Test and Validate Feature Quality with Tecton

Tecton is a system used to power features in production machine learning environments, enabling organizations to perform millions of predictions daily and ensuring feature quality is crucial at this scale. In development, interactive testing allows for immediate validation of feature transformation logic using the run() command, while feature variants create branches for testing new or altered features before promoting them to production. Tecton's UI provides advanced capabilities for validating models in production and monitoring data quality, including Data Quality Validations that perform daily checks on Feature Views' non-null and non-empty values. Unit tests are critical for guaranteeing proper format, with a feature repository defining a directory for tests, and tecton test running every test in the repository, while tecton apply applies updates only if all unit tests pass. Additionally, Tecton's new compute engine, Rift, simplifies computing features and running tests on them.