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Review of Part One
Review of Part One
Difficulty
Intermediate
Duration
1h 5m
Students
2085
Ratings
4.6/5
Description

This course is part 2 of 2 on how to stream data using Amazon Kinesis Data Streams.

The course covers shard capacity, Kinesis Data Streams as a streaming storage layer, and the basics of securing data in a Kinesis Data Stream.

Learning Objectives

  • Build upon the topics covered in Amazon Kinesis Data Streams Part 1
  • Learn about shard capacity, scaling, and limits
  • Obtain an in-depth understanding of how a data streaming service is layered and its operations
  • Understand how to secure a Kinesis Data Stream

Intended Audience

This course is intended for people that want to learn how to stream data into the AWS cloud using Amazon Kinesis Data Streams.

Prerequisites

To get the most out of this course, you should have a basic knowledge of the AWS platform.

 

Transcript

Hello, I'm Stephen Cole, a trainer here at Cloud Academy. As a reminder, here's what was covered in part one of this course. Streaming data exists because some data moves faster than others and not all data is created--or used--equally.  

Some data only has value for a short period of time and, by short, I mean measured in seconds.  That's part of the reason why streaming data is a thing today.  It can capture data and use it while it still has value.  

Streaming data works well in the cloud because the cloud has the promise of agility, scalability, and elasticity.  Agility is about changing to meet needs. Being agile is more than adapting to change, it’s also about being able to fit into places that were at one time too big or too small. Scalability means that growth can happen when needed. Elasticity, at least in the cloud, is the opposite of scalability. Even though environments can expand, one of the cloud's key characteristics is that they can return to its original size. This means that environments in the cloud can grow and shrink as needed.

So, if you are no longer using a resource, you can turn it off -- and stop paying for it. This is how I think about it. When I was a kid, my dad would go through the house grumbling about me forgetting to turn the lights out when I left a room.  He'd say things like, "Why am I paying to light up a room nobody is using." This was not far from one of his other remarks, "Close the front door, I'm not paying to heat the whole neighborhood."  Maybe I'm alone in this experience.  I'm not sure.  Still, to me, that's the fundamental principle of elasticity.  It's my dad reminding me that it's a bad idea to pay for something if it isn't being used.

Kinesis Data Streams is one of the features of Amazon Kinesis.  It is a massively scalable and durable real-time data streaming service.  It is not designed for binary data.  For that, use Amazon Kinesis Video Streams.  For data streaming that is near-real time and destined for AWS storage or an HTTP endpoint, use Kinesis Data Firehose.

Kinesis Data Streams  is used to collect data in real time from sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, location tracking events, and IoT devices.

Data collected is available within milliseconds inside a stream and enables applications to do things like analytics, dashboards, anomaly detection, and dynamic pricing in real time.

About the Author
Students
35404
Courses
20
Learning Paths
16

Stephen is the AWS Certification Specialist at Cloud Academy. His content focuses heavily on topics related to certification on Amazon Web Services technologies. He loves teaching and believes that there are no shortcuts to certification but it is possible to find the right path and course of study.

Stephen has worked in IT for over 25 years in roles ranging from tech support to systems engineering. At one point, he taught computer network technology at a community college in Washington state.

Before coming to Cloud Academy, Stephen worked as a trainer and curriculum developer at AWS and brings a wealth of knowledge and experience in cloud technologies.

In his spare time, Stephen enjoys reading, sudoku, gaming, and modern square dancing.