work items have complex dependencies and can\'t be processed independently
Structure
How It Works
Job Queue
Jobs are queued for processing.
Basic Implementation
Simple worker pool with job processing:
Real-World Example: URL Fetcher
Concurrent HTTP fetching with controlled parallelism: