What is Impact stream
Impact stream is a focused, run-specific view of the pipelines and datasets affected by a single pipeline failure. It’s generated automatically from a failed run, so you can see the downstream impact of a failure the moment you notice it, instead of reconstructing it yourself in the Lineage view. Impact stream is available for pipeline runs with a Failed status.Open the Impact stream
You can open the Impact stream for a failed pipeline run from Pipeline run history. On the Your activity page, locate a run with a Failed status and click the target iconRead the Impact stream
The Impact stream page has two panels: a pipeline tree on the left, and an Impact stream canvas on the right.Pipeline tree
The pipeline tree shows the hierarchy of pipelines and transformations involved in the run, starting from the root pipeline. Each node displays the pipeline or transformation name, its environment, and a colored dot indicating its status:
Click the target icon
Impact stream canvas
The Impact stream canvas visualizes how datasets and pipelines connect to one another, with arrows showing the direction of data flow. Each node is outlined in a color indicating its status:
The pipeline tree uses three statuses (Successful, Failed, Not executed) because it only shows nodes that were part of the run. The Impact stream canvas adds Potentially affected and Unaffected because it also shows downstream datasets and pipelines that weren’t executed but sit within—or outside—the failure’s dependency path.
Each pipeline node also displays an Impacted assets count, showing how many downstream datasets and pipelines it affects. Dataset nodes display the source connector, dataset name, and column count.
Impact stream and Lineage
Impact stream and Lineage both show dependency relationships between pipelines and datasets, but they serve different purposes:- Impact stream is scoped to a single failed run. It’s generated automatically and answers “what does this failure affect, right now?”
- Lineage is a standing, comprehensive map of dependencies across all your pipelines and datasets. You browse it manually, at any time, independent of any specific run.
