Docker Deployment Guide

This comprehensive guide covers deploying QuData using Docker for consistent, scalable, and portable deployments across different environments. QuData provides production-ready Docker configurations with security, monitoring, and scalability features built-in.

Quick Start

Prerequisites

Docker 20.10+ and Docker Compose 2.0+
At least 4GB RAM and 10GB disk space
Basic understanding of Docker and containerization

1. Clone and Setup

# Clone the repository
git clone https://github.com/qubasehq/qudata.git
cd qudata

# Copy environment template
cp .env.example .env

# Edit configuration (see Configuration section below)
nano .env

2. Development Deployment

# Start development environment
docker-compose up -d

# Check status
docker-compose ps

# View logs
docker-compose logs -f qudata

# Access services
# API: http://localhost:8000/docs
# Dashboard: http://localhost:8001
# Database: localhost:5432

3. Production Deployment

# Create secrets directory
mkdir -p secrets

# Generate secure passwords
openssl rand -base64 32 > secrets/db_password.txt
openssl rand -base64 32 > secrets/redis_password.txt
openssl rand -base64 32 > secrets/secret_key.txt
openssl rand -base64 32 > secrets/grafana_password.txt

# Set proper permissions
chmod 600 secrets/*

# Deploy production environment
docker-compose -f docker-compose.prod.yml up -d

# Check deployment status
docker-compose -f docker-compose.prod.yml ps

Architecture Overview

QuData's Docker architecture provides:

Multi-stage builds for optimized production images
Security-first design with non-root users and secrets management
Horizontal scalability with load balancing
Comprehensive monitoring with Prometheus and Grafana
Centralized logging with ELK stack
Health checks and automatic recovery
Development and production configurations

Production Deployment

Multi-Stage Dockerfile

# Multi-stage Dockerfile for production
FROM python:3.9-slim as builder

# Install build dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    libpq-dev \
    && rm -rf /var/lib/apt/lists/*

# Create virtual environment
RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

# Copy and install requirements
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Production stage
FROM python:3.9-slim as production

# Install runtime dependencies
RUN apt-get update && apt-get install -y \
    libpq5 \
    tesseract-ocr \
    libtesseract4 \
    libxml2 \
    libxslt1.1 \
    && rm -rf /var/lib/apt/lists/*

# Copy virtual environment from builder
COPY --from=builder /opt/venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

# Create non-root user
RUN groupadd -r qudata && useradd -r -g qudata qudata

# Set working directory
WORKDIR /app

# Copy application code
COPY --chown=qudata:qudata . .

# Install QuData
RUN pip install -e .

# Create directories with proper permissions
RUN mkdir -p data/{raw,processed,exports} logs && \
    chown -R qudata:qudata data logs

# Switch to non-root user
USER qudata

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:8000/health || exit 1

# Default command
CMD ["gunicorn", "--bind", "0.0.0.0:8000", "--workers", "4", "--worker-class", "uvicorn.workers.UvicornWorker", "qudata.api.main:app"]

Production Docker Compose

# docker-compose.prod.yml
version: '3.8'

services:
  qudata:
    build:
      context: .
      target: production
    ports:
      - "8000:8000"
    volumes:
      - ./data:/app/data:rw
      - ./configs:/app/configs:ro
      - ./logs:/app/logs:rw
    environment:
      - ENVIRONMENT=production
      - DB_HOST=postgres
      - DB_USER=qudata
      - DB_PASSWORD_FILE=/run/secrets/db_password
      - DB_NAME=qudata
      - REDIS_URL=redis://redis:6379/0
      - SECRET_KEY_FILE=/run/secrets/secret_key
    secrets:
      - db_password
      - secret_key
    depends_on:
      - postgres
      - redis
    restart: unless-stopped
    deploy:
      replicas: 3
      resources:
        limits:
          cpus: '2'
          memory: 4G
        reservations:
          cpus: '1'
          memory: 2G

  postgres:
    image: postgres:13
    environment:
      - POSTGRES_DB=qudata
      - POSTGRES_USER=qudata
      - POSTGRES_PASSWORD_FILE=/run/secrets/db_password
    volumes:
      - postgres_data:/var/lib/postgresql/data
      - ./backups:/backups
    secrets:
      - db_password
    restart: unless-stopped
    deploy:
      resources:
        limits:
          cpus: '1'
          memory: 2G

  redis:
    image: redis:7-alpine
    command: redis-server --appendonly yes --requirepass ${REDIS_PASSWORD}
    volumes:
      - redis_data:/data
    restart: unless-stopped

  nginx:
    image: nginx:alpine
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./nginx/nginx.conf:/etc/nginx/nginx.conf:ro
      - ./nginx/ssl:/etc/nginx/ssl:ro
      - ./logs/nginx:/var/log/nginx
    depends_on:
      - qudata
    restart: unless-stopped

secrets:
  db_password:
    file: ./secrets/db_password.txt
  secret_key:
    file: ./secrets/secret_key.txt

volumes:
  postgres_data:
  redis_data:

