Building with Docker: A Collaborative Learning and Deployment Story
1. Introduction
A hands-on Docker Demo Session was successfully conducted with the objective of introducing students to modern containerization technology. The session focused on helping participants understand how Docker is used in real-world software development to build, ship, and run applications efficiently. With active participation from more than 50 students, the workshop created an interactive learning environment that combined theory with practical exposure.
2. Learning Outcomes
Through this session, students gained a clear understanding of Docker fundamentals, including images, containers, and Docker workflows. They learned how containerization simplifies application deployment,
improves scalability, and ensures consistency across different environments. The session also highlighted the importance of Docker in DevOps and cloud-based applications, enabling students to connect theoretical concepts with real-time industry use cases
3.Spoken Tutorials
To strengthen conceptual understanding, students were encouraged to explore Spoken Tutorials, which provide self-paced learning through audio-video explanations. These tutorials help learners revise Docker concepts such as installation, basic commands, and container management at their own convenience.
🔗 Spoken Tutorial Link: Tutorial link
4.Implementation
During the implementation phase, participants actively worked on Docker by executing basic commands, running containers, and understanding how applications are packaged and deployed using Docker images. Real-time demonstrations of projects built using Docker helped students visualize practical use cases. This hands-on approach ensured that learners not only understood Docker theoretically but also developed confidence in applying it practically, making the session both effective and impactful.
5. Docker Demo Session
We successfully conducted a hands-on workshop focused on Docker applications, where we explained in detail the real-time projects that we had built using Docker. The session aimed to help students understand how Docker can be used to build, ship, and run applications efficiently through containerization. More than 50 students actively participated in the workshop, and all participants were encouraged to work on a project during the session to gain practical exposure. This approach helped students not only understand the concepts theoretically but also apply them practically, making the workshop highly interactive and effective.
LinkedIn links
JYOSHIKA - https://www.linkedin.com/posts/jyoshika-ramu-09a383327_docker-containerization-devops-activity-7374697510033854464-mjb
AYUSHI - https://www.linkedin.com/posts/ayushi-singh-0b2478329_project-demonstration-experience-activity-7372519216136077312-O-a9
SWATI - https://www.linkedin.com/posts/swati-gouda-4a17b731b_docker-containerization-devops-activity-7372525409919381504-7BOi
Name of the students with their projects:-
Description about projects
1.Cloud Computing Project Documentation :- By Charan Gnanasekar Geetha
The project is a Dynamic Multi-Language Code Runner built using Docker, Node.js, and React. It features a backend API that receives code and language input, executes it inside a secure Docker container, and returns the output. The Docker image is based on Ubuntu 22.04 and includes compilers/interpreters for 25+ languages, controlled by a run.sh script. A React frontend provides a code editor, language selector, and output view. The system demonstrates isolated, scalable execution of user code, full frontend–backend communication, and practical use of REST APIs and containerization. It successfully mimics online code-runner platforms with secure, portable execution environments.
2. Personal Cloud Storage System with Docker:- By Gaurav Singh
This project explains how to build a secure, self-hosted personal cloud storage system using Docker. It progresses through three phases: first, creating a Flask backend, simple HTML/JS frontend, Docker Compose setup, and persistent volumes. Next, the system is upgraded to a React frontend, multi-stage Docker builds, analytics with Chart.js, CORS handling, and Material-UI-based UI with drag-and-drop uploads. Finally, the containers are production-hardened by adding non-root users, health checks, optimized images, and pushing tagged builds to Docker Hub. The result is a fully containerized, secure, persistent, and professional cloud storage application that runs on any system with Docker.
3. Weather Application Cloud Deployment:- By Arman Ranjan
This project demonstrates the complete lifecycle of building, containerizing, and deploying a cloud-based weather application using Flask, Docker, and AWS EC2. It begins with developing a Python Flask app that fetches real-time weather data from the OpenWeather API and serves it through an HTML interface. The application is containerised using a Dockerfile, tested locally, and pushed to Docker Hub for global access. Finally, an Ubuntu-based AWS EC2 instance is provisioned, configured with Docker, and used to pull and run the container as a live service on port 80. The result is a fully deployed, scalable, and publicly accessible weather application on the cloud.
4.RAGChat: A Web App for Intelligent PDF Information Retrieval and Question Answering: - By Arjun A
RAGChat is an intelligent, containerised document query system that enables users to upload PDFs and ask natural-language questions to retrieve precise, context-aware answers. Built using the Retrieval-Augmented Generation (RAG) pipeline, it extracts text, generates vector embeddings, stores them in ChromaDB, and uses Together AI LLMs for response generation. Development progressed in three phases: a single-container CLI proof of concept, a full web application using FastAPI and Streamlit, and a multi-container deployment orchestrated with Docker Compose. Separate frontend and backend containers were built and published on Docker Hub. The final system demonstrates effective AI-driven document understanding, practical Docker usage, and scalable architecture.
