DEPLOYMENT.md

Cloud Deployment Guide

This guide covers multiple options for deploying your text summarizer backend to the cloud.

🚀 Option 1: Railway (Recommended - Easiest)

Railway is perfect for this project because it supports Docker Compose and persistent volumes.

Steps:

1. Create Railway Account

   # Install Railway CLI
   npm install -g @railway/cli
   
   # Login
   railway login
   

2. Deploy from GitHub

   • Go to railway.app
   • Connect your GitHub repository
   • Select your SummerizerApp repository
   • Railway will automatically detect docker-compose.yml

3. Set Environment Variables In Railway dashboard, add these environment variables:

   OLLAMA_MODEL=llama3.1:8b
   OLLAMA_HOST=http://ollama:11434
   OLLAMA_TIMEOUT=30
   SERVER_HOST=0.0.0.0
   SERVER_PORT=8000
   LOG_LEVEL=INFO
   

4. Deploy

   # Or deploy via CLI
   railway up
   

Railway Advantages:

• ✅ Supports Docker Compose
• ✅ Persistent volumes for Ollama models
• ✅ Automatic HTTPS
• ✅ Easy environment variable management
• ✅ Built-in monitoring

---

☁️ Option 2: Google Cloud Run

Steps:

1. Build and Push to Google Container Registry

   # Set up gcloud CLI
   gcloud auth login
   gcloud config set project YOUR_PROJECT_ID
   
   # Build and push
   docker build -t gcr.io/YOUR_PROJECT_ID/summarizer-backend .
   docker push gcr.io/YOUR_PROJECT_ID/summarizer-backend
   

2. Deploy with Cloud Run

   gcloud run deploy summarizer-backend \
     --image gcr.io/YOUR_PROJECT_ID/summarizer-backend \
     --platform managed \
     --region us-central1 \
     --allow-unauthenticated \
     --memory 4Gi \
     --cpu 2 \
     --timeout 300 \
     --set-env-vars OLLAMA_MODEL=llama3.1:8b,SERVER_HOST=0.0.0.0,SERVER_PORT=8000
   

Cloud Run Advantages:

• ✅ Serverless scaling
• ✅ Pay per request
• ✅ Global CDN
• ✅ Integrated with Google Cloud

---

🐳 Option 3: AWS ECS with Fargate

Steps:

1. Create ECR Repository

   aws ecr create-repository --repository-name summarizer-backend
   

2. Build and Push

   # Get login token
   aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin YOUR_ACCOUNT.dkr.ecr.us-east-1.amazonaws.com
   
   # Build and push
   docker build -t summarizer-backend .
   docker tag summarizer-backend:latest YOUR_ACCOUNT.dkr.ecr.us-east-1.amazonaws.com/summarizer-backend:latest
   docker push YOUR_ACCOUNT.dkr.ecr.us-east-1.amazonaws.com/summarizer-backend:latest
   

3. Create ECS Task Definition

   {
     "family": "summarizer-backend",
     "networkMode": "awsvpc",
     "requiresCompatibilities": ["FARGATE"],
     "cpu": "2048",
     "memory": "4096",
     "executionRoleArn": "arn:aws:iam::YOUR_ACCOUNT:role/ecsTaskExecutionRole",
     "containerDefinitions": [
       {
         "name": "summarizer-backend",
         "image": "YOUR_ACCOUNT.dkr.ecr.us-east-1.amazonaws.com/summarizer-backend:latest",
         "portMappings": [
           {
             "containerPort": 8000,
             "protocol": "tcp"
           }
         ],
         "environment": [
           {
             "name": "OLLAMA_MODEL",
             "value": "llama3.1:8b"
           },
           {
             "name": "SERVER_HOST",
             "value": "0.0.0.0"
           },
           {
             "name": "SERVER_PORT",
             "value": "8000"
           }
         ],
         "logConfiguration": {
           "logDriver": "awslogs",
           "options": {
             "awslogs-group": "/ecs/summarizer-backend",
             "awslogs-region": "us-east-1",
             "awslogs-stream-prefix": "ecs"
           }
         }
       }
     ]
   }
   

---

🌊 Option 4: DigitalOcean App Platform

Steps:

1. Create App Spec

   # .do/app.yaml
   name: summarizer-backend
   services:
   - name: api
     source_dir: /
     github:
       repo: MingLu0/SummarizerBackend
       branch: main
     run_command: uvicorn app.main:app --host 0.0.0.0 --port 8080
     environment_slug: python
     instance_count: 1
     instance_size_slug: basic-xxl
     http_port: 8080
     envs:
     - key: OLLAMA_MODEL
       value: llama3.1:8b
     - key: SERVER_HOST
       value: 0.0.0.0
     - key: SERVER_PORT
       value: 8080
   

2. Deploy

   doctl apps create --spec .do/app.yaml
   

---

🔧 Option 5: Render (Simple)

Steps:

1. Connect GitHub Repository

   • Go to render.com
   • Connect your GitHub account
   • Select your repository

2. Create Web Service

   • Choose "Web Service"
   • Select your repository
   • Use these settings:

     Build Command: docker-compose build
     Start Command: docker-compose up
     Environment: Docker
     

3. Set Environment Variables

   OLLAMA_MODEL=llama3.1:8b
   OLLAMA_HOST=http://ollama:11434
   SERVER_HOST=0.0.0.0
   SERVER_PORT=8000
   

---

⚠️ Important Considerations

Model Download in Cloud

Your Ollama models need to be downloaded after deployment. Add this to your deployment:

# Add to docker-compose.yml or startup script
ollama pull llama3.1:8b

Memory Requirements

• llama3.1:8b needs ~8GB RAM
• llama3.1:7b needs ~7GB RAM
• mistral:7b needs ~7GB RAM

Cost Optimization

• Use smaller models for production: mistral:7b or llama3.1:7b
• Consider using spot instances for development
• Monitor usage and scale accordingly

Security

• Enable API key authentication for production
• Use HTTPS (most platforms provide this automatically)
• Set up rate limiting
• Monitor logs for abuse

---

🎯 Recommended Deployment Flow

1. Start with Railway (easiest setup)
2. Test with a smaller model (mistral:7b)
3. Monitor performance and costs
4. Scale up model size if needed
5. Add security features

Quick Railway Deploy:

# 1. Install Railway CLI
npm install -g @railway/cli

# 2. Login and deploy
railway login
railway init
railway up

Your backend will be live at https://your-app.railway.app! 🚀