Introduction

Laravel Queue Autoscale is a smart queue worker manager that automatically scales your queue workers based on workload, predicted demand, and service level objectives. Unlike traditional reactive solutions, it uses a hybrid predictive algorithm combining queueing theory (Little's Law), trend analysis, and backlog-based scaling to maintain your SLA targets.

What is Laravel Queue Autoscale?

Instead of manually managing worker counts or using simple threshold-based scaling, Laravel Queue Autoscale lets you define service level objectives (SLOs) and automatically maintains the optimal number of workers to meet those targets.

Traditional approach:

// Manual: "I want 10 workers"
supervisord config: numprocs=10

Laravel Queue Autoscale approach:

// SLA-based: "Jobs should start processing within 30 seconds"
'max_pickup_time_seconds' => 30

The package calculates and maintains the worker count needed to meet your SLA target automatically.

Key Features

🎯 SLA/SLO-Based Scaling

Define max pickup time instead of arbitrary worker counts. The autoscaler maintains enough workers to meet your service level targets.

📈 Predictive Algorithm

Proactive scaling using trend analysis and forecasting. Scale up before demand increases, not after jobs start piling up.

🔬 Queueing Theory Foundation

Built on Little's Law (L = λW) for mathematically sound steady-state calculations.

⚡ SLA Breach Prevention

Aggressive backlog drain algorithm activates when approaching SLA violations, preventing breaches before they occur.

🖥️ Resource-Aware

Respects CPU and memory limits from cboxdk/system-metrics package. Won't spawn more workers than your system can handle.

🔄 Metrics-Driven

Uses cboxdk/laravel-queue-metrics for automatic queue discovery and comprehensive metrics collection.

🎛️ Extensible

Custom scaling strategies and policies via clean interfaces. Implement your own business logic easily.

📊 Event Broadcasting

React to scaling decisions, SLA predictions, and worker changes through Laravel events.

🛡️ Graceful Shutdown

Proper worker termination with SIGTERM → SIGKILL sequence. Workers finish current jobs before terminating.

💎 Developer Experience

Clean API following Spatie package conventions. Easy to configure, understand, and extend.

How It Works

The autoscaler uses a three-phase hybrid algorithm:

1. Little's Law (Steady State)

Calculates baseline worker count for current workload:

Workers = Arrival_Rate × Average_Job_Time

2. Trend Prediction (Proactive)

Forecasts future demand and scales ahead:

Workers = Forecasted_Rate × Average_Job_Time

3. Backlog Drain (SLA Protection)

Aggressively scales when jobs approach SLA breach:

Workers = Backlog / (Time_Until_Breach / Avg_Job_Time)

The autoscaler takes the maximum of these three calculations to ensure SLA compliance.

Use Cases

High-Volume Applications

Applications processing thousands of jobs per minute with strict SLA requirements.

Variable Traffic Patterns

E-commerce sites with peak hours, marketing campaigns, or seasonal traffic.

Multi-Tenant Systems

SaaS platforms with varying workloads across different customers.

Cost Optimization

Minimize worker count during off-peak hours while meeting SLA targets.

Mission-Critical Queues

Systems requiring guaranteed processing times for critical operations.

Requirements

• PHP: 8.3 or 8.4
• Laravel: 11.0+
• Dependencies:
  • cboxdk/laravel-queue-metrics ^1.0.0
  • cboxdk/system-metrics ^1.2

Package Architecture

Laravel Queue Autoscale is designed as a metrics consumer rather than a metrics collector:

• laravel-queue-metrics: Discovers queues, scans connections, collects all metrics
• laravel-queue-autoscale: Consumes metrics, applies algorithms, manages workers

This separation of concerns keeps each package focused and maintainable.

Next Steps

Ready to get started? Follow the Installation guide to set up the package in your Laravel application.

Want to understand the scaling algorithm? See How It Works.

Looking for configuration options? Check the Configuration Guide.