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TG_autoposter/docs/PRODUCTION_DEPLOYMENT.md
Andrew K. Choi a6817e487e init commit
2025-12-18 05:55:32 +09:00

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Production Deployment Guide

Pre-Deployment Checklist

  • Environment variables configured in .env
  • PostgreSQL database created and migrated
  • Redis running and accessible
  • Telegram credentials verified
  • SSL certificates prepared (if needed)
  • Log rotation configured
  • Monitoring and alerts set up
  • Backups configured
  • Health checks tested

Deployment Methods

1. Docker Compose on VPS

1.1 Prepare Server

# Update system
sudo apt update && sudo apt upgrade -y

# Install Docker
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh

# Install Docker Compose
sudo curl -L "https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose

# Create non-root user for Docker
sudo usermod -aG docker $USER
newgrp docker

1.2 Deploy Application

# Clone repository
mkdir -p /home/bot
cd /home/bot
git clone https://github.com/yourusername/TG_autoposter.git
cd TG_autoposter

# Create environment file
nano .env
# Fill in production values

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

# Verify services
docker-compose ps

1.3 Database Migrations

# Run migrations
docker-compose exec bot alembic upgrade head

# Verify
docker-compose exec bot alembic current

1.4 Monitoring

# View logs
docker-compose logs -f

# Monitor specific service
docker-compose logs -f bot
docker-compose logs -f celery_worker_send

# Check health
docker-compose ps

2. Kubernetes Deployment

2.1 Create Kubernetes Manifests

# Create namespace
kubectl create namespace telegram-bot
kubectl config set-context --current --namespace=telegram-bot

# Create ConfigMap for environment variables
kubectl create configmap bot-config --from-env-file=.env.prod

# Create Secrets for sensitive data
kubectl create secret generic bot-secrets \
  --from-literal=telegram-bot-token=$TELEGRAM_BOT_TOKEN \
  --from-literal=db-password=$DB_PASSWORD \
  --from-literal=redis-password=$REDIS_PASSWORD

2.2 Deploy Services

See k8s/ directory for manifests:

  • postgres-deployment.yaml
  • redis-deployment.yaml
  • bot-deployment.yaml
  • celery-worker-deployment.yaml
  • celery-beat-deployment.yaml
  • flower-deployment.yaml
# Apply manifests
kubectl apply -f k8s/

# Monitor deployment
kubectl get pods
kubectl logs -f deployment/bot

3. Using Systemd Service

3.1 Create Service File

sudo tee /etc/systemd/system/tg-autoposter.service > /dev/null <<EOF
[Unit]
Description=TG Autoposter Bot
After=network.target docker.service
Requires=docker.service

[Service]
Type=simple
User=bot
WorkingDirectory=/home/bot/TG_autoposter
ExecStart=/usr/local/bin/docker-compose up
ExecStop=/usr/local/bin/docker-compose down
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target
EOF

3.2 Enable Service

sudo systemctl daemon-reload
sudo systemctl enable tg-autoposter
sudo systemctl start tg-autoposter

# Check status
sudo systemctl status tg-autoposter

# View logs
sudo journalctl -u tg-autoposter -f

Configuration for Production

1. Environment Variables

Create .env with production values:

# Core
TELEGRAM_BOT_TOKEN=your_production_token
TELEGRAM_API_ID=your_api_id
TELEGRAM_API_HASH=your_api_hash
ADMIN_ID=your_admin_id

# Database (use managed service like RDS, CloudSQL)
DB_HOST=db.example.com
DB_PORT=5432
DB_USER=bot_user
DB_PASSWORD=secure_password_here
DB_NAME=tg_autoposter_prod
DB_SSL_MODE=require

# Redis (use managed service like ElastiCache, Redis Cloud)
REDIS_HOST=redis.example.com
REDIS_PORT=6379
REDIS_DB=0
REDIS_PASSWORD=secure_redis_password

