Production Deployment

This guide covers deploying bunqueue in production. bunqueue is designed as a single-instance job queue - it doesn’t support clustering or horizontal scaling.

Caution

bunqueue runs as a single process. There’s no built-in clustering or multi-node support. Tested and validated up to 1 million jobs with 100% data integrity.

Architecture Overview

┌─────────────────────────────────────────────────────────────┐
│                     Your Application                         │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐         │
│  │   Web App   │  │   API       │  │   Workers   │         │
│  └──────┬──────┘  └──────┬──────┘  └──────┬──────┘         │
│         │                │                │                 │
│         └────────────────┼────────────────┘                 │
│                          │                                  │
│                          ▼                                  │
│              ┌───────────────────────┐                     │
│              │      bunqueue         │ ◄── Single instance │
│              │   (embedded mode)     │                     │
│              └───────────┬───────────┘                     │
│                          │                                  │
│                          ▼                                  │
│              ┌───────────────────────┐                     │
│              │   SQLite Database     │ ◄── Local file      │
│              │   (./data/bunq.db)    │                     │
│              └───────────────────────┘                     │
└─────────────────────────────────────────────────────────────┘
                          │
                          ▼ (optional)
              ┌───────────────────────┐
              │      S3 Backup        │
              │  (disaster recovery)  │
              └───────────────────────┘

Deployment Options

Option 1: Embedded Mode (Recommended)

Run bunqueue directly in your application process. No separate server needed.

app.ts

import { Queue, Worker } from 'bunqueue/client';

// Your web framework (Hono, Elysia, Express...)
const app = new Hono();

// Queue is embedded in the same process
const emailQueue = new Queue('emails');

app.post('/send-email', async (c) => {
  const { to, subject } = await c.req.json();
  await emailQueue.add('send', { to, subject });
  return c.json({ queued: true });
});

// Worker runs in the same process
new Worker('emails', async (job) => {
  await sendEmail(job.data);
  return { sent: true };
}, { concurrency: 5 });

export default app;

Pros:

• Simplest setup
• No network latency
• Single deployment unit

Cons:

• Queue dies if app dies
• Harder to scale workers independently

Option 2: Separate Worker Process

Run your API and workers as separate processes sharing the same database.

// api.ts - Your web server
import { Queue } from 'bunqueue/client';

const queue = new Queue('tasks');

app.post('/task', async (c) => {
  await queue.add('process', { data: '...' });
  return c.json({ ok: true });
});

// worker.ts - Separate process
import { Worker } from 'bunqueue/client';

new Worker('tasks', async (job) => {
  // Heavy processing here
  return { done: true };
}, { concurrency: 10 });

console.log('Worker started');

# Run both
bun run api.ts &
bun run worker.ts &

Pros:

• Workers can be restarted independently
• Better resource isolation

Cons:

• Two processes to manage
• Still single SQLite file (no true distribution)

Option 3: Server Mode (CLI)

Run bunqueue as a standalone server. Interact via CLI or HTTP API.

# Start server
bunqueue start --tcp-port 6789 --http-port 6790

# Add jobs via CLI
bunqueue push emails '{"to": "user@example.com", "subject": "Hello"}'

# Or via HTTP API
curl -X POST http://localhost:6790/queues/emails/jobs \
  -H "Content-Type: application/json" \
  -d '{"data": {"to": "user@example.com"}}'

Note

There is no programmatic SDK client for server mode. Use the CLI, HTTP API, or embedded mode.

Docker Deployment

Dockerfile

FROM oven/bun:1

WORKDIR /app

# Copy package files
COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile --production

# Copy application
COPY . .

# Create data directory
RUN mkdir -p /app/data

# Environment
ENV DATA_PATH=/app/data/bunq.db
ENV NODE_ENV=production

# Health check
HEALTHCHECK --interval=30s --timeout=3s \
  CMD curl -f http://localhost:6790/health || exit 1

EXPOSE 6789 6790

CMD ["bun", "run", "start"]

