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Policy types for @turbot/azure-datafactory

Azure > Data Factory > Approved Regions [Default]

A list of Azure regions in which Azure Data Factory resources are approved for use.

The expected format is an array of regions names. You may use the '*' and
'?' wildcard characters.

This policy is the default value for all Azure Data Factory resources' Approved > Regions policies.

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryApprovedRegionsDefault
Category
Parent
Targets
Default Template Input
"{\n  regions: policyValue(uri:\"tmod:@turbot/azure#/policy/types/approvedRegionsDefault\") {\n    value\n  }\n}\n"
Default Template
"{% if $.regions.value | length == 0 %} [] {% endif %}{% for item in $.regions.value %}- '{{ item }}'\n{% endfor %}"
Schema

Azure > Data Factory > Dataset > Active

Determine the action to take when an Azure Data Factory dataset, based on the Azure > Data Factory > Dataset > Active > * policies.

The control determines whether the resource is in active use, and if not,
has the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Dataset > Active > *), raises an alarm, and takes the defined enforcement
action. Each Active sub-policy can calculate a status of active, inactive
or skipped. Generally, if the resource appears to be Active for any reason
it will be considered Active.

Note: In contrast with Approved, where if the
resource appears to be Unapproved for any reason it will be considered
Unapproved.

See Active for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetActive
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Active",
  "Enforce: Delete inactive with 1 day warning",
  "Enforce: Delete inactive with 3 days warning",
  "Enforce: Delete inactive with 7 days warning",
  "Enforce: Delete inactive with 14 days warning",
  "Enforce: Delete inactive with 30 days warning",
  "Enforce: Delete inactive with 60 days warning",
  "Enforce: Delete inactive with 90 days warning",
  "Enforce: Delete inactive with 180 days warning",
  "Enforce: Delete inactive with 365 days warning"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Active",
    "Enforce: Delete inactive with 1 day warning",
    "Enforce: Delete inactive with 3 days warning",
    "Enforce: Delete inactive with 7 days warning",
    "Enforce: Delete inactive with 14 days warning",
    "Enforce: Delete inactive with 30 days warning",
    "Enforce: Delete inactive with 60 days warning",
    "Enforce: Delete inactive with 90 days warning",
    "Enforce: Delete inactive with 180 days warning",
    "Enforce: Delete inactive with 365 days warning"
  ],
  "example": [
    "Check: Active"
  ],
  "default": "Skip"
}

Azure > Data Factory > Dataset > Active > Age

The age after which the Azure Data Factory dataset
is no longer considered active. If a create time is unavailable, the time Guardrails discovered the resource is used.

The Active
control determines whether the resource is in active use, and if not, has
the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Dataset > Active > *),
raises an alarm, and takes the defined enforcement action. Each Active
sub-policy can calculate a status of active, inactive or skipped. Generally,
if the resource appears to be Active for any reason it will be considered Active.

Note In contrast with Approved, where if the resource appears to be Unapproved
for any reason it will be considered Unapproved.

See Active for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetActiveAge
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Force inactive if age > 1 day",
  "Force inactive if age > 3 days",
  "Force inactive if age > 7 days",
  "Force inactive if age > 14 days",
  "Force inactive if age > 30 days",
  "Force inactive if age > 60 days",
  "Force inactive if age > 90 days",
  "Force inactive if age > 180 days",
  "Force inactive if age > 365 days"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Force inactive if age > 1 day",
    "Force inactive if age > 3 days",
    "Force inactive if age > 7 days",
    "Force inactive if age > 14 days",
    "Force inactive if age > 30 days",
    "Force inactive if age > 60 days",
    "Force inactive if age > 90 days",
    "Force inactive if age > 180 days",
    "Force inactive if age > 365 days"
  ],
  "example": [
    "Force inactive if age > 90 days"
  ],
  "default": "Skip"
}

Azure > Data Factory > Dataset > Active > Last Modified

The number of days since the Azure Data Factory dataset was last modified before it is considered
inactive.

The Active
control determines whether the resource is in active use, and if not, has
the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Dataset > Active > *), raises an alarm, and takes the defined enforcement
action. Each Active sub-policy can calculate a status of active, inactive
or skipped. Generally, if the resource appears to be Active for any reason
it will be considered Active.

Note In contrast with Approved, where if the
resource appears to be Unapproved for any reason it will be considered
Unapproved.

