Cloud CV - SRE/DevOps Engineer Portfolio

A modern, cloud-hosted resume showcasing SRE/DevOps expertise with AWS best practices.

🏗️ Architecture

This project demonstrates enterprise-grade DevOps practices:

• Infrastructure as Code: Terraform for reproducible infrastructure
• CI/CD Pipeline: GitHub Actions for automated deployment
• Serverless: AWS Lambda for visitor counter
• CDN: CloudFront for global content delivery
• Security: SSL/TLS, IAM roles, least privilege access
• Monitoring: CloudWatch for observability

🚀 Local Development

Prerequisites

• Docker
• AWS CLI (for LocalStack)

Start LocalStack

# Start LocalStack environment
./scripts/local-dev-start.sh start

# Upload files to local S3
./scripts/local-dev-start.sh upload

# Check status
./scripts/local-dev-start.sh status

# Stop when done
./scripts/local-dev-start.sh stop

Access Local Development

• Website: http://localhost:4566/cloud-cv-local/index.html
• S3 Browser: http://localhost:4566/cloud-cv-local/
• LocalStack Health: http://localhost:4566/_localstack/health

🚀 Production Deployment

Infrastructure as Code (Terraform)

The project uses Terraform to provision AWS resources:

📋 View Terraform Configuration

# S3 Bucket for static website hosting
resource "aws_s3_bucket" "website" {
  bucket = "cloud-cv-${random_id.bucket_suffix.hex}"
}

# CloudFront distribution for CDN
resource "aws_cloudfront_distribution" "website" {
  origin {
    domain_name = aws_s3_bucket.website.bucket_regional_domain_name
    origin_access_control_id = aws_cloudfront_origin_access_control.website.id
  }
}

# Lambda function for visitor counter
resource "aws_lambda_function" "visitor_counter" {
  filename         = "../lambda/visitor_counter.zip"
  function_name    = "cloud-cv-visitor-counter"
  runtime         = "python3.11"
}

# DynamoDB table for visitor data
resource "aws_dynamodb_table" "visitor_counter" {
  name           = "visitor-counter"
  billing_mode   = "PAY_PER_REQUEST"
  hash_key       = "id"
}

GitHub Actions CI/CD Pipeline

The project uses GitHub Actions for automated deployment via .github/workflows/deploy.yml:

🔄 View GitHub Actions Workflow

name: Deploy Cloud CV
on:
  push:
    branches: [main]
  workflow_dispatch:

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
      
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v4
        with:
          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
          aws-region: us-east-1
      
      - name: Deploy Infrastructure
        run: |
          cd infra/terraform
          terraform init
          terraform plan
          terraform apply -auto-approve
      
      - name: Upload Frontend Files
        run: |
          aws s3 cp frontend/index.html s3://$(terraform output -raw bucket_name)/
          aws s3 cp frontend/styles.css s3://$(terraform output -raw bucket_name)/
          aws s3 cp frontend/script.js s3://$(terraform output -raw bucket_name)/
          aws s3 cp cv.pdf s3://$(terraform output -raw bucket_name)/
      
      - name: Invalidate CloudFront Cache
        run: |
          aws cloudfront create-invalidation --distribution-id $(terraform output -raw cloudfront_distribution_id) --paths "/*"

Deployment Process

1. Push to main branch triggers GitHub Actions
2. Terraform applies infrastructure changes
3. Frontend files are uploaded to S3
4. CloudFront cache is invalidated
5. Website is live with latest changes

Required GitHub Secrets

• AWS_ACCESS_KEY_ID
• AWS_SECRET_ACCESS_KEY

👨‍💻 Author

SRE/DevOps Engineer with 12+ years of experience

• Website: l4linux.com
• LinkedIn: https://www.linkedin.com/in/lekshmin
• GitHub: https://github.com/Lforlinux

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This project demonstrates modern DevOps practices and cloud architecture expertise.