About This Site
Welcome! This site serves two purposes: showcasing my professional background and demonstrating cloud engineering skills through the Cloud Resume Challenge.
About Cloud Resume Challenge
This site is part of the Cloud Resume Challenge, demonstrating a serverless full-stack application deployed entirely on AWS using infrastructure as code.
Architecture Overview
Frontend & Distribution
Static HTML, CSS, and JavaScript files are hosted in Amazon S3 and distributed globally via CloudFront CDN. CloudFront provides HTTPS through ACM certificates, applies security headers, and integrates with Route53 for custom domain management.
Visitor Tracking System
The real-time visitor counter demonstrates serverless backend integration. When the page loads, JavaScript
calls the /v1/visitors endpoint.
CloudFront injects an X-API-Key header and forwards the request to API Gateway, which
invokes a Python Lambda function.
The function validates the API key using SHA-256 hashing, reads and increments the count in
DynamoDB, and returns the updated value.
Infrastructure as Code
Five CloudFormation templates define the entire infrastructure: S3 bucket for Lambda code, DynamoDB table for storing visitors count, Lambda function to read, increment and write visitors count, API Gateway REST API, and CloudFront distribution with dual origins (S3 for static content, API Gateway for the API).
CI/CD Pipeline
Automated deployment uses GitHub Actions with centralized configuration and reusable composite actions. Seven workflows handle infrastructure deployment with explicit dependencies: foundational stacks (S3, DynamoDB), compute layer (Lambda), API layer (API Gateway), and distribution layer (CloudFront). Automatic triggers deploy changes when CloudFormation templates, Lambda code, or static assets are modified. A main orchestration workflow provides manual control with dependency enforcement.
Architecture Diagram
My CV
I'm a backend engineer with 6+ years of commercial experience building event-driven, cloud-native systems — primarily in Python and Java on AWS. My current focus is observability platforms and AI-powered incident analysis, including contributing to a multi-agent Root Cause Investigation system (built on the Strands Agents SDK) that automates alert triage and integrates with monitoring and deployment systems via MCP servers.
Highlights
- Built a Slack-integrated AI agent that lets engineers trigger root-cause investigations directly from alert notifications, with live progress streamed over a WebSocket API Gateway.
- Designed AWS Lambda automation (SQS, EventBridge, Batch) for alert classification and synchronization between monitoring system and internal systems.
- Engineered a workflow change at a previous company that boosted a customer team's order-processing productivity by 35–50%.
- AWS Certified Solutions Architect – Associate.
Core Stack
Python, Java, FastAPI, Spring Boot, AWS (Lambda, ECS, SQS, EventBridge, API Gateway, DynamoDB, RDS), Terraform, Docker, Kubernetes, Claude Code
For the full breakdown of my professional experience, education, and skills, see my
LinkedIn profile