Parallel Laravel Package

Product Decisions This Supports

• Performance Optimization for Blocking Operations:

  • Enable parallel execution of CPU-intensive or I/O-bound tasks (e.g., batch processing, image manipulation, data transformations) without blocking the main event loop.
  • Justify investment in scaling infrastructure for high-throughput workloads (e.g., ETL pipelines, report generation).

• Roadmap for Event-Driven Architecture:

  • Align with broader adoption of Amp/PHP’s fiber-based concurrency model, reducing reliance on synchronous, blocking code.
  • Phase out legacy synchronous workers (e.g., exec(), shell_exec()) in favor of structured parallelism.

• Build vs. Buy Decision:

  • Buy: Avoid reinventing parallelism for PHP (no native threads/processes in core PHP). Leverage Amp’s battle-tested IPC and task isolation.
  • Build: Only if custom worker lifecycle (e.g., GPU offloading, specialized IPC) is required—this package abstracts 80% of use cases.

• Use Cases:

  • Batch Processing: Parallelize data validation, transformations, or API calls (e.g., scraping, webhooks).
  • Microservices: Offload heavy computations (e.g., PDF generation, video encoding) to worker pools without blocking HTTP handlers.
  • Real-Time Systems: Pair with amphp/http-client for concurrent API polling or WebSocket message processing.
  • Testing: Simulate distributed workloads or stress-test components in isolation.

When to Consider This Package

Adopt When:

• Your PHP app has blocking bottlenecks (e.g., file_get_contents(), exec(), or synchronous libraries like Guzzle).
• You need true parallelism (not just concurrency) for CPU-bound tasks (e.g., image processing, ML inference).
• You’re already using Amp/PHP fibers and want to extend it with parallel workers.
• You require task isolation (e.g., avoiding memory leaks or global state pollution in workers).
• Your team prefers structured concurrency over manual process management (e.g., pcntl_fork).

Look Elsewhere When:

• You need GPU acceleration or hardware-specific parallelism (consider rayon for Rust or CUDA bindings).
• Your tasks are trivially fast (parallelism overhead > benefit; e.g., microsecond operations).
• You’re locked into synchronous frameworks (e.g., Symfony’s Process component) with no fiber support.
• You require shared memory between workers (use ext-parallel or pcntl directly).
• Your use case fits Amp’s built-in tools (e.g., amphp/http-client for HTTP parallelism).

How to Pitch It (Stakeholders)

For Executives:

"This package lets us turn PHP’s blocking operations into parallel speedups—without rewriting our app in Go or Rust. For example:

• Batch jobs: Process 10x more records per hour by parallelizing data pipelines.
• User-facing features: Offload heavy computations (e.g., video thumbnails) to workers, keeping APIs responsive.
• Cost savings: Reduce cloud costs by using fewer, more efficient servers for CPU-bound tasks. It’s a drop-in upgrade for Amp users, with minimal dev overhead—think ‘Turbo for PHP.’"

For Engineers:

"amphp/parallel gives you:

• Worker pools: Submit tasks to a pool of processes/threads (configurable via ProcessContextFactory or ThreadContextFactory).
• Task isolation: Run blocking code (e.g., file_get_contents()) without crashing the event loop.
• IPC built-in: Bidirectional channels for parent-worker communication (e.g., streaming data, cancellation).
• Zero extensions: Works with vanilla PHP 8.1+ (threads require ext-parallel + ZTS). Use it for:
• Replacing exec() or shell_exec() with structured workers.
• Parallelizing ETL, API calls, or image processing.
• Testing distributed systems locally. Tradeoff: Serialization limits (no closures/resources), but Amp’s design mitigates this."**

For Architects:

"This complements Amp’s fiber model by adding:

1. Horizontal scaling: Distribute work across multiple processes/threads.
2. Fault tolerance: Workers crash independently; parent can retry or fallback.
3. Observability: Track task execution via Execution futures (e.g., timeouts, cancellation). Integration tips:

• Pair with amphp/http-client for parallel HTTP requests.
• Use AtomicCache for shared state in workers.
• Avoid global state in tasks (serialize/deserialize constraints). Alternatives: If you need shared memory, consider ext-parallel or pcntl, but this package abstracts 90% of use cases cleanly."**