Run a pipeline
A pipeline run is a single execution of a pipeline with a specific set of parameters. Each run tracks per-step status, logs, metrics, and output artifacts.
Trigger a pipeline run from the SDK and monitor its progress in the UI.
Trigger a run from the SDK
from vantage_sdk import VantageClient
client = VantageClient()
run = client.pipelines.run(
pipeline_name="training-pipeline",
params={"data_path": "/data/raw/dataset.csv"},
experiment="nightly-training",
)
print(f"Run ID: {run.id}")
Success looks like this: the pipeline runs to completion, and each step's output artifacts are available.
Monitor a run in the UI
Open the Pipelines page
Click Workbench in the left sidebar, then click Pipelines.
Navigate to runs
Click the pipeline name, then select the Runs tab.
Browse the runs list
The runs list shows:
| Column | Description |
|---|---|
| Name | Display name of the run |
| Pipeline | Pipeline version |
| Status | Running, Succeeded, Failed, or Skipped |
| Started | Timestamp when the run began |
| Duration | Elapsed time |
Open run details
Click a run row to open the detail view.
Inspect run details
The run detail page shows:
- DAG visualization with color-coded step status (green = succeeded, blue = running, red = failed, grey = skipped)
- Step details -- click any step node to view its inputs, outputs, container image, and logs
- Parameters -- the input parameters used for this run
- Metrics -- output metrics produced by the pipeline steps