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetActiveLastModified
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Active if last modified <= 1 day",
  "Active if last modified <= 3 days",
  "Active if last modified <= 7 days",
  "Active if last modified <= 14 days",
  "Active if last modified <= 30 days",
  "Active if last modified <= 60 days",
  "Active if last modified <= 90 days",
  "Active if last modified <= 180 days",
  "Active if last modified <= 365 days",
  "Force active if last modified <= 1 day",
  "Force active if last modified <= 3 days",
  "Force active if last modified <= 7 days",
  "Force active if last modified <= 14 days",
  "Force active if last modified <= 30 days",
  "Force active if last modified <= 60 days",
  "Force active if last modified <= 90 days",
  "Force active if last modified <= 180 days",
  "Force active if last modified <= 365 days"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Active if last modified <= 1 day",
    "Active if last modified <= 3 days",
    "Active if last modified <= 7 days",
    "Active if last modified <= 14 days",
    "Active if last modified <= 30 days",
    "Active if last modified <= 60 days",
    "Active if last modified <= 90 days",
    "Active if last modified <= 180 days",
    "Active if last modified <= 365 days",
    "Force active if last modified <= 1 day",
    "Force active if last modified <= 3 days",
    "Force active if last modified <= 7 days",
    "Force active if last modified <= 14 days",
    "Force active if last modified <= 30 days",
    "Force active if last modified <= 60 days",
    "Force active if last modified <= 90 days",
    "Force active if last modified <= 180 days",
    "Force active if last modified <= 365 days"
  ],
  "example": [
    "Active if last modified <= 90 days"
  ],
  "default": "Skip"
}

Azure > Data Factory > Dataset > Approved

Determine the action to take when an Azure Data Factory dataset is not approved based on Azure > Data Factory > Dataset > Approved > * policies.

The Approved control checks the status of the defined Approved sub-policies for the resource. If the resource is not approved according to any of these policies, this control raises an alarm and takes the defined enforcement action.

For any enforcement actions that specify if new, e.g., Enforce: Delete unapproved if new, this control will only take the enforcement actions for resources created within the last 60 minutes.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetApproved
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Approved",
  "Enforce: Delete unapproved if new"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Approved",
    "Enforce: Delete unapproved if new"
  ],
  "example": [
    "Check: Approved"
  ],
  "default": "Skip"
}

Azure > Data Factory > Dataset > Approved > Custom

Determine whether the Azure Data Factory dataset is allowed to exist.
This policy will be evaluated by the Approved control. If an Azure Data Factory dataset is not approved, it will be subject to the action specified in the Azure > Data Factory > Dataset > Approved policy.
See Approved for more information.

Note: The policy value must be a string with a value of Approved, Not approved or Skip, or in the form of YAML objects. The object(s) must contain the key result with its value as Approved or Not approved. A custom title and message can also be added using the keys title and message respectively.

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetApprovedCustom
Category
Parent
Targets
Schema
{
  "example": [
    "Approved",
    "Not approved",
    "Skip",
    {
      "result": "Approved"
    },
    {
      "title": "string",
      "result": "Not approved"
    },
    {
      "title": "string",
      "result": "Approved",
      "message": "string"
    },
    [
      {
        "title": "string",
        "result": "Approved",
        "message": "string"
      },
      {
        "title": "string",
        "result": "Not approved",
        "message": "string"
      }
    ]
  ],
  "anyOf": [
    {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string",
            "pattern": "^[\\W\\w]{1,32}$"
          },
          "message": {
            "type": "string",
            "pattern": "^[\\W\\w]{1,128}$"
          },
          "result": {
            "type": "string",
            "pattern": "^(Approved|Not approved|Skip)$"
          }
        },
        "required": [
          "result"
        ],
        "additionalProperties": false
      }
    },
    {
      "type": "object",
      "properties": {
        "title": {
          "type": "string",
          "pattern": "^[\\W\\w]{1,32}$"
        },
        "message": {
          "type": "string",
          "pattern": "^[\\W\\w]{1,128}$"
        },
        "result": {
          "type": "string",
          "pattern": "^(Approved|Not approved|Skip)$"
        }
      },
      "required": [
        "result"
      ],
      "additionalProperties": false
    },
    {
      "type": "string",
      "pattern": "^(Approved|Not approved|Skip)$"
    }
  ],
  "default": "Skip"
}

Azure > Data Factory > Dataset > Approved > Usage

Determine whether the Azure Data Factory dataset is allowed to exist.

