Table of Contents

1. Challenge

   Create an Amazon Kinesis Data Stream

   Create a Kinesis Data Stream named input-stream.

2. Challenge

   Populate Data on the Cloud9 Instance

   1. Add the lab1.py file from the lab GitHub repo to the Cloud9 instance.
   2. Install boto3 on the instance using pip install boto3.
   3. Run the newly created lab.py file with python lab.py.
3. Challenge

   Create a DynamoDB Table

   Create a new DynamoDB table named kinesisAggs and add a partition key named vendorId with type of Number.

4. Challenge

   Create and Configure a Lambda Function

   1. Create a new Lambda function named kinesisLambdaConsumer01.
   2. Set the IAM role to KinesisLambdaConsumerRole-Kinesislab
   3. Download and modify the lambda-deploy.zip file from the lab GitHub repo.
5. Challenge

   Confirm Data is Populating to DynamoDB

   In the DynamoDB section of the console, explore items in the table and confirm that you have at least two entries.

   (If you are not seeing data after 5 minutes, your python script may have timed out. If you do not see data flowing in the CLI, rerun the python lab.py command and data should start flowing through in about 3-5 minutes)

6. Challenge

   Create a CloudFormation Stack

   Create a CloudFormation stack using the template file provided in the GitHub repo for this lab named CFN Build.yaml.