Deploying a FastAPI Application with CI/CD Pipeline: HNG Task 3

deploying-a-fastapi-application-with-ci/cd-pipeline:-hng-task-3

Introduction

In this article, I will walk you through how I deployed a FastAPI application with continuous integration (CI) and continuous deployment (CD).

Requirements

  • Python
  • FastAPI Application
  • Docker
  • GitHub Actions Secrets
  • AWS Linux server

Step 1: Clone the Repository

The first step is to fork the repo and clone the repository to your local device
git clone https://github.com/hng12-devbotops/fastapi-book-project.git
cd fastapi-book-project/

Step 2: Setting Up a Virtual Environment

I am testing the application locally before deploying, using a virtual environment is the best practice to manage your Python dependencies. To do this you need to create and activate a virtual environment.
python3 -m venv hng
source hng/bin/activate

  • install the required dependency using this command

pip install -r requirements.txt

Step 3: Implementing the Missing Endpoint

Our API is currently unable to fetch a single book using its ID. In this step, I added a new endpoint to the FastAPI router that handles a GET request to retrieve a book based on its provided ID.

@router.get("https://dev.to/{book_id}", response_model=Book, status_code=status.HTTP_200_OK)  # New endpoint
async def get_book(book_id: int):
    book = db.books.get(book_id)
    if not book:
        raise HTTPException(
            status_code=status.HTTP_404_NOT_FOUND, 
            detail="Book not found"
        )
    return book
  • Ensure to import HTTPException from fastapi

Step 4: Testing the Endpoint

Once you’ve implemented the endpoint, it’s important to test it to ensure it behaves as expected, I did this by running this command
pytest

pytest

  • I then started the FastAPI application using Uvicorn
    uvicorn main:app --reload

app

  • The applications seem to be running fine on our localhost
    ### Step 5: Dockerizing Our Application
    create a Dockerfile in the project directory
# Use an official lightweight Python image
FROM python:3.9-slim

# Set work directory
WORKDIR /app

# Install dependencies
COPY requirements.txt .
RUN pip install --upgrade pip
RUN pip install -r requirements.txt

# Copy project files
COPY . .

# Expose the port FastAPI runs on
EXPOSE 8000

# Run the FastAPI application using Uvicorn
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Step 6: Integrating Nginx as a Reverse Proxy

To make things easier for me, I used a docker-compose.yml file to configure Nginx as a reverse proxy. To do this I created an nginx.conf file with the configurations for my application. The purpose of this configuration is to have Nginx listen on port 80 and forward incoming HTTP requests to the FastAPI application running on port 8000 inside its container.
nginx.conf

server {
    listen 80;
    server_name your_domain_or_IP;
    location / {
        proxy_pass http://app:8000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For 
        $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}
  • listen 80: Nginx listens for incoming HTTP requests on port 80.
  • server_name: Replace with your domain or IP address.
  • proxy_pass: Directs traffic to the service named app (defined in the docker-compose file) on port 8000.
    docker-compose.yml
version: '3.8'
services:
  app:
    build: .
    container_name: fastapi-app
    ports:
      - "8000:8000"

  nginx:
    image: nginx:latest
    container_name: fastapi-nginx
    volumes:
      - ./nginx.conf:/etc/nginx/conf.d/default.conf
    ports:
      - "80:80"
    depends_on:
      - app
  • The app service builds and runs our FastAPI application.
  • The Nginx service uses an Nginx image, mounts the custom configuration file, and maps port 80 of the container to port 80 on the host.
  • The depends_on command ensures that the FastAPI container starts before Nginx.

  • Then I used this command to build the containers
    docker-compose up --build

docker

compose

  • As you can see, our containers are up and running and Nginx is successfully routing incoming traffic to our FastAPI application.

Step 7: Create a Linux Server

For hosting and deploying our FastAPI application, I set up a Linux server on AWS. This server serves as the backbone of our deployment environment, where our Dockerized application will run and be accessible to users.

Step 8: Set Up the CI Pipeline

I created a GitHub Actions Workflow File for this step to automatically run tests on every pull request targeting the main branch. This ensures that any new changes are validated before they can be merged.
mkdir -p .github/workflows/
cd .github/workflows/
touch ci.yml

name: ci pipeline

on:
  pull_request:
    branches: [ main ]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: '3.9'
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install -r requirements.txt
    - name: Run tests
      run: pytest
  • push your changes to GitHub and check the status of your pipeline
    ci-pipeline

Step 9: Set Up the Deployment Pipeline

For continuous deployment, I created another GitHub Actions Workflow File named deploy.yml. This deployment pipeline is triggered whenever changes are pushed to the main branch, automating the process of updating the live application.
touch deploy.yml

name: CD Pipeline
on:
  push:
    branches: [main]
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
        uses: actions/checkout@v3

      - name: Deploy via SSH
        uses: appleboy/ssh-action@master
        with:
          host: ${{ secrets.SSH_HOST }}
          username: ${{ secrets.SSH_USERNAME }}
          key: ${{ secrets.SSH_PRIVATE_KEY }}
          script: |
            # Update package index and install dependencies
            sudo apt-get update -y
            sudo apt-get install -y apt-transport-https ca-certificates curl software-properties-common

            # Add Docker's official GPG key
            curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
            sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

            # Install Docker
            sudo apt-get update -y
            sudo apt-get install -y docker-ce docker-ce-cli containerd.io

            # Add the SSH user to the Docker group
            sudo usermod -aG docker ${{ secrets.SSH_USERNAME }}

            # Install Docker Compose
            sudo curl -L "https://github.com/docker/compose/releases/download/v2.20.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
            sudo chmod +x /usr/local/bin/docker-compose

            # Verify installations
            docker --version
            docker-compose --version

            # Navigate to the project directory and deploy
            cd /home/ubuntu/
            git clone 
            cd fastapi-book-project/
            git pull
            docker-compose up -d --build
  • Ensure your secrets are stored: Make sure SSH_HOST, SSH_USERNAME, and SSH_PRIVATE_KEY are added to your GitHub repository’s secrets.
  • Push your changes to GitHub and check the status of your pipeline.
    cd-pipeline
  • Post-Deployment Verification: Once the pipeline completes, verify that your application is running as expected.
    server

Step 10: Repository Access Requirement

Before submission, we are supposed to invite the hng12-devbotops to our GitHub account as a collaborator in our repository. To do this;

  • Open the repository you want to add a collaborator
  • Click on the Settings tab, which is usually located on the right side of the repository menu.
  • In the left sidebar, under access, select Collaborators.
  • Click on add people, add hng12-devbotops
    bot

Thanks for reading, don’t forget to drop a like and comment 😄😄 👩🏻‍💻👩🏻‍💻

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