Laravel Horizon Tuning & Production Scaling | Mohamed Said [ ![Mohamed Said](https://cdn.msaied.com/01KT78WE565VEMM3PSNQAAB0MH.png) Mohamed Said Laravel Backend Engineer ](https://msaied.com) [ Home ](https://msaied.com) [ Projects ](https://msaied.com/projects) [ Articles ](https://msaied.com/articles) [ Certificates ](https://msaied.com/certificates) [ Contact ](https://msaied.com#contact-section) [ ](https://github.com/EG-Mohamed) [ Home ](https://msaied.com) [ Projects ](https://msaied.com/projects) [ Articles ](https://msaied.com/articles) [ Certificates ](https://msaied.com/certificates) [ Contact ](https://msaied.com#contact-section) [ home ](https://msaied.com) [ articles ](https://msaied.com/articles) Laravel Horizon: Queue Metrics, Supervisor Tuning, and Graceful Scaling in Production On this page 1. [ Laravel Horizon in Production: Beyond the Pretty Dashboard ](#laravel-horizon-in-production-beyond-the-pretty-dashboard) 2. [ How Horizon Supervisors Actually Work ](#how-horizon-supervisors-actually-work) 3. [ Choosing the Right Balance Strategy ](#choosing-the-right-balance-strategy) 4. [ Reading Horizon Metrics Programmatically ](#reading-horizon-metrics-programmatically) 5. [ Graceful Termination and Long-Running Jobs ](#graceful-termination-and-long-running-jobs) 6. [ Memory Leaks and maxJobs ](#memory-leaks-and-codemaxjobscode) 7. [ Takeaways ](#takeaways) ![Laravel Horizon: Queue Metrics, Supervisor Tuning, and Graceful Scaling in Production](https://cdn.msaied.com/390/25668fca0fa0cd1acbd22f27230b8ef5.png) #laravel #horizon #queues #production #redis Laravel Horizon: Queue Metrics, Supervisor Tuning, and Graceful Scaling in Production ======================================================================================= 8 Jul 2026 3 min read ![Mohamed Said](https://cdn.msaied.com/01KT78WE565VEMM3PSNQAAB0MJ.jpg) Mohamed Said Table of contents 1. [ 01 Laravel Horizon in Production: Beyond the Pretty Dashboard ](#laravel-horizon-in-production-beyond-the-pretty-dashboard) 2. [ 02 How Horizon Supervisors Actually Work ](#how-horizon-supervisors-actually-work) 3. [ 03 Choosing the Right Balance Strategy ](#choosing-the-right-balance-strategy) 4. [ 04 Reading Horizon Metrics Programmatically ](#reading-horizon-metrics-programmatically) 5. [ 05 Graceful Termination and Long-Running Jobs ](#graceful-termination-and-long-running-jobs) 6. [ 06 Memory Leaks and maxJobs ](#memory-leaks-and-codemaxjobscode) 7. [ 07 Takeaways ](#takeaways) Laravel Horizon in Production: Beyond the Pretty Dashboard ---------------------------------------------------------- Horizon ships with a slick UI, but most teams stop there. The real value is in its supervisor model, metric snapshots, and the knobs that determine whether your queue survives a traffic spike or silently drops work. ### How Horizon Supervisors Actually Work Horizon manages one or more *supervisor* processes, each of which spawns a pool of `queue:work` child processes. The key insight: **supervisors are not queues**. A single supervisor can watch multiple queues with a priority order. ```php // config/horizon.php 'environments' => [ 'production' => [ 'supervisor-default' => [ 'connection' => 'redis', 'queue' => ['critical', 'default', 'low'], 'balance' => 'auto', 'autoScalingStrategy' => 'time', 'maxProcesses' => 20, 'minProcesses' => 2, 'maxTime' => 0, 'maxJobs' => 500, 'memory' => 256, 'tries' => 3, 'timeout' => 90, 'nice' => 0, ], ], ], ``` `balance => 'auto'` tells Horizon to redistribute workers across queues based on wait time. `autoScalingStrategy => 'time'` scales toward minimising wait time rather than raw queue size — better for latency-sensitive work. ### Choosing the Right Balance Strategy | Strategy | Scales on | Best for | |---|---|---| | `simple` | Queue size ratio | Predictable, uniform jobs | | `auto` | Wait time | Mixed job durations | | `false` | Fixed processes | Isolated, critical queues | For a SaaS with a `critical` queue (password resets, webhooks) and a `low` queue (report generation), use **two supervisors** with `balance => false` on critical and `auto` on low: ```php 'supervisor-critical' => [ 'queue' => ['critical'], 