# Logging
LOG_LEVEL=INFO
LOG_FILE=/var/log/tg-autoposter/bot.log

# Security
SECRET_KEY=your_secret_key_here
DEBUG=False
ALLOWED_HOSTS=yourdomain.com,www.yourdomain.com

2. Database Configuration

# docker-compose.prod.yml
services:
  postgres:
    image: postgres:15-alpine
    environment:
      POSTGRES_PASSWORD: ${DB_PASSWORD}
      POSTGRES_DB: ${DB_NAME}
    volumes:
      - postgres_data:/var/lib/postgresql/data
    ports:
      - "5432:5432"
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U ${DB_USER}"]
      interval: 10s
      timeout: 5s
      retries: 5

3. Redis Configuration

# docker-compose.prod.yml
services:
  redis:
    image: redis:7-alpine
    command: redis-server --requirepass ${REDIS_PASSWORD}
    volumes:
      - redis_data:/data
    ports:
      - "6379:6379"
    healthcheck:
      test: ["CMD", "redis-cli", "--raw", "incr", "ping"]
      interval: 10s
      timeout: 5s
      retries: 5

Scaling Considerations

1. Horizontal Scaling

# docker-compose.prod.yml - Multiple workers
services:
  celery_worker_send_1:
    # ... worker configuration
    
  celery_worker_send_2:
    # ... worker configuration
    
  celery_worker_send_3:
    # ... worker configuration
    
  # Use load balancer or Docker Swarm for orchestration

2. Performance Tuning

# app/settings.py
CELERY_WORKER_PREFETCH_MULTIPLIER = 1
CELERY_WORKER_MAX_TASKS_PER_CHILD = 1000
CELERY_TASK_TIME_LIMIT = 30 * 60  # 30 minutes
CELERY_TASK_SOFT_TIME_LIMIT = 25 * 60  # 25 minutes

# Database connection pooling
DB_POOL_SIZE = 20
DB_MAX_OVERFLOW = 0
DB_POOL_TIMEOUT = 30
DB_POOL_RECYCLE = 3600

3. Caching Strategy

# Use Redis for caching
CACHE_TTL = 300  # 5 minutes
BROADCAST_CACHE_TTL = 3600  # 1 hour
MEMBERS_CACHE_TTL = 1800  # 30 minutes

Monitoring & Logging

1. Logging Setup

# Create log directory
sudo mkdir -p /var/log/tg-autoposter
sudo chown bot:bot /var/log/tg-autoposter

# Configure log rotation
sudo tee /etc/logrotate.d/tg-autoposter > /dev/null <<EOF
/var/log/tg-autoposter/*.log {
    daily
    rotate 14
    compress
    delaycompress
    notifempty
    create 0640 bot bot
    sharedscripts
    postrotate
        systemctl reload tg-autoposter > /dev/null 2>&1 || true
    endscript
}
EOF

2. Prometheus Metrics

# app/metrics.py
from prometheus_client import Counter, Histogram, Gauge

message_sent = Counter('messages_sent_total', 'Total messages sent')
message_failed = Counter('messages_failed_total', 'Total failed messages')
send_duration = Histogram('message_send_duration_seconds', 'Message send duration')
queue_size = Gauge('celery_queue_size', 'Celery queue size')

3. Monitoring with ELK Stack

# docker-compose.prod.yml
services:
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.0.0
    
  kibana:
    image: docker.elastic.co/kibana/kibana:8.0.0
    ports:
      - "5601:5601"
      
  logstash:
    image: docker.elastic.co/logstash/logstash:8.0.0
    volumes:
      - ./logstash.conf:/usr/share/logstash/pipeline/logstash.conf

Backup & Recovery

1. Database Backup

#!/bin/bash
# backup-db.sh
BACKUP_DIR="/backups/postgres"
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
BACKUP_FILE="$BACKUP_DIR/tg_autoposter_$TIMESTAMP.sql"

mkdir -p $BACKUP_DIR

# Backup
docker-compose exec -T postgres pg_dump -U $DB_USER $DB_NAME > $BACKUP_FILE

# Compress
gzip $BACKUP_FILE

# Remove old backups (keep 7 days)
find $BACKUP_DIR -name "*.sql.gz" -mtime +7 -delete

echo "Backup completed: $BACKUP_FILE.gz"

