Zero-to-Cloud Automated API

A professional-grade DevOps pipeline that takes a Python FastAPI application from local development to a live, auto-deploying cloud service. Every git push to main automatically builds, containerises, and deploys the latest version to AWS — no manual steps required.

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What This Project Does

This project demonstrates a complete, production-style DevOps workflow:

• A Python FastAPI application with a root endpoint and a /health monitoring endpoint
• Dockerised for consistent, portable execution across any environment
• Hosted on AWS EC2 (Ubuntu Linux) and accessible publicly via the internet
• Fully automated via a GitHub Actions CI/CD pipeline — push code, and the server updates itself

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Architecture Overview

Your Laptop
    │
    │  git push
    ▼
GitHub Repository
    │
    ├── Triggers GitHub Actions (deploy.yml)
    │       │
    │       ├── Builds Docker image
    │       ├── Pushes image → Docker Hub
    │       └── SSHs into AWS EC2
    │               │
    │               ├── Stops old container
    │               └── Runs new container on :8000
    │
    └── Live API accessible at http://<SERVER_IP>:8000

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Tech Stack

Layer	Technology
Application	Python, FastAPI, Uvicorn
Containerisation	Docker, Docker Hub
Cloud Infrastructure	AWS EC2 (Ubuntu, t2.micro)
CI/CD Automation	GitHub Actions
Version Control	Git, GitHub

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Project Structure

devops-cloud-api/
├── main.py                        # FastAPI application
├── requirements.txt               # Python dependencies (fastapi, uvicorn)
├── Dockerfile                     # Container build instructions
├── .dockerignore                  # Excludes venv/ and __pycache__/
├── .gitignore                     # Excludes venv/ and __pycache__/
└── .github/
    └── workflows/
        └── deploy.yml             # CI/CD pipeline definition

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API Endpoints

Method	Endpoint	Description
GET	/	Returns a Hello World message
GET	/health	Health check for monitoring
GET	/docs	Interactive Swagger UI (auto-generated)

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How the CI/CD Pipeline Works

On every push to main, the deploy.yml workflow:

1. Checks out the latest code
2. Logs into Docker Hub using stored credentials
3. Builds a fresh Docker image and pushes it to Docker Hub
4. SSHs into the AWS EC2 server using the stored key
5. Stops and removes the currently running container
6. Pulls the new image and runs it on port 8000

No manual deployment needed after initial setup.

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Setup & Deployment

Prerequisites

• Docker and Docker Hub account
• AWS account with an EC2 instance running Ubuntu
• GitHub repository with Actions enabled

Required GitHub Secrets

Configure these in your repository under Settings → Secrets and variables → Actions:

Secret	Description
DOCKER_USERNAME	Your Docker Hub username
DOCKER_PASSWORD	Your Docker Hub password
SERVER_IP	Public IPv4 address of your EC2 instance
SERVER_KEY	Contents of your .pem private key file

EC2 Security Group Rules

Ensure your AWS Security Group has the following inbound rules:

Port	Protocol	Source	Purpose
22	TCP	Your IP	SSH access
8000	TCP	0.0.0.0/0	Public API access

Local Development

# Clone the repository
git clone https://github.com/YOUR_USERNAME/devops-cloud-api.git
cd devops-cloud-api

# Create and activate a virtual environment
python3 -m venv venv
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run locally
uvicorn main:app --reload

The API will be available at http://localhost:8000.

Running with Docker Locally

# Build the image
docker build -t devops-api .

# Run the container
docker run -p 8000:8000 devops-api

Deploy

Simply push to main:

git add .
git commit -m "Your changes"
git push origin main

GitHub Actions handles everything from there.

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AWS Instance Management

Important: Every time you stop and restart your EC2 instance, AWS assigns a new public IP address. You must update the SERVER_IP secret in GitHub to match.

Action	Effect
Stop instance	Saves your files, pauses billing for compute time
Terminate instance	Permanently destroys the server — only do this when finished

The AWS Free Tier includes 750 hours/month of t2.micro compute — enough to run one instance 24/7 without charges.

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Skills Demonstrated

• Writing and containerising a Python web API
• Authoring a multi-stage Dockerfile with layer caching optimisation
• Provisioning and securing cloud infrastructure on AWS
• Linux server administration via SSH
• Writing a GitHub Actions CI/CD workflow from scratch
• Managing secrets securely in a CI/CD context