'balance' => false, 'minProcesses' => 3, 'maxProcesses' => 3, ], 'supervisor-bulk' => [ 'queue' => ['default', 'low'], 'balance' => 'auto', 'minProcesses' => 1, 'maxProcesses' => 15, 'autoScalingStrategy' => 'time', ], ``` This guarantees critical work always has dedicated workers, while bulk work scales elastically. ### Reading Horizon Metrics Programmatically Horizon stores throughput and runtime snapshots in Redis. You can query them directly: ```php use Laravel\Horizon\Contracts\MetricsRepository; $metrics = app(MetricsRepository::class); $throughput = $metrics->throughputForQueue('default'); // jobs/min $runtime = $metrics->runtimeForQueue('default'); // ms average ``` Pipe these into your observability stack (Datadog, Prometheus via a custom exporter) rather than relying solely on the Horizon UI. Alert when `throughputForQueue` drops to zero during business hours — that's a dead worker, not an empty queue. ### Graceful Termination and Long-Running Jobs Horizon sends `SIGTERM` to workers during deploys. Workers finish their current job, then exit. The danger: a job that runs for 180 seconds will block the deploy for 180 seconds per worker. Mitigate with `maxTime` (seconds a worker runs before self-terminating after its current job) and by designing long jobs to be interruptible: ```php public function handle(): void { foreach ($this->chunks() as $chunk) { if ($this->job->isDeleted() || $this->job->isReleased()) { return; } $this->processChunk($chunk); // Respect the terminate signal between chunks if (app('queue.worker')->shouldQuit) { $this->release(5); return; } } } ``` Accessing `app('queue.worker')->shouldQuit` lets a job voluntarily release itself back to the queue when a shutdown is pending, preventing message loss. ### Memory Leaks and `maxJobs` PHP workers accumulate memory over time — Eloquent model event listeners, static caches, and package bootstrapping all contribute. `maxJobs => 500` forces a worker restart after 500 jobs, which is a pragmatic ceiling. Pair it with `memory => 256` (MB) as a hard cap: ```php 'maxJobs' => 500, 'memory' => 256, ``` Monitor actual worker memory with `horizon:snapshot` on a schedule: ```php // app/Console/Kernel.php $schedule->command('horizon:snapshot')->everyFiveMinutes(); ``` Without snapshots, the Horizon metrics graphs are empty. ### Takeaways - Use **two supervisors** to isolate critical queues from bulk work; never mix them with `auto` balance. - Set `autoScalingStrategy => 'time'` for latency-sensitive queues; `size` can over-provision on bursty workloads. - Export Horizon metrics to your APM — don't rely on the UI for alerting. - Design long jobs to check `shouldQuit` between chunks so deploys don't stall. - Schedule `horizon:snapshot` every five minutes or your throughput graphs will be blank. Found this useful? [ ](https://twitter.com/intent/tweet?url=https%3A%2F%2Fmsaied.com%2Farticles%2Flaravel-horizon-queue-metrics-supervisor-tuning-and-graceful-scaling-in-production&text=Laravel+Horizon%3A+Queue+Metrics%2C+Supervisor+Tuning%2C+and+Graceful+Scaling+in+Production) [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fmsaied.com%2Farticles%2Flaravel-horizon-queue-metrics-supervisor-tuning-and-graceful-scaling-in-production) Frequently Asked Questions ---------------------------- 3 questions Q01 What is the difference between `balance => 'auto'` and `balance => 'simple'` in Horizon? `simple` distributes workers proportionally to queue size. `auto` targets wait time, so it shifts workers toward queues where jobs are waiting longest regardless of raw count — better when jobs have variable durations. Q02 How do I prevent a long-running job from blocking a Horizon deploy? Check `app('queue.worker')->shouldQuit` between processing units inside your job. When it is true, call `$this->release()` to put the job back on the queue and return early, allowing the worker to exit cleanly. Q03 Why are my Horizon throughput graphs empty? Horizon only records metric snapshots when `horizon:snapshot` runs. Schedule it every five minutes in your console kernel; without it, the metrics repository has no data to display. 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