streamsets/aws-marketplace-reports

AWS Lambda function to generate AWS Marketplace Commerce Analytics Service reports

Generate AWS Marketplace Commerce Analytics Data Sets

This project contains source code and supporting files for a serverless application to generate AWS Marketplace Commerce Analytics data sets

• generate_data_sets_function - Code for the application's Lambda function.
• events - Invocation events that you can use to invoke the function.
• template.yaml - A template that defines the application's AWS resources.

This application reacts to Amazon CloudWatch scheduled events, calling the AWS generate_data_set to generate the most recently available data sets.

Deploy the application

The Serverless Application Model Command Line Interface (SAM CLI) is an extension of the AWS CLI that adds functionality for building and testing Lambda applications. It uses Docker to run your functions in an Amazon Linux environment that matches Lambda.

To use the SAM CLI, you need the following tools.

• SAM CLI - Install the SAM CLI
• Python 3 installed
• Docker - Install Docker community edition

To build and deploy this application for the first time, run the following in your shell:

sam build --use-container
sam deploy --guided

The first command will build the source of your application. The second command will package and deploy your application to AWS, with a series of prompts:

• Stack Name: The name of the stack to deploy to CloudFormation. This should be unique to your account and region, and a good starting point would be something matching your project name.
• AWS Region: The AWS region you want to deploy your app to.
• Confirm changes before deploy: If set to yes, any change sets will be shown to you before execution for manual review. If set to no, the AWS SAM CLI will automatically deploy application changes.
• Allow SAM CLI IAM role creation: Many AWS SAM templates, including this example, create AWS IAM roles required for the AWS Lambda function(s) included to access AWS services. By default, these are scoped down to minimum required permissions. To deploy an AWS CloudFormation stack which creates or modified IAM roles, the CAPABILITY_IAM value for capabilities must be provided. If permission isn't provided through this prompt, to deploy this example you must explicitly pass --capabilities CAPABILITY_IAM to the sam deploy command.
• Save arguments to samconfig.toml: If set to yes, your choices will be saved to a configuration file inside the project, so that in the future you can just re-run sam deploy without parameters to deploy changes to your application.

Use the SAM CLI to build and test locally

Build the application with the sam build --use-container command.

AWS$ sam build --use-container

The SAM CLI installs dependencies defined in generate_data_sets_function/requirements.txt, creates a deployment package, and saves it in the .aws-sam/build folder.

Test a single function by invoking it directly with a test event. An event is a JSON document that represents the input that the function receives from the event source. Test events are included in the events folder in this project.

Run functions locally and invoke them with the sam local invoke command.

AWS$ sam local invoke GenerateDataSetsFunction --event events/event.json

      Events:
        GenerateDataSets:
          Type: Schedule
          Properties:
            Schedule: cron(30 0 * * ? *)

Fetch, tail, and filter Lambda function logs

To simplify troubleshooting, SAM CLI has a command called sam logs. sam logs lets you fetch logs generated by your deployed Lambda function from the command line. In addition to printing the logs on the terminal, this command has several nifty features to help you quickly find the bug.

NOTE: This command works for all AWS Lambda functions; not just the ones you deploy using SAM.

AWS$ sam logs -n GenerateDataSetsFunction --stack-name AWS --tail

You can find more information and examples about filtering Lambda function logs in the SAM CLI Documentation.

Cleanup

To delete the application, use the AWS CLI. Assuming you used your project name for the stack name, you can run the following:

aws cloudformation delete-stack --stack-name AWS

Resources

See this blog post for an explanation of how to build a data pipeline with StreamSets Data Collector to ingest the generated data sets into a relational database.