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Labs

Create an Amazon Kinesis Data Stream Using AWS Cloud9

In this lab, you are playing the role of a Data Engineer currently working for Pluralsight Taxis. You have been given some data that eventually needs to be examined to see which taxi ride fares and starting points are most popular. To start, you will create a Cloud9 instance to send data to a Kinesis Data Stream. You will then use a Kinesis Firehose to extract and load the data into an S3 bucket where it can easily be examined and eventually processed.

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Lab platform
Lab Info
Level
Beginner
Last updated
Sep 20, 2025
Duration
45m

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Table of Contents
  1. Challenge

    Create an Amazon Kinesis Data Stream

    In the console, create a new Kinesis Data Stream named input-stream

  2. Challenge

    Create a Data Creation File

    Copy the code from the lab.py file from the GitHub repo and paste it into a new file within the Cloud9 instance. Be sure to save it! https://github.com/pluralsight-cloud/amazon-kinesis-deep-dive/blob/main/Create%20an%20Amazon%20Kinesis%20Data%20Stream%20Using%20AWS%20Cloud9/lab.py

  3. Challenge

    Send Data to the Kinesis Data Stream and Monitor Progress
    • Run the lab.py file on the Cloud9 instance.
    • In the Kinesis section of the console, navigate to the input-stream and check the monitoring tab to make sure the data is coming to the stream correctly.
  4. Challenge

    Install Boto3 in the Cloud9 Instance

    Use pip install boto3 to run the python file you just created.

  5. Challenge

    Create a Kinesis Data Firehose and Examine the Output in S3

    Create a Kinesis Data Firehose using the previously created input-stream as the source and a newly created S3 bucket as the destination.

  6. Challenge

    Create a Cloud9 Instance

    Get to the Cloud9 section of the console and create a new cloud9 instance as a T3.micro

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