Configuration for Docker

Environment-Specific Configuration

# configs/docker.yaml
pipeline:
  input_directory: "/app/data/raw"
  output_directory: "/app/data/processed"
  export_directory: "/app/data/exports"
  temp_directory: "/tmp/qudata"
  
  # Docker-optimized settings
  parallel_processing: true
  max_workers: ${MAX_WORKERS:-4}
  batch_size: ${BATCH_SIZE:-100}
  max_memory_usage: "${MAX_MEMORY:-4GB}"

database:
  type: "postgresql"
  host: "${DB_HOST:-localhost}"
  port: ${DB_PORT:-5432}
  database: "${DB_NAME:-qudata}"
  username: "${DB_USER:-qudata}"
  password: "${DB_PASSWORD}"
  pool_size: ${DB_POOL_SIZE:-10}

cache:
  type: "redis"
  url: "${REDIS_URL:-redis://localhost:6379/0}"
  ttl: ${CACHE_TTL:-3600}

logging:
  level: "${LOG_LEVEL:-INFO}"
  file: "/app/logs/qudata.log"
  format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"

Docker Environment Variables

# .env file for docker-compose
COMPOSE_PROJECT_NAME=qudata

# Application settings
MAX_WORKERS=4
BATCH_SIZE=100
MAX_MEMORY=4GB
LOG_LEVEL=INFO

# Database settings
DB_HOST=postgres
DB_PORT=5432
DB_NAME=qudata
DB_USER=qudata
DB_PASSWORD=secure_password_here
DB_POOL_SIZE=10

# Redis settings
REDIS_URL=redis://redis:6379/0
CACHE_TTL=3600

# Security
SECRET_KEY=your_secret_key_here
ALLOWED_HOSTS=localhost,127.0.0.1,your-domain.com

Scaling and Load Balancing

Horizontal Scaling

# docker-compose.scale.yml
version: '3.8'

services:
  qudata-worker:
    build: .
    command: ["qudata", "worker", "--concurrency", "4"]
    volumes:
      - ./data:/app/data
      - ./configs:/app/configs
    environment:
      - WORKER_TYPE=processing
      - CELERY_BROKER_URL=redis://redis:6379/0
      - CELERY_RESULT_BACKEND=redis://redis:6379/1
    depends_on:
      - redis
    deploy:
      replicas: 3
    restart: unless-stopped

  qudata-api:
    build: .
    command: ["gunicorn", "--bind", "0.0.0.0:8000", "--workers", "4", "qudata.api.main:app"]
    ports:
      - "8000-8002:8000"
    volumes:
      - ./configs:/app/configs:ro
    environment:
      - API_WORKERS=4
    depends_on:
      - postgres
      - redis
    deploy:
      replicas: 3
    restart: unless-stopped

  nginx-lb:
    image: nginx:alpine
    ports:
      - "80:80"
    volumes:
      - ./nginx/load-balancer.conf:/etc/nginx/nginx.conf:ro
    depends_on:
      - qudata-api
    restart: unless-stopped

Load Balancer Configuration

# nginx/load-balancer.conf
upstream qudata_backend {
    least_conn;
    server qudata-api:8000 max_fails=3 fail_timeout=30s;
    server qudata-api:8001 max_fails=3 fail_timeout=30s;
    server qudata-api:8002 max_fails=3 fail_timeout=30s;
}

server {
    listen 80;
    server_name your-domain.com;

    location / {
        proxy_pass http://qudata_backend;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
        
        # Timeouts
        proxy_connect_timeout 60s;
        proxy_send_timeout 60s;
        proxy_read_timeout 60s;
        
        # Buffer settings
        proxy_buffering on;
        proxy_buffer_size 4k;
        proxy_buffers 8 4k;
    }

    location /health {
        access_log off;
        proxy_pass http://qudata_backend/health;
    }
}

