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Worker Pool Patterns

performance PHP 5.0+ Advanced

Also Known As

worker pool process pool parallel workers

TL;DR

Fixed pool of pre-spawned workers for parallel tasks — avoiding per-task process spawn overhead.

Explanation

A worker pool maintains N pre-spawned workers ready to accept tasks. Benefits: no per-task spawn overhead (50ms each), bounded resource usage, backpressure. PHP implementations: amphp/parallel for process pools, Laravel Horizon for queue workers.

Common Misconception

Spawning a new process per task is equivalent to a pool — process spawning costs 10-100ms; pre-spawned workers handle tasks in <1ms overhead.

Why It Matters

1000 images with per-process spawn wastes 50+ seconds in overhead — a pre-spawned pool of 8 workers processes all in parallel efficiently.

Common Mistakes

  • Pool larger than CPU cores for CPU-bound work
  • No backpressure
  • Not restarting crashed workers
  • Shared mutable state between workers

Code Examples

✗ Vulnerable
foreach ($images as $img) { $p = new Process(['php','resize.php',$img]); $p->start(); }
✓ Fixed
$pool = new DefaultPool(8);
$promises = array_map(fn($img) => $pool->enqueue(new CallableTask('resize',[$img])), $images);
await Promise\all($promises);

Added 16 Mar 2026
Edited 22 Mar 2026
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Amazonbot 7 Perplexity 2 Unknown AI 1 Google 1 Ahrefs 1
crawler 12
DEV INTEL Tools & Severity
🟠 High ⚙ Fix effort: Medium
⚡ Quick Fix
Size your PHP-FPM worker pool: pm.max_children = available_RAM / average_worker_memory; use pm = dynamic for variable traffic and pm = static for steady high-throughput loads
📦 Applies To
PHP 5.0+ web cli
🔗 Prerequisites
🔍 Detection Hints
pm.max_children default or guessed value; OOM kills due to too many workers; pm=ondemand causing cold start latency on burst traffic
Auto-detectable: ✓ Yes php-fpm-status datadog prometheus
⚠ Related Problems
🤖 AI Agent
Confidence: Medium False Positives: Medium ✗ Manual fix Fix: High Context: File Tests: Update

✓ schema.org compliant