module10_deployment_ci_cd.md

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Module 10: Deployment & CI/CD

🚀 Overview

• Dockerizing a FastAPI app
• Managing secrets with .env
• Deploying to Render, Railway, or AWS
• Intro to CI/CD with GitHub Actions

---

🐳 Dockerizing a FastAPI App

1. Create a Dockerfile
2. Use an official Python base image
3. Install dependencies
4. Run with Uvicorn
5. Test locally before deployment

---

🐳 Backend Dockerfile

FROM python:3.11-slim

WORKDIR /app

# Install system dependencies for psycopg2
RUN apt-get update && apt-get install -y \
    build-essential \
    libpq-dev \
 && rm -rf /var/lib/apt/lists/*

# Install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy backend code
COPY . .

EXPOSE 8000

# Start FastAPI with Uvicorn
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

---

🐳 Frontend Dockerfile

# Build stage
FROM node:18-alpine AS build

WORKDIR /app
COPY package.json package-lock.json ./
RUN npm install

COPY . .
RUN npm run build

# Serve stage
FROM nginx:alpine

# Copy Vite build output to Nginx HTML folder
COPY --from=build /app/dist /usr/share/nginx/html

# Optional: SPA routing support
COPY nginx.conf /etc/nginx/conf.d/default.conf

EXPOSE 80
CMD ["nginx", "-g", "daemon off;"]

---

🐳 Docker compose file

version: "3.9"

services:
  db:
    image: postgres:15
    restart: always
    environment:
      - POSTGRES_USER=postgres
      - POSTGRES_PASSWORD=postgres123!
      - POSTGRES_DB=fastapi_week10
    volumes:
      - postgres_data:/var/lib/postgresql/data
    ports:
      - "5440:5432"
  backend:
    build: ./backend
    ports:
      - "8000:8000"
    environment:
      - DATABASE_URL=postgresql://postgres:postgres123!@db:5440/fastapi_week10
    depends_on:
      - db

  frontend:
    build: ./frontend/my-app
    ports:
      - "3000:80"
    depends_on:
      - backend

volumes:
  postgres_data:

---

Database

db:
    image: postgres:15
    restart: always
    environment:
      - POSTGRES_USER=postgres
      - POSTGRES_PASSWORD=postgres123!
      - POSTGRES_DB=fastapi_week10
    volumes:
      - postgres_data:/var/lib/postgresql/data
    ports:
      - "5440:5432"

---

Database - explanation (1)

• environments:
  • POSTGRES_USER, POSTGRES_PASSWORD → Creates a database superuser and sets the password
  • POSTGRES_DB=fastapi_week10 → Creates a database named fastapi_week10 on startup.
• volumes:
  • Stores PostgreSQL’s data files inside the container --> your database data persists even if the container is deleted.
• ports: "5440:5432"
  • container port: 5432, localhost:5440.

---

Database - explanation (2)

• How you would connect?
  • From your host (outside Docker):

psql -h localhost -p 5440 -U postgres -d fastapi_week10

• Inside another container (e.g., your FastAPI app):

host=db
port=5432
user=postgres
password=postgres123!
database=fastapi_week10

---

Backend

backend:
    build: ./backend
    ports:
      - "8000:8000"
    depends_on:
      - db

---

Backend - explanation

• build: ./backend

  • Tells Docker to build an image from the Dockerfile located in the ./backend directory.

• ports:

  • "8000:8000": maps host port 8000 → container port 8000.
  • you can access it at http://localhost:8000 on your machine.

• depends_on:

  • db: Ensures that Docker starts the db service before backend

---

Frontend

 frontend:
    build: ./frontend/my-app
    ports:
      - "3000:80"
    depends_on:
      - backend

---

Frontend - explanation

• build: ./frontend/my-app
  • Docker will build an image using the Dockerfile inside ./frontend/my-app.
• ports:
  • "3000:80": maps host port 3000 → container port 80.
  • Inside the container, the app is served on port 80 (like Nginx serving static files).
  • On your local machine, you open the app at 👉 http://localhost:3000.

---

🔑 Using .env & Environment Variables

• Store secrets like:
  • Database URLs
  • API keys
  • Debug flags
• Use python-dotenv or Pydantic Settings
• Never commit .env to GitHub

---

☁️ Deployment Options

• Render

  • Simple, free tier
  • Auto deploy from GitHub

• Railway

  • Great for quick prototypes
  • Easy database integration

• AWS

  • Full flexibility
  • Options: EC2, Elastic Beanstalk, ECS, Lambda

---

⚙️ Introduction to CI/CD

• Continuous Integration (CI)
  • Automated tests
  • Linting & type checks
• Continuous Deployment (CD)
  • Auto-deploy after successful CI
• Tools: GitHub Actions, GitLab CI, CircleCI

---

💡 GitHub Actions Workflow Example

name: CI/CD
on:
  push:
    branches: [ main ]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - uses: actions/setup-python@v4
        with:
          python-version: "3.11"
      - run: pip install -r requirements.txt
      - run: pytest

---

🎯 Remember

• Containerize with Docker for portability
• Manage secrets via .env
• Choose a hosting platform that fits your needs
• Automate testing & deployment with CI/CD