Azure Data Factory Declaration

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 resource
pipelineName - 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:

- 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

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Promitor

Bringing Azure Monitor metrics where you need them.

Azure Data Factory