5.Cookbook Recipe App Dockerisation: - By Mrigankrautela
The RecipeBook project is a full-stack CRUD web application built using Flask, SQLite, and Docker. It allows users to create, view, update, search, and delete recipes through a clean HTML/CSS interface while storing all data in a persistent SQLite database. After completing local development, the app was fully containerised using a custom Dockerfile and Docker Compose configuration, ensuring portability and consistent deployment. A dedicated Docker network and persistent volume were added to support scalable architecture and long-term data retention. The final Dockerized image (mrigankr/recipebook) was deployed on an EC2 instance, demonstrating a complete, real-world pipeline from development to production.
6.Smart Home Monitoring System Using Docker: - By Soham Shahapure
This project builds a fully containerized smart home monitoring system using a microservices architecture. A Python-based sensor-publisher simulates multi-room temperature and humidity data and sends it to a Mosquitto MQTT broker. A Python data-subscriber listens to MQTT topics, processes sensor streams, and stores them in InfluxDB, a time-series database. Grafana visualizes these measurements through real-time dashboards. Docker Compose orchestrates all containers, ensuring reproducibility, portability, health checks, resource limits, and persistent storage. Additional Bash management scripts handle backups, logs, service status, retries, and graceful shutdown. The system demonstrates a production-style IoT pipeline covering data generation, transport, ingestion, storage, and visualization—ready for scaling, automation, or cloud deployment.
7. Smart PDF Summarizer using AI, FastAPI, React, and Docker: - By Hansa Leo Chemmanda
The Smart PDF Summarizer is an AI-powered web application designed to automatically read and summarize PDF documents using advanced NLP models. The system consists of a FastAPI backend for text extraction and summarization, and a React frontend for file upload and result display. Across three development phases, the project evolved from a single-container application into a fully modular, multi-container architecture managed through Docker Compose. The backend uses PyPDF2, pdfplumber, and HuggingFace’s BART/DistilBART models to achieve high-accuracy text extraction and concise summaries, while the frontend provides a clean, user-friendly interface. Both containers were optimized using lightweight base images and deployed to Docker Hub for easy distribution. The final system supports health checks, restart policies, and efficient memory usage, summarising large PDFs within seconds. Overall, the project showcases strong integration of AI, full-stack development, and containerization, resulting in a scalable, portable, and production-ready summarization platform.
8. TRAVELLIO-An AI Based Travel Planner: - By Thinakkar T
The Travellio – AI Travel Planner is a full-stack, Dockerized web application designed to simplify travel planning. Users enter preferences through an interactive frontend, which communicates with a Flask backend that uses the Gemini API to generate personalized travel itineraries. DA1 focused on building and containerizing the static frontend using nginx. DA2 introduced a separate backend container and connected both using Docker Compose. DA3 consolidated the complete multi-container architecture and prepared final documentation and demonstration. The project demonstrates modern full-stack development, containerization, and microservice design while delivering an intelligent, user-friendly travel-planning solution.
9. Real-time Chat Application Using Docker :- By Devnarayan R
This project demonstrates containerization of a real-time chat application using Docker. The system includes a responsive frontend (HTML, CSS, Socket.IO client) served through an Nginx container and a backend Node.js + Express + Socket.IO server running in a separate container. Docker Compose orchestrates both services with secure internal networking. The frontend and backend were built using lightweight Alpine images, with production-only dependencies and a non-root backend user for security. Real-time messaging, multi-user broadcasting, and smooth inter-container communication were successfully achieved. The project highlights Docker-based microservice design, optimization, and practical full-stack deployment techniques.
10.End-to-End ETL Pipeline for Network Security using Docker & AWS: -By Kannepalli Venkata Bangaru Sreekar
This project presents a modular, cloud-native ETL workflow for network security analytics using Docker, AWS, and automated CI/CD pipelines. The system ingests raw data from multiple sources, stores it in MongoDB Atlas, validates schemas, detects drift, and transforms data through scaling, encoding, and imbalance handling. Machine learning models are trained, evaluated, and deployed as containerized services via AWS. Each ETL stage runs in an independent Docker container, ensuring reproducibility, security, and easy scaling. The pipeline produces structured artifacts, metrics, and deployment logs, demonstrating an end-to-end, automated, and production-ready ML workflow for real-world security applications.