Docker Compose

version: '3.8'

services:
  bunqueue:
    build: .
    ports:
      - "6789:6789"  # TCP
      - "6790:6790"  # HTTP
    volumes:
      - bunqueue-data:/app/data
    environment:
      - DATA_PATH=/app/data/bunq.db
      - AUTH_TOKENS=${AUTH_TOKENS}
      - S3_BACKUP_ENABLED=1
      - S3_ACCESS_KEY_ID=${S3_ACCESS_KEY_ID}
      - S3_SECRET_ACCESS_KEY=${S3_SECRET_ACCESS_KEY}
      - S3_BUCKET=${S3_BUCKET}
      - S3_REGION=${S3_REGION}
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 512M
        reservations:
          memory: 256M

volumes:
  bunqueue-data:

Systemd Service

For bare-metal or VM deployments:

/etc/systemd/system/bunqueue.service

[Unit]
Description=bunqueue Job Queue
After=network.target

[Service]
Type=simple
User=bunqueue
Group=bunqueue
WorkingDirectory=/var/lib/bunqueue
ExecStart=/usr/local/bin/bunqueue start
Restart=always
RestartSec=5

# Environment
Environment=NODE_ENV=production
Environment=DATA_PATH=/var/lib/bunqueue/bunq.db
EnvironmentFile=/etc/bunqueue/env

# Security
NoNewPrivileges=true
ProtectSystem=strict
ProtectHome=true
ReadWritePaths=/var/lib/bunqueue

# Resource limits
MemoryMax=512M
CPUQuota=200%

[Install]
WantedBy=multi-user.target

# Install
sudo systemctl daemon-reload
sudo systemctl enable bunqueue
sudo systemctl start bunqueue

# Check status
sudo systemctl status bunqueue
sudo journalctl -u bunqueue -f

Building from Source

Compile bunqueue into a standalone executable for production deployment.

Build Command

# Clone the repository
git clone https://github.com/egeominotti/bunqueue.git
cd bunqueue

# Install dependencies
bun install

# Build standalone binary
bun run build

This creates dist/bunqueue (~56 MB), a self-contained executable with no runtime dependencies.

Verify Build

# Check version
./dist/bunqueue --version

# Show help
./dist/bunqueue --help

# Start server
./dist/bunqueue start

Install Globally

# Copy to system path
sudo cp dist/bunqueue /usr/local/bin/

# Verify installation
bunqueue --version

Tip

The compiled binary includes the Bun runtime. No need to install Bun on the target server.

---

PM2 Process Manager

For cross-platform process management with PM2:

Compiled Binary (Recommended)

First, build the standalone executable:

bun run build

Then configure PM2:

ecosystem.config.js

module.exports = {
  apps: [{
    name: 'bunqueue',
    script: '/usr/local/bin/bunqueue',  // Compiled binary
    args: 'start',
    instances: 1,  // Single instance only - no cluster mode
    exec_mode: 'fork',
    autorestart: true,
    watch: false,
    max_memory_restart: '512M',
    env: {
      NODE_ENV: 'production',
      DATA_PATH: '/var/lib/bunqueue/bunq.db',
      TCP_PORT: 6789,
      HTTP_PORT: 6790,
    },
    error_file: '/var/log/bunqueue/error.log',
    out_file: '/var/log/bunqueue/out.log',
    log_date_format: 'YYYY-MM-DD HH:mm:ss Z',
    merge_logs: true,
  }]
};

Development Mode (with Bun)

For development or when using the source directly:

ecosystem.config.js

module.exports = {
  apps: [{
    name: 'bunqueue',
    script: 'bun',
    args: 'run start',
    cwd: '/opt/bunqueue',
    instances: 1,
    exec_mode: 'fork',
    autorestart: true,
    max_memory_restart: '512M',
    env: {
      NODE_ENV: 'production',
      DATA_PATH: '/var/lib/bunqueue/bunq.db',
      TCP_PORT: 6789,
      HTTP_PORT: 6790,
    },
  }]
};

PM2 Commands

# Start
pm2 start ecosystem.config.js

# Restart
pm2 restart bunqueue

# Stop
pm2 stop bunqueue

# View logs
pm2 logs bunqueue

# Monitor
pm2 monit

# Save process list for startup
pm2 save
pm2 startup

Caution

Do not use PM2 cluster mode (instances > 1). bunqueue is a single-instance queue and multiple instances will cause data corruption.

