Data pipeline monitoring 101: Tracking health and performance across the data stack

This article outlines the necessity of end-to-end monitoring to ensure data quality and integrity within the complex, multi-layered structures of modern data pipelines. It provides a framework for tracking essential signals—such as data freshness, volume, and schema changes—using standardized telemetry and data lineage. Finally, the piece introduces Datadog’s suite of observability solutions designed to provide comprehensive visibility and troubleshooting capabilities across the entire data stack.