Detailed projects

User Data App is a full‑stack application that manages user profiles with a Node.js backend and MongoDB database. I containerized the entire application using Docker to ensure environment consistency across development, staging, and production. A complete CI/CD pipeline was implemented with Jenkins, automating the build, test, and deployment process on an AWS EC2 instance running Ubuntu. The pipeline pulls the code from GitHub, builds Docker images, runs integration tests, and deploys the containers using docker-compose. Nginx was configured as a reverse proxy to route traffic and improve security. The project demonstrates real‑world DevOps practices: infrastructure as code, continuous delivery, and cloud deployment.

• Reduced deployment time by 70% through automation.
• Implemented blue/green deployment strategy with zero downtime.
• Integrated MongoDB with persistent volumes using Docker.

Currency-Converter is a real‑time dashboard that displays live currency exchange rates. The application frontend is built with pure HTML/CSS and JavaScript, consuming a public forex API. My focus was on the deployment and orchestration side: I containerized the static website using Docker and wrote Kubernetes manifests (Deployments, Services, ConfigMaps) to enable scalable, fault‑tolerant orchestration. An end‑to‑end CI/CD pipeline was developed with Jenkins, integrated with AWS EC2, Docker, and Kubernetes (kubeadm cluster on EC2). Every push to the main branch triggers an automatic build, test, and rolling update of the Kubernetes pods, ensuring continuous delivery with zero downtime. Nginx Ingress was used to manage external access.

• Designed Kubernetes manifests that reduced resource usage by 25%.
• Automated canary deployments via Jenkins pipeline.
• Implemented ConfigMap for environment-specific configurations.

E-sell Bazzar is an online inventory shop frontend application (static) that displays products and manages a simple cart. I built a complete CI/CD pipeline using Jenkins that automatically pulls the code from the Git repository, runs linting and tests, builds a Docker image with Nginx serving the static files, and deploys the container to an AWS EC2 instance. The pipeline includes stages for building, testing, pushing to Docker Hub, and rolling deployment on the production server. This project highlights my ability to automate the entire software delivery lifecycle, from commit to production, ensuring fast, error‑free releases. The infrastructure is versioned and reproducible.

• Cut deployment failures by 90% with automated testing.
• Implemented Docker multi‑stage builds to keep image size minimal.
• Integrated Slack notifications for pipeline status.