Environment Variables

Variable	Description	Default
DATA_PATH	SQLite database path	./data/bunq.db
TCP_PORT	TCP server port	6789
HTTP_PORT	HTTP server port	6790
AUTH_TOKENS	Comma-separated auth tokens	-
S3_BACKUP_ENABLED	Enable S3 backups	0
S3_ACCESS_KEY_ID	S3 access key	-
S3_SECRET_ACCESS_KEY	S3 secret key	-
S3_BUCKET	S3 bucket name	-
S3_REGION	S3 region	us-east-1
S3_ENDPOINT	Custom S3 endpoint	-
S3_BACKUP_INTERVAL	Backup interval (ms)	21600000 (6h)
S3_BACKUP_RETENTION	Backups to keep	7

S3 Backup Configuration

Tip

Always enable S3 backups in production. SQLite is a single file - if it corrupts or the disk fails, you lose everything.

AWS S3

S3_BACKUP_ENABLED=1
S3_ACCESS_KEY_ID=AKIA...
S3_SECRET_ACCESS_KEY=...
S3_BUCKET=my-bunqueue-backups
S3_REGION=us-east-1
S3_BACKUP_INTERVAL=3600000  # Every hour
S3_BACKUP_RETENTION=24       # Keep 24 backups

Cloudflare R2

S3_BACKUP_ENABLED=1
S3_ACCESS_KEY_ID=...
S3_SECRET_ACCESS_KEY=...
S3_BUCKET=bunqueue-backups
S3_ENDPOINT=https://ACCOUNT_ID.r2.cloudflarestorage.com
S3_REGION=auto

MinIO (Self-hosted)

S3_BACKUP_ENABLED=1
S3_ACCESS_KEY_ID=minioadmin
S3_SECRET_ACCESS_KEY=minioadmin
S3_BUCKET=bunqueue
S3_ENDPOINT=http://minio:9000
S3_REGION=us-east-1

Health Checks

bunqueue exposes health endpoints:

# HTTP health check (detailed)
curl http://localhost:6790/health
# {"ok":true,"status":"healthy","uptime":3600,"version":"1.0.4",
#  "queues":{"waiting":5,"active":2},"connections":{"ws":0,"sse":0},
#  "memory":{"heapUsed":45,"heapTotal":64,"rss":128}}

# Simple liveness probe
curl http://localhost:6790/healthz
# OK

# Readiness probe
curl http://localhost:6790/ready
# {"ok":true,"ready":true}

# Queue stats
curl http://localhost:6790/stats
# {"ok":true,"stats":{"waiting":5,"active":2,"completed":1000,"dlq":0}}

# Prometheus metrics (text format)
curl http://localhost:6790/prometheus

Kubernetes Probes

livenessProbe:
  httpGet:
    path: /healthz
    port: 6790
  initialDelaySeconds: 5
  periodSeconds: 10

readinessProbe:
  httpGet:
    path: /ready
    port: 6790
  initialDelaySeconds: 5
  periodSeconds: 5

Resource Requirements

Memory

Workload	Recommended RAM
Light (<1k jobs/day)	128 MB
Medium (1k-10k jobs/day)	256 MB
Heavy (10k-100k jobs/day)	512 MB
Very Heavy (>100k jobs/day)	1 GB+

Disk

SQLite database size depends on:

• Number of jobs retained
• Job data size
• removeOnComplete setting

// Reduce disk usage
new Queue('tasks', {
  defaultJobOptions: {
    removeOnComplete: true,  // Don't keep completed jobs
    removeOnFail: false,     // Keep failed for debugging
  }
});

CPU

bunqueue is I/O bound, not CPU bound. A single core handles most workloads.

Production Checklist

1. Enable S3 backups

   Don’t skip this. SQLite corruption = data loss.

2. Set auth tokens

   AUTH_TOKENS=token1,token2,token3

3. Configure resource limits

   Prevent runaway memory/CPU usage.

4. Set up monitoring

   Scrape /prometheus with Prometheus or similar.

5. Configure log aggregation

   Send logs to a central system.

6. Test backup restoration

   # List backups first
   bunqueue backup list
   # Then restore by key
   bunqueue backup restore backups/bunq-2026-01-30T12:00:00.db --force

7. Set up alerts

   • DLQ count > threshold
   • Waiting jobs growing
   • Worker not processing

Scaling Limitations

No Clustering

bunqueue does not support horizontal scaling or clustering. It’s a single-instance queue.

