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Docker Deployment Guide

This guide explains how to deploy the Earning Robot using Docker.

Prerequisites

  • Docker installed
  • Docker Compose installed
  • .env file configured

Quick Start with Docker

1. Build the Image

docker build -t earning-robot .

2. Run with Docker Compose

# Make sure .env is configured
cp .env.example .env
# Edit .env with your credentials

# Start the robot
docker-compose up -d

# View logs
docker-compose logs -f

# Stop the robot
docker-compose down

3. Run with Docker Only

docker run -d \
  --name earning-robot \
  --env-file .env \
  -p 5000:5000 \
  -v $(pwd)/data:/app/data \
  -v $(pwd)/logs:/app/logs \
  earning-robot

Viewing Logs

# Docker Compose
docker-compose logs -f

# Docker
docker logs -f earning-robot

Updating

# Pull latest code
git pull

# Rebuild and restart
docker-compose down
docker-compose build
docker-compose up -d

Health Check

# Check if container is healthy
docker ps

# Manual health check
curl http://localhost:5000/health

Troubleshooting

Container won't start

Check logs:

docker-compose logs

Database issues

Remove and recreate:

docker-compose down
rm -rf data/
docker-compose up -d

Port conflicts

Change port in .env:

PORT=5001

Then restart:

docker-compose down
docker-compose up -d

Production Deployment

Using Docker Swarm

docker swarm init
docker stack deploy -c docker-compose.yml robot

Using Kubernetes

See k8s/ directory for Kubernetes manifests (if available).

Environment Variables in Production

Never commit .env to version control. Use:

  • Docker secrets
  • Kubernetes secrets
  • Cloud provider secret management
  • Environment variable injection

Example with Docker secrets:

echo "your_token" | docker secret create telegram_token -

Update docker-compose.yml:

services:
  robot:
    secrets:
      - telegram_token
    environment:
      - TELEGRAM_BOT_TOKEN_FILE=/run/secrets/telegram_token

secrets:
  telegram_token:
    external: true

Multi-Stage Build (Advanced)

For smaller images, use multi-stage builds:

# Build stage
FROM python:3.10-slim as builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --user --no-cache-dir -r requirements.txt

# Runtime stage
FROM python:3.10-slim
WORKDIR /app
COPY --from=builder /root/.local /root/.local
COPY . .
ENV PATH=/root/.local/bin:$PATH
CMD ["python", "main.py"]

Resource Limits

Add resource limits to docker-compose.yml:

services:
  robot:
    deploy:
      resources:
        limits:
          cpus: '0.5'
          memory: 512M
        reservations:
          cpus: '0.25'
          memory: 256M

Backup and Restore

Backup

# Backup database and data
tar -czf backup-$(date +%Y%m%d).tar.gz data/

# Or use Docker volume backup
docker run --rm \
  -v earning-robot_data:/data \
  -v $(pwd):/backup \
  alpine tar czf /backup/data-backup.tar.gz /data

Restore

# Extract backup
tar -xzf backup-20250115.tar.gz

# Restart container
docker-compose restart

Monitoring

Use Docker stats:

docker stats earning-robot

Or integrate with monitoring tools:

  • Prometheus
  • Grafana
  • Datadog
  • New Relic

Security

  1. Don't run as root: Add to Dockerfile:

    RUN useradd -m appuser
USER appuser

  2. Use secrets for sensitive data

  3. Keep images updated:

    docker-compose pull
docker-compose up -d

  4. Scan for vulnerabilities:

    docker scan earning-robot

Cloud Deployment

AWS ECS

# Build and push to ECR
aws ecr get-login-password | docker login --username AWS --password-stdin <ecr-url>
docker tag earning-robot:latest <ecr-url>/earning-robot:latest
docker push <ecr-url>/earning-robot:latest

Google Cloud Run

# Build and deploy
gcloud builds submit --tag gcr.io/<project-id>/earning-robot
gcloud run deploy --image gcr.io/<project-id>/earning-robot

Azure Container Instances

# Build and push to ACR
az acr build --registry <registry> --image earning-robot:latest .
az container create --resource-group <rg> --name robot --image <registry>.azurecr.io/earning-robot:latest

Support

For Docker-specific issues:

  • Check container logs
  • Verify .env configuration
  • Ensure ports are available
  • Check Docker daemon status