Azure Data Factory Trigger Tumbling Window
This page shows how to write Terraform for Data Factory Trigger Tumbling Window and write them securely.
The Trigger Tumbling Window in Data Factory can be configured in Terraform with the resource name
azurerm_data_factory_trigger_tumbling_window. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
The following arguments are supported:
name- (Required) Specifies the name of the Data Factory Tumbling Window Trigger. Changing this forces a new resource to be created.
data_factory_id- (Required) The ID of Data Factory in which to associate the Trigger with. Changing this forces a new resource.
frequency- (Required) Specifies the frequency of Tumbling Window. Possible values are
Month. Changing this forces a new resource.
interval- (Required) Specifies the interval of Tumbling Window. Changing this forces a new resource.
pipeline- (Required) A
pipelineblock as defined below.
start_time- (Required) Specifies the start time of Tumbling Window, formatted as an RFC3339 string. Changing this forces a new resource.
activated- (Optional) Specifies if the Data Factory Tumbling Window Trigger is activated. Defaults to
additional_properties- (Optional) A map of additional properties to associate with the Data Factory Tumbling Window Trigger.
annotations- (Optional) List of tags that can be used for describing the Data Factory Tumbling Window Trigger.
delay- (Optional) Specifies how long the trigger waits before triggering new run. formatted as an
description- (Optional) The description for the Data Factory Tumbling Window Trigger.
end_time- (Required) Specifies the end time of Tumbling Window, formatted as an RFC3339 string.
max_concurrency- (Optional) The max number for simultaneous trigger run fired by Tumbling Window. Possible values are between
50. Defaults to
retry- (Optional) A
retryblock as defined below.
trigger_dependency- (Optional) One or more
trigger_dependencyblock as defined below.
pipeline block supports the following:
name- (Required) The Data Factory Pipeline name that the trigger will act on.
parameters- (Optional) The Data Factory Pipeline parameters that the trigger will act on.
retry block supports the following:
count- (Required) The maximum retry attempts if the pipeline run failed.
interval- (Optional) The Interval in seconds between each retry if the pipeline run failed.
trigger_dependency block supports the following:
offset- (Optional) The offset of the dependency trigger. Must be in Timespan format (±hh:mm:ss) and must be a negative offset for a self dependency.
size- (Optional) The size of the dependency tumbling window. Must be in Timespan format (hh:mm:ss).
trigger_name- (Optional) The dependency trigger name. If not specified, it will use self dependency.
The following attributes are exported:
id- The ID of the Data Factory Tumbling Window Trigger.
Explanation in Terraform Registry
Manages a Tumbling Window Trigger inside an Azure Data Factory.
Tips: Best Practices for The Other Azure Data Factory Resources
In addition to the azurerm_data_factory, Azure Data Factory has the other resources that should be configured for security reasons. Please check some examples of those resources and precautions.
Ensure to disable public access
It is better to disable public access for Data Factory, which is enabled as default.
Azure Resource Manager Example
Azure Resource Manager code does not have the related resource.