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Showing posts with the label GitHub Portfolio

Building a Production-Ready AWS Web Application with Failure Simulation, Self-Healing, and High Availability

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In today’s cloud-driven world, deploying an application is only half the job. The real challenge lies in handling failures, ensuring uptime, and building systems that can recover automatically. To bridge the gap between theory and real-world engineering, I built a hands-on project: Production Web App with Failure Simulation on AWS GitHub Repository: https://github.com/anupddas/production-webapp-failure-simulation-aws.git Tags: AWS, Cloud Computing, DevOps, Web Development, Software Engineering Why This Project Matters Most beginner cloud projects focus on deployment. However, in real production environments, systems fail frequently due to misconfigurations, resource exhaustion, or service crashes. This project was designed to simulate those real-world failures and develop the ability to: Diagnose issues quickly Apply structured debugging approaches Implement automated recovery mechanisms Design highly available systems Architecture Overview The application follows a production-grade ar...

Quantum vs Classical Optimization: A Practical Analysis of the Traveling Salesman Problem

 Quantum vs Classical TSP Tags: Quantum vs Classical Algorithms, Traveling Salesman Problem Python, Quantum Inspired Optimization, TSP Algorithm Comparison, Optimization Algorithms Project, Python Algorithm Benchmarking, Computational Optimization Analysis, Heuristic vs Quantum Algorithms, GitHub Optimization Projects, Algorithm Performance Evaluation

Cricket Analytics: Turning Match Data into Actionable Insights

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  Project Spotlight: Cricket Analytics

Attendance Management System Project

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 Project Spotlight: Attendance Insights Tags: Beginner Data Analytics Projects, Attendance Management System Project, Data visualization student project, Scalable data processing project