Setting Up Kinesis Agent

Contents

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Course Introduction
1
Introduction
PREVIEW41s
Kinesis Analytics
Course Conclusion
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Overview
DifficultyIntermediate
Duration25m
Students1881
Ratings
3.5/5
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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 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

  • 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.

Updates

28/05/2019 - Re-record of lectures to improve audio 

Transcript

- [Instructor] Welcome back to Working with Amazon Kinesis streams. I'm Richard Augenti and I'll be your instructor for this demo. In this demo, we'll be working with installing the Amazon Kinesis stream Agent. The Kenesis stream Agent is used to connect, create checkpoints, and perform log-rotation on data that you're looking to looking to load into an Amazon Kinesis stream. So, the first thing we're going to do is do a yum install on our Red Hat Linux Operating System here, to install the streaming agent. Okay, results good so far. Great, it installed correctly. Now we're actually creating our stream that we connect our Agent to. So now we're going to edit the Agent and we're going to add our stream name to it and we're going to collect the information from the tmp/app.log. That's where we're loading our data from. Of course, you could point that to wherever you need to collect information from in your particular case. Okay, great. So we save that. Okay, so the Agent's already started so now we're going to set it up so that when the system reboots, the service will start-up automatically. Okay, great. Now we're going to restart the service. Great, everything checks out. Great, so that wraps up our demo on creating an Amazon Kinesis stream Agent. I'm Richard Augenti and I'll see you in the next lesson.

About the Author

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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.