Beanstalkd + Console

beginner

Simple, fast work queue with web UI.

Overview

Beanstalkd is a simple, fast work queue designed for high throughput and low latency job processing. Originally created by Keith Rarick in 2007, beanstalkd follows a minimalist philosophy with a straightforward protocol that makes it easy to integrate with applications written in any programming language. Unlike complex message brokers, beanstalkd focuses on doing one thing well: managing job queues with features like job priorities, delays, and automatic retry mechanisms. This stack combines the beanstalkd daemon with a web-based management console that provides real-time visibility into queue operations. The beanstalkd service handles job queuing operations on port 11300 using its simple text-based protocol, while the console application connects to the daemon and exposes a web interface on port 2080 for monitoring tube statistics, job states, and queue depths. The console communicates with beanstalkd through the standard protocol, allowing administrators to inspect jobs, manage tubes, and troubleshoot queue issues without command-line tools. This combination is ideal for developers building distributed applications that need reliable task queuing without the complexity of enterprise message brokers. Small to medium-sized teams benefit from beanstalkd's operational simplicity and the console's visual interface for monitoring job flows. The lightweight nature of both components makes this stack perfect for microservices architectures, background job processing systems, and any application requiring asynchronous task execution with minimal infrastructure overhead.

Key Features

Simple text-based protocol supporting put, reserve, delete, and touch operations
Tube-based job organization allowing logical separation of different job types
Job priority system with configurable priority levels from 0 to 4294967295
Delayed job execution with precise timing control for scheduled tasks
Automatic job time-to-run (TTR) management with configurable timeouts
Real-time web dashboard showing tube statistics, ready jobs, and buried jobs
Job state visualization including ready, reserved, delayed, and buried states
Interactive job management through the web console for debugging and monitoring

Common Use Cases

1Background email processing for web applications with variable send volumes
2Image and video processing pipelines requiring queued transcoding jobs
3E-commerce order fulfillment systems managing inventory and shipping workflows
4Social media platforms handling like, comment, and notification processing
5IoT data processing systems queuing sensor data for batch analysis
6Web scraping operations coordinating multiple crawler instances
7Report generation systems managing long-running analytical tasks

Prerequisites

Docker and Docker Compose installed on the host system
Minimum 256MB RAM available for both beanstalkd and console containers
Ports 11300 and 2080 available and not blocked by firewall rules
Basic understanding of job queue concepts and asynchronous processing
Network connectivity between application clients and the beanstalkd port
Web browser access to port 2080 for console management interface

For development & testing. Review security settings, change default credentials, and test thoroughly before production use. See Terms

docker-compose.yml

1services: 
2  beanstalkd: 
3    image: schickling/beanstalkd:latest
4    container_name: beanstalkd
5    restart: unless-stopped
6    ports: 
7      - "11300:11300"
8
9  console: 
10    image: schickling/beanstalkd-console:latest
11    container_name: beanstalkd-console
12    environment: 
13      BEANSTALKD_HOST: beanstalkd
14      BEANSTALKD_PORT: 11300
15    ports: 
16      - "2080:2080"
17    depends_on: 
18      - beanstalkd

.env Template

.env

1# No additional config needed

Usage Notes

1Docs: https://beanstalkd.github.io/
2Beanstalkd on port 11300, console at http://localhost:2080
3Simple protocol: put (add job), reserve (get job), delete (complete)
4Tubes for job segregation - like topics/queues
5Delayed jobs: put with delay parameter
6Lightweight - great for simple task queues

Individual Services(2 services)

Copy individual services to mix and match with your existing compose files.

beanstalkd

beanstalkd:
  image: schickling/beanstalkd:latest
  container_name: beanstalkd
  restart: unless-stopped
  ports:
    - "11300:11300"

console

console:
  image: schickling/beanstalkd-console:latest
  container_name: beanstalkd-console
  environment:
    BEANSTALKD_HOST: beanstalkd
    BEANSTALKD_PORT: 11300
  ports:
    - "2080:2080"
  depends_on:
    - beanstalkd

Quick Start

terminal

1# 1. Create the compose file
2cat > docker-compose.yml << 'EOF'
3services:
4  beanstalkd:
5    image: schickling/beanstalkd:latest
6    container_name: beanstalkd
7    restart: unless-stopped
8    ports:
9      - "11300:11300"
10
11  console:
12    image: schickling/beanstalkd-console:latest
13    container_name: beanstalkd-console
14    environment:
15      BEANSTALKD_HOST: beanstalkd
16      BEANSTALKD_PORT: 11300
17    ports:
18      - "2080:2080"
19    depends_on:
20      - beanstalkd
21EOF
22
23# 2. Create the .env file
24cat > .env << 'EOF'
25# No additional config needed
26EOF
27
28# 3. Start the services
29docker compose up -d
30
31# 4. View logs
32docker compose logs -f

One-Liner

Run this command to download and set up the recipe in one step:

terminal

1curl -fsSL https://docker.recipes/api/recipes/beanstalkd/run | bash

Troubleshooting

Console shows 'Connection refused' to beanstalkd: Verify beanstalkd container is running and check Docker network connectivity between services
Jobs appear stuck in reserved state: Check if worker processes are properly deleting completed jobs or if TTR timeout is too short
Cannot connect to beanstalkd from external applications: Ensure port 11300 is properly exposed and firewall allows connections
Console interface not loading at localhost:2080: Verify console container is running and BEANSTALKD_HOST environment variable is correctly set
High memory usage in beanstalkd container: Check for buried jobs accumulation or jobs with very large payloads consuming memory
Jobs disappearing without processing: Examine if job TTR is expiring before workers complete processing, causing jobs to return to ready state

Community Notes

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