This policy will be evaluated by the Approved control. If an Azure Data Factory dataset is not approved, it will be subject to the action specified in the Azure > Data Factory > Dataset > Approved policy.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetApprovedUsage
Category
Parent
Targets
Valid Value
[
  "Not approved",
  "Approved",
  "Approved if Azure > Data Factory > Enabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Not approved",
    "Approved",
    "Approved if Azure > Data Factory > Enabled"
  ],
  "example": [
    "Not approved"
  ],
  "default": "Approved if Azure > Data Factory > Enabled"
}

Azure > Data Factory > Dataset > CMDB

Configure whether to record and synchronize details for the Azure Data Factory dataset into the CMDB.

The CMDB control is responsible for populating and updating all the attributes for that resource type in the Guardrails CMDB.
All policies and controls in Guardrails are based around the resource, so usually the CMDB policy is set to "Enforce: Enabled".

If set to Skip then all changes to the CMDB are paused - no new resources will be discovered, no updates will be made and deleted resources will not be removed.

To cleanup resources and stop tracking changes, set this policy to "Enforce: Disabled".

URI
tmod:@turbot/azure-datafactory#/policy/types/datasetCmdb
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Enforce: Enabled",
  "Enforce: Enabled if Data Factory provider is Registered",
  "Enforce: Disabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Enforce: Enabled",
    "Enforce: Enabled if Data Factory provider is Registered",
    "Enforce: Disabled"
  ],
  "example": [
    "Skip"
  ],
  "default": "Enforce: Enabled if Data Factory provider is Registered"
}

Azure > Data Factory > Enabled

Enable Azure Data Factory service.

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryEnabled
Category
Parent
Targets
Valid Value
[
  "Enabled",
  "Enabled: Metadata Only",
  "Disabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Enabled",
    "Enabled: Metadata Only",
    "Disabled"
  ],
  "example": [
    "Enabled"
  ],
  "default": "Disabled"
}

Azure > Data Factory > Factory > Active

Determine the action to take when an Azure Data Factory factory, based on the Azure > Data Factory > Factory > Active > * policies.

The control determines whether the resource is in active use, and if not,
has the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Factory > Active > *), raises an alarm, and takes the defined enforcement
action. Each Active sub-policy can calculate a status of active, inactive
or skipped. Generally, if the resource appears to be Active for any reason
it will be considered Active.

Note: In contrast with Approved, where if the
resource appears to be Unapproved for any reason it will be considered
Unapproved.

See Active for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryActive
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Active",
  "Enforce: Delete inactive with 1 day warning",
  "Enforce: Delete inactive with 3 days warning",
  "Enforce: Delete inactive with 7 days warning",
  "Enforce: Delete inactive with 14 days warning",
  "Enforce: Delete inactive with 30 days warning",
  "Enforce: Delete inactive with 60 days warning",
  "Enforce: Delete inactive with 90 days warning",
  "Enforce: Delete inactive with 180 days warning",
  "Enforce: Delete inactive with 365 days warning"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Active",
    "Enforce: Delete inactive with 1 day warning",
    "Enforce: Delete inactive with 3 days warning",
    "Enforce: Delete inactive with 7 days warning",
    "Enforce: Delete inactive with 14 days warning",
    "Enforce: Delete inactive with 30 days warning",
    "Enforce: Delete inactive with 60 days warning",
    "Enforce: Delete inactive with 90 days warning",
    "Enforce: Delete inactive with 180 days warning",
    "Enforce: Delete inactive with 365 days warning"
  ],
  "example": [
    "Check: Active"
  ],
  "default": "Skip"
}

Azure > Data Factory > Factory > Active > Age

The age after which the Azure Data Factory factory
is no longer considered active. If a create time is unavailable, the time Guardrails discovered the resource is used.

The Active
control determines whether the resource is in active use, and if not, has
the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Factory > Active > *),
raises an alarm, and takes the defined enforcement action. Each Active
sub-policy can calculate a status of active, inactive or skipped. Generally,
if the resource appears to be Active for any reason it will be considered Active.

