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Azure Data Factory Trigger Schedule

This page shows how to write Terraform and Azure Resource Manager for Data Factory Trigger Schedule and write them securely.

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azurerm_data_factory_trigger_schedule (Terraform)

The Trigger Schedule in Data Factory can be configured in Terraform with the resource name azurerm_data_factory_trigger_schedule. The following sections describe 10 examples of how to use the resource and its parameters.

Example Usage from GitHub

main.tf#L1
resource "azurerm_data_factory_trigger_schedule" "adfts" {
  name                = var.data_factory_trigger_schedule_name
  data_factory_name   = var.data_factory_name
  resource_group_name = var.resource_group_name
  pipeline_name       = var.pipeline_name
module.tf#L1
resource "azurerm_data_factory_trigger_schedule" "schedule" {
  name                = var.name
  resource_group_name = var.resource_group_name
  data_factory_name   = var.data_factory_name
  pipeline_name       = var.pipeline_name
  start_time          = try(var.start_time, null)
main.tf#L7
resource "azurerm_data_factory_trigger_schedule" "this" {
  annotations         = var.annotations
  data_factory_name   = var.data_factory_name
  end_time            = var.end_time
  frequency           = var.frequency
  interval            = var.interval
main.tf#L7
resource "azurerm_data_factory_trigger_schedule" "this" {
  annotations         = var.annotations
  data_factory_name   = var.data_factory_name
  end_time            = var.end_time
  frequency           = var.frequency
  interval            = var.interval
module.tf#L1
resource "azurerm_data_factory_trigger_schedule" "schedule" {
  name                = var.name
  resource_group_name = var.resource_group_name
  data_factory_name   = var.data_factory_name
  pipeline_name       = var.pipeline_name
  start_time          = try(var.start_time, null)
module.tf#L1
resource "azurerm_data_factory_trigger_schedule" "schedule" {
  name                = var.name
  resource_group_name = var.resource_group_name
  data_factory_name   = var.data_factory_name
  pipeline_name       = var.pipeline_name
  start_time          = try(var.start_time, null)
module.tf#L10
resource "azurerm_data_factory_trigger_schedule" "schedule" {
  name                = azurecaf_name.schedule.name
  resource_group_name = var.resource_group_name
  data_factory_name   = var.data_factory_name
  pipeline_name       = var.pipeline_name
  start_time          = try(var.settings.start_time, null)
main.tf#L116
resource "azurerm_data_factory_trigger_schedule" "testtrigger" {
  name                = "copytrigger"
  data_factory_name   = azurerm_data_factory.adf.name
  resource_group_name = azurerm_resource_group.rg.name
  pipeline_name       = azurerm_data_factory_pipeline.pipeline_test.name
main.tf#L43
resource "azurerm_data_factory_trigger_schedule" "main" {
  name                = var.data_factory_trigger_name
  data_factory_name   = azurerm_data_factory.main.name
  resource_group_name = data.azurerm_resource_group.main.name
  pipeline_name       = azurerm_data_factory_pipeline.main.name
main.tf#L107
resource "azurerm_data_factory_trigger_schedule" "testtrigger" {
  name                = "copytrigger"
  data_factory_name   = azurerm_data_factory.adf.name
  resource_group_name = azurerm_resource_group.rg.name
  pipeline_name       = azurerm_data_factory_pipeline.pipeline_test.name

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Parameters

>> from Terraform Registry

Explanation in Terraform Registry

Manages a Trigger Schedule inside a Azure Data Factory.

>> from Terraform Registry

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.

risk-label

azurerm_data_factory

Ensure to disable public access

It is better to disable public access for Data Factory, which is enabled as default.

Review your Azure Data Factory settings

In addition to the above, there are other security points you should be aware of making sure that your .tf files are protected in Shisho Cloud.

Microsoft.DataFactory/factories/triggers (Azure Resource Manager)

The factories/triggers in Microsoft.DataFactory can be configured in Azure Resource Manager with the resource name Microsoft.DataFactory/factories/triggers. The following sections describe how to use the resource and its parameters.

Example Usage from GitHub

An example could not be found in GitHub.

Parameters

  • apiVersion required - string
  • name required - string

    The trigger name.

  • properties required
      • additionalProperties optional - object

        Unmatched properties from the message are deserialized this collection

      • annotations optional - array

        List of tags that can be used for describing the trigger.

      • description optional - string

        Trigger description.

  • type required - string

>> from Azure Resource Manager Documentation

The Other Related Azure Data Factory Resources

Frequently asked questions

What is Azure Data Factory Trigger Schedule?

Azure Data Factory Trigger Schedule is a resource for Data Factory of Microsoft Azure. Settings can be wrote in Terraform.

Where can I find the example code for the Azure Data Factory Trigger Schedule?

For Terraform, the FabLabGent/InfrastructureFabLabGent, anmoltoppo/Terraform and kevinhead/azurerm source code examples are useful. See the Terraform Example section for further details.

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