11.Real-Time Chat Application: - By Vinayak Uttam Killedar
This project develops and deploys a real-time “Who’s Online” chat application using Node.js, React, Socket.IO, Redis, Docker, and AWS EC2. The backend manages messaging, online presence, and typing indicators, while the frontend provides an interactive chat interface. All components are containerized using multi-stage Docker builds, Docker Compose, networks, and volumes. Images are pushed to Docker Hub and deployed on an Ubuntu EC2 instance with Nginx as a reverse proxy. Redis ensures fast presence tracking, and the app becomes globally accessible via the EC2 public IP. The project demonstrates a complete DevOps workflow from local development to cloud deployment.
12.MemoMaster — A Dockerized Cloud Note-Taking Application: - By Rishabh Jain
MemoMaster is a lightweight cloud-style note-taking application built using a fully containerized three-tier architecture. The system consists of a frontend served through NGINX, a Node.js + Express backend providing REST APIs, and a MongoDB database for persistent storage. Each component runs in its own Docker container, connected through Docker networks and managed using docker-compose for portability and reproducibility. MongoDB volumes ensure data persistence, while the backend handles all CRUD operations via Mongoose. The project demonstrates modern DevOps practices, including multi-container orchestration, Docker image creation, and cloud-ready modular design, showcasing a scalable and efficient full-stack deployment model.
13.WEATHER WEBSITE PROJECT USING DOCKERS: - By Abhishek Prabakar
The Weather Website Project is a full-stack, multi-container application that delivers real-time and ML-based weather forecasts using Docker. The frontend, built with HTML, CSS, and JavaScript, is served through Nginx, while the Flask backend integrates OpenWeatherMap APIs, processes weather data, and uses a trained ML model to predict temperatures for the next 3, 6, and 9 hours. MongoDB provides persistent storage for logs, alerts, and historical queries. Each component runs in its own Docker container, orchestrated using Docker Compose. The project demonstrates scalable deployment, modular architecture, real-time alerts, and practical DevOps integration across frontend, backend, and database services.
14. Sentiment Analysis Multi-Container Setup Dockerized :- By Aryan Agarwal
The Multi-Service Docker Application with NGINX is a containerized microservices-based system that integrates machine learning, data analytics, logging, and frontend interaction. The Streamlit frontend enables users to perform sentiment analysis and dataset visualization through an interactive interface. Backend services include a VADER-based sentiment analysis service, a dataset analysis service generating correlation heatmaps, and a logging service using SQLite3 to track system activities. NGINX functions as a reverse proxy and load balancer, ensuring secure and efficient request routing. Docker Compose orchestrates all services, enabling scalability, modularity, fault tolerance, and simplified deployment following modern DevOps principles.
15. Vibehive Dockerized Blog :- By Sai Sathya Krishna A R
VibeHive is a full-stack web application featuring a blog and real-time chat, developed through a three-phase progression to reflect real-world software development. DA1 implemented a serverless MVP using HTML, CSS, JavaScript, and Firebase for authentication and chat. DA2 refactored the system into a 3-tier architecture with a Node.js/Express backend and PostgreSQL database for persistent storage. DA3 containerized the complete application using Docker and Docker Compose, isolating frontend, backend, database, and admin services. The final architecture ensures portability, scalability, and reliability through custom networking, volumes, and production-ready configurations, demonstrating modern DevOps and containerization best practices.
16. A Dockerized Full-Stack To-D5o List Application :- By Arjun Mahalingam
This project presents a full-stack, 3-tier To-Do List web application built using a React frontend, a Node.js/Express backend, and a PostgreSQL database, all containerized with Docker. Each component runs in its own isolated container and is orchestrated using Docker Compose to ensure scalability, portability, and reproducibility. The frontend handles user interaction, the backend processes RESTful API requests and business logic, and PostgreSQL provides persistent data storage through Docker volumes. Custom Docker images were built and published to Docker Hub. The project demonstrates best practices in containerization, service networking, automated database initialization, and end-to-end deployment of modern web applications.
17. Pathfinder: A Dockerized Node.js Backend with Kubernetes Deployment and Monitoring:- By Harishankar R
Pathfinder is a Node.js backend application developed for an event management and campus navigation platform, demonstrating a complete DevOps lifecycle. The project began with containerizing the Express-based backend using Docker and securely connecting it to a cloud-hosted MongoDB Atlas database through environment variables. It was then deployed to a local Kubernetes cluster using Minikube, with deployments, services, and resource limits defined through YAML manifests. Auto-scaling and observability were implemented using Prometheus and Grafana via Helm. The final outcome is a scalable, monitored, and portable backend system, showcasing practical experience in containerization, orchestration, monitoring, and modern cloud-native DevOps practices.
