Cloud Platform Deployment

This guide covers deploying StreamBot on major cloud platforms with comprehensive instructions for each provider, including video streaming optimizations.

Platform Comparison

Platform	Ease of Use	Cost	Performance	Video Streaming	Free Tier
Railway	⭐⭐⭐⭐⭐	$$	⭐⭐⭐⭐	⭐⭐⭐⭐	✅
Heroku	⭐⭐⭐⭐	$$$	⭐⭐⭐	⭐⭐⭐	✅
DigitalOcean	⭐⭐⭐⭐	$$	⭐⭐⭐⭐⭐	⭐⭐⭐⭐⭐	❌
AWS	⭐⭐⭐	$	⭐⭐⭐⭐⭐	⭐⭐⭐⭐⭐	✅
Google Cloud	⭐⭐⭐	$$	⭐⭐⭐⭐⭐	⭐⭐⭐⭐⭐	✅
Render	⭐⭐⭐⭐	$$	⭐⭐⭐⭐	⭐⭐⭐⭐	✅

Railway (Recommended for Beginners)

Railway offers the simplest deployment process with excellent performance for video streaming.

Quick Deploy

Manual Deployment

1. Create Railway Account: Sign up at railway.app

2. Connect GitHub Repository:

   # Fork the repository first
   git clone https://github.com/AnikethJana/Telegram-Download-Link-Generator.git
   cd Telegram-Download-Link-Generator
   

3. Create New Project in Railway dashboard

4. Deploy from GitHub:

5. Connect your GitHub account
6. Select the forked repository

7. Railway will auto-detect the Python app

8. Configure Environment Variables:

   API_ID=your_api_id
   API_HASH=your_api_hash
   BOT_TOKEN=your_bot_token
   LOG_CHANNEL=-1001234567890
   DATABASE_URL=${{MongoDB.DATABASE_URL}}
   BASE_URL=https://your-app.railway.app
   PORT=8080
   VIDEO_FRONTEND_URL=https://cricster.pages.dev
   ADMINS=your_telegram_user_id
   

9. Add MongoDB Service:

10. Click "New Service" → "Database" → "MongoDB"

11. Railway will automatically provide DATABASE_URL

12. Custom Domain (Optional):

13. Go to Settings → Custom Domain
14. Add your domain and configure DNS

Railway Optimization for Video Streaming

# Railway-specific optimizations
RAILWAY_ENVIRONMENT=production
PYTHONUNBUFFERED=1
WEB_CONCURRENCY=4
MAX_WORKERS=4

# Video streaming optimizations
VIDEO_CHUNK_SIZE=1048576
STREAM_TIMEOUT=3600
MAX_CONCURRENT_STREAMS=50

Heroku

Heroku provides a robust platform with excellent addon ecosystem.

Prerequisites

• Heroku CLI installed
• Git repository ready

Deployment Steps

1. Install Heroku CLI:

   # Windows (using Chocolatey)
   choco install heroku-cli
   
   # macOS (using Homebrew)
   brew tap heroku/brew && brew install heroku
   
   # Ubuntu/Debian
   curl https://cli-assets.heroku.com/install.sh | sh
   

2. Login and Create App:

   heroku login
   heroku create your-streambot-app
   

3. Add MongoDB Addon:

   heroku addons:create mongolab:sandbox
   

4. Configure Environment Variables:

   heroku config:set API_ID=your_api_id
   heroku config:set API_HASH=your_api_hash
   heroku config:set BOT_TOKEN=your_bot_token
   heroku config:set LOG_CHANNEL=-1001234567890
   heroku config:set BASE_URL=https://your-streambot-app.herokuapp.com
   heroku config:set VIDEO_FRONTEND_URL=https://cricster.pages.dev
   heroku config:set ADMINS=your_telegram_user_id
   heroku config:set PYTHON_VERSION=3.11.0
   

5. Create Procfile:

   web: python -m StreamBot
   worker: python -m StreamBot --worker-mode
   

6. Deploy:

   git add .
   git commit -m "Deploy to Heroku"
   git push heroku main
   

7. Scale Dynos:

   heroku ps:scale web=1 worker=1
   

Heroku Video Streaming Configuration

# Configure for video streaming
heroku config:set MAX_REQUEST_SIZE=2147483648
heroku config:set STREAM_CHUNK_SIZE=1048576
heroku config:set ENABLE_RANGE_REQUESTS=true
heroku config:set VIDEO_CACHE_TTL=3600

DigitalOcean App Platform

DigitalOcean App Platform offers excellent performance for video streaming with competitive pricing.

