The following labs will give you hands-on experience with a number of the topics discussed during the AWS Summit Online.
ℹ️ You will run these lab in your own AWS account. Please follow directions at the end of the labs to remove resources to minimize costs.
These labs will remain available after AWS Summit Online. You can do them at any time, even after AWS Summit Online.
Amazon ECS Containerized Web App
In this lab we will learn how to build and run a containerised application. We will then use the Amazon Elastic Container Service to host and run this container in the Cloud.
Duration: Approximately 45 minutes
Virtual Contact Center
In this lab, you will be building a contact center using Amazon Connect and integrating with Amazon Lex.
Duration: Approximately 60 minutes
Recommendation Engine
In this lab, you will learn the basics of how to use Amazon Neptune in order to create a recommendation system using collaborative filtering.
Duration: Approximately 60 minutes
Sentiment Analysis Web App
In this lab, we will demonstrate how to add the AI and ML cloud service feature to your web application with React and the Amplify Framework.
Duration: Approximately 30 minutes
Lambda@Edge in A/B Testing
In this lab, we will learn how we can use lambda@edge functions to serve different variants of the same static resources from a CloudFront distribution.
Duration: Approximately 60 minutes
Customer Churn Prediction
This lab describes using machine learning (ML) for the automated identification of unhappy customers, also known as customer churn prediction
Duration: Approximately 60 - 90 minutes
Modern Serverless Web App
In this lab, you will learn how to build the Vote Rocket voting web application with React and the Amplify Framework s Duration: Approximately 45 - 60 minutes
Deploy Locust Cluster By AWS CDK
This lab walks you through creating a CDK project in Python that will implement an ECS Service running Locust.io.
Duration: Approximately 45 - 60 minutes
The 2048 Game On Amazon EKS
The lab walks through the steps of setting up ALB Ingress controller, deploying sample application (game 2048) and exposing the application publicly via ALB.
Duration: Approximately 60 minutes
Movies Batch Recommendations
This lab will walk you through on how to train and create batch recommendations using Amazon Personalize.
Duration: Approximately 60 - 90 minutes
Amazon EKS On Fargate
In this lab, we demonstrate how to run Elastic Kubernetes Service on Fargate
Duration: Approximately 60 minutes
Website Authentication
In this lab, you will be building a website with a simple Login button. The goal is to have a public website available to everyone, and another page only visible for authenticated users.
Duration: Approximately 45 minutes
Personalized Recommendations
In this lab you will learn the basics of how to use Amazon Personalize in order to create a recommendation system. Be aware that the data upload and training steps do take a long period to perform.
Duration: Approximately 60 - 90 minutes
Health Visibility Dashboard
This lab is intended to showcase the Health API Organization View feature. Organization View is intended to aggregate Personal Health Dashboard/Health events at the PAYER account level within an organization.
Duration: Approximately 45 - 60 minutes