I transform complex infrastructure into secure, scalable solutions - streamlining systems, automating workflows, and blending system administration, DevOps, and cloud engineering to power the next generation of business innovation.
SCANNING USER...
MATCH FOUND
Systems Administrator
Serving IT Infastructure since 2020
Infrastructure / Cloud / Automation
STATUS: VERIFIED_
MY STORY
My interest in technology started early when I saved up for my first budget PC and learned how to build it myself. That hands-on experience sparked a deeper interest in how systems work, how they fail, and how they can be improved.
Over time, that curiosity grew into a career centered around infrastructure, support, and backend systems. What began with fixing and building machines evolved into designing environments that are stable, secure, and built to last.
WHAT I DO
I build, maintain, and improve the core systems organizations depend on every day.
I streamline repetitive work and turn manual processes into efficient workflows.
I work across on-prem and cloud environments to keep systems connected, stable, and scalable.
CORE STACK
Platforms, tools, and languages I use across infrastructure, cloud, automation, and development workflows.
Kubernetes 
Azure 
Amazon Web Services 
Google Workspace 
Java 
Python 
Linux 
JavaScript 
TypeScript 
Shell 
Bash 
Docker 
Google Cloud Platform 
Microsoft 365 
Terraform Production-ready Azure backend API
The interactive window above demonstrates how a frontend application can communicate with a deployed backend service. When a command is triggered, the Astro frontend sends a request to the backend API running on Azure App Service.
Cross-Origin Resource Sharing (CORS) rules allow the portfolio site to securely communicate with the API, while environment-based configuration in Azure App Service provides the connection settings required for the application to reach its supporting services.
CloudLab is an Infrastructure as Code project built to demonstrate how a complete Azure application environment can be provisioned and managed through Terraform instead of being created manually in the Azure portal.
The project deploys the core cloud resources required to run a web application, including resource groups, an App Service-hosted API, database services, and the supporting configuration needed to connect them together. This makes the environment reproducible, easier to maintain, and suitable for real-world cloud deployment workflows.
During development the backend API was containerized with Docker to ensure consistent behavior between local testing and cloud deployment. This allows the application to be built, tested, and validated in a controlled environment before being deployed to Azure infrastructure managed by Terraform.
Terraform acts as the source for the infrastructure. When the configuration is applied, Azure resources are created and wired together automatically. The frontend communicates with the deployed API, and the API uses environment-based configuration to connect securely to its supporting services.
The diagram below represents the Azure environment provisioned by Terraform and shows how the application, database, and supporting cloud resources fit together.
Cloud-native monitoring dashboard
I built a full-stack DevOps monitoring platform designed to simulate and visualize real-world infrastructure behavior, including service health, traffic patterns, system metrics, and Kubernetes-style autoscaling.
The system uses a React (Vite) frontend and a FastAPI backend deployed to Azure, with full CI/CD pipelines through GitHub Actions.
It is designed to operate in two modes: a cost-efficient Azure Container Apps deployment used now, and a future-ready AKS path for a true Kubernetes-native runtime later.
The live dashboard is hosted in Azure and showcases service health, deployment info, request testing, traffic simulation, live metrics, charts, and a Kubernetes-style runtime layer.
Open Live DashboardReact (Vite) Frontend
↓
Azure Static Web Apps (CI/CD)
↓
FastAPI Backend
↓
Azure Container Apps
↓
(Optional) Kubernetes / AKS/health and displays uptime and service state.
Because the current deployment runs on Azure Container Apps rather than a live AKS cluster, the Kubernetes runtime layer operates in a fallback demo mode.
cluster_connected = falseThis keeps the platform interactive and visually realistic while staying low-cost and preserving an AKS-ready architecture.
GitHub → Azure Static Web Apps → Build → Deploy GitHub → Docker Build → ACR → Container Apps → Deploy VITE_API_BASE_URL to manage frontend-to-backend communication and handled build-time versus
runtime environment differences.
This project demonstrates my ability to design, build, and deploy a full-stack cloud-native system using real DevOps practices, including CI/CD, containerization, Azure deployment, observability, environment management, and scalable architecture planning.
self-deploying GPT backend
When a user submits a prompt in the terminal above, the Astro frontend
sends a POST request to the AutoForge API endpoint (/ai/chat). The FastAPI backend forwards the request to Azure OpenAI and returns
the generated response, which is then rendered in the terminal interface.
