Congratulations! In this project, you have learned how to develop a serverless data processing app. In this module, you can find additional challenges to dive deeper into the application and explanations on how to delete the resources you used in this project.

Here’s a list of other things to try if you have spare time to continue tinkering with the unicorn monitoring system:

  • Write a consumer for the wildrydes stream in the programming language of your choice using the AWS SDKs. Experiment with the output format.
  • Build an Amazon Kinesis Data Analytics application which reads from the wildrydes stream and selects data points where any of the unicorns' vital signs is below 100 points.
  • Create an AWS Lambda function to read from the stream and send proactive alerts to operations personnel when any of the unicorns' vital signs is below 100 points.
  • Write additional Amazon Athena queries. Find:
    - Select all latitude and longitude pairs reported by a unicorn on a trip.
    - All data points captured after a specific timestamp
    - The total all-time distance traveled by each unicorn.
    - All data points where a unicorns' vitals were below 100 points.

You have succesfully finished the Serverless real-time Data Processing App Project.

Learn more on how to get started with AWS Lambda >>


  • Amazon Athena

    wildrydes table

    a. Select Services then select Athena in the Analytics section.

    b. Select on the overflow (three vertical dots) icon next to the wildrydes table and select Delete table.

    c. Select Yes to confirm the deletion.

  • Amazon Kinesis Data Firehose

    wildrydes delivery stream

    a. Select Services then select Kinesis in the Analytics section.

    b. Select View all in Kinesis Firehose delivery streams.

    c. Select wildrydes to select the radio button.

    d. Select Delete.

  • Amazon S3

    Data bucket (e.g. wildrydes-data-yourname)

    a. Select Services then select S3 in the Storage section.

    b. Select your bucket's row (e.g. wildrydes-data-yourname) to highlight it.

    c. Select Delete bucket.

    d. Type the name of the bucket (e.g. wildryde-data-yourname) and select Confirm to confirm the deletion.

  • AWS Lambda

    WildRydesStreamProcessor function

    a. Select Services then select Lambda in the Compute section.

    b. Select the radio button next to WildRydesStreamProcessor.

    c. Select Actions and Delete. Select the Delete button to confirm the deletion.

  • Amazon DynamoDB

    UnicornSensorData table

    a. Select Services then select DynamoDB in the Database section.

    b. Select Tables from the left-hand navigation.

    c. Select the radio button next to UnicornSensor Data.

    d. Select Delete table and select Delete to confirm the deletion.

  • AWS IAM

    WildRydesDynamoDBWritePolicy policy

    a. Select Services then select IAM in the Security, Identity & Compliance section.

    b. Select Policies from the left-hand navigation.

    c. Select Customer managed from Filter.

    d. Select the checkbox next to WildRydesDynamoDBWritePolicy.

    e. Select Policy actions and Delete. Select the Delete button to confirm the deletion.

     

    Wildrydes Kinesis Data Analytics policy

    a. Select Policies from the left-hand navigation.

    b. In the search box, enter wildrydes.

    c. Select the checkbox next to kinesis-analytics-service-wildrydes-[region].

    d. Select Policy actions and Delete. Select the Delete to confirm the deletion.

     

    WildRydesStreamProcessor role

    a. Select Roles from the left-hand navigation.

    b. Select the checkbox next to WildRydesStreamProcessor.

    c. Select Delete role and select Yes, delete to confirm the deletion.

     

    wildrydes Amazon Cognito and Kinesis Data Analytics roles

    a. Select Roles from the left-hand navigation.

    b. In the search box, enter wildrydes.  

    c. Select the checkboxes next to Cognito_wildrydesAuth_Role, Cognito_wildrydesUnauth_Role, and kinesis-analytics-wildrydes-[region].

    d. Select Delete role and select Yes, delete to confirm the deletion.

  • Amazon Cognito

    wildrydes identity pool

    a. Select Services, then select Cognito in the Security, Identity & Compliance section.

    b. Select Manage Identity Pools.

    c. Select wildrydes.

    d. Select Edit identity pool.

    e. Scroll down and select Delete identity pool.

    f. Select Delete pool.

  • Amazon Kinesis Data Analytics

    wildrydes application

    a. Select Services then select Kinesis in the Analytics section.

    b. Select View all in Kinesis analytics applications.

    c. Select wildrydes to select the radio button.

    d. Select Actions and Delete application. Select Delete application to confirm the deletion.

  • Amazon Kinesis Data Streams

    wildrydes and wildrydes-summary

    a. Select Services then select Kinesis in the Analytics section.

    b. Select View all in Kinesis data streams.

    c. Select the checkboxes next to wildrydes and wildrydes-summary.

    d. Select Actions and Delete. Select Delete to confirm the deletion.


Now that you built your first serverless real-time data processing app, learn how to create more sophisticated applications. If you are interested in building web apps you can try out the WildRydes Serverless Web App Project. If you want to find more getting started resources for AWS Lambda and serverless data processing, visit the Lambda Getting Started Page. You can also find more advanced resources on the Lambda Resources page.

In this tutorial, you'll create a simple serverless web application that enables users to request unicorn rides from the WildRydes fleet. The application will present users with an HTML based user interface for indicating the location where they would like to be picked up and will interface on the backend with a RESTful web service to submit the request and dispatch a nearby unicorn.

On the Lambda Getting Started page you can find tutorials, workshop, and webinars on how to use AWS Lambda. You can also find resources for a specific use case like data processing, web app development, mobile backend development, and edge computing.

On the Lambda Getting Resources page you can find all kinds of resources for every level of expertise. Besides tutorials and workshops, you will also find advanced customer case studies, customer presentations, whitepapers, and reference architectures.