✈️ Flight Route Optimizer

Deployed in EC2 http://44.204.70.162/

A full-stack aviation routing platform that finds the most optimal flight route between airports using advanced graph algorithms such as Dijkstra, BFS, and DFS.

The project combines:

• DSA + Graph Theory
• Modern Full-Stack Development
• Authentication & Database Integration
• CI/CD Automation
• Docker + Kubernetes Deployment
• Jenkins-Based DevOps Workflow

Built as a real-world learning project to understand how scalable route optimization systems and DevOps pipelines work together in production environments.

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📌 Project Overview

Flight Route Optimizer allows users to:

• Search routes between airports
• Optimize by cost or distance
• Compare graph algorithms
• Benchmark algorithm performance
• Use dynamic + fallback airport datasets
• Authenticate users securely
• Deploy scalable containers using Kubernetes
• Automate deployments with Jenkins CI/CD

The application demonstrates practical implementation of:

• Graph Data Structures
• Shortest Path Algorithms
• REST API Architecture
• Authentication Systems
• Docker Containerization
• Kubernetes Orchestration
• Jenkins Automation
• Cloud Deployment Pipelines

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🌟 Key Features

✈️ Flight Optimization

• 🔎 Dynamic airport search
• 🧮 Algorithm comparison (BFS, DFS, Dijkstra)
• 💰 Optimize by cost or distance
• 📊 Route benchmarking & graph visualization
• 🌍 Aviation API integration with fallback airport dataset

🔐 Authentication & Backend

• User Login & Registration
• JWT-based authentication
• MongoDB Atlas integration
• Secure API handling
• Environment variable configuration

⚙️ DevOps & Deployment

• Dockerized frontend & backend
• Jenkins CI/CD pipeline
• Kubernetes deployment automation
• Automated rollout restarts
• Health verification after deployments
• Parallelized builds for faster CI execution
• ngrok integration for webhook exposure during development
• Vercel deployment support
• Render deployment alternative

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🧠 Algorithms Implemented

Algorithm	Purpose	Time Complexity
Dijkstra	Finds the shortest weighted route	O((V + E) log V)
BFS	Finds minimum-hop route	O(V + E)
DFS	Explores possible paths	O(V + E)

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🏗️ Tech Stack

Frontend

• React
• Vite
• Axios
• Tailwind CSS
• Modern responsive UI

Backend

• Node.js
• Express.js
• MongoDB Atlas
• JWT Authentication
• AviationStack API

DevOps & Cloud

• Docker
• Jenkins
• Kubernetes
• ngrok
• Vercel
• Render
• GitHub

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📂 Project Structure

flight-optimizer/
│
├── client/
│   ├── api/
│   │   └── index.js           # Serverless backend API
│   ├── src/
│   │   ├── components/
│   │   ├── pages/
│   │   ├── utils/
│   │   └── App.jsx
│   ├── public/
│   ├── vite.config.js
│   └── package.json
│
├── backend/
│   ├── routes/
│   ├── models/
│   ├── middleware/
│   ├── controllers/
│   └── server.js
│
├── kubernetes/
│   ├── deployment.yaml
│   ├── service.yaml
│   └── secrets.yaml
│
├── Jenkinsfile
├── Dockerfile
├── docker-compose.yml
└── README.md

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⚙️ Installation & Setup

1️⃣ Clone the Repository

git clone https://github.com/hridayesh68/flight-optimizer.git
cd flight-optimizer

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2️⃣ Install Dependencies

Frontend

cd client
npm install

Backend

cd backend
npm install

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3️⃣ Configure Environment Variables

Create a .env file inside the backend directory:

PORT=5000
MONGO_URI=your_mongodb_connection
JWT_SECRET=your_secret
AVIATIONSTACK_API_KEY=your_api_key

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4️⃣ Run Locally

Start Backend

cd backend
npm run dev

Start Frontend

cd client
npm run dev

Frontend runs on:

http://localhost:5173

Backend runs on:

http://localhost:5000

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🐳 Docker Setup

Build Docker Image

docker build -t flight-optimizer .

Run Docker Container

docker run -d -p 3000:3000 flight-optimizer

Explanation

Command	Meaning
docker run	Starts a container
-d	Runs container in detached mode
-p 3000:3000	Maps localhost port 3000 to container port 3000
flight-optimizer	Docker image name

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☸️ Kubernetes Deployment

The project supports Kubernetes-based deployments for scalable container orchestration.