Deployment via GitHub

1. Create DigitalOcean Account: Sign up at digitalocean.com

2. Create App:

3. Go to Apps → Create App
4. Connect GitHub repository

5. Select your StreamBot repository

6. Configure Build Settings:

   # .do/app.yaml
   name: streambot
   services:
   - name: web
     source_dir: /
     github:
       repo: your-username/Telegram-Download-Link-Generator
       branch: main
     run_command: python -m StreamBot
     environment_slug: python
     instance_count: 1
     instance_size_slug: basic-xxs
     http_port: 8080
     routes:
     - path: /
   databases:
   - name: mongodb
     engine: MONGODB
     version: "5"
   

7. Environment Variables:

   API_ID=${API_ID}
   API_HASH=${API_HASH}
   BOT_TOKEN=${BOT_TOKEN}
   LOG_CHANNEL=${LOG_CHANNEL}
   DATABASE_URL=${mongodb.DATABASE_URL}
   BASE_URL=https://your-app.ondigitalocean.app
   VIDEO_FRONTEND_URL=https://cricster.pages.dev
   ADMINS=${ADMINS}
   

DigitalOcean CDN for Video Streaming

# Enable CDN for better video streaming
curl -X POST \
  https://api.digitalocean.com/v2/cdn/endpoints \
  -H "Authorization: Bearer $DO_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "origin": "your-app.ondigitalocean.app",
    "ttl": 3600,
    "custom_domain": "cdn.yourdomain.com"
  }'

Amazon Web Services (AWS)

AWS provides the most comprehensive cloud infrastructure with global CDN for optimal video streaming.

AWS Elastic Beanstalk Deployment

1. Install AWS CLI and EB CLI:

   pip install awscli awsebcli
   aws configure
   

2. Initialize Elastic Beanstalk:

   eb init streambot --platform python-3.11 --region us-east-1
   

3. Create Environment:

   eb create streambot-production
   

4. Configure Environment Variables:

   eb setenv API_ID=your_api_id \
            API_HASH=your_api_hash \
            BOT_TOKEN=your_bot_token \
            LOG_CHANNEL=-1001234567890 \
            DATABASE_URL=mongodb://your-mongodb-url \
            VIDEO_FRONTEND_URL=https://cricster.pages.dev \
            ADMINS=your_telegram_user_id
   

5. Deploy:

   eb deploy
   

AWS DocumentDB (MongoDB Compatible)

# Create DocumentDB cluster
aws docdb create-db-cluster \
    --db-cluster-identifier streambot-cluster \
    --engine docdb \
    --master-username admin \
    --master-user-password your-secure-password \
    --vpc-security-group-ids sg-xxxxxxxx

AWS CloudFront for Video Streaming

{
  "DistributionConfig": {
    "CallerReference": "streambot-cdn",
    "DefaultRootObject": "index.html",
    "Origins": {
      "Quantity": 1,
      "Items": [
        {
          "Id": "streambot-origin",
          "DomainName": "your-app.elasticbeanstalk.com",
          "CustomOriginConfig": {
            "HTTPPort": 80,
            "HTTPSPort": 443,
            "OriginProtocolPolicy": "https-only"
          }
        }
      ]
    },
    "DefaultCacheBehavior": {
      "TargetOriginId": "streambot-origin",
      "ViewerProtocolPolicy": "redirect-to-https",
      "CachePolicyId": "4135ea2d-6df8-44a3-9df3-4b5a84be39ad",
      "Compress": true
    }
  }
}

Google Cloud Platform (GCP)

GCP offers excellent global infrastructure with competitive pricing for video streaming.

Google Cloud Run Deployment

1. Install Google Cloud SDK:

   # Linux/macOS
   curl https://sdk.cloud.google.com | bash
   
   # Windows
   # Download and install from cloud.google.com/sdk
   

2. Initialize Project:

   gcloud auth login
   gcloud config set project your-project-id
   gcloud services enable run.googleapis.com
   

3. Create Dockerfile (if not exists):

   FROM python:3.11-slim
   
   WORKDIR /app
   COPY requirements.txt .
   RUN pip install -r requirements.txt
   
   COPY . .
   
   CMD ["python", "-m", "StreamBot"]
   

4. Build and Deploy:

   gcloud builds submit --tag gcr.io/your-project-id/streambot
   gcloud run deploy streambot \
     --image gcr.io/your-project-id/streambot \
     --platform managed \
     --region us-central1 \
     --allow-unauthenticated \
     --memory 2Gi \
     --cpu 2 \
     --max-instances 10
   

5. Set Environment Variables:

   gcloud run services update streambot \
     --set-env-vars="API_ID=your_api_id,API_HASH=your_api_hash,BOT_TOKEN=your_bot_token,LOG_CHANNEL=-1001234567890,VIDEO_FRONTEND_URL=https://cricster.pages.dev"
   

Google Cloud CDN for Video Streaming

# Create Cloud CDN
gcloud compute backend-services create streambot-backend \
    --global \
    --load-balancing-scheme=EXTERNAL

gcloud compute url-maps create streambot-map \
    --default-service streambot-backend

gcloud compute target-https-proxies create streambot-proxy \
    --url-map streambot-map \
    --ssl-certificates streambot-ssl

Render

Render provides a modern platform with automatic SSL and easy deployments.

