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Prometheus Client Php Laravel Package
promphp/prometheus_client_php
Prometheus client library for PHP with counters, gauges, histograms, and summaries. Supports Redis, Predis, APCu/APCng, or in-memory storage for metric aggregation across workers, with simple APIs to register, update, and expose metrics for scraping.
Prometheus instrumentation library for PHP applications
Frequently asked questions about Prometheus Client Php
- How do I integrate Prometheus metrics into a Laravel application with minimal setup?
- Use Composer to install the package (`composer require promphp/prometheus_client_php`), then bootstrap the `CollectorRegistry` in your `AppServiceProvider`. For HTTP metrics, add middleware to track request durations, and expose metrics via a `/metrics` endpoint. Laravel’s service container makes global access easy.
- Which Laravel versions and PHP versions are supported by this package?
- The package requires PHP 8.2+ and works with Laravel 9 or 10. Ensure your Laravel app aligns with these PHP requirements, as older versions (e.g., Laravel 8 with PHP 8.1) may cause compatibility issues.
- Can I use this package for Laravel queue workers or cron jobs?
- Yes, but you’ll need a shared storage adapter like Redis or APCu to aggregate metrics across worker processes. Redis is recommended for production due to its scalability and persistence, while APCu is simpler for single-server setups.
- How do I automatically track HTTP request metrics (e.g., response time, status codes) in Laravel?
- Create middleware that records start time, increments counters for status codes, and observes request durations with a histogram. Register the middleware in `app/Http/Kernel.php` to apply it globally. Example: `response_time_seconds->observe($duration, ['method' => $request->method()]).`
- What’s the best storage backend for production: Redis, APCu, or InMemory?
- Redis is the safest choice for production, especially in multi-server or high-cardinality environments. APCu is lightweight but risks memory bloat with many metrics. InMemory is only suitable for single-process scripts or testing.
- How do I expose metrics for Prometheus to scrape?
- Add a route like `Route::get('/metrics', [MetricsController::class, 'render'])` and use the `RenderTextFormat` class to output Prometheus exposition format. Ensure your Prometheus server targets this endpoint (e.g., `scrape_configs: [targets: ['laravel-app:8000/metrics']]`).
- Are there performance concerns with histograms or summaries in Laravel?
- Histograms and summaries have higher overhead than counters/gauges due to bucket calculations. Benchmark under load—if using Redis, ensure it’s configured with sufficient memory. For high-throughput apps, limit bucket granularity or use sampling.
- Can I use this package with Laravel’s queue jobs to track execution time?
- Yes, decorate your jobs with a trait or use job events to record start/end times. For example, observe a histogram with `job_execution_seconds->observe($duration, ['job' => $job->getJob()])`. Redis ensures metrics persist across worker restarts.
- What alternatives exist for Prometheus metrics in Laravel if Redis isn’t available?
- If Redis is unavailable, APCu is a lightweight alternative for single-server setups, but avoid it for high-cardinality metrics. For distributed systems, consider the `promphp/prometheus_push_gateway_php` companion library to push metrics to a central gateway.
- How do I test Prometheus metrics locally before deploying to production?
- Run a local Redis instance (e.g., via Docker) and configure the package to use it. Test by triggering HTTP requests, queue jobs, or CLI commands, then verify metrics appear in Prometheus (`prometheus -target=http://localhost/metrics`). Use tools like `curl` to check the `/metrics` endpoint.
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