My Projects

Automated a Jenkins CI/CD pipeline integrating GitHub, Maven, SonarQube, Nexus, Docker, and Trivy for secure and fast deployments. Enhanced the software delivery process with security scanning and artifact management.

Created a secure VPC with public/private subnets on EKS, configured Application Load Balancer for routing, and used Ingress Controller for efficient traffic management to application pods. Demonstrates advanced Kubernetes networking and AWS integration.

Implemented AWS Lambda functions to automatically remove unattached EC2 snapshots, reducing unnecessary storage costs. Optimized memory, timeouts, and triggers for efficient execution, resulting in significant AWS cost savings and improved serverless performance.

Containerized a Spring Boot Java web service using Maven and Docker. Created a production-ready Dockerfile, built the image, and deployed the container on port 8080 (exposed via port 80). This approach streamlines deployment and enhances scalability.

Deployed a full-stack application (React, TypeScript, Node.js, MongoDB) with Docker on AWS EC2. Configured backend infrastructure using NVM and MongoDB for seamless performance. Followed AWS DevOps best practices for scalability and reliability.

Implemented a robust Jenkins pipeline integrating Docker, SonarQube, Trivy, and Gradle for automated build, test, and deployment on AWS EC2. This pipeline ensures code quality, security, and rapid delivery for banking applications.

Developed a Jenkins-based CI/CD pipeline for the Secret Santa app, featuring Docker containerization, SonarQube integration, and AWS deployment. Automated testing and deployment streamline the release process and improve reliability.

Built a CI/CD pipeline in GitLab using Docker, Maven, SonarQube, and AWS EC2 runners for automated deployment. This setup ensures continuous integration, code quality checks, and seamless deployments for Java applications.

A robust shell script leveraging AWS CLI and jq to fetch and display EC2, S3, IAM, and RDS details in a readable format. Enables automated monitoring for real-time AWS insights, helping teams maintain visibility and control over their cloud resources.

A Bash script to monitor AWS node health including CPU, memory, and disk space. Utilizes standard Unix tools for analysis and Git for version control. This tool ensures proactive detection of resource bottlenecks and supports operational reliability.