CloudForge AI: Build Cloud Architectures with Google AI Studio & Gemini

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DEV Community · Chandrashekhar Mehta · 2026-09-26 개발(SW)
Cover image for CloudForge AI: Build Cloud Architectures with Google AI Studio & Gemini

Chandrashekhar Mehta

Education Track: Build Apps with Google AI Studio

This post is my submission for DEV Education Track: Build Apps with Google AI Studio.

CloudForge AI — AI-Powered Cloud Architecture Designer

What I Built

CloudForge AI is an AI-powered cloud architecture designer that turns a natural-language application requirement into a structured cloud architecture.

Instead of manually starting from a blank architecture diagram, I can describe what I want to build — for example, a highly available e-commerce application — and CloudForge generates an architecture with cloud components, security considerations, scalability recommendations, observability, estimated costs, and Terraform starter code.

I built the application using Google AI Studio and Gemini, with a modern React + TypeScript interface.

Key features

  • 🤖 AI-powered architecture generation
  • ☁️ AWS cloud architecture design
  • 🏗️ Interactive architecture visualization
  • 🔐 Security audit and recommendations
  • 📈 High Availability & scalability analysis
  • 📊 Observability recommendations
  • 💰 Rough infrastructure cost estimation
  • 🧩 Component breakdown
  • ⚙️ Terraform starter code
  • 📤 Architecture export
  • 🕒 Local architecture history
  • 🧪 Sample/offline architectures for reliable demos
  • 🛡️ Graceful fallback when the AI service is temporarily unavailable

Key prompt

One of the main prompts I used in Google AI Studio was essentially:

Build a production-style AI cloud architecture designer where a user describes an application in natural language and Gemini converts the requirements into a structured cloud architecture. Generate the architecture components, relationships, security analysis, high-availability and scalability recommendations, observability recommendations, estimated infrastructure cost, and Terraform starter code. Visualize the resulting architecture interactively and provide export/history functionality.

I then iteratively refined the application through Google AI Studio by improving the architecture schema, UI, error handling, model integration, and deployment behavior.

Demo

Example workflow


text
Natural-language requirements
          ↓
     Gemini analysis
          ↓
 Structured architecture
          ↓
 ┌────────┬──────────┬──────────────┐
 │Security│ HA/Scale │Observability │
 └────────┴──────────┴──────────────┘
          ↓
 Architecture Diagram
          ↓
 Cost Estimate + Terraform

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