What this means

• ❌ No multi-node deployment
• ❌ No automatic failover
• ❌ No distributed processing across machines
• ✅ Multiple workers in same process (concurrency)
• ✅ Multiple worker processes on same machine (shared SQLite)

When bunqueue is enough

Scenario	Jobs/day	bunqueue?
Small SaaS	<10k	✅ Perfect
Medium app	10k-100k	✅ Fine
Large app	100k-1M	✅ Tested
Enterprise	>1M	⚠️ Test first

When to use something else

If you need:

• High availability → Redis + BullMQ with Sentinel
• Distributed processing → Kafka, RabbitMQ
• Multi-region → Managed queues (SQS, Cloud Tasks)
• Complex workflows → Temporal, Inngest

Vertical scaling

bunqueue scales vertically well:

• More RAM = more jobs in memory
• Faster disk (NVMe) = faster SQLite
• More CPU cores = more worker concurrency

// Scale worker concurrency with available CPUs
import { cpus } from 'os';

new Worker('tasks', processor, {
  concurrency: cpus().length * 2
});

Disaster Recovery

Backup Strategy

Every 1 hour  → S3 backup
Every 6 hours → Verify backup integrity
Every day     → Test restore in staging

Recovery Steps

1. Stop bunqueue

   systemctl stop bunqueue

2. List available backups

   bunqueue backup list

3. Restore from backup

   bunqueue backup restore backups/bunq-2024-01-30T12:00:00.db --force

4. Start bunqueue

   systemctl start bunqueue

Point-in-Time Recovery

SQLite WAL mode allows recovery to recent states:

# Backup includes WAL file
cp data/bunq.db data/bunq.db-wal /backup/

# Restore
cp /backup/bunq.db* data/

Security

Network

• Run behind reverse proxy (nginx, Caddy)
• Use TLS for external connections
• Firewall TCP/HTTP ports

Authentication

# Generate strong tokens
AUTH_TOKENS=$(openssl rand -hex 32),$(openssl rand -hex 32)

File Permissions

# Restrict database access
chmod 600 /var/lib/bunqueue/bunq.db
chown bunqueue:bunqueue /var/lib/bunqueue/bunq.db

Monitoring with Prometheus

prometheus.yml

scrape_configs:
  - job_name: 'bunqueue'
    static_configs:
      - targets: ['localhost:6790']
    metrics_path: /prometheus

Key Metrics

Metric	Alert Threshold
bunqueue_jobs_waiting	> 1000 for 5 min
bunqueue_jobs_dlq	> 10
bunqueue_jobs_active	0 for 5 min (workers dead?)
bunqueue_jobs_failed_total	increasing rapidly

Example: Full Production Setup

/etc/bunqueue/env

NODE_ENV=production
DATA_PATH=/var/lib/bunqueue/bunq.db
TCP_PORT=6789
HTTP_PORT=6790
AUTH_TOKENS=prod-token-abc123,deploy-token-xyz789

# S3 Backups
S3_BACKUP_ENABLED=1
S3_ACCESS_KEY_ID=AKIA...
S3_SECRET_ACCESS_KEY=...
S3_BUCKET=company-bunqueue-backups
S3_REGION=eu-west-1
S3_BACKUP_INTERVAL=3600000
S3_BACKUP_RETENTION=48

production.ts

import { Queue, Worker } from 'bunqueue/client';

const queue = new Queue('production-tasks', {
  defaultJobOptions: {
    attempts: 5,
    backoff: 5000,
    removeOnComplete: true,
  }
});

// Configure DLQ alerts
queue.setDlqConfig({
  maxEntries: 1000,
  maxAge: 7 * 24 * 60 * 60 * 1000, // 7 days
});

// Worker with production settings
new Worker('production-tasks', async (job) => {
  await job.updateProgress(0, 'Starting...');

  try {
    const result = await processJob(job.data);
    await job.log(`Completed: ${JSON.stringify(result)}`);
    return result;
  } catch (error) {
    await job.log(`Error: ${error.message}`);
    throw error;
  }
}, {
  concurrency: 10,
  heartbeatInterval: 5000,
});