CASE STUDY FOR MOVIE HIVE PROJECT

Overview

MovieHive was a personal project I built as part of my full stack web development course at CareerFoundry. This movie listing site is designed to help users search for various movies, add them to their favorites, and easily find the movies they want. The main goal is to provide a support fast search and filtering features. This project focuses on helping movie enthusiasts manage their favorite films according to their preferences.

Technology Stack

Frontend	React, SCSS, React router, Redux, Bootstrap	Github
Backend	Node.js, JSON, Postman, Heroku, MongoDB, JWT, Express	Github
Deployment	Netlify (Frontend), Mongoose (Backend API server, database server), GitHub	Live App

Implementation Process

Movie Data Management

Fetch movie lists from JSON files or MongoDB and provide them to the client
Create API endpoints using an Express server
Fetch and display data in React via API calls

Favorites Feature

When a user adds a movie to favorites, store it in local storage or a database
Manage a separate favorites list for easy user access

Filtering and Search Functionality

Implement real-time movie search via an input field
Apply filters such as genre, release year, etc., to display only desired movies

Cloud Usage

Frontend Deployment: Deployed as a static website using Netlify
Backend Deployment: API server hosted on MongoDB
Database Management: Separate database server on AWS or managed through JSON files
CD/CI Setup: Automated deployment pipeline via Netlify

Achievements & Lessons Learned

Achievements

Gained experience in building a full-stack application using React and Express
Successfully deployed and managed the application on Netlify and AWS
Optimized UI/UX design and filtering functionalities for better user

Lessons Learned

Improved problem-solving skills in cloud deployment

Understood the importance of API design and data management
Realized the necessity of implementing features with user experience in mind

Future Improvements

Adding more filtering options
Implementing user reviews and rating features
Enhancing UI design and optimizing for responsive web
Exploring serverless technologies like AWS Lambda