Production systems, owned end-to-end.
Full-stack engineer focused on AI, cloud, automation, and construction technology. Building scalable products from idea to production.
Tran Quang Duong · dtducas
Production systems that stay reliable, observable, and fast — owned end to end
Production systems, owned end-to-end.
Building AI, cloud, automation, and construction technology products — from architecture and code to deployment, monitoring, and operations.
End-to-end ownership across frontend, backend, databases, infrastructure, CI/CD, observability, and production operations.
Systems are designed to be scalable, maintainable, observable, and automatable — with clear architecture and measurable outcomes.
How this site actually works
An encrypted request/response handshake, polyglot persistence, observability, and a full Docker + CI/CD pipeline — documented and live.
Interfaces that load fast and read clearly
Next.js App Router, Server Components, TypeScript, Tailwind. Accessible, SEO-ready, and lean on client JS.
Services with clean architecture and DI
NestJS / .NET, module-per-feature, validated contracts, typed end to end. Cross-cutting concerns kept out of handlers.
Pipelines and models that hold up
Relational design, ETL pipelines, polyglot persistence. Postgres for the transactional core, MongoDB for documents and events.
Shipped and operated like production
AWS, Docker, GitHub Actions, observability and health probes. Reliability built in: retries, recovery, logging, monitoring.
Systems that prove the range
What this site demonstrates, in production
Signup and login payloads are encrypted end to end: ephemeral ECDH P-256 → HKDF → AES-256-GCM, with replay protection.
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PostgreSQL for the transactional core; MongoDB for append-heavy documents and events. One writer per concern.
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Multi-stage images, GitHub Actions gates (lint, typecheck, test, Lighthouse), structured logging and health probes.
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End-to-end ownership across the stack
From frontend experiences and backend services to databases, cloud infrastructure, deployment pipelines, and production operations.
Production engineering in practice
Authentication, data persistence, monitoring, containerization, CI/CD, and operational excellence — implemented as real systems, not just concepts.