Monitoring and Logging

Logging Configuration

# docker-compose.logging.yml
version: '3.8'

services:
  qudata:
    logging:
      driver: "json-file"
      options:
        max-size: "10m"
        max-file: "3"
        labels: "service=qudata"

  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:7.15.0
    environment:
      - discovery.type=single-node
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    volumes:
      - elasticsearch_data:/usr/share/elasticsearch/data
    ports:
      - "9200:9200"

  logstash:
    image: docker.elastic.co/logstash/logstash:7.15.0
    volumes:
      - ./logstash/pipeline:/usr/share/logstash/pipeline:ro
      - ./logs:/logs:ro
    depends_on:
      - elasticsearch

  kibana:
    image: docker.elastic.co/kibana/kibana:7.15.0
    ports:
      - "5601:5601"
    environment:
      - ELASTICSEARCH_HOSTS=http://elasticsearch:9200
    depends_on:
      - elasticsearch

volumes:
  elasticsearch_data:

Health Checks

# Add to Dockerfile
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD python -c "
import requests
import sys
try:
    response = requests.get('http://localhost:8000/health', timeout=5)
    sys.exit(0 if response.status_code == 200 else 1)
except:
    sys.exit(1)
"

Monitoring with Prometheus

# docker-compose.monitoring.yml
version: '3.8'

services:
  prometheus:
    image: prom/prometheus:latest
    ports:
      - "9090:9090"
    volumes:
      - ./prometheus/prometheus.yml:/etc/prometheus/prometheus.yml:ro
      - prometheus_data:/prometheus
    command:
      - '--config.file=/etc/prometheus/prometheus.yml'
      - '--storage.tsdb.path=/prometheus'
      - '--web.console.libraries=/etc/prometheus/console_libraries'
      - '--web.console.templates=/etc/prometheus/consoles'

  grafana:
    image: grafana/grafana:latest
    ports:
      - "3000:3000"
    volumes:
      - grafana_data:/var/lib/grafana
      - ./grafana/dashboards:/etc/grafana/provisioning/dashboards:ro
      - ./grafana/datasources:/etc/grafana/provisioning/datasources:ro
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin

volumes:
  prometheus_data:
  grafana_data:

Security Best Practices

Secrets Management

# Create secrets directory
mkdir -p secrets

# Generate secure passwords
openssl rand -base64 32 > secrets/db_password.txt
openssl rand -base64 32 > secrets/secret_key.txt
openssl rand -base64 32 > secrets/redis_password.txt

# Set proper permissions
chmod 600 secrets/*

Network Security

# docker-compose.secure.yml
version: '3.8'

networks:
  frontend:
    driver: bridge
  backend:
    driver: bridge
    internal: true

services:
  qudata:
    networks:
      - frontend
      - backend
    # Remove direct port exposure in production

  postgres:
    networks:
      - backend
    # Only accessible from backend network

  nginx:
    networks:
      - frontend
    ports:
      - "80:80"
      - "443:443"

SSL/TLS Configuration

# nginx/ssl.conf
server {
    listen 443 ssl http2;
    server_name your-domain.com;

    ssl_certificate /etc/nginx/ssl/cert.pem;
    ssl_certificate_key /etc/nginx/ssl/key.pem;
    
    ssl_protocols TLSv1.2 TLSv1.3;
    ssl_ciphers ECDHE-RSA-AES256-GCM-SHA512:DHE-RSA-AES256-GCM-SHA512;
    ssl_prefer_server_ciphers off;
    
    add_header Strict-Transport-Security "max-age=63072000" always;
    add_header X-Frame-Options DENY;
    add_header X-Content-Type-Options nosniff;

    location / {
        proxy_pass http://qudata:8000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}

server {
    listen 80;
    server_name your-domain.com;
    return 301 https://$server_name$request_uri;
}

Backup and Recovery

Database Backup

#!/bin/bash
# backup.sh

BACKUP_DIR="/backups"
DATE=$(date +%Y%m%d_%H%M%S)
BACKUP_FILE="qudata_backup_${DATE}.sql"

# Create backup
docker-compose exec postgres pg_dump -U qudata qudata > "${BACKUP_DIR}/${BACKUP_FILE}"

# Compress backup
gzip "${BACKUP_DIR}/${BACKUP_FILE}"

# Clean old backups (keep last 7 days)
find "${BACKUP_DIR}" -name "qudata_backup_*.sql.gz" -mtime +7 -delete

echo "Backup completed: ${BACKUP_FILE}.gz"