Render Deployment

1. Connect GitHub: Link your GitHub account to Render

2. Create Web Service:

3. Select your repository
4. Choose "Web Service"

5. Configure build settings:

6. Build Configuration:

   # render.yaml
   services:
     - type: web
       name: streambot
       env: python
       buildCommand: pip install -r requirements.txt
       startCommand: python -m StreamBot
       envVars:
         - key: API_ID
           value: your_api_id
         - key: API_HASH
           value: your_api_hash
         - key: BOT_TOKEN
           value: your_bot_token
         - key: LOG_CHANNEL
           value: -1001234567890
         - key: VIDEO_FRONTEND_URL
           value: https://cricster.pages.dev
         - key: DATABASE_URL
           fromDatabase:
             name: streambot-db
             property: connectionString
   
   databases:
     - name: streambot-db
       databaseName: streambot
       user: streambot
   

7. Auto-Deploy: Render automatically deploys on git push

Video Streaming Optimizations

CDN Configuration

For optimal video streaming performance across all platforms:

# Nginx configuration for video streaming
location /stream/ {
    proxy_pass http://localhost:8080;
    proxy_buffering off;
    proxy_request_buffering off;
    proxy_http_version 1.1;
    proxy_set_header Connection "";

    # Enable range requests
    proxy_set_header Range $http_range;
    proxy_set_header If-Range $http_if_range;

    # Optimize for video streaming
    proxy_cache_bypass $http_range;
    proxy_no_cache $http_range;
}

Environment Variables for Video Streaming

# Video streaming optimizations (all platforms)
VIDEO_CHUNK_SIZE=1048576
MAX_CONCURRENT_STREAMS=50
STREAM_TIMEOUT=3600
ENABLE_RANGE_REQUESTS=true
VIDEO_CACHE_TTL=3600
CORS_ORIGINS=https://cricster.pages.dev,https://yourdomain.com

Cost Optimization

Free Tier Recommendations

1. Development: Railway or Render free tier
2. Small Production: Heroku hobby tier
3. High Traffic: DigitalOcean or AWS with reserved instances

Cost Monitoring

# Set up billing alerts (AWS example)
aws budgets create-budget \
    --account-id 123456789012 \
    --budget '{
        "BudgetName": "StreamBot Monthly Budget",
        "BudgetLimit": {
            "Amount": "50",
            "Unit": "USD"
        },
        "TimeUnit": "MONTHLY",
        "BudgetType": "COST"
    }'

Monitoring and Scaling

Health Checks

All platforms should monitor these endpoints:

# Health check endpoint
curl https://your-app.com/api/info

# Video streaming health
curl -I https://your-app.com/stream/test

Auto-Scaling Configuration

# Kubernetes auto-scaling example
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: streambot-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: streambot
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80

Troubleshooting

Common Deployment Issues

Build Failures:

# Check Python version
python --version  # Should be 3.11+

# Install dependencies locally first
pip install -r requirements.txt

Environment Variable Issues:

# Test environment variables
python -c "import os; print(os.getenv('BOT_TOKEN'))"

Video Streaming Issues:

# Test streaming endpoint
curl -I https://your-app.com/stream/test
curl -H "Range: bytes=0-1023" https://your-app.com/stream/test

Performance Optimization

# Add to your deployment configuration
import os

# Optimize for cloud deployment
if os.getenv('CLOUD_PROVIDER') == 'heroku':
    # Heroku-specific optimizations
    MAX_WORKERS = int(os.getenv('WEB_CONCURRENCY', 4))
    WORKER_TIMEOUT = 120

elif os.getenv('CLOUD_PROVIDER') == 'aws':
    # AWS-specific optimizations
    MAX_WORKERS = int(os.getenv('AWS_LAMBDA_FUNCTION_MEMORY_SIZE', 512)) // 128

elif os.getenv('CLOUD_PROVIDER') == 'gcp':
    # GCP-specific optimizations
    MAX_WORKERS = int(os.getenv('CLOUD_RUN_CPU', 1)) * 2

Next Steps

After deployment:

1. Configure Custom Domain: Set up your own domain for better branding
2. Enable HTTPS: Ensure SSL certificates are properly configured
3. Set Up Monitoring: Configure uptime monitoring and alerts
4. Optimize Performance: Implement CDN and caching strategies
5. Security Hardening: Follow security best practices for your platform
6. Backup Strategy: Set up automated backups for your database

For platform-specific advanced configurations, refer to: - Docker Deployment for containerized deployments - VPS Setup for self-hosted solutions - Security Configuration for hardening your deployment

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These comprehensive cloud deployment guides are currently in development. Stay tuned for detailed instructions!