18.SecureLynk – Secure IoT Data Transmission Using Docker & Cloud Introduction:- By G Nandha Kishore
SecureLynk is a Docker-based IoT security project that demonstrates safe data transmission using a three-tier architecture. It consists of an IoT Simulator that generates device data, a Cloud Application that encrypts and stores messages, and a Receiver Dashboard that authenticates users to decrypt and view data. Each module runs in its own Docker container and communicates over a virtual network while sharing a SQLite database through a common volume. Lightweight security is implemented using XOR Cipher and Base64 encoding. Docker Compose orchestrates all services, enabling modular deployment, secure communication, real-time analytics,
and easy scalability in a cloud-like environment.
19. Building and Containerising a Multi-Agent AI Web Application using Docker and Ollama: - By Sankar Raja
The AI Agent System is a fully containerised web application that delivers multiple AI-powered text services through a modular microservice architecture. Built with a Next.js frontend and an Ollama backend, the system supports five agents: Summarizer, Email Writer, Resume Tailor, Code Explainer, and Meeting Notes Generator. The project evolved across three phases—from a single-container prototype to a dual-container setup orchestrated with Docker Compose, and finally to deployment-ready images published on Docker Hub. By leveraging Docker, internal networking, and local LLM inference, the system ensures portability, scalability, consistent performance, and seamless AI-driven user interaction.
20. Microservices, Macro Impact: Building Scalable Apps with Docker:- By Catherine George
The AI Agent System is a fully containerized web application that delivers multiple AI-powered text services through a modular microservice architecture. Built with a Next.js frontend and an Ollama backend, the system supports five agents: Summarizer, Email Writer, Resume Tailor, Code Explainer, and Meeting Notes Generator. The project evolved across three phases—from a single-container prototype to a dual-container setup orchestrated with Docker Compose, and finally to deployment-ready images published on Docker Hub. By leveraging Docker, internal networking, and local LLM inference, the system ensures portability, scalability, consistent performance, and seamless AI-driven user interaction.
21.AI -TO DO LIST:- By Muthuram M
The AI To-Do List is a Docker-based task management web application enhanced with intelligent task organization and prioritization. The project evolved across three stages, starting with a single-container Node.js application and expanding into a scalable multi-container architecture using Docker Compose. The final system separates frontend, backend, database, and optional phpMyAdmin services, ensuring modularity, persistence, and easy deployment. A MySQL database with Docker volumes guarantees data durability, while Traefik handles efficient request routing. The project demonstrates practical full-stack development, container orchestration, and microservice design, highlighting how Docker simplifies deployment, scalability, and maintenance of AI-enabled applications.
22.Building & Dockerizing a Task Manager App — Three-Part Journey:- By Sarvepalli Krishna Pranav
This project presents a three-phase journey of building a containerized, AI-enhanced Task Manager web application using Docker. Starting with Docker fundamentals, the system evolved from a static frontend prototype to a fully orchestrated multi-container architecture. The final solution includes a frontend served via Nginx, a Node.js and Express backend handling authentication and task management with Firebase, and a FastAPI-based AI assistant that summarizes tasks using the Hugging Face API. Docker Compose enables seamless service communication, portability, and reproducibility. The project demonstrates real-world DevOps practices, microservice design, scalable deployment, and effective documentation through blogs, demos, and Docker Hub publishing.
23.House Rent Predictor — Dockerized App with Health Checkpoints and Docker Hub Deployment:- By Shebin Chinnaraj Sivakumar
The House Rent Predictor is a Dockerized machine learning web application that predicts monthly house rent based on property features such as BHK, area, city, furnishing status, and tenant preference. A pre-trained regression model is integrated into a Streamlit-based user interface for real-time predictions. The system is deployed using a multi-container Docker architecture consisting of a Streamlit application container and a MySQL database container, orchestrated with Docker Compose. Health checks, persistent storage using Docker volumes, and environment-based configuration ensure reliability and portability. The final application image is published on Docker Hub, enabling easy deployment, scalability, and reproducible machine learning inference across environments.
24. Web_Vulnerability_Scanner :- By Keerthivasan E
This blog documents the design and deployment of VulnScan Analyzer, a full-stack web vulnerability scanner built with a React frontend and Flask backend. The tool audits web applications for common security issues such as missing security headers, weak cookie policies, unvalidated HTML forms, and information disclosure through HTTP responses. Developed in three structured phases, the project integrates frontend–backend communication, robust scanning logic, and clear result visualization. Containerized using Docker, the application ensures portability and reproducibility across environments. The scanner was successfully demonstrated at the ACM DockerShowdown event at VIT Chennai, validating its practical relevance, ethical design, and real-world cybersecurity utility.
