This lab continues to build Windows application development skills, this time leveraging the Security Token Service (STS) to provide secure access to cloud storage in S3. After demonstrating the basic steps of installing Visual Studio Community Edition and the AWS Toolkit for .NET, the student builds a simple console application in C# using the AWS SDK for .NET. The lab will then demonstrate how to use STS to obtain temporary credentials to access protected S3 resources.
This lab demonstrates the common steps of developing a web application and deploying it to production on AWS. At the start of this lab, you will deploy a functioning web application to AWS Elastic Beanstalk and learn how to deploy applications from version control using command line tools. You will expose a scalability problem with the application, and iterate over the application so that it can seamlessly scale by externalizing server side sessions. You will verify that the issue has been solved with the second deployment. You will learn about AWS Elastic Beanstalk, AWS ElastiCache, and managing AWS resources in an AWS Elastic Beanstalk application via configuration files.
This is a two part lab. In part one of the lab, you will create a Lambda function from a blueprint, create an Amazon Kinesis Stream, then trigger the function with data from your stream and monitor the process with Amazon CloudWatch. In part two of the lab, you will learn the basics of event-driven programming using Amazon DynamoDB, its Streams feature, and AWS Lambda. You will walk through the process of building a real-world application using AWS Triggers, which combines DynamoDB Streams and Lambda. Prerequisites: To successfully complete this lab, you should be familiar with DynamoDB and Kinesis through taking those introductory labs. Node.js and Python programming are required, although full solution code is provided. You should have at a minimum taken the “Introduction to AWS Lambda” lab at qwiklabs.com.
This is a two part lab. In part one of the lab, you will learn how to use a Lambda function with CloudWatch events to monitor the creation of an EC2 instance, using a Lambda function you create manually. In part two of the lab, you will create a Lambda function from a blueprint to alert you to a CloudWatch alarm, with notification through an Amazon SNS topic. Prerequisites: To successfully complete this lab, you should be familiar with basic CloudWatch and SNS concepts. Node.js and Python programming are required, although full solution code is provided. You should have at a minimum taken the “Introduction to AWS Lambda” lab at qwiklabs.com.
This lab introduces the basics of Auto Scaling, highlighting multiple Auto Scaling use cases and the command-line tools used for Auto Scaling configuration. After completing this lab you will have configured and tested an elastic web farm which automatically scales capacity to accommodate load. In addition you will have explored a steady state use case in which Auto Scaling is used to maintain high availability of critical resources.