Students will use AWS cloud services to build and host a dynamic web application as part of this project. The application will run on EC2 instances, and the Elastic Load Balancer (ELB) will spread out the traffic. Auto Scaling will make sure that the application is always available, even when there are a lot of users. Amazon S3 will hold the static files, and Amazon RDS will be used for the database layer. CloudWatch will be used to set up monitoring and alerts to keep an eye on performance and system health. This project teaches students how to use AWS to design, deploy, and manage an application that can grow, is safe, and can handle errors.

This project is all about making an application that doesn't need a server to show how powerful event-driven computing can be. Uploading a file to an Amazon S3 bucket automatically starts an AWS Lambda function that processes the file. DynamoDB will store the processed data, and Amazon SNS will send messages about the upload status. IAM roles and policies will be used to keep things safe. Through this project, students will learn how to build apps without having to manage servers, which will save money and make the apps easier to grow.

In this advanced project, students will use AWS analytics services to build a pipeline for processing data in real time. Amazon Kinesis Data Streams will take in the data, and either Kinesis Data Analytics or AWS Lambda functions will process it in real time. Amazon Redshift will store the cleaned-up data for analysis, and Amazon QuickSight dashboards will show the data in a different way. To keep data safe, AWS KMS encryption will be used. This project teaches students how to work with streaming data, do analytics in real time, and make dashboards that show useful information.