25.AI-Powered Business Analyzer :- By Gaurish Kumar A S
This project presents the development of an AI-powered Business Analyzer platform built using Docker containerization and modern cloud computing principles. Designed for entrepreneurs and business professionals, the system delivers intelligent market research, strategic insights, and professional business reports through a scalable web application. The platform follows a microservices-based architecture, integrating a React frontend, FastAPI backend, AI-driven analysis workflows, and robust infrastructure orchestration. By leveraging Docker, Docker Compose, and multiple cloud-ready services, the project demonstrates real-world implementation of containerized applications, AI integration, and production-grade deployment practices, making it a comprehensive showcase of modern software engineering and DevOps concepts.
26. Automated CI/CD Pipeline for Spring Boot Application: - By Jivin K S
This project demonstrates the implementation of a complete DevOps CI/CD pipeline for a Spring Boot application using industry-standard tools. Continuous Integration is achieved through GitHub Actions, Maven, and JUnit to automate building and testing on every code commit. Continuous Deployment is implemented using Docker, Docker Hub, and a self-hosted GitHub runner to containerize and deploy the application automatically. Continuous Monitoring is enabled using Nagios and the check_http plugin to track application uptime and performance. The pipeline minimizes manual intervention, ensures consistent deployments, and provides proactive monitoring, showcasing a real-world, end-to-end DevOps automation workflow.
27. ScholarScope - A Multi-Container Scholarship Search Portal:- By V Padmasree
ScholarScope is a full-stack web application designed to help students search and filter scholarships efficiently. The project follows a three-phase development approach. DA1 establishes the foundation by building a PostgreSQL database and a Flask backend API. DA2 integrates a React frontend to enable user interaction and dynamic data retrieval. DA3 completes the system through full containerization using Docker Compose and an Nginx reverse proxy, creating a production-ready deployment. The application runs as four isolated services—database, backend, frontend, and gateway—ensuring scalability, portability, and reliability. ScholarScope demonstrates modern DevOps practices, microservice architecture principles, and real-world containerized application deployment.
28. StegoShield: Building a Secure Image Steganography App with LSB, XOR, and Docker :- By Ashley Dylan J
StegoShield is a secure, containerized image steganography web application that hides encrypted messages inside images using XOR encryption and LSB (Least Significant Bit) embedding. The project follows a three-part approach: local application development and testing, single-container Dockerization, and multi-container orchestration using Docker Compose. A Streamlit-based interface enables easy encoding and decoding of messages with zero visible image distortion. Docker ensures portability, reproducibility, and consistent deployment, while Docker Compose adds persistence, health checks, and auto-restart capabilities. The project demonstrates strong DevOps practices, secure data handling, and production-ready container orchestration suitable for real-world deployment.
29. StreamFlow Analytics Platform :- By Rohith Ganesh Kanchi
StreamFlow Analytics Platform is a production-grade, real-time stock market data processing system built using a microservices architecture. It processes live stock tick data for major technology stocks using Apache Kafka for event streaming and TimescaleDB for time-series storage. The platform consists of 13 Dockerized services orchestrated with Docker Compose, covering data generation, analytics, storage, alerting, APIs, WebSocket streaming, monitoring, and visualization. A React-based dashboard provides real-time updates and historical insights, while Prometheus and Grafana enable observability. The project demonstrates scalable, fault-tolerant, cloud-native design and delivers sub-second end-to-end data processing performance.
30.CodeMaster:- By S.D.Madhumitha
CodeMaster is a fully containerized competitive programming platform designed for automated code judging and real-time evaluation. Built using a microservices architecture, it integrates six Dockerized services: React frontend, Node.js backend API, judge worker, MongoDB, RabbitMQ, and Redis. The system supports real-time submission tracking through Socket.IO, asynchronous code execution via message queues, and persistent data storage. Docker Compose orchestrates all services with health checks, restart policies, and isolated networking, enabling single-command deployment. CodeMaster successfully evaluates multiple problem types with high accuracy, demonstrating a scalable design, adherence to DevOps best practices, and the development of production-ready, containerised applications.
