Documenting cloud projects and foundational insights on my path to cloud / AI architecture.
I'm building toward cloud engineering with a strong foundation in AWS, Linux, and networking. My work spans infrastructure deployment & operations, automation, and applied AI, with an emphasis on architectural decisions and system behavior.
My strong interest in technology is understanding how complete systems fit together. I'm naturally drawn to following the relationships between components, including how information flows, what each component depends on, and how everything behaves when something goes wrong. That inclination, alongside my fascination with intelligent, autonomous systems and conviction in their transformative potential, is what draws me toward building cloud and AI solutions.
Admitted B.S. Cloud & Network Engineering student at WGU (Target Q2 2028)
Scenario-based cloud training covering Linux, Python, networking, security, databases, GenAI, automation, AWS Cloud, and professional readiness.
AWS application infrastructure built with Terraform, featuring multi-AZ compute, private networking, RDS, CloudWatch monitoring, and GitHub Actions deployment using OIDC.
Deploying and validating compute, storage, and databases.
Managing, monitoring, and securing AWS workloads.
Connecting serverless workflows, APIs, and managed AI.
Connectivity diagnosis across hosts and AWS networks.
Service, log, permission, and filesystem investigation.
Practical tooling for diagnostics and operational tasks.
Multi-AZ AWS application infrastructure provisioned with Terraform. Incorporates observability, failure testing, and controlled CI/CD.
An AWS AI application project combining cloud engineering, AI systems integration, and reusable infrastructure deployment automation.
Elastic compute, cloud operations, storage & recovery, database migration, serverless systems, containers & orchestration, and agentic AI.
CLI evidence gathering, automation, and systems troubleshooting through incident-style investigation.
![Cloud With David [.com] project preview.](assets/projects/cloud-with-david-com/cover.webp)
Personal portfolio site designed and deployed to track progress, and showcase proofs.
Revisiting an AI assistant lab on AWS: what RAG, MCP, and AgentCore revealed about the engineering hiding beneath managed services.
Rebuilding the basics: keys, permissions, and the habits behind reliable SSH access.
Study system, resources, and the approach that helped turn preparation into a passing result.
Follow the journey, explore the work, or get in touch