Emmanuel Yeboah

I build cloud-ready applications and AWS infrastructure that make deployments faster, more reliable, and easier to operate. My work combines cloud engineering, DevOps automation, backend development, and an electrical engineering foundation.

For a full-stack barbering shop management system, I shipped a FastAPI, Python, and PostgreSQL backend with 12+ RESTful endpoints, JWT authentication, and role-based access control. I containerized the API and database with Docker, reducing setup time from hours to under 10 minutes, and designed an AWS deployment using EC2, RDS, S3, ALB, Auto Scaling, and CloudFront.

In an AWS infrastructure and DevOps project, I provisioned EC2, VPC, IAM, and S3 resources and built GitHub Actions pipelines that cut average deployment time by about 50%. I also implemented load balancing and Auto Scaling to support 99%+ uptime and automatic recovery from instance failures.

My engineering background includes building a thermoelectric solarimeter with an integrated machine-learning model that achieved 92% accuracy. During my internship with VRA-NEDCo, I analyzed billing and consumption data across 10 districts, contributing to a 12% reduction in flagged energy loss.