Data Volume Backup

#!/bin/bash
# backup-volumes.sh

DATE=$(date +%Y%m%d_%H%M%S)

# Backup data volumes
docker run --rm \
  -v qudata_postgres_data:/data \
  -v $(pwd)/backups:/backup \
  alpine tar czf /backup/postgres_data_${DATE}.tar.gz -C /data .

docker run --rm \
  -v qudata_redis_data:/data \
  -v $(pwd)/backups:/backup \
  alpine tar czf /backup/redis_data_${DATE}.tar.gz -C /data .

echo "Volume backups completed"

Deployment Commands

Development Deployment

# Start development environment
docker-compose -f docker-compose.yml up -d

# View logs
docker-compose logs -f

# Execute commands in container
docker-compose exec qudata qudata process --help

# Stop services
docker-compose down

Production Deployment

# Deploy to production
docker-compose -f docker-compose.prod.yml up -d

# Scale services
docker-compose -f docker-compose.prod.yml up -d --scale qudata=3

# Rolling update
docker-compose -f docker-compose.prod.yml up -d --no-deps qudata

# Health check
docker-compose -f docker-compose.prod.yml ps

Maintenance Commands

# Update images
docker-compose pull
docker-compose up -d

# Clean up
docker system prune -f
docker volume prune -f

# Backup before maintenance
./backup.sh

# Database migration
docker-compose exec qudata alembic upgrade head

This Docker deployment guide provides a comprehensive setup for running QuData in containerized environments, from development to production, with proper scaling, monitoring, and security considerations.

Deployment Configurations

Development Environment

The development configuration (docker-compose.yml) includes:

Hot reload for code changes
Debug logging and development tools
Exposed ports for direct access
Volume mounts for live code editing
Optional services via profiles

Services included:

QuData API server with auto-reload
PostgreSQL database
Redis cache
Nginx reverse proxy (optional)
Elasticsearch + Kibana (optional, --profile logging)
Prometheus + Grafana (optional, --profile monitoring)

Production Environment

The production configuration (docker-compose.prod.yml) includes:

Multi-replica deployment with load balancing
Secrets management for sensitive data
Resource limits and health checks
Network isolation for security
Comprehensive monitoring and logging
Backup and recovery mechanisms

Services included:

QuData API (3 replicas by default)
QuData Worker (2 replicas for background processing)
PostgreSQL with optimized settings
Redis with persistence
Nginx load balancer with SSL
Elasticsearch for centralized logging
Logstash for log processing
Prometheus for metrics collection
Grafana for visualization

Configuration

Environment Variables

Key environment variables in .env:

# Application
ENVIRONMENT=production
DEBUG=false
LOG_LEVEL=INFO
VERSION=1.0.1

# Database
DB_HOST=postgres
DB_NAME=qudata
DB_USER=qudata
# DB_PASSWORD loaded from secrets/db_password.txt

# Performance
WORKERS=4
MAX_WORKERS=8
BATCH_SIZE=200
MAX_MEMORY=8GB

# Security
# SECRET_KEY loaded from secrets/secret_key.txt
ALLOWED_HOSTS=your-domain.com,api.your-domain.com

# Features
ENABLE_GRAPHQL=true
ENABLE_WEBHOOKS=true
ENABLE_MONITORING=true

Secrets Management

Production deployments use Docker secrets for sensitive data:

# Create secrets directory
mkdir -p secrets

# Database password
echo "your-secure-db-password" > secrets/db_password.txt

# Redis password
echo "your-secure-redis-password" > secrets/redis_password.txt

# Application secret key
openssl rand -base64 32 > secrets/secret_key.txt

# Grafana admin password
echo "your-grafana-password" > secrets/grafana_password.txt

# Set proper permissions
chmod 600 secrets/*

SSL/TLS Configuration

For production HTTPS deployment:

Obtain SSL certificates (Let's Encrypt recommended):

# Using certbot
certbot certonly --webroot -w /var/www/certbot -d your-domain.com

# Copy certificates
cp /etc/letsencrypt/live/your-domain.com/fullchain.pem docker/nginx/ssl/cert.pem
cp /etc/letsencrypt/live/your-domain.com/privkey.pem docker/nginx/ssl/key.pem

