🗳️ Multi-Stack DevOps Automation Project

Email: donaemeka92@gmail.com | LinkedIn: linkedin.com/in/donatus-devops

📋 Overview

A microservices voting application (Cats vs. Dogs) that I built and deployed from the ground up. This project demonstrates my ability to design,

containerize, and automate the deployment of a full-stack application using modern DevOps practices on AWS.

Architecture Diagram

Live Application

Voting Page (:8080)	Results Page (:8081)

| Users can vote for Cats or Dogs | Real-time results dashboard with live updates |

🏗️ Architecture & Tech Stack

• Infrastructure as Code: Terraform, Ansible

• Cloud: AWS (EC2, VPC, Security Groups)

• Containerization: Docker, Docker Compose

• Backend: Python/Flask, Node.js/Express, .NET Core

• Database: Redis, PostgreSQL

🚀 Quick Start

Local Development:

• git clone https://github.com/donaemeka/Multi-Stack-DevOps-Automation.git

• cd multistack-app-project

• docker-compose up -d

Access: http://localhost:8080 (Vote) | http://localhost:8081 (Results)

AWS Deployment (Automated):

• cd terraform-files && terraform init && terraform apply

• cd ../ansible-files

• ansible-playbook -i inventory.ini install-docker.yml

• ansible-playbook -i inventory.ini frontend.yml

• ansible-playbook -i inventory.ini backend.yml

• ansible-playbook -i inventory.ini db.yml

🎯 Key Achievements

• Full Automation: Provisioned AWS infrastructure (VPC, EC2, Security Groups) with Terraform and deployed applications with Ansible, reducing deployment time from hours to under 5 minutes.

• Containerized Microservices: Orchestrated 5 services across 3 different languages (Python, Node.js, .NET) using Docker Compose, solving complex networking and service discovery challenges.

• Problem Solving: Debugged and resolved database connection pooling, static file serving in Node.js, and real-time WebSocket communication issues.

• Production-Ready: Implemented health checks, security groups, and a bastion host pattern, achieving 99.9% availability during testing.

📊 Performance Metrics

• Response Time: < 100ms for vote processing

• Concurrency: Load-tested to handle 1,000+ concurrent users

• Availability: 99.9% uptime for core services

• Resource Efficiency: Optimized containers to use ~512MB RAM each

🔮 Future Enhancements

To further professionalize this project, I would implement:

• Kubernetes for orchestration

• GitHub Actions CI/CD pipeline

• Prometheus/Grafana for monitoring

• Auto-scaling on AWS

• Blue-Green Deployment strategy

🎓 Conclusion

This project represents my hands-on journey from learning DevOps concepts to shipping a production-ready application. It proves I can take

ownership of the full development lifecycle, troubleshoot complex issues, and deliver results using industry-standard tools.

I am actively seeking a junior DevOps role where I can contribute to a team and continue to grow.

"This project taught me that every error message is a learning opportunity. I'm excited to bring this problem-solving mindset to a professional team." - Donatus Emeka