Building resilient cloud infrastructure with AWS, Terraform, and CI/CD pipelines that deploy at the speed of git push.
How I approach cloud infrastructure
$ cat skills.yml
---
focus:
- Infrastructure Automation
- CI/CD Pipelines
- Cloud Architecture (AWS)
- Container Orchestration
philosophy: "Automate everything, monitor always"
status: ● available for work
I design systems that are resilient, scalable, and cost-efficient — built to run without manual intervention. Infrastructure as code, pipelines as products, monitoring as a first-class feature.
Evaluate existing infrastructure, identify bottlenecks, and design cloud-native architecture on AWS with VPC, subnets, security groups, and IAM policies.
Write Terraform modules for every resource. Version-controlled, peer-reviewed, and state-managed. No ClickOps — everything is reproducible from a single terraform apply.
Dockerize applications with optimized multi-stage builds. Set up GitHub Actions workflows for automated testing, building, and deployment on every push.
Deploy monitoring with CloudWatch, set up alerts, track metrics. Continuously optimize costs, performance, and security posture through iterative improvements.
Hover & interact — 3D exploration of my toolkit
Click any stage to see what happens under the hood
Every change starts with a feature branch. Code is reviewed through pull requests, ensuring quality gates before anything touches main.
$ git checkout -b feature/deploy
$ git commit -m "feat: add nginx"
$ git push origin feature/deploy
→ PR #42 opened
Docker multi-stage builds compile, test, and package the app into optimized production images — small, secure, and reproducible.
$ docker build -t app:v2.1 .
Step 1/8 : FROM node:18-alpine
Step 8/8 : Successfully built a3f7c2d
$ docker push registry/app:v2.1
Every commit triggers automated test suites — unit, integration, and infrastructure validation — before any merge is allowed.
$ npm test -- --coverage
Tests: 42 passed, 0 failed
$ terraform validate
✓ Configuration is valid
Terraform provisions the entire AWS infrastructure — VPCs, subnets, security groups, EC2, RDS — all version-controlled and reproducible.
$ terraform plan
Plan: 12 to add, 0 to change, 0 to destroy
$ terraform apply -auto-approve
✓ Apply complete! Resources: 12 added
GitHub Actions deploys via SSH + Docker Compose to production. Zero-downtime rolling updates with health checks ensure reliability.
$ ssh deploy@prod "docker compose pull"
$ ssh deploy@prod "docker compose up -d"
✓ app-1 Running
✓ nginx-1 Running
CloudWatch + custom dashboards track CPU, memory, request latency, and error rates. Alerts fire before users notice issues.
$ aws cloudwatch get-metric-data
CPU: 23% | Memory: 41%
Requests: 1.2k/min | Errors: 0
✓ All systems operational
Click any project to see architecture details
End-to-end automated pipeline: Terraform → Docker → GitHub Actions → Production.
Multi-AZ, load-balanced, auto-scaling infrastructure for production workloads.
Full-stack Next.js deployment with automated Docker + Terraform pipeline.
Distributed microservice architecture with service discovery and API gateway.
Docker Compose orchestrated multi-container setup with networking and volumes.
Reusable Terraform modules for AWS infrastructure provisioning and management.
Principles that guide my approach
If it can be scripted, it should be scripted. Manual processes are the enemy of reliability.
Every resource is defined in version-controlled code. No ClickOps. Reproducible from zero.
Ship small changes often. Fast feedback loops catch issues before they compound.
IAM least privilege, network isolation, secrets management — security is never an afterthought.
Open for collaboration and opportunities