Kubernetes Features

• Automated deployments
• Replica management
• Service exposure
• Rolling updates
• Pod health checks
• Zero-downtime deployments

Apply Kubernetes Configurations

kubectl apply -f kubernetes/

Verify Pods

kubectl get pods

Verify Services

kubectl get svc

Restart Deployment

kubectl rollout restart deployment flight-optimizer

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🚀 Jenkins CI/CD Pipeline

The project includes a complete Jenkins automation pipeline.

CI/CD Workflow

GitHub Push
     ↓
Jenkins Webhook Trigger
     ↓
Install Dependencies
     ↓
Run Tests
     ↓
Build Docker Images
     ↓
Push Images
     ↓
Deploy to Kubernetes
     ↓
Verify Deployment

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🔥 Jenkins Features Implemented

✅ Parallelized Builds

Frontend and backend Docker images can be built in parallel to reduce deployment time.

✅ Automated Secret Injection

Environment variables are securely managed using Jenkins credentials and injected during build/deployment.

✅ Health Verification

Deployment verification stage checks:

• Pod availability
• Kubernetes service health
• Successful rollout

✅ Zero-Downtime Rollouts

Uses:

kubectl rollout restart deployment <deployment-name>

to ensure the newest containers are deployed safely.

✅ Automated GitHub Integration

GitHub webhooks automatically trigger Jenkins builds whenever new commits are pushed.

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📄 Sample Jenkins Pipeline

pipeline {
    agent any

    stages {
        stage('Install Dependencies') {
            steps {
                sh 'npm install'
            }
        }

        stage('Build Docker Image') {
            steps {
                sh 'docker build -t flight-optimizer .'
            }
        }

        stage('Deploy to Kubernetes') {
            steps {
                sh 'kubectl apply -f kubernetes/'
            }
        }
    }
}

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🌐 Deployment Architecture

GitHub Repository
        ↓
     Jenkins
        ↓
 Docker Build & Push
        ↓
   Kubernetes Cluster
        ↓
Frontend + Backend Pods
        ↓
     User Access

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🔐 Security Features

• JWT Authentication
• Protected API Routes
• Environment Variable Protection
• Secure MongoDB Atlas Connection
• Jenkins Secret Credential Injection
• Kubernetes Secret Support

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📊 Benchmarking & Performance

The project benchmarks graph algorithms using generated route datasets.

Metrics include:

• Route calculation speed
• Memory usage
• Graph traversal performance
• Weighted vs unweighted path efficiency

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🐞 Recent Improvements & Bug Fixes

✅ Fixed Double /api/api Routing Bug

Resolved incorrect API path concatenation that caused:

404 Not Found

errors after hard refreshes.

Solution

• Centralized Axios base URL handling
• Unified API route management
• Improved Vite proxy configuration

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✅ Improved Jenkins Secret Handling

Migrated environment configuration handling to:

writeFile

for safer and more reliable secret injection.

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✅ Enhanced Deployment Observability

Added a dedicated:

Verify Deployment

stage inside Jenkins pipeline to immediately confirm:

• Pods are running
• Services are accessible
• Rollouts completed successfully

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✅ Optimized Build Process

• Added parallel build execution
• Improved Docker layer caching
• Explicit directory context handling
• Faster CI execution time

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📌 Future Improvements

• Real-time flight tracking
• Redis caching
• Graph visualization dashboard
• Microservices architecture
• Helm charts for Kubernetes
• GitHub Actions integration
• AWS EKS deployment
• Prometheus & Grafana monitoring
• AI-based route prediction

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🧪 Useful DevOps Commands

Git Commands

git status
git add .
git commit -m "message"
git push origin main

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Docker Commands

docker build -t flight-optimizer .
docker images
docker ps
docker stop <container-id>
docker rm <container-id>

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Kubernetes Commands

kubectl get pods
kubectl get svc
kubectl apply -f deployment.yaml
kubectl describe pod <pod-name>
kubectl logs <pod-name>

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Jenkins Commands

systemctl status jenkins
systemctl restart jenkins

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🤝 Contributing

Contributions are welcome.

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to your branch
5. Open a Pull Request

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📜 License

This project is licensed under the MIT License.

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👨‍💻 Author

Developed by Hridayesh Debsarma

Passionate about:

• Full-Stack Development
• DevOps
• Algorithms & DSA
• Cloud Computing
• System Design

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⭐ Support

If you found this project useful:

⭐ Star the repository 🍴 Fork the project 📢 Share with others

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