Update Nginx configuration in docker/nginx/nginx-prod.conf:

server {
    listen 443 ssl http2;
    server_name your-domain.com;
    
    ssl_certificate /etc/nginx/ssl/cert.pem;
    ssl_certificate_key /etc/nginx/ssl/key.pem;
    
    # ... rest of configuration
}

Deployment Scripts

Automated Deployment

Use the provided deployment script for automated deployments:

# Development deployment
./scripts/deploy.sh -e development

# Production deployment with backup
./scripts/deploy.sh -e production -b -p -c

# Deploy specific services
./scripts/deploy.sh -e production -s api,worker

# Scale services
./scripts/deploy.sh -e production --scale api=3 --scale worker=2

Manual Deployment Steps

For manual deployment control:

# 1. Build images
docker-compose -f docker-compose.prod.yml build

# 2. Create networks and volumes
docker-compose -f docker-compose.prod.yml up --no-start

# 3. Start infrastructure services
docker-compose -f docker-compose.prod.yml up -d postgres redis

# 4. Wait for services to be ready
docker-compose -f docker-compose.prod.yml exec postgres pg_isready -U qudata

# 5. Start application services
docker-compose -f docker-compose.prod.yml up -d qudata-api qudata-worker

# 6. Start monitoring and proxy
docker-compose -f docker-compose.prod.yml up -d nginx prometheus grafana

Scaling and Load Balancing

Horizontal Scaling

Scale services based on load:

# Scale API servers
docker-compose -f docker-compose.prod.yml up -d --scale qudata-api=5

# Scale workers
docker-compose -f docker-compose.prod.yml up -d --scale qudata-worker=3

# Check scaled services
docker-compose -f docker-compose.prod.yml ps

Load Balancer Configuration

Nginx automatically load balances across API replicas:

upstream qudata_api {
    least_conn;
    server qudata-api:8000 max_fails=3 fail_timeout=30s weight=1;
    # Additional servers added automatically by Docker Compose
    keepalive 32;
}

Resource Management

Configure resource limits in production:

services:
  qudata-api:
    deploy:
      resources:
        limits:
          cpus: '2'
          memory: 4G
        reservations:
          cpus: '1'
          memory: 2G

Monitoring and Logging

Health Checks

All services include comprehensive health checks:

healthcheck:
  test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
  interval: 30s
  timeout: 10s
  retries: 3
  start_period: 60s

Metrics Collection

Prometheus collects metrics from:

Application performance metrics
System resource usage
Database performance
Request/response metrics
Custom business metrics

Access Grafana dashboard at http://localhost:3000 (admin/admin)

Centralized Logging

ELK stack processes logs from all services:

Elasticsearch: Log storage and indexing
Logstash: Log processing and transformation
Kibana: Log visualization and analysis

Access Kibana at http://localhost:5601

Log Aggregation

Application logs are structured and include:

{
  "timestamp": "2024-01-15T10:30:00Z",
  "level": "INFO",
  "service": "qudata-api",
  "message": "Document processed successfully",
  "document_id": "uuid-here",
  "processing_time": 1.23,
  "quality_score": 0.85
}

Backup and Recovery

Automated Backups

Production deployment includes automated backup:

# Database backup script
#!/bin/bash
BACKUP_DIR="/backups/$(date +%Y%m%d_%H%M%S)"
mkdir -p "$BACKUP_DIR"

# Backup database
docker-compose -f docker-compose.prod.yml exec -T postgres \
  pg_dump -U qudata qudata > "$BACKUP_DIR/database.sql"

# Backup data volumes
docker run --rm \
  -v qudata_postgres_data:/data \
  -v $(pwd)/backups:/backup \
  alpine tar czf "/backup/postgres_data_$(date +%Y%m%d_%H%M%S).tar.gz" -C /data .

