Cloud Systems Portfolio

RYAN CHEUNG

RYAN CHEUNG

Portfolio 2026

CLOUD
ARCHITECT

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About Me

I am an engineer focused on cloud architecture design and cloud-native development. I am dedicated to transforming complex physical environments into highly resilient, self-healing modern cloud clusters through orchestration techniques and infrastructure automation frameworks.

Cloud Engineering Practice

I continuously explore high-availability architecture in multi-cloud environments, striving for the perfect balance between computing performance, operational costs, and security compliance. To me, cloud technology is not just a development tool, but an engineering art form for building the digital world.

Technical Deployment Strategy

Specializing in Infrastructure as Code (IaC) and CI/CD automation. My goal is to build seamless and elastic development environments, comprehensively accelerating product delivery and the stability of modern digital transformation.

Core Expertise

Cloud & DevOps Architecture

Designing resilient, high-availability multi-cloud ecosystems that bridge infrastructure and application agility.

  • Automating Lifecycle Management via Terraform & Ansible
  • Orchestrating Scalable K8s Clusters with Istio Mesh
  • Architecting Disaster Recovery (DR) & RTO/RPO Compliance
Infrastructure as Code Cloud-Native

Data Center Operations

Mastering the physical foundation of the cloud through Tier-3 standards and enterprise network engineering.

  • Full-Stack Rack Deployment & High-Density Power Management
  • Enterprise L2/L3 Network Security & VLAN Segmentation
  • Uptime SLA Management & Environmental Compliance OS
Connectivity Mission Critical

Selected Works

01 / Hybrid Cloud Orchestration

Multi Cloud Deploy with Terraform

Architected and deployed a highly available, multi-node Kubernetes cluster across AWS, GCP, and Azure using a unified Control Plane. This project focused on solving complex hybrid cloud networking challenges, implementing seamless inter-cloud VPC peering, and automating full-stack provisioning via Terraform. The solution delivered robust auto-scaling capabilities and unified observability for mission-critical distributed workloads.

AWS / GCP Terraform Kubernetes
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02 / AI & Computer Vision Pipeline

Intelligent Child Dev Analysis

Developed a sophisticated Computer Vision platform for pediatric behavioral analytics, integrated with a Cloud-Native backend. The system leverages MediaPipe for real-time skeletal tracking and behavioral pattern recognition. To scale intelligence, I implemented a Retrieval-Augmented Generation (RAG) architecture using a Vector Database, allowing the AI agent to provide clinical-grade analysis by querying a curated foundation of medical literature.

Python / Flask RAG AI Agent Computer Vision Docker Google Cloud (GCP)
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Professional Journey