CORS rules allow the portfolio site to communicate securely with the backend while API keys and deployment configuration are stored as environment variables in Azure App Service.
AutoForge AI is a cloud-deployed AI backend platform designed to demonstrate how modern applications integrate AI services with automated DevOps pipelines. The system exposes a FastAPI endpoint that forwards prompts to Azure OpenAI, allowing the portfolio site to interact with a live AI service.
The focus of this project is not just the AI integration but the infrastructure and deployment workflow behind it. Every change pushed to GitHub automatically builds, tests, and deploys the backend to Azure App Service using a CI/CD pipeline.
AutoForge begins at the Astro frontend, where the user submits a prompt through the terminal interface. That request is sent to a FastAPI backend hosted on Azure App Service.
The backend validates the request, loads its configuration from Azure App Service environment variables, and forwards the prompt to Azure OpenAI. The generated response is then returned to the frontend and rendered back into the terminal UI.
During development and CI, Docker is used to keep the application behavior consistent across local testing, automated validation, and deployment workflows.
The sketch below shows how prompts move from the Astro frontend to the FastAPI backend, through Azure OpenAI, and back to the user, while GitHub Actions handles automated deployment to Azure App Service.
Hands-off device encryption
Click Start to simulate Day 1 → Day 4 rollout. Data shown here
mirrors the
daily_counts.csv produced by aggregate.ps1 (Encrypted
/ Pending / Error).
A fully automated PowerShell-driven system that enforces BitLocker encryption and collects telemetry across all domain-joined Windows computers. It ensures every endpoint is encrypted, recovery keys are securely backed up, and compliance metrics are automatically generated for dashboards.
Bitlocker-Enforcement.ps1) runs at startup via GPO or a SYSTEM-level task. It checks each
drive’s BitLocker state and:
\\fserver\Data\Chicago\IT\Private_IT\Bitlocker\keys\ and telemetry JSON is written to \\fserver\...\telemetry\YYYY-MM\.
aggregate.ps1) runs
daily to summarize all telemetry JSONs. It counts Encrypted, Pending, and Error states, then updates a
daily_counts.csv for visualization.
Together, these scripts form a self-healing, policy-driven encryption pipeline that maintains compliance across your Windows fleet while providing transparent encryption telemetry.
# Detect drive state and enable BitLocker if missing
$vol = Get-BitLockerVolume -MountPoint "C:"
if ($vol.ProtectionStatus -eq 'Off') {
Enable-BitLocker -MountPoint "C:" -EncryptionMethod XtsAes256 -UsedSpaceOnly
Add-BitLockerKeyProtector -MountPoint "C:" -RecoveryPasswordProtector
Backup-BitLockerKeyProtector -MountPoint "C:" -RecoveryKeyPath $keyPath
}
CompTIA 4 ▾ 
Foundational IT concepts: hardware, software, security, troubleshooting, databases, and basic programming.
Support, OS, networking, hardware, and troubleshooting skills for technical roles.
Network design, configuration, routing/switching, wireless, security, and troubleshooting.
Core security principles, risk management, identity, cloud, and incident response.
Microsoft 7 ▾ 
Azure core services, governance, security, pricing, and cloud concepts.
Identity, governance, storage, compute, networking in Azure with automation focus.
Focuses on unifying people, process, and technology to deliver continuous value. Covers CI/CD, source control, infrastructure as code, and release strategies in Azure DevOps.
Validates skills in building, testing, deploying, and maintaining cloud applications and services on Microsoft Azure using SDKs, APIs, and developer tools.
Focuses on designing secure, scalable, and reliable cloud solutions. Covers governance, identity, networking, storage, and application architecture decisions.
Windows deployment, Intune/UEM, policy, security baselines, and app lifecycle.
Tenant management, identity, security, compliance, and modern workplace administration.
Cisco 1 ▾ 
Networking fundamentals, IP services, security, automation, and programmability.
Amazon 1 ▾ 
Cloud concepts, AWS services, security, pricing, and support at a foundational level.