Note In contrast with Approved, where if the resource appears to be Unapproved
for any reason it will be considered Unapproved.

See Active for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryActiveAge
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Force inactive if age > 1 day",
  "Force inactive if age > 3 days",
  "Force inactive if age > 7 days",
  "Force inactive if age > 14 days",
  "Force inactive if age > 30 days",
  "Force inactive if age > 60 days",
  "Force inactive if age > 90 days",
  "Force inactive if age > 180 days",
  "Force inactive if age > 365 days"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Force inactive if age > 1 day",
    "Force inactive if age > 3 days",
    "Force inactive if age > 7 days",
    "Force inactive if age > 14 days",
    "Force inactive if age > 30 days",
    "Force inactive if age > 60 days",
    "Force inactive if age > 90 days",
    "Force inactive if age > 180 days",
    "Force inactive if age > 365 days"
  ],
  "example": [
    "Force inactive if age > 90 days"
  ],
  "default": "Skip"
}

Azure > Data Factory > Factory > Active > Last Modified

The number of days since the Azure Data Factory factory was last modified before it is considered
inactive.

The Active
control determines whether the resource is in active use, and if not, has
the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Factory > Active > *), raises an alarm, and takes the defined enforcement
action. Each Active sub-policy can calculate a status of active, inactive
or skipped. Generally, if the resource appears to be Active for any reason
it will be considered Active.

Note In contrast with Approved, where if the
resource appears to be Unapproved for any reason it will be considered
Unapproved.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryActiveLastModified
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Active if last modified <= 1 day",
  "Active if last modified <= 3 days",
  "Active if last modified <= 7 days",
  "Active if last modified <= 14 days",
  "Active if last modified <= 30 days",
  "Active if last modified <= 60 days",
  "Active if last modified <= 90 days",
  "Active if last modified <= 180 days",
  "Active if last modified <= 365 days",
  "Force active if last modified <= 1 day",
  "Force active if last modified <= 3 days",
  "Force active if last modified <= 7 days",
  "Force active if last modified <= 14 days",
  "Force active if last modified <= 30 days",
  "Force active if last modified <= 60 days",
  "Force active if last modified <= 90 days",
  "Force active if last modified <= 180 days",
  "Force active if last modified <= 365 days"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Active if last modified <= 1 day",
    "Active if last modified <= 3 days",
    "Active if last modified <= 7 days",
    "Active if last modified <= 14 days",
    "Active if last modified <= 30 days",
    "Active if last modified <= 60 days",
    "Active if last modified <= 90 days",
    "Active if last modified <= 180 days",
    "Active if last modified <= 365 days",
    "Force active if last modified <= 1 day",
    "Force active if last modified <= 3 days",
    "Force active if last modified <= 7 days",
    "Force active if last modified <= 14 days",
    "Force active if last modified <= 30 days",
    "Force active if last modified <= 60 days",
    "Force active if last modified <= 90 days",
    "Force active if last modified <= 180 days",
    "Force active if last modified <= 365 days"
  ],
  "example": [
    "Active if last modified <= 90 days"
  ],
  "default": "Skip"
}

Azure > Data Factory > Factory > Approved

Determine the action to take when an Azure Data Factory factory is not approved based on Azure > Data Factory > Factory > Approved > * policies.

The Approved control checks the status of the defined Approved sub-policies for the resource. If the resource is not approved according to any of these policies, this control raises an alarm and takes the defined enforcement action.

For any enforcement actions that specify if new, e.g., Enforce: Delete unapproved if new, this control will only take the enforcement actions for resources created within the last 60 minutes.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryApproved
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Approved",
  "Enforce: Delete unapproved if new"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Approved",
    "Enforce: Delete unapproved if new"
  ],
  "example": [
    "Check: Approved"
  ],
  "default": "Skip"
}

Azure > Data Factory > Factory > Approved > Custom

Determine whether the Azure Data Factory factory is allowed to exist.
This policy will be evaluated by the Approved control. If an Azure Data Factory factory is not approved, it will be subject to the action specified in the Azure > Data Factory > Factory > Approved policy.
See Approved for more information.

