5.1 Project Overview

Scenario

CloudQuery, an online cloud learning platform, plans to launch an AI-powered tutor that can instantly answer AWS questions, simplify complex concepts, and even generate quizzes for learners.

They want to create a 24×7 intelligent learning assistant that students can access through a web app. The tutor should respond naturally to questions such as:

  • “What is the difference between IAM Role and Policy?”
  • “Explain S3 bucket versioning.”
  • “Generate 3 quiz questions on Amazon EC2.”

The goal is to make cloud learning interactive and reduce the need for manual support, providing learners with quick and reliable answers.

Our Solution

We’ll build a serverless AI Cloud Tutor using Gemini API + AWS services that can understand natural language questions and generate clear, contextual answers.

The tutor will use Amazon API Gateway, AWS Lambda, and DynamoDB for backend logic, and will be deployed as a web application hosted on AWS Amplify.

This architecture ensures high scalability, low maintenance, and real-time AI-powered responses.

About the Project

In this hands-on lab, you’ll learn to:

  • Build a serverless backend connecting AWS Lambda with the Gemini API
  • Securely store API credentials using AWS Secrets Manager or Parameter Store
  • Log questions and AI-generated answers in Amazon DynamoDB
  • Deploy and host a web application using AWS Amplify
  • Monitor your tutor’s performance using Amazon CloudWatch

By the end of this project, you’ll have your own AI Cloud Tutor capable of explaining, summarizing, and quizzing users on any AWS concept in real time.

This project provides practical experience with Generative AI integration, serverless workflows, and secure API orchestration core skills for every modern AI/ML engineer.

Steps To Be Performed

We’ll complete the following steps in sequence:

  1. Store the Gemini API key securely using Secrets Manager.
  2. Create a DynamoDB table for storing questions and answers
  3. Develop the Lambda function to connect with the Gemini API
  4. Configure API Gateway to expose the Lambda as an HTTPS endpoint
  5. Build and deploy a web application using AWS Amplify

Services Used

  • Amazon API Gateway - Exposes the HTTP endpoint for user queries
  • AWS Lambda - Executes code and connects to the Gemini API
  • Amazon DynamoDB - Stores user questions and AI responses
  • AWS Secrets Manager - Stores Gemini API keys securely
  • Amazon CloudWatch - Tracks logs and monitors performance
  • AWS Amplify - Hosts and manages the web application
  • Gemini API - Provides natural language understanding and generation

Estimated Time & Cost

  • Estimated Time: 2 to 3 hours
  • Estimated Cost: ~$1–$2 (within AWS Free Tier and Gemini’s free usage limits)
Note: Gemini API offers a generous free tier, making this project cost-effective for learners.

Architectural Diagram

Final Result

Once completed, you’ll have:

  • A fully functional AI Cloud Tutor web app powered by Gemini and AWS Serverless
  • A secure, scalable backend that integrates cloud infrastructure with AI capabilities
  • A modern web interface for interactive learning
  • Hands-on experience building real-world Generative AI applications on AWS

Complete and Continue