Recovery Procedures

To restore from backup:

# Stop services
docker-compose -f docker-compose.prod.yml down

# Restore database
docker-compose -f docker-compose.prod.yml up -d postgres
docker-compose -f docker-compose.prod.yml exec -T postgres \
  psql -U qudata -d qudata < backups/20240115_103000/database.sql

# Restore data volumes
docker run --rm \
  -v qudata_postgres_data:/data \
  -v $(pwd)/backups:/backup \
  alpine tar xzf /backup/postgres_data_20240115_103000.tar.gz -C /data

# Restart services
docker-compose -f docker-compose.prod.yml up -d

Security Best Practices

Container Security

Non-root user: All containers run as non-root user qudata
Read-only filesystems: Where possible, containers use read-only root filesystems
Minimal base images: Using Alpine Linux for smaller attack surface
Security scanning: Regular vulnerability scanning of images

Network Security

Network isolation: Backend services isolated from external access
TLS encryption: All external communication encrypted
Rate limiting: API endpoints protected with rate limiting
Firewall rules: Only necessary ports exposed

Secrets Management

Docker secrets: Sensitive data stored as Docker secrets
Environment separation: Different secrets for each environment
Rotation policy: Regular rotation of passwords and keys
Access control: Restricted access to secrets files

Troubleshooting

Common Issues

Service won't start:

# Check logs
docker-compose logs service-name

# Check health status
docker-compose ps

# Restart service
docker-compose restart service-name

Database connection issues:

# Check database status
docker-compose exec postgres pg_isready -U qudata

# Check network connectivity
docker-compose exec qudata-api nc -z postgres 5432

# Reset database
docker-compose down
docker volume rm qudata_postgres_data
docker-compose up -d

Performance issues:

# Check resource usage
docker stats

# Scale services
docker-compose up -d --scale qudata-api=3

# Check logs for bottlenecks
docker-compose logs --tail=100 qudata-api

Debug Mode

Enable debug mode for troubleshooting:

# Set debug environment
export DEBUG=true
export LOG_LEVEL=DEBUG

# Restart with debug logging
docker-compose restart qudata-api

# Follow debug logs
docker-compose logs -f qudata-api

Health Check Endpoints

Monitor service health:

# Application health
curl http://localhost:8000/health

# Database health
curl http://localhost:8000/health/db

# Redis health
curl http://localhost:8000/health/redis

# Detailed system status
curl http://localhost:8000/status

Maintenance

Updates and Upgrades

# Pull latest images
docker-compose pull

# Backup before update
./scripts/backup.sh

# Update services with zero downtime
docker-compose up -d --no-deps qudata-api

# Verify update
docker-compose ps
curl http://localhost:8000/health

Log Rotation

Configure log rotation to prevent disk space issues:

# Add to crontab
0 2 * * * docker system prune -f --filter "until=24h"
0 3 * * * find /var/lib/docker/containers -name "*.log" -exec truncate -s 0 {} \;

Performance Tuning

Optimize for your workload:

# Increase worker processes
environment:
  - WORKERS=8
  - MAX_WORKERS=16

# Adjust batch sizes
  - BATCH_SIZE=500
  - MAX_MEMORY=16GB

# Database tuning
postgres:
  command: >
    postgres
    -c shared_buffers=256MB
    -c effective_cache_size=1GB
    -c maintenance_work_mem=64MB

Production Checklist

Before deploying to production:

Support and Resources

Documentation: docs/
API Reference: http://localhost:8000/docs
Monitoring: http://localhost:3000 (Grafana)
Logs: http://localhost:5601 (Kibana)
Issues: GitHub Issues
Community: Discussions

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Docker Deployment Guide

Quick Start

Prerequisites

1. Clone and Setup

2. Development Deployment

3. Production Deployment

Architecture Overview

Production Deployment

Multi-Stage Dockerfile

Production Docker Compose

Configuration for Docker

Environment-Specific Configuration

Docker Environment Variables

Scaling and Load Balancing

Horizontal Scaling

Load Balancer Configuration

Monitoring and Logging

Logging Configuration

Health Checks

Monitoring with Prometheus

Security Best Practices

Secrets Management

Network Security

SSL/TLS Configuration

Backup and Recovery

Database Backup

Data Volume Backup

Deployment Commands

Development Deployment

Production Deployment

Maintenance Commands

Deployment Configurations

Development Environment

Production Environment

Configuration

Environment Variables

Secrets Management

SSL/TLS Configuration

Deployment Scripts

Automated Deployment

Manual Deployment Steps

Scaling and Load Balancing

Horizontal Scaling

Load Balancer Configuration

Resource Management

Monitoring and Logging

Health Checks

Metrics Collection

Centralized Logging

Log Aggregation

Backup and Recovery

Automated Backups

Recovery Procedures

Security Best Practices

Container Security

Network Security

Secrets Management

Troubleshooting

Common Issues

Debug Mode

Health Check Endpoints

Maintenance

Updates and Upgrades

Log Rotation

Performance Tuning

Production Checklist

Support and Resources