Note: The policy value must be a string with a value of Approved, Not approved or Skip, or in the form of YAML objects. The object(s) must contain the key result with its value as Approved or Not approved. A custom title and message can also be added using the keys title and message respectively.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryApprovedCustom
Category
Parent
Targets
Schema
{
  "example": [
    "Approved",
    "Not approved",
    "Skip",
    {
      "result": "Approved"
    },
    {
      "title": "string",
      "result": "Not approved"
    },
    {
      "title": "string",
      "result": "Approved",
      "message": "string"
    },
    [
      {
        "title": "string",
        "result": "Approved",
        "message": "string"
      },
      {
        "title": "string",
        "result": "Not approved",
        "message": "string"
      }
    ]
  ],
  "anyOf": [
    {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string",
            "pattern": "^[\\W\\w]{1,32}$"
          },
          "message": {
            "type": "string",
            "pattern": "^[\\W\\w]{1,128}$"
          },
          "result": {
            "type": "string",
            "pattern": "^(Approved|Not approved|Skip)$"
          }
        },
        "required": [
          "result"
        ],
        "additionalProperties": false
      }
    },
    {
      "type": "object",
      "properties": {
        "title": {
          "type": "string",
          "pattern": "^[\\W\\w]{1,32}$"
        },
        "message": {
          "type": "string",
          "pattern": "^[\\W\\w]{1,128}$"
        },
        "result": {
          "type": "string",
          "pattern": "^(Approved|Not approved|Skip)$"
        }
      },
      "required": [
        "result"
      ],
      "additionalProperties": false
    },
    {
      "type": "string",
      "pattern": "^(Approved|Not approved|Skip)$"
    }
  ],
  "default": "Skip"
}

Azure > Data Factory > Factory > Approved > Regions

A list of Azure regions in which Azure Data Factory factorys are approved for use.

The expected format is an array of regions names. You may use the '*' and '?' wildcard characters.

This policy will be evaluated by the Approved control. If an Azure Data Factory factory is created in a region that is not in the approved list, it will be subject to the action specified in the Azure > Data Factory > Factory > Approved policy.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryApprovedRegions
Category
Parent
Targets
Default Template Input
"{\n  regions: policyValue(uri:\"tmod:@turbot/azure-datafactory#/policy/types/dataFactoryApprovedRegionsDefault\") {\n    value\n  }\n}\n"
Default Template
"{% if $.regions.value | length == 0 %} [] {% endif %}{% for item in $.regions.value %}- &#39;{{ item }}&#39;&#92;n{% endfor %}"
Schema

Azure > Data Factory > Factory > Approved > Usage

Determine whether the Azure Data Factory factory is allowed to exist.

This policy will be evaluated by the Approved control. If an Azure Data Factory factory is not approved, it will be subject to the action specified in the Azure > Data Factory > Factory > Approved policy.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryApprovedUsage
Category
Parent
Targets
Valid Value
[
  "Not approved",
  "Approved",
  "Approved if Azure > Data Factory > Enabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Not approved",
    "Approved",
    "Approved if Azure > Data Factory > Enabled"
  ],
  "example": [
    "Not approved"
  ],
  "default": "Approved if Azure > Data Factory > Enabled"
}

Azure > Data Factory > Factory > CMDB

Configure whether to record and synchronize details for the Azure Data Factory factory into the CMDB.

The CMDB control is responsible for populating and updating all the attributes for that resource type in the Guardrails CMDB.
All policies and controls in Guardrails are based around the resource, so usually the CMDB policy is set to "Enforce: Enabled".

If set to Skip then all changes to the CMDB are paused - no new resources will be discovered, no updates will be made and deleted resources will not be removed.

To cleanup resources and stop tracking changes, set this policy to "Enforce: Disabled".

CMDB controls also use the Regions policy associated with the resource. If region is not in Azure > Data Factory > Factory > Regions policy, the CMDB control will delete the resource from the CMDB.

(Note: Setting CMDB to "Skip" will also pause these changes.)

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryCmdb
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Enforce: Enabled",
  "Enforce: Enabled if Data Factory provider is Registered",
  "Enforce: Disabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Enforce: Enabled",
    "Enforce: Enabled if Data Factory provider is Registered",
    "Enforce: Disabled"
  ],
  "example": [
    "Skip"
  ],
  "default": "Enforce: Enabled if Data Factory provider is Registered"
}

Azure > Data Factory > Factory > Regions

A list of Azure regions in which Azure Data Factory factorys are supported for use.

Any factorys in a region not listed here will not be recorded in CMDB.

