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Capstone 1 project from AWS Cloud Institute – serverless app using Lambda, S3, Rekognition, DynamoDB, and Step Functions.

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DiegoLabra/capstone-awsci

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Capstone 1 – AWS Cloud Institute

This project was part of my AWS Cloud Institute training, where I built a real-world serverless application using multiple AWS services. The goal was to simulate a workflow for processing and validating customer documents in a cloud-native way.

What the Project Does

The app handles a customer’s application package, which includes a selfie, a photo ID, and a details file. Here's what it does behind the scenes:

  • Pulls the documents from an S3 bucket
  • Unzips and organizes them
  • Parses the customer details from a CSV file
  • Compares the face on the ID and the selfie using Amazon Rekognition
  • Saves the results into DynamoDB
  • Sends out an SNS notification about the match status

It’s all event-driven and fully serverless.

AWS Services Used

  • Lambda – backend logic (split across multiple functions)
  • API Gateway – for triggering Lambda if needed
  • Amazon S3 – to store zipped and unzipped files
  • Amazon Rekognition – to compare facial images
  • Amazon DynamoDB – for storing application and match results
  • SNS – to send out notification messages
  • AWS Step Functions – to orchestrate the process
  • AWS SAM – used to build and deploy everything as infrastructure-as-code

Folder Breakdown

  • CompareDetailsLambdaFunction/ – Parses and stores CSV details
  • CompareFacesLambdaFunction/ – Handles face comparison with Rekognition
  • SubmitLicenseLambdaFunction/ – Moves license image to the right place
  • UnzipLambdaFunction/ – Extracts files from zipped input
  • ValidateLicenseLambdaFunction/ – Validates document structure
  • WriteToDynamoLambdaFunction/ – Writes final results to DynamoDB
  • template.yaml – SAM template defining the infrastructure
  • README.md – You're reading it

What I Learned

Before this, I had a good understanding of AWS basics. This project pushed me deeper into how all the services work together — especially Step Functions and SAM. I also got more comfortable troubleshooting issues during deployment and thinking about security, scalability, and permissions the way real cloud developers do.

About Me

I'm Diego Labra, an AWS Cloud Institute student and aspiring cloud developer. I come from a healthcare background but have shifted into cloud computing because I love solving problems and building things that run at scale. If you're hiring or just want to connect, I’d love to chat!

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Capstone 1 project from AWS Cloud Institute – serverless app using Lambda, S3, Rekognition, DynamoDB, and Step Functions.

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