31. TalkHub: A Containerized Social Media Platform: - By Azhagesh.S
TalkHub is a production-ready, containerized social media platform inspired by Reddit, built to demonstrate modern full-stack and DevOps practices. Developed using React with TypeScript, Node.js, MongoDB, Redis, Prometheus, and Nginx, the platform follows a six-container microservices architecture orchestrated using Docker Compose. TalkHub supports user authentication, community creation, post management, voting systems, and a comprehensive admin panel with role-based access control. Redis caching improves performance, Prometheus enables monitoring, and Nginx handles secure request routing. The project highlights scalable design, container security, observability, and real-world deployment readiness.
32. Dockerize Your Personal Portfolio :- Nukala Satwik
Dockerizing a personal portfolio website into a professional, multi-container application. The project is divided into three parts: containerizing the React frontend, building and Dockerizing an Express backend with SQLite for persistent message storage, and orchestrating both services using Docker Compose. A terminal-style interface allows users to send and view messages, demonstrating real-world API interaction and data persistence through Docker volumes. By the end of the project, the portfolio becomes fully portable, reproducible, and easy to deploy with a single command, highlighting practical Docker fundamentals for beginners.
33. Containerizing and Orchestrating of TaskZen :- By Dhilip Kumar P
This document describes the complete containerization and deployment of the full-stack web application TaskZen, consisting of a FastAPI backend and a React frontend. The project demonstrates a practical DevOps workflow using Docker and Docker Compose. Separate Dockerfiles were created for frontend and backend, images were built and tested independently, and services were orchestrated using Docker Compose for seamless communication. The application follows a clean client-server architecture, with Nginx serving the frontend and FastAPI handling backend logic connected to Supabase. Finally, the images were published to Docker Hub, enabling easy distribution, portability, and deployment across any Docker-enabled system.
34. DeployFlow:- By Giridharen Goguladhevan
DeployFlow is a self-hosted Platform-as-a-Service (PaaS) that demonstrates end-to-end cloud application deployment using Docker-based microservices. Built with Node.js, Next.js, MongoDB, Redis, Nginx, and custom Git and DNS servers, it supports automated, Git-based CI/CD workflows. The platform includes a real-time monitoring dashboard, RESTful backend API, container orchestration, and secure authentication. Across three phases, the project establishes core infrastructure, builds an interactive frontend with live logs and metrics, and integrates all services into a production-ready system. DeployFlow highlights key cloud-native concepts such as containerization, orchestration, service discovery, scalability, persistence, and DevOps best practices.
35. Carbon Calculator :- By Sakthidhara B
This project explores Docker-based containerization of a full-stack carbon footprint calculator using a React frontend and Node.js backend. Developed in three phases, it demonstrates core cloud and DevOps practices. Part 1 focuses on Docker Desktop setup, creating Dockerfiles, and orchestrating services with Docker Compose. Part 2 enhances the system with health checks, persistent logging, secure container networking, and reliable service orchestration. Part 3 publishes custom images to Docker Hub, enabling reproducible, production-ready deployments. The project showcases container health monitoring, automatic recovery, and portability, highlighting how Docker simplifies scalable application deployment and reinforces modern cloud computing and DevOps fundamentals.
36. Expense Splitter using Docker :- By Meghana Y
This project documents the design and deployment of a scalable, three-tier Expense Splitter application using Docker and Docker Compose. It progresses through three phases: DA1 establishes persistent data storage using a PostgreSQL container with volume management; DA2 expands into a full microservice architecture by integrating a Flask web application, Redis caching, and an Nginx reverse proxy; DA3 focuses on professional documentation, architectural visualization, and public distribution via DockerHub and GitHub. The system demonstrates container orchestration, secure configuration, health checks, and best practices such as non-root execution. Overall, the project showcases practical expertise in cloud-native development, scalability, and maintainable microservice design.
37. LegalMind AI — Dockerized Legal Document Analyzer with Google Gemini and Docker Hub Deployment :- By Palaniyappan S
LegalMind AI is a fully containerized, AI-powered legal document analysis platform built using a microservices architecture. It automates clause extraction, risk classification, and explanation of legal documents using a FastAPI backend integrated with Google Gemini AI and a lightweight Nginx frontend. The project is implemented in three phases: backend containerization, frontend and reverse proxy setup, and deployment to Docker Hub. Docker Compose orchestrates the multi-container system, ensuring seamless inter-service communication. The solution demonstrates scalable design, clean separation of concerns, secure API routing, and reproducible deployment, showcasing strong proficiency in Docker, cloud-native development, and AI-driven application engineering.
