🚗 Car Dealership Web Application Development

Django, React, REST APIs, IBM Cloud, Docker, Kubernetes, Sentiment Analysis, Authentication

Project Summary: Developed a full-stack Car Dealership Web Application, providing users with a seamless car browsing experience and offering dealerships valuable insights into customer feedback. The application is structured using Django for backend services and React for the frontend, with RESTful APIs to ensure efficient data handling and communication.

Dealership Listings and Filtering: Allows users to view dealerships by location, with dealership data dynamically loaded and filtered by state.

Authentication and User Management: Implemented secure authentication and user registration using Django’s framework for robust data protection.

Sentiment Analysis with IBM Cloud: Integrated IBM Watson NLP for sentiment analysis, enabling dealerships to gain insights from customer reviews.

Real-Time Inventory Updates: Displays an up-to-date list of cars by make and model, populated through backend scripts, providing users with live data.

User Reviews and Feedback: Allows authenticated users to submit reviews on dealerships, with validations ensuring data accuracy and consistency.

Containerization and Orchestration: Used Docker for containerization to enable a consistent setup across development and production environments. Kubernetes is employed for container orchestration, scaling, and resilience.

Integrated REST APIs to handle data exchange, including state-based filtering of dealerships and managing complex JSON structures.

Utilized Docker to ensure the application runs consistently across various environments, simplifying deployment.

Configured Kubernetes to manage and scale containers effectively, ensuring optimal uptime and load management in production.

Project Outcome: This Car Dealership Web Application is designed to improve user experience in car browsing and dealership discovery, while providing dealerships with sentiment insights to enhance customer engagement. Through containerization with Docker and orchestration with Kubernetes, the application achieved consistent, scalable, and resilient deployment. This project enabled me to enhance my skills in full-stack web development, cloud integration, sentiment analysis, and container management.