2. Redis Snapshot

#!/bin/bash
# backup-redis.sh
BACKUP_DIR="/backups/redis"
TIMESTAMP=$(date +%Y%m%d_%H%M%S)

mkdir -p $BACKUP_DIR

# Create snapshot
docker-compose exec -T redis redis-cli BGSAVE

# Copy snapshot
docker-compose exec -T redis cp /data/dump.rdb /data/dump_$TIMESTAMP.rdb

echo "Redis backup completed"

3. Restore Database

# Drop and recreate database
docker-compose exec -T postgres dropdb -U $DB_USER $DB_NAME
docker-compose exec -T postgres createdb -U $DB_USER $DB_NAME

# Restore from backup
gunzip < /backups/postgres/tg_autoposter_*.sql.gz | \
  docker-compose exec -T postgres psql -U $DB_USER $DB_NAME

Security Best Practices

1. Environment Hardening

# Restrict file permissions
chmod 600 .env
chmod 700 /var/log/tg-autoposter
chmod 700 /backups

# Set ownership
sudo chown bot:bot /home/bot/TG_autoposter -R

2. Network Security

# docker-compose.prod.yml
services:
  bot:
    networks:
      - backend
    expose:
      - 8000
      
  postgres:
    networks:
      - backend
    expose:
      - 5432

networks:
  backend:
    driver: bridge
    driver_opts:
      com.docker.network.bridge.name: br_backend

3. SSL/TLS

# Generate SSL certificate
certbot certonly --standalone -d yourdomain.com

# Configure in docker-compose.prod.yml
services:
  nginx:
    image: nginx:latest
    volumes:
      - /etc/letsencrypt:/etc/letsencrypt
      - ./nginx.conf:/etc/nginx/nginx.conf
    ports:
      - "443:443"

Troubleshooting Production Issues

Issue: Memory Leaks

# Monitor memory usage
docker stats

# Restart worker
docker-compose restart celery_worker_send

# Check logs for errors
docker-compose logs celery_worker_send | grep -i error

Issue: Database Connection Timeouts

# Increase pool size in settings
DB_POOL_SIZE = 30

# Check database status
docker-compose exec postgres psql -U bot -d tg_autoposter -c "SELECT datname, pid FROM pg_stat_activity;"

# Restart database
docker-compose restart postgres

Issue: High CPU Usage

# Identify problematic tasks
docker-compose exec flower curl -s http://localhost:5555/api/stats | python -m json.tool

# Reduce worker concurrency
CELERY_WORKER_CONCURRENCY = 2

CI/CD Integration

GitHub Actions Example

# .github/workflows/deploy.yml
name: Deploy to Production

on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Deploy to VPS
        uses: appleboy/ssh-action@master
        with:
          host: ${{ secrets.VPS_HOST }}
          username: ${{ secrets.VPS_USER }}
          key: ${{ secrets.VPS_SSH_KEY }}
          script: |
            cd /home/bot/TG_autoposter
            git pull origin main
            docker-compose -f docker-compose.yml -f docker-compose.prod.yml up -d
            docker-compose exec bot alembic upgrade head

Support and Monitoring Links

  • Flower Dashboard: http://yourserver.com:5555
  • PostgreSQL Monitoring: pgAdmin (if enabled)
  • Application Logs: /var/log/tg-autoposter/
  • Health Check Endpoint: /health (if implemented)

Maintenance Schedule

  • Daily: Check logs for errors
  • Weekly: Review resource usage
  • Monthly: Security updates, dependency updates
  • Quarterly: Performance analysis, capacity planning

Contact & Support

For issues or questions:

  1. Check logs and error messages
  2. Review GitHub issues
  3. Contact team lead
  4. Escalate to DevOps team if needed