Bull + Bull Board

intermediate

Node.js job queue with monitoring dashboard.

Overview

Bull is a Redis-based queue library for Node.js that enables background job processing with features like delayed jobs, job prioritization, rate limiting, and automatic retries. Originally created to handle asynchronous task processing in Node.js applications, Bull has become a cornerstone for building scalable microservices that need reliable job scheduling and execution. Bull Board complements this by providing a web-based monitoring dashboard that visualizes queue statistics, job status, and system performance in real-time. This stack combines Bull's robust job processing capabilities with Redis's high-performance in-memory storage and Bull Board's intuitive monitoring interface. Redis serves as the message broker and job storage backend, ensuring jobs persist across application restarts while maintaining sub-millisecond response times. Bull Board connects to the same Redis instance to provide live insights into queue health, failed job analysis, and throughput metrics without requiring additional database setup. Development teams building Node.js applications with background processing requirements will find this combination particularly valuable. E-commerce platforms processing order workflows, SaaS applications handling user notifications, and data processing pipelines benefit from Bull's reliability combined with Bull Board's operational visibility. The stack is especially useful for teams transitioning from simple setTimeout-based processing to enterprise-grade job management with proper monitoring and failure handling.

Key Features

Priority-based job scheduling with weighted queue processing
Automatic job retry mechanisms with exponential backoff strategies
Delayed job execution for scheduled tasks and time-based workflows
Real-time job progress tracking with custom progress indicators
Rate limiting capabilities to prevent API throttling and resource exhaustion
Job concurrency control with configurable worker limits per queue
Web-based dashboard showing queue statistics, failed jobs, and processing metrics
Redis persistence ensuring job durability across application restarts

Common Use Cases

1E-commerce order processing workflows with payment verification and inventory updates
2Email and notification delivery systems with retry logic for failed sends
3Image and video processing pipelines for user-generated content
4Data ETL jobs for analytics and reporting dashboards
5Scheduled maintenance tasks and database cleanup operations
6Social media content moderation and automated posting systems
7Financial transaction processing with fraud detection workflows

Prerequisites

Docker and Docker Compose installed on the host system
Minimum 512MB RAM for Redis data storage and job queue operations
Port 3000 available for Bull Board dashboard access
Basic understanding of Node.js job queue concepts and Redis data structures
Network connectivity for Redis communication between Bull and Bull Board containers

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

docker-compose.yml

1services: 
2  redis: 
3    image: redis:alpine
4    container_name: bull-redis
5    volumes: 
6      - redis_data:/data
7    networks: 
8      - bull
9
10  bull-board: 
11    image: deadly0/bull-board:latest
12    container_name: bull-board
13    environment: 
14      REDIS_HOST: redis
15      REDIS_PORT: 6379
16    ports: 
17      - "3000:3000"
18    depends_on: 
19      - redis
20    networks: 
21      - bull
22
23volumes: 
24  redis_data: 
25
26networks: 
27  bull: 
28    driver: bridge

.env Template

.env

1# Configure your Bull queues

Usage Notes

1Docs: https://docs.bullmq.io/
2Bull Board dashboard at http://localhost:3000
3Add queues in Node.js: new Queue('my-queue', { connection })
4Monitor job status, progress, failed jobs, and retries
5BullMQ (v4+) recommended over Bull for new projects
6Redis-backed - jobs persist across restarts

Individual Services(2 services)

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

redis

redis:
  image: redis:alpine
  container_name: bull-redis
  volumes:
    - redis_data:/data
  networks:
    - bull

bull-board

bull-board:
  image: deadly0/bull-board:latest
  container_name: bull-board
  environment:
    REDIS_HOST: redis
    REDIS_PORT: 6379
  ports:
    - "3000:3000"
  depends_on:
    - redis
  networks:
    - bull

Quick Start

terminal

1# 1. Create the compose file
2cat > docker-compose.yml << 'EOF'
3services:
4  redis:
5    image: redis:alpine
6    container_name: bull-redis
7    volumes:
8      - redis_data:/data
9    networks:
10      - bull
11
12  bull-board:
13    image: deadly0/bull-board:latest
14    container_name: bull-board
15    environment:
16      REDIS_HOST: redis
17      REDIS_PORT: 6379
18    ports:
19      - "3000:3000"
20    depends_on:
21      - redis
22    networks:
23      - bull
24
25volumes:
26  redis_data:
27
28networks:
29  bull:
30    driver: bridge
31EOF
32
33# 2. Create the .env file
34cat > .env << 'EOF'
35# Configure your Bull queues
36EOF
37
38# 3. Start the services
39docker compose up -d
40
41# 4. View logs
42docker 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/bull-board/run | bash

Troubleshooting

Bull Board shows empty dashboard: Ensure your Node.js application is creating queues with the same Redis connection parameters
Jobs stuck in waiting state: Check Redis memory usage and increase maxmemory limit or enable memory eviction policies
Connection refused errors: Verify Redis container is running and accessible on the bull network with correct hostname 'redis'
Jobs not processing: Confirm your Node.js workers are consuming from the correct queue names and Redis host configuration
Dashboard not updating: Restart Bull Board container to refresh Redis connection and clear any cached queue metadata
High memory usage in Redis: Enable Redis persistence (RDB/AOF) and configure appropriate job TTL settings to prevent memory leaks

Community Notes

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Components

bullredis

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