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Testing and QA workflows

As a Snowplow BDP customer there are a number of ways you can test and QA your pipeline to follow good data practices.

Testing new tracking implementations, schema changes, and enrichment changes

When implementing new tracking, or when making changes to your schemas or enrichments, we recommend you run testing by sending events to your sandbox environment before deploying your changes to Production environments.

  1. Find the sandbox endpoint in Snowplow Console - this is accessible on the Environments screen, as well as in the 'Testing details' modal on Data Structures and Enrichments screens.
  2. Send a few events from your application to the sandbox endpoint.
  3. Visit the Kibana interface for your sandbox environment to check that your events have landed in the good queue (i.e. are valid) and that the data looks as you expect it to look (i.e. enriched appropriately, formatted and structured correctly).
  4. Once you are happy that your changes are valid, you can deploy them to Production along with any application code.

Test tracking using automated testing

For more automated testing of your tracking we have a tool called Snowplow Micro which allows you to integrate with your automated testing suite to check that your tracking remains intact as application-level changes are made.

Follow this guide to get familiar with Micro and set it up. Next, take a look at te examples of integrating Micro with Nightwatch and Cypress.

Verify schema dependencies using the Data Structures CI tool

The Data Structures CI is a command-line tool which integrates Data Structures API into your CI/CD pipelines and currently has one task which verifies that all schema dependencies for a project are already deployed into a specified environment, thus preventing tracking going live in your application without the required schemas being published in your Snowplow schema registries.

You can learn about this tool in documentation.

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