This repository explains serverless application deployment on AWS.
Workshop Link: https://catalog.us-east-1.prod.workshops.aws/v2/workshops/841ce16b-9d86-48ac-a3f6-6a1b29f95d2b
In this tutorial, you'll create a simple serverless web application that implements a "Todo app" with an API to store and retrieve tasks in a cloud database. In addition, we will integrate machine learning to automatically identify and label objects in images attached to tasks.
Amazon S3, AWS Lambda, SAM, Amazon API Gateway, AWS Amplify, Amazon DynamoDB, Amazon Rekognition, AWS Cloud9.
The application architecture uses AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon Simple Storage Service (S3), and AWS Amplify Console. Amplify Console provides continuous deployment and hosting of the static web resources including HTML, CSS, JavaScript, and image files which are loaded in the user's browser. JavaScript executed in the browser sends and receives data from a public backend API built using Lambda and API Gateway. DynamoDB provides a persistence layer where data can be stored by the API's Lambda function. S3 is used to store uploaded images. Finally, Amazon Rekognition is used to detect and label objects in those images.
This Project is divided into multiple steps. Each step describes a scenario of what we're going to build and step-by-step directions to help you implement the architecture and verify your work. The steps must be performed in order for the workshop to be successful.
- Install prerequisites
- Build a serverless backend
- Configure a Lambda Authorizer
- Build and deploy the web application
- Test the application
- Configure Amazon Rekognition Integration
- Terminate Resources