The expected format is an array of regions names. You may use the '*' and
'?' wildcard characters.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryRegions
Category
Parent
Targets
Schema
{
  "allOf": [
    {
      "$ref": "azure#/definitions/regionNameMatcherList"
    },
    {
      "default": [
        "australiaeast",
        "brazilsouth",
        "canadacentral",
        "centralindia",
        "centralus",
        "eastasia",
        "eastus",
        "eastus2",
        "francecentral",
        "japaneast",
        "koreacentral",
        "northcentralus",
        "northeurope",
        "southafricanorth",
        "southcentralus",
        "southeastasia",
        "uksouth",
        "usgovtexas",
        "usgovvirginia",
        "westcentralus",
        "westeurope",
        "westus",
        "westus2"
      ]
    }
  ]
}

Azure > Data Factory > Factory > Tags

Determine the action to take when an Azure Data Factory factory tags are not updated based on the Azure > Data Factory > Factory > Tags > * policies.

The control ensure Azure Data Factory factory tags include tags defined in Azure > Data Factory > Factory > Tags > Template.

Tags not defined in Factory Tags Template will not be modified or deleted. Setting a tag value to undefined will result in the tag being deleted.

See Tags for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryTags
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Tags are correct",
  "Enforce: Set tags"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Tags are correct",
    "Enforce: Set tags"
  ],
  "example": [
    "Check: Tags are correct"
  ],
  "default": "Skip"
}

Azure > Data Factory > Factory > Tags > Template

The template is used to generate the keys and values for Azure Data Factory factory.

Tags not defined in Factory Tags Template will not be modified or deleted. Setting a tag value to undefined will result in the tag being deleted.

See Tags for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/factoryTagsTemplate
Category
Parent
Targets
Default Template Input
[
  "{\n  subscription {\n    turbot {\n      id\n    }\n  }\n}\n",
  "{\n  defaultTags: policyValue(uri:\"tmod:@turbot/azure-datafactory#/policy/types/dataFactoryTagsTemplate\" resourceId: \"{{ $.subscription.turbot.id }}\") {\n    value\n  }\n}\n"
]
Default Template
"{%- if $.defaultTags.value | length == 0 %} [] {%- elif $.defaultTags.value != undefined %}{{ $.defaultTags.value | dump | safe }}{%- else %}{% for item in $.defaultTags.value %}- {{ item }}{% endfor %}{% endif %}"
Schema

Azure > Data Factory > Permissions

Configure whether permissions policies are in effect for Azure Data Factory
This setting does not affect Subscription level permissions (Azure/Admin, Azure/Owner, etc)

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryPermissions
Category
Parent
Targets
Valid Value
[
  "Enabled",
  "Disabled",
  "Enabled if Azure > Data Factory > Enabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Enabled",
    "Disabled",
    "Enabled if Azure > Data Factory > Enabled"
  ],
  "example": [
    "Enabled"
  ],
  "default": "Enabled if Azure > Data Factory > Enabled"
}

Azure > Data Factory > Permissions > Levels

Define the permissions levels that can be used to grant access to Storage an
Azure Subscription. Permissions levels defined will appear in the UI to assign
access to Guardrails users.

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryPermissionsLevels
Category
Parent
Targets
Default Template Input
[
  "{\n  item: subscription {\n    turbot{\n      id\n    }\n  }\n}\n",
  "{\n  availableLevels: policyValues(filter:\"policyTypeLevel:self resourceId:{{ $.item.turbot.id }} policyTypeId:'tmod:@turbot/azure-iam#/policy/types/permissionsLevelsDefault'\") {\n    items {\n      value\n    }\n  }\n}\n"
]
Default Template
"{% if $.availableLevels.items[0].value | length == 0 %} [] {% endif %}{% for item in $.availableLevels.items[0].value %}- {{ item }}&#92;n{% endfor %}"
Schema
{
  "type": "array",
  "items": {
    "type": "string",
    "enum": [
      "User",
      "Metadata",
      "ReadOnly",
      "Operator",
      "Admin",
      "Owner"
    ]
  }
}

Azure > Data Factory > Permissions > Levels > Modifiers

A map of Azure API to Guardrails Permission Level used to customize Guardrails'
standard permissions. You can add, remove or redefine the mapping of
Azure API operations to Guardrails permissions levels here.

