Azure Data Factory¶
You can declare to scrape an Azure Data Factory resource via the DataFactory
resource
type.
When using declared resources, the following fields need to be provided:
factoryName
- The name of the Azure Data Factory resourcepipelineName
- The name of the data pipeline (optional)
All supported metrics are documented in the official Azure Monitor documentation.
The following scraper-specific metric label will be added:
pipeline_name
- Name of the data pipeline.
Example¶
Here is an example configuration:
- name: azure_data_factory_pipeline_run_successful
description: "Amount of successful runs for 'data-pipeline-example' pipline in Azure Data Factory"
resourceType: DataFactory
azureMetricConfiguration:
metricName: PipelineSucceededRuns
aggregation:
type: Total
resources: # Optional, required when no resource discovery is configured
- factoryName: promitor-data-factory
pipelineName: data-pipeline-example
resourceDiscoveryGroups: # Optional, requires Promitor Resource Discovery agent (https://promitor.io/concepts/how-it-works#using-resource-discovery)
- name: data-factory-landscape