Deep Dive into AWS IoT Rules Engine

This is an interactive course that includes two hours of topical information and two hours of hands-on exercises that are performed within the AWS Console. Through this course, you learn to utilize the AWS IoT rules engine to leverage incoming MQTT messages to interact with AWS services. This course was designed so that you can gain comprehensive and deep knowledge about the AWS IoT rules engine, or select individual topics to deepen your current understanding.

Intended Audience

This course is intended for:

• Device engineers

• Fleet managers

• Cloud architects

• Line of business application developers

• Data engineers

Course Objectives

In this course, you will learn how to:

• Describe the anatomy of an AWS IoT rule

• Manage MQTT messages

• Write rule query statements

• Create actions and error actions

• Route data to endpoints

• Operationalize your systems with the rules engine

Prerequisites

We recommend that attendees of this course have the following prerequisites:

• IoT Foundation: Telemetry

Delivery Method

This course is delivered through:

• Digital training

Duration

5 hours

Course Outline

This course covers the following concepts:

• Introduction

o Welcome to Deep Dive into AWS IoT Rules Engine

o Introduction to AWS IoT rules engine

o Anatomy of a rule

• Managing MQTT Messages

o Managing MQTT messages

o MQTT topics

o Writing the FROM clause

o Choosing the message broker vs. Basic Ingest

• Rule Query Statements

o Introduction to rule query statements

o Writing the SELECT clause

o Writing the WHERE clause

o Passing in literals

o Using functions

o Adjusting for binary payloads

• Actions

o Taking action

o Taking error action

o Using substitution templates

• Destinations

o Introduction to destinations

o Destination lifecycle

o Confirming destinations

• Advanced Rule Query Statements

o Creating case statements

o Implementing inter-object queries

• IoT Operations with the Rules Engine

o Introduction to rules engine for operations

o Tracking performance

o Finding and remediating errors

• Closing

o Summary

o Best practices

o Knowledge check

o Feedback