INFRASTRUCTURE AS CODE PORTFOLIO

Programmatic management of cloud infrastructure using AWS CDK, Terraform, and CloudFormation

Designing and implementing reproducible, version-controlled cloud infrastructure across multiple platforms with security, cost optimization, and compliance automation. These projects demonstrate Infrastructure as Code capabilities for multi-environment deployments, automated governance, and production-ready infrastructure patterns.

Infrastructure as Code · Multi-Environment · Cost Optimization · Security Automation

Infrastructure as Code Projects

Production-grade Infrastructure as Code implementations using AWS CDK and comprehensive IaC frameworks for reproducible, version-controlled environments.

MLOps Platform
MLflow on AWS ECS Fargate

MLflow Platform on AWS ECS Fargate

AWS CDK

Production-grade MLflow tracking platform deployed on AWS ECS Fargate using AWS CDK (Python) with RDS MySQL, S3 artifact storage, VPC networking, and auto-scaling.

AWS CDK (Python) Amazon ECS Fargate Amazon RDS (MySQL) Amazon S3 AWS Secrets Manager Application Load Balancer
Infrastructure as Code MLOps Platform Production Deployment Auto-Scaling
Complete VPC networking with public/private subnets
RDS MySQL backend store with Secrets Manager
S3 artifact storage with IAM permissions
ECS Fargate with CPU-based auto-scaling
View Project
Infrastructure Patterns
AWS CDK Infrastructure Patterns

AWS CDK Infrastructure Patterns

CDK Patterns

Comprehensive AWS CDK patterns library featuring VPC designs, CI/CD platforms, container orchestration, serverless architectures, and security-first infrastructure patterns.

AWS CDK (Python/TypeScript) CloudFormation Terraform Integration Multi-Environment Security Automation Cost Optimization
Infrastructure Patterns Multi-Environment Security Automation Cost Optimization
Multi-environment deployments (dev/staging/prod)
Security and compliance automation
Cost optimization strategies and monitoring
Terraform and CloudFormation integration
View Patterns
MLOps Platform
Azure ML IaC Platform

Azure ML Platform Infrastructure as Code

Azure DevOps

Automated end-to-end Azure ML platform provisioning using Infrastructure as Code with secure RBAC, autoscaling compute, and CI/CD pipelines.

Azure DevOps YAML Azure Machine Learning Azure CLI v2 RBAC & Service Principals Autoscaling Compute
Infrastructure as Code Cloud MLOps CI/CD Automation
Automated Azure ML workspace provisioning
Secure RBAC with Service Principals
Autoscaling compute clusters (scale-to-zero)
CI/CD pipeline-driven infrastructure deployment
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MLOps Platform
GCP Vertex AI Platform Foundation

GCP Vertex AI Platform Foundation (Pipeline-1)

GCP

Programmatic MLOps infrastructure on Google Cloud – bootstraps Vertex AI Pipelines runtime, IAM least‑privilege service accounts, GCS artifact root, and Workload Identity Federation for secure, reproducible AI platform provisioning.

Vertex AI Kubeflow Pipelines v2 GCP IAM Workload Identity Federation Cloud Storage Vertex SDK
MLOps Platform Infrastructure as Code CI/CD Bootstrap
Vertex AI Pipelines runtime & artifact root
IAM least‑privilege + service account impersonation
GCS pipeline root (versioned, encrypted)
GitHub Actions + Workload Identity Federation
View Project
MLOps Platform
Kubeflow MLOps Foundation

Kubeflow AI Platform Foundation (Pipeline‑1)

Kubernetes

Kubernetes‑native MLOps platform bootstrap – provisions Kubeflow Pipelines v2, Argo Workflows, MinIO artifact store, ML Metadata (MLMD) and RBAC. Creates a standardized, governed foundation for training and deployment pipelines.

Kubeflow Pipelines Argo Workflows MinIO ML Metadata Kubernetes RBAC Kustomize
Platform Engineering Infrastructure as Code Multi‑env
Kubeflow Pipelines control plane install
MinIO artifact store + ML Metadata
RBAC & namespace isolation
Reproducible platform bootstrap (IaC)
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MLOps Platform
AWS AI Platform IaC

AWS SageMaker AI Platform (Pipeline‑1)

AWS

Enterprise‑ready AWS AI platform foundation – provisions SageMaker Domain, Organization Templates (Service Catalog), IAM/KMS, S3, and environment stacks via AWS CDK. Secure CI/CD with GitHub Actions + OIDC, enabling governed, repeatable ML workspace setup across Dev/Pre‑Prod/Prod.

AWS CDK (Python) SageMaker Domain Service Catalog OIDC (GitHub→AWS) IAM least‑privilege KMS encryption SSM Parameter Store
Infrastructure as Code MLOps Platform Multi‑env
SageMaker Domain + Organization Templates
IAM least‑privilege + KMS encryption
GitHub Actions + OIDC (no static keys)
Multi‑environment CDK stacks (Dev/Pre‑Prod/Prod)
View Project

Infrastructure as Code Tools & Principles

AWS CDK

Infrastructure as Code with familiar programming languages (Python, TypeScript, Java, C#)

Terraform

Cloud-agnostic Infrastructure as Code with declarative configuration language

CloudFormation

AWS-native Infrastructure as Code with JSON/YAML templates and drift detection

VERSION-CONTROLLED INFRASTRUCTURE

All infrastructure definitions stored in Git with full change history, peer reviews, and automated testing.

MULTI-ENVIRONMENT DEPLOYMENTS

Consistent infrastructure across development, staging, and production environments with environment-specific configurations.

COST OPTIMIZATION STRATEGIES

Right-sizing, auto-scaling, spot instances, and budget alerts integrated into infrastructure design.

SECURITY & COMPLIANCE AUTOMATION

Security groups, IAM policies, encryption, and compliance controls automated through code.

Infrastructure as Code Pipeline

aws-cdk-deploy.sh
$ cdk synth
Generating CloudFormation template from CDK code...
✓ CloudFormation template generated successfully
$ cdk deploy --require-approval never
✓ VPC with public/private subnets created
✓ RDS MySQL instance provisioned
✓ S3 bucket with encryption enabled
✓ ECS Fargate service with auto-scaling configured
🚀 Infrastructure deployed successfully!