38. Dockerized Expense Tracker Web Application:- By U Yuvaraj
The Expense Tracker is a full-stack, Dockerized web application that enables users to efficiently manage personal finances. It features secure authentication, transaction management (add, edit, delete), real-time summaries, and category-wise analytics. The backend, built with Node.js and Express, connects to a PostgreSQL database for persistent storage, while the frontend uses HTML, CSS, and JavaScript, served via Nginx with API proxying. Each component runs in a separate Docker container, orchestrated using Docker Compose for seamless networking, volume management, and reproducible deployment. The project demonstrates full-stack development, containerization, multi-container orchestration, and cloud-ready deployment, with all images hosted on Docker Hub for easy reuse.
39.Containerized Real-Time Web Chat Application Monitoring Using Kubernetes, Prometheus and Grafana:- By Roshan Parveen
This project demonstrates a fully containerized, real-time web chat application with automated orchestration, monitoring, and performance evaluation. The system uses Docker to package a React frontend, Node.js backend, and traffic simulator into isolated containers, orchestrated with Docker Compose for resilience and auto-recovery. Deployment on a Kubernetes Minikube cluster enables scalable replicas, rolling updates, and service discovery. Observability is achieved through a dual-layer Prometheus and Grafana setup, providing real-time metrics on CPU usage, memory, latency, and throughput. Performance testing with Apache Benchmark validated stability under load. The project integrates containerization, orchestration, monitoring, and optimization, showcasing cloud-native DevOps practices for resilient microservices.
39.ResumeGenAI: AI-Powered Resume Generation with Semantic Search:- By S.Madhavan
ResumeGenAI is an AI-powered web application that generates professional resumes tailored to specific job roles. Leveraging FAISS-based semantic search with Sentence-BERT embeddings, it intelligently matches user qualifications to creative, minimal, or modern templates. Users complete a multi-step form capturing personal, educational, and professional details, after which the system populates DOCX and PDF templates with smart placeholder replacement. The platform employs a microservices architecture with a Flask backend for AI processing and an Nginx frontend for responsive interaction, fully containerized with Docker and orchestrated via docker-compose. ResumeGenAI reduces creation time, ensures ATS-friendly formatting, and demonstrates scalable, efficient AI-driven document automation.
40. AI RADIO JOCKEY FOR BLR NOW:- By Kaustubh
This Design Assignment implements an AI Radio Jockey pipeline using three containers: news_gen, mixer, and Icecast. news_gen continuously fetches news from Firestore, generating RJ-style scripts via the Gemini API with metadata for duration, tone, and priority. The mixer converts scripts to speech, blends them with music beds, jingles, and effects using FFmpeg, normalizes loudness, and pushes live audio to Icecast. Icecast streams the final broadcast over HTTP, providing a stable endpoint with admin controls. Modular containerization allows independent scaling and updates. The system demonstrates an end-to-end AI-driven, automated radio broadcast pipeline with resilience, flexibility, and real-time streaming capabilities.
41. API Testing Suite using Docker:- By V A Sri Harsha
This Docker Assignment builds a containerized API testing framework using Docker and Newman. Part 1 creates a lightweight Node.js-based Newman container to run Postman collections and generate HTML reports. Part 2 introduces Docker Compose for orchestration, volume mapping for report persistence, and JSON reporting, enabling tests to run with a single command. Part 3 documents the entire process, including architecture, workflow, and results. The system features layered architecture with containerized test execution, orchestrated builds, and persistent reporting. Outcomes include an automated, reproducible API testing pipeline, portable images, and comprehensive documentation, demonstrating how containerization enhances efficiency, reliability, and scalability in modern DevOps practices.
42. Dockerized Flask Web Application with Redis, PostgreSQL & Nginx :- By Prasenjit Choudhury
This project demonstrates a Dockerized full-stack web application built with Flask, Redis, PostgreSQL, and Nginx. Phase 1 implemented a visitor counter with Redis for real-time updates and PostgreSQL for persistent logging, accessible via Flask routes. Phase 2 containerized the application, database, cache, and Nginx reverse proxy using Docker and orchestrated them with Docker Compose for seamless deployment. Phase 3 enhanced the frontend with Bootstrap and Chart.js to visualize visit analytics. The architecture allows dynamic data rendering, scalable containerized services, and efficient orchestration. The project highlights containerization’s role in simplifying deployment, enabling microservice-like isolation, and creating production-ready, fully integrated web applications.
43.Python Code Explainer - Dockerized Project:- By Prasenjit Choudhury
This project demonstrates a Dockerized full-stack Hostel Finder web application with frontend and backend services running in separate containers. The backend, built with Flask, handles API requests, user authentication, and MongoDB database interactions, while the frontend, using HTML, CSS, and JavaScript, provides a responsive user interface. Docker Compose orchestrates both containers with a shared network for seamless communication. The project progressed through three phases: initial backend container setup, full deployment with frontend-backend integration, and final testing with API and UI validation. Containers were modified for CORS, port exposure, and environment variables. Both images are hosted on Docker Hub for reuse.
