Daniel Buaon
Cloud & DevOps Engineering
Cloud Engineer and University Instructor specializing in AWS, DevOps, Linux, and infrastructure automation.
I combine over 20 years of experience in IT systems and infrastructure with the design and implementation of cloud solutions, containerized platforms, Infrastructure as Code (IaC), and CI/CD pipelines.
I work with AWS, Docker, Kubernetes, Terraform, Python, and TypeScript, leveraging AI-assisted development tools to improve productivity, automate processes, and accelerate solution delivery.
I also explore emerging technologies, including local LLMs, GPU infrastructure for AI workloads, and blockchain.
I create training materials on Linux, Docker, Kubernetes, and AWS, and I use Python and TypeScript to build tools, automation workflows, and cloud-native solutions. I also have practical experience with Linux-based GPU infrastructure for AI workloads and local LLM experimentation, along with blockchain node deployment and operations.
AWS Cloud Consulting & Architecture
Strategic guidance on AWS adoption, cloud architecture design, cost optimization, security best practices, and infrastructure modernization. I help teams design reliable, scalable, and maintainable cloud environments aligned with business and technical requirements.
Hybrid Cloud & AWS Infrastructure Management
Design, deployment, and operation of hybrid cloud environments combining on-premises infrastructure with AWS services. Experience with Linux servers, virtualization platforms, networking, monitoring, backups, and high-availability deployments.
AWS Cloud-Native & Serverless Solutions
Design and implementation of cloud-native solutions using AWS services such as Lambda, API Gateway, CloudFront, S3, RDS, Cognito, and Amplify. Focused on scalable architectures, secure integrations, and efficient serverless application delivery.
IaC, CI/CD & AWS Automation
Infrastructure automation using Terraform, CloudFormation, AWS CDK, Ansible, Bash, Python, and other scripting tools. Implementation of CI/CD pipelines with GitHub Actions, GitLab CI, Jenkins, AWS CodePipeline, and AWS CodeBuild to support repeatable, reliable, and auditable deployments. I also use AI-assisted workflows to accelerate scripting, troubleshooting, documentation, and infrastructure delivery.
Dockerization & Containerized Environments
Containerization of applications, Docker Compose environments, image build workflows, AWS ECR integration, and deployments on ECS, EKS, and Kubernetes-based platforms. Focused on practical, maintainable, and production-oriented container setups.
Virtualization, Proxmox & Hybrid Lab Infrastructure
Design and configuration of Linux-based virtualization environments using Proxmox VE, VMware ESXi, and Docker-based workloads. Experience with VM provisioning, storage, networking, backups, remote access, GPU passthrough scenarios, and hybrid lab environments connected to AWS.
AI & GPU Infrastructure Services
Deployment and configuration of GPU-enabled Linux environments for AI workloads, including NVIDIA drivers, CUDA, Python dependencies, ComfyUI, local LLM tools, and automation workflows. Focused on practical setups for image generation, model experimentation, and self-hosted AI infrastructure.
TLS/SSL Configuration & Full-Stack Application Deployments
Deployment of full-stack applications with Nginx reverse proxy, HTTPS certificates, DNS configuration, Docker-based environments, and production-ready web server setups. Experience integrating frontend, backend, database, and proxy layers in Linux environments.
Linux Systems Administration & DevOps Training
Linux systems administration, shell scripting, process management, networking basics, permissions, services, logging, and troubleshooting. I also create and deliver hands-on training materials for Linux, Docker, Kubernetes, AWS, and DevOps practices.
