CloudAcademy

Introduction

The course is part of these learning paths

Solutions Architect – Professional Certification Preparation for AWS (2019)
course-steps 45 certification 1 lab-steps 18 description 2
Certified Developer – Associate Certification Preparation for AWS - June 2018
course-steps 26 certification 4 lab-steps 22 description 2
AWS Big Data – Specialty Certification Preparation for AWS
course-steps 14 lab-steps 4 quiz-steps 3

Contents

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Course Introduction
Operating Systems
Kinesis Analytics
Course Conclusion
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Overview
DifficultyIntermediate
Duration40m
Students922

Description

Course Description:

This course will provide you with a good foundation to better understand Amazon Kinesis, along with helping you to get started with building streamed solutions. In this course we'll put a heavier emphasis on hands-on demos along with breaking down the concepts and introducing you to the components that make up Amazon Kinesis.

Intended audience:

  • People working with Big Data
  • Business intelligence
  • DevOps
  • Development

Learning Objectives:

  • Demonstrate knowledge of Amazon Kinesis, what are the core aspects of the service (streams, firehose, analytics), their common use cases, big data use cases, and how do you access / integrate with the Kinesis service Demonstrate how to work with and create Kinesis streams
  • Demonstrate how to work with Kinesis Firehose and how to use Firehose with Redshift
  • Set up monitoring and analysis of the stream services
  • Understand the how to extract analysis from Kinesis

This Course Includes:

  • 45 minutes of high-definition video
  • Live demonstrations on key course concepts

What You'll Learn:

  • Course Intro: What to expect from this course
  • Setting Up CLI on the Linux OS: A demo on setting up the Amazon command line on a Linux operating system.
  • Setting Up CLI on the Windows OS: A demo on setting up the Amazon command line on a Windows operating system.
  • What is Streaming Data: An overview of streaming data and it’s common uses.
  • Setting Up Kinesis Agent: In this demo, we're working with installing the Amazon Kinesis Stream agent.
  • Kinesis Streams: An overview of Kinesis Streams, what they do, and common use cases.
  • Performing Basic Stream Operations: In this demo, we'll be pulling a basic Amazon Kinesis stream from the command line.
  • Firehose: In this lesson we'll be discussing the fully managed solution,Amazon Kinesis Firehose.
  • Firehose Delivery Stream: In this demo we're going to set up an Amazon Kinesis Firehose stream.
  • Testing Delivery Stream: In this lesson we're going to do a quick follow up to the Firehose stream, and test the data delivery.
  • Kinesis Analytics: In this lesson we'll go over the analytics components of Kinesis.
  • Kinesis Analytics Demo: In this demo we're going to begin working with Amazon Kinesis Analytics.
  • Kinesis Features Comparison: In this lesson, we'll compare some products within the Amazon Kinesis suite, as well as some other Amazon services.
  • Course Conclusion: A wrap-up and review of the course.

Transcript

Welcome to the Introduction to Amazon Kinesis. In this course, we'll provide you with a good foundation to better understand Amazon Kinesis, along with helping you to get started with building streamed solutions. I really believe in learning by doing, so in this course we'll put a heavier emphasis on hands-on labs along with breaking down the concepts and introducing you to the components that make up Amazon Kinesis.

This course has been developed for those looking to start working with building solutions to collect, process, transform, and analyze streaming data. Generally, people attending this course work with big data, business intelligence, DevOps, or development. In this course, we will cover these main components. We will address what is Amazon Kinesis? We'll break down the software suite by discussing the three main components, which include Amazon Kinesis Streams, Amazon Kinesis Firehose, and Amazon Kinesis Analytics.

We will also discuss some comparisons between different products and additional features. Now, for a brief introduction, my name is Richard Augenti. I'm a Technology Specialist focused on cloud technologies, internet of things and DevOps solutions. I look forward to joining through this course on working with Kinesis. Well, that wraps up our brief introduction. Next up, we'll discuss what is Amazon Kinesis?

About the Author

Students1049
Courses2
Learning paths1

Richard Augenti is a DevOps Engineer with 23 years of IT professional experience and 7 years of cloud experience with AWS and Azure. He has been engaged with varying sized projects with clients all across the globe including most sectors. He enjoys finding the best and most efficient way to make things work so, working with automation, cloud technologies, and DevOps has been the perfect fit. When Richard is not engaged with work, he can also be found presenting workshops and talks at user conferences on cloud technologies and other techie talks.