44.Smart-attendance-tracker:- By Alladu Sahasra
This project implements a Dockerized Smart Attendance System, evolving from a monolithic Flask app (DA1) to a microservices architecture (DA2) and a demo-ready deployment for DockerShowdown (DA3). DA1 packages a Flask web app with data persistence in a single container, supporting attendance tracking and health checks. DA2 splits functionality into attendance, user/auth, and email services orchestrated via Docker Compose with inter-service communication over a private network. DA3 focuses on optimized, production-ready images, documentation, and demo preparation. Modifications include environment variable handling, health checks, and persistent volumes. GitHub and Docker Hub hosts provide access to code and images for reproducibility.
45. Automated CI/CD Pipeline for Spring Boot Application:- By Jivin K S
This project implements a fully automated DevOps CI/CD pipeline for a Spring Boot application using GitHub Actions, Maven, JUnit, Docker, and Nagios. Part 1 (CI) automates code build and testing via GitHub Actions and Maven, ensuring reliable JUnit-verified builds. Part 2 (CD) containerizes the application using Docker, pushes the image to Docker Hub, and deploys it on a self-hosted runner. Part 3 (Monitoring) leverages Nagios and the check_http plugin for continuous uptime and performance tracking. The pipeline minimizes manual intervention, ensures reproducibility, and demonstrates end-to-end automation from source code to deployment and monitoring.
Docker Showdown
Following the completion of the Docker projects, the students who had built applications were asked to participate in an expo-style event where they showcased their work. The expo featured more than 50 Docker-based projects, demonstrating a wide range of real-world applications and innovative ideas. Over 150 participants visited the expo, actively exploring the projects and interacting with the presenters to understand the technologies used. We three served as the coordinators for this event, managing the planning, execution, and overall flow of the expo. The event turned out to be a great success, fostering technical learning, collaboration, and enthusiasm among all the participants.
Outcomes of the Showdown
The Docker Story consisted of two major events—the Docker Demo Session and the Docker Showdown—both of which were highly enriching experiences for us as organizers and presenters. These events allowed us not only to share our technical knowledge but also to grow in confidence, communication, and teamwork.
The Docker Demo Session was conducted by the three of us—Jyoshika, Ayushi, and Swati—with the objective of introducing third-year students to the fundamentals of Docker and containerization. Preparing for this session helped us strengthen our own understanding of Docker concepts such as images, containers, Dockerfiles, and workflows. During the session, we explained these concepts through live demonstrations and simplified examples. We also presented our posters in front of third-year students, which visually explained Docker architecture, use cases, and real-time applications. The interaction with students during the poster presentation made the session highly engaging and insightful, as we were able to clarify doubts and receive immediate feedback.
The Docker Showdown, the second event, was another valuable experience for us. In this event, all third-year students presented their Docker-based projects in a showdown format, creating an atmosphere of healthy competition and collaboration. Watching multiple teams showcase their projects helped us understand different approaches to Docker implementation and deployment. The event emphasized practical learning, innovation, and teamwork, and it highlighted how Docker can be effectively used in real-world projects.
Overall, the outcomes of the Docker Story were extremely positive for us. Conducting the demo session improved our presentation and teaching skills, while organizing and observing the showdown enhanced our ability to evaluate technical work and manage events. These experiences helped us grow both technically and personally. The Docker Story not only benefited the participants but also played a significant role in shaping our confidence and competence as student facilitators and learners.
Acknowledgement
We would like to express our sincere gratitude to our Faculty Coordinator, Subbulakshmi T Ma’am, for her constant guidance, encouragement, and unwavering support throughout the planning and execution of the Docker Demo Session and Docker Showdown. Her valuable insights, motivation, and belief in our abilities played a crucial role in the success of these events. Her mentorship not only helped us organize the sessions effectively but also inspired us to strive for excellence.
We are also deeply thankful to our Senior mentor, Arun Santosh, for his continuous support and technical guidance. His willingness to share knowledge, clarify doubts, and provide practical insights into Docker and real-world applications greatly enhanced our learning experience. His mentorship helped us gain confidence and approach challenges with clarity and determination.
We sincerely appreciate the time, effort, and encouragement provided by both our mentors, which made this learning journey meaningful and successful. Their guidance has been instrumental in shaping our technical understanding, teamwork, and leadership skills, and we are truly grateful for their invaluable support.
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