working as SDE1

Ansh mehta  • Peerlist

1. Full-Stack Implementation with FastAPI & React

->Developed a table booking reservation system with FastAPI (Python) backend and React.js with TypeScript frontend.
->Implemented role-based access control where users can book, edit, and manage reservations, while admins can create, update, and delete bookings.
->JWT-based authentication ensures secure access management.

2. Scalable & Containerized Deployment with Docker & AWS

->The application is Dockerized using Docker Compose with three services: frontend, backend, and MySQL database.
->Successfully deployed on an AWS EC2 instance, making it accessible via a public IP.

3.  Database & State Management

->MySQL is used as the relational database, handling structured booking data efficiently.
->Utilized Context API and Local Storage for frontend state management, ensuring smooth user interactions.

4.  Logging & Monitoring with ELK Stack

->Integrated Elasticsearch, Logstash, and Kibana (ELK Stack) for real-time log monitoring and system observability.
->Configured Elastic Agent to capture FastAPI logs, enabling powerful querying and dashboard visualizations in Kibana.

5.  Efficient Development & Type Safety

->Built the frontend with Vite for optimized performance and TypeScript for type safety.

Booking reservation application with AWS & El

Developed a backend application for generating andmanaging QR code images of URLs, including URLshortening,interactive local fi le system operations, andseamless user redirection.
Utilized Node.js fi le system module with read/writemethods for dynamic QR code creation, integrated npmpackages to enhance performance, and optimized codehandling for faster generation.
Optimized QR code generation to achieve responsetimes under 300ms, signifi cantly enhancing effi ciencyand improving the overall user experience.

ScrambleQr- full backend service genrating QR

What It Does??
This project focuses on building a Tiered Search System using Apache Solr, designed to improve search relevance by prioritizing results based on weighted fields. It ensures users get the most accurate and meaningful results when searching through large datasets.

How It Works??
We implemented a custom Tiered Search Handler in Solr that categorizes searchable fields into different priority levels. By assigning relevance scores, the system enhances search ranking and precision. Additional features like highlighting, boosting, and debugging further refine the search experience.

Technology Used:

Apache Solr – For full-text search and indexing, providing high scalability.
Docker & Docker Compose – For easy deployment and containerized setup.
Zookeeper – To manage distributed indexing and ensure high availability.

In future i am planning to :

explore AI-driven search enhancements, integrating semantic search and NLP-based ranking to further improve search relevance.

Tiered Search System with Solr

TravBook is a comprehensive travel booking platformthat supports travel package bookings, personalizedtravel planning, and effi cient expense tracking, coveringdata on 40+ prime destinations in India.
Actively collaborated with a team of 4 in developingbackend features, crafted database schemas, andcontributed to the project’s research paper, which waspublished and approved by academic mentors.
Gathered feedback from 70+ users to refi nefunctionalities, leading to a signifi cant improvement inuser engagement and satisfaction with the platform’senhanced features.

Travbook- MERN stack travel planning applicat

Developed a CRUD application for managing user blogposts, featuring media management including photos,videos, likes, comments, and media validation, along withauthentication, authorization and mailing functionalities.
Implemented secure authentication using JWT andsession cookies, utilized EJS for dynamic contentrendering, integrated Cloudinary for managing mediafi les, and employed Nodemailer for sending emails uponsuccessful fi le uploads.
Conducted REST API testing with Postman on 100+requests, reducing bugs and improving user satisfaction.