This is part two of a three-part lab which teaches you how to create a "serverless" web app with an Amazon DynamoDB backend data store. In this second part of the lab, you will build upon the infrastructure created in part one. You will go on to create Lambda functions that interact with the DynamoDB table and add data, then build the necessary IAM roles and polices to support access to the functions and database via API Gateway. To successfully complete this lab, you should be familiar with DynamoDB, API Gateway, and IAM.
In this hands-on lab, you'll learn how to load data from Amazon S3 into an Amazon Redshift cluster and use Tableau Desktop for creating visualizations from that dataset. Note: registration and providing your personal contact information to Tableau is required for access to the trial version of Tableau Desktop needed for this lab. You may be contacted by Tableau as per their license agreements, which are provided during installation.
This lab will demonstrate the basics of search engines and Amazon CloudSerach. It will cover how to create a search domain, how to configure it, how to upload data, how to build queries, and how to tune your ranking. You will explore the features of the AWS Management Console and learn how easy it is to get started with Amazon CloudSearch.
This is part three of a three-part lab which teaches you how to create a "serverless" web app with an Amazon DynamoDB backend data store. In this lab you will configure an API using Amazon API Gateway and set up a public website to retrieve information from your DynamoDB table via Lambda functions, using what you learned in all three labs. To successfully complete this lab, you should be familiar with DynamoDB and API Gateway through taking those introductory labs at qwiklabs.com.
This lab will provide you with a basic understanding of using the AWS Database Migration Service. In this lab you will migrate data from a MySQL database running on an Amazon EC2 instance to an Amazon Aurora RDS instance. This lab has a longer startup time of at least 15 minutes to allow the lab resources to fully launch and initialize. For the lab to function as written, please DO NOT change the auto assigned region.
This lab provides a basic understanding and hands-on experience of AWS Key Management Service. It will demonstrate the basic steps required to get started with Key Management Service, creating keys, assigning management and usage permissions for the keys, encrypting data and monitoring the access and usage of keys. For the lab to function as written, please DO NOT change the auto assigned region.
In this lab, you will take a close look at different types of table layout and schema design. You will create tables using various methods for data compression and distribution, and analyze which methods work best, including incorporating Amazon Redshift recommendations. You will conclude the lab by building five different versions of the same table, and analyzing how the differences impact storage requirements and query performance. Pre-requisites: To successfully complete this lab, you should be familiar with Redshift concepts. Knowledge of SQL programming is required, although full solution code is provided.
In this lab, you will run a simple IoT device simulator on Amazon EC2. The device simulator will generate and publish sample sensor data to an AWS device gateway. You will then build a simple rule that will publish a notification to an AWS SNS topic when the temperature of the device is within a defined threshold. By connecting your email address with the SNS topic, you will receive an email notification when the threshold is met. Finally, you will update the device shadow, instructing the device to “turn on the air conditioning”, resulting in lowering temperatures.
Amazon ElastiCache is a web service that helps improve the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying on slower disk-based databases. Amazon ElastiCache has no upfront costs. With on-demand nodes you pay only for the resources you consume by the hour without any long-term commitments. In this lab, you will use open source Landsat data and a MySQL database to illustrate the capabilities of ElastiCache with Redis.
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.