Background Jobs Commands

Background job processing commands for managing JoobQ workers and queues.

Overview

The Azu CLI provides comprehensive commands for managing background jobs using the JoobQ framework. These commands handle worker processes, monitor queue status, retry failed jobs, and provide a web interface for job management.

Prerequisites

Before using job commands, ensure:

1. JoobQ is installed in your project:

   azu generate joobq

2. Redis is running:

   redis-server

3. Redis URL is configured:

   export REDIS_URL="redis://localhost:6379"

Commands

azu jobs:worker

Start background job worker processes to execute queued jobs.

Synopsis

azu jobs:worker [options]

Description

Starts one or more worker processes that poll the job queue and execute background jobs. Workers run continuously until stopped with Ctrl+C.

Options

Option	Short	Description	Default
--workers <n>	-w	Number of worker processes	1
--queues <list>	-q	Comma-separated queue names	default
--daemon	-d	Run as daemon process	false
--verbose	-v	Verbose output	false

Examples

# Start single worker
azu jobs:worker

# Start multiple workers
azu jobs:worker --workers 4

# Process specific queues
azu jobs:worker --queues critical,default,low

# Start workers with all options
azu jobs:worker --workers 4 --queues critical,default --verbose

# Run as daemon
azu jobs:worker --daemon

Environment Variables

Variable	Description	Default
REDIS_URL	Redis connection URL	redis://localhost:6379
JOOBQ_REDIS_URL	JoobQ-specific Redis URL	Falls back to REDIS_URL
JOOBQ_QUEUE	Default queue name	default
JOOBQ_WORKERS	Number of workers	1

Worker Requirements

The workers expect a src/worker.cr file in your project:

require "./app"
require "joobq"

# Configure JoobQ
JoobQ.configure do |config|
  config.redis_url = ENV["REDIS_URL"]
  config.queues = ENV["JOOBQ_QUEUES"]?.try(&.split(",")) || ["default"]
end

# Start processing jobs
JoobQ.start

---

azu jobs:status

Display current status and statistics for all job queues.

Synopsis

azu jobs:status

Description

Connects to Redis and displays real-time statistics for all JoobQ queues, including pending, processing, and failed job counts.

Output Format

Job Queue Status
================================================================================
Redis: redis://localhost:6379
Queue: default

Queue                |    Pending |   Processing |     Failed
================================================================================
critical             |          5 |            2 |          0
default              |         23 |            4 |          1
low                  |         12 |            1 |          0
mailers              |          8 |            0 |          0
================================================================================
Total                |         48 |            7 |          1

Examples

# Show status for all queues
azu jobs:status

# Show status with custom Redis URL
REDIS_URL="redis://localhost:6380" azu jobs:status

Queue States

• Pending: Jobs waiting to be processed

• Processing: Jobs currently being executed by workers

• Failed: Jobs that encountered errors during execution

---

azu jobs:clear

Clear jobs from queues.

Synopsis

azu jobs:clear [options]

Description

Remove jobs from specified queues. Use with caution as this operation is irreversible.

Options

Option	Short	Description
--queue <name>	-q	Specific queue to clear (default: default)
--all		Clear all queues
--failed		Clear only failed jobs
--force	-f	Skip confirmation prompt

Examples

# Clear default queue (with confirmation)
azu jobs:clear

# Clear specific queue
azu jobs:clear --queue mailers

# Clear failed jobs only
azu jobs:clear --failed

# Clear all queues without confirmation
azu jobs:clear --all --force

# Clear failed jobs in specific queue
azu jobs:clear --queue default --failed

Confirmation Prompt

Unless --force is specified, you'll be prompted to confirm:

⚠️  This will permanently delete jobs from the queue.
Are you sure? (y/N):

---

azu jobs:retry

Retry failed jobs.

Synopsis

azu jobs:retry [options]

Description

Re-queue failed jobs for another execution attempt. Useful for recovering from temporary failures like network issues or external service downtime.

Options

Option	Short	Description
--queue <name>	-q	Specific queue (default: default)
--all		Retry all failed jobs
--limit <n>	-l	Maximum number of jobs to retry

Examples

# Retry all failed jobs in default queue
azu jobs:retry

# Retry all failed jobs across all queues
azu jobs:retry --all

# Retry limited number of failed jobs
azu jobs:retry --limit 10

# Retry failed jobs in specific queue
azu jobs:retry --queue critical --all

Retry Behavior

• Jobs are moved from failed queue to pending queue

• Original job parameters and metadata are preserved

• Retry count is incremented

• Jobs exceeding max retries are not re-queued

---

azu jobs:ui

Launch the JoobQUI web interface for visual job management.

Synopsis

azu jobs:ui [options]

Description

Starts a web server providing a graphical interface to monitor and manage background jobs. The UI displays real-time statistics, job details, and allows manual job management.

Options

Option	Short	Description	Default
--port <port>	-p	UI server port	4000
--host <host>	-h	UI server host	localhost
--verbose	-v	Verbose output	false

Examples

# Start UI on default port
azu jobs:ui

# Start on custom port
azu jobs:ui --port 5000

# Make accessible from network
azu jobs:ui --host 0.0.0.0 --port 8080

# Start with verbose logging
azu jobs:ui --verbose

Web Interface Features

The JoobQUI provides:

• Dashboard: Overview of all queues and statistics

• Job List: Browse pending, processing, and failed jobs

• Job Details: View job parameters, status, and error messages

• Retry Controls: Manually retry individual failed jobs

• Queue Management: Pause, resume, or clear queues

• Real-time Updates: Live statistics and job status

Accessing the UI

Once started, open your browser to:

http://localhost:4000

Or with custom host/port:

http://your-host:your-port

---

Common Workflows

Development Setup

# Terminal 1: Start application server
azu serve

# Terminal 2: Start job workers
azu jobs:worker --verbose

# Terminal 3: Monitor job status
watch -n 1 azu jobs:status

Production Deployment

# Start multiple workers for high throughput
azu jobs:worker --workers 8 --queues critical,default,low

# Or use process manager like systemd
# /etc/systemd/system/myapp-workers.service

Queue Monitoring

# Check queue status
azu jobs:status

# Launch web UI for detailed monitoring
azu jobs:ui --port 5000

Handling Failed Jobs

# Check for failed jobs
azu jobs:status

# Review failures in web UI
azu jobs:ui

# Retry all failed jobs
azu jobs:retry --all

# Or retry limited batch
azu jobs:retry --limit 10

Queue Maintenance

# Clear old failed jobs
azu jobs:clear --failed --force

# Clear test queue
azu jobs:clear --queue test

# Clear all queues (caution!)
azu jobs:clear --all --force

Best Practices

1. Use Multiple Queues

Prioritize jobs by using separate queues:

# High priority workers
azu jobs:worker --queues critical --workers 4

# General purpose workers
azu jobs:worker --queues default --workers 8

# Low priority workers
azu jobs:worker --queues low --workers 2

2. Monitor Queue Health

Regularly check queue status:

# Add to cron or monitoring system
*/5 * * * * azu jobs:status | mail -s "Job Status" [e-mail]

3. Set Up Alerting

Monitor for stuck or growing queues:

# Script to check queue depth
#!/bin/bash
pending=$(azu jobs:status | grep default | awk '{print $2}')
if [ "$pending" -gt 1000 ]; then
  echo "WARNING: Queue depth is $pending"
fi

4. Handle Failed Jobs Promptly

Review and retry or clear failed jobs regularly:

# Daily cleanup of old failures
0 2 * * * azu jobs:clear --failed

5. Scale Workers Based on Load

Adjust worker count based on queue depth:

# Light load
azu jobs:worker --workers 2

# Heavy load
azu jobs:worker --workers 16

Process Management

Using Systemd (Linux)

Create /etc/systemd/system/myapp-workers.service:

[Unit]
Description=MyApp Background Workers
After=network.target redis.service

[Service]
Type=simple
User=myapp
WorkingDirectory=/var/www/myapp
Environment=REDIS_URL=redis://localhost:6379
Environment=JOOBQ_WORKERS=4
ExecStart=/usr/local/bin/azu jobs:worker --workers 4
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target

Enable and start:

sudo systemctl enable myapp-workers
sudo systemctl start myapp-workers
sudo systemctl status myapp-workers

Using Docker

# Worker container
FROM crystallang/crystal:latest

WORKDIR /app
COPY . .
RUN shards install
RUN shards build

CMD ["azu", "jobs:worker", "--workers", "4"]

Docker Compose:

version: '3'
services:
  worker:
    build: .
    command: azu jobs:worker --workers 4 --queues critical,default
    environment:
      REDIS_URL: redis://redis:6379
    depends_on:
      - redis

Using Foreman

Create Procfile:

web: azu serve
worker: azu jobs:worker --workers 4

Start all services:

foreman start

Troubleshooting

Workers Not Processing Jobs

Check worker is running:

ps aux | grep "jobs:worker"

Verify Redis connection:

redis-cli ping
# Should return: PONG

Check queue status:

azu jobs:status

Redis Connection Errors

Verify Redis URL:

echo $REDIS_URL
# Should be: redis://localhost:6379

Test connection:

redis-cli -u $REDIS_URL ping

Jobs Stuck in Processing

Failed workers may leave jobs in processing state. Clear and retry:

# Restart workers
pkill -f jobs:worker
azu jobs:worker --workers 4 &

# Clear stuck jobs (if needed)
azu jobs:clear --force

High Memory Usage

Reduce worker count:

azu jobs:worker --workers 2

Or implement job batching in your application.

Environment Variables

All job commands respect these variables:

Variable	Description	Default
REDIS_URL	Primary Redis connection URL	redis://localhost:6379
JOOBQ_REDIS_URL	JoobQ-specific Redis URL	Falls back to REDIS_URL
JOOBQ_QUEUE	Default queue name	default
JOOBQ_WORKERS	Default number of workers	1

Related Commands

• azu generate joobq - Set up JoobQ infrastructure

• azu generate job - Create new job classes

• azu serve - Development server

See Also

• JoobQ Documentation

• Background Jobs Guide

• Production Deployment