AWS Serverless Design for IoT
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 44100 Hz
Language: English | VTT | Size: 3.28 GB | Duration: 12 section | 65 lectures | (7h 3m)
What you'll learn

Basic IoT Serverless design patterns on AWS
AWS IoT workflows, rules, and actions with AWS IoT Core
Programming the ESP8266 and the ESP32 with the free Arduino IDE
AWS serverless design patterns
Gain experience with AWS serverless services such as Lambda, S3, API Gateway, DynamoDB, and IoT Analytics
Become familiar with device to cloud communication
Learn how to host static websites on AWS s3 and set bucket permissions and CORS
Gain competency understanding visualizations in jаvascript with IoT data

Requirements
Basic Knowledge of AWS cloud services
Familiarity with jаvascript
Fundamental knowledge of the Internet of Things ( IoT)
Ability to configure and run a basic Arduino Sketch on the ESP8266 or ESP32
Ability to create a free tier AWS account, create a root/super user, and navigate between AWS services
Description
This course is a hands-on introduction to device to cloud communication using Amazon's AWS serverless design flow. This course is meant as a basic, non-production level, introduction to both device to cloud communications, and how to the manipulate IoT data on AWS using the serverless model.

In the course we focuses on a serverless design flow utilizing simple IoT data generated data by either the ESP8266 12-E or ESP32 embedded development boards using WiFi. The course will cover how to program the devices, send the IoT data wirelessly to AWS through the AWS IoT Core MQTT broker, and then demonstrate how to store and visualize the IoT data utilizing various serverless services and design flows on AWS. We will be using the AWS website to navigate services, and not the "Serverless" framework.

Some of the important AWS services covered in in the course for IoT Data are: Lambda, API Gateway, S3, and DynamoDB. In addition, the course will cover other important AWS services such as AWS IoT Analytics, QuickSight, SageMaker, Kinesis, Cognito, and AWS IoT Core. We will also be using jаvascript and Node.js for our static web host and Lambda respectively.

We will start off the course by learning how to program the ESP device to connect to the AWS IoT Core MQTT broker. From there we will cover AWS IoT Analytic s which is a managed services which tacitly utilizes additional underlying AWS services. We will then move on to storing sensor information from our device using Lambda to form a data lake in S3 which we will use a repository for our IoT data. We will then access our IoT data, generated from our ESP device, with a statically hosted website in S3 demonstrating various visualizations methods such as Google Charts, Chart.js, and Highcharts as jаvascript visualization libraries. From this point we can now move on to slightly more complex examples using the AWS-JS-SDK in the browser to invoke AWS services directly on our S3 web host. At this point we can move on to a more advanced serverless flow by having our static web host request IoT data held in a data lake repository on S3, or stored in DynamoDB, by making a request to an endpoint generated by API Gateway connecting a Lambda function that's programmed to fetch our data from our IoT data repository.