<br />example:<br /> - &quot;Microsoft.Data Factory/Data Factory/delete&quot;: operator<br /> - &quot;Microsoft.Data Factory/Data Factory/write&quot;: admin<br /> - &quot;Microsoft.Data Factory/Data Factory/read&quot;: readonly<br />

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryPermissionsLevelsModifiers
Category
Parent
Targets
Schema

Azure > Data Factory > Pipeline > Active

Determine the action to take when an Azure Data Factory pipeline, based on the Azure > Data Factory > Pipeline > Active > * policies.

The control determines whether the resource is in active use, and if not,
has the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Pipeline > Active > *), raises an alarm, and takes the defined enforcement
action. Each Active sub-policy can calculate a status of active, inactive
or skipped. Generally, if the resource appears to be Active for any reason
it will be considered Active.

Note: In contrast with Approved, where if the
resource appears to be Unapproved for any reason it will be considered
Unapproved.

See Active for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineActive
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Active",
  "Enforce: Delete inactive with 1 day warning",
  "Enforce: Delete inactive with 3 days warning",
  "Enforce: Delete inactive with 7 days warning",
  "Enforce: Delete inactive with 14 days warning",
  "Enforce: Delete inactive with 30 days warning",
  "Enforce: Delete inactive with 60 days warning",
  "Enforce: Delete inactive with 90 days warning",
  "Enforce: Delete inactive with 180 days warning",
  "Enforce: Delete inactive with 365 days warning"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Active",
    "Enforce: Delete inactive with 1 day warning",
    "Enforce: Delete inactive with 3 days warning",
    "Enforce: Delete inactive with 7 days warning",
    "Enforce: Delete inactive with 14 days warning",
    "Enforce: Delete inactive with 30 days warning",
    "Enforce: Delete inactive with 60 days warning",
    "Enforce: Delete inactive with 90 days warning",
    "Enforce: Delete inactive with 180 days warning",
    "Enforce: Delete inactive with 365 days warning"
  ],
  "example": [
    "Check: Active"
  ],
  "default": "Skip"
}

Azure > Data Factory > Pipeline > Active > Age

The age after which the Azure Data Factory pipeline
is no longer considered active. If a create time is unavailable, the time Guardrails discovered the resource is used.

The Active
control determines whether the resource is in active use, and if not, has
the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Pipeline > Active > *),
raises an alarm, and takes the defined enforcement action. Each Active
sub-policy can calculate a status of active, inactive or skipped. Generally,
if the resource appears to be Active for any reason it will be considered Active.

Note In contrast with Approved, where if the resource appears to be Unapproved
for any reason it will be considered Unapproved.

See Active for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineActiveAge
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Force inactive if age > 1 day",
  "Force inactive if age > 3 days",
  "Force inactive if age > 7 days",
  "Force inactive if age > 14 days",
  "Force inactive if age > 30 days",
  "Force inactive if age > 60 days",
  "Force inactive if age > 90 days",
  "Force inactive if age > 180 days",
  "Force inactive if age > 365 days"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Force inactive if age > 1 day",
    "Force inactive if age > 3 days",
    "Force inactive if age > 7 days",
    "Force inactive if age > 14 days",
    "Force inactive if age > 30 days",
    "Force inactive if age > 60 days",
    "Force inactive if age > 90 days",
    "Force inactive if age > 180 days",
    "Force inactive if age > 365 days"
  ],
  "example": [
    "Force inactive if age > 90 days"
  ],
  "default": "Skip"
}

Azure > Data Factory > Pipeline > Active > Last Modified

The number of days since the Azure Data Factory pipeline was last modified before it is considered
inactive.

The Active
control determines whether the resource is in active use, and if not, has
the ability to delete / cleanup the resource. When running an automated
compliance environment, it's common to end up with a wide range of alarms
that are difficult and time consuming to clear. The Active control brings
automated, well-defined control to this process.

The Active control checks the status of all defined Active policies for the
resource (Azure > Data Factory > Pipeline > Active > *), raises an alarm, and takes the defined enforcement
action. Each Active sub-policy can calculate a status of active, inactive
or skipped. Generally, if the resource appears to be Active for any reason
it will be considered Active.

Note In contrast with Approved, where if the
resource appears to be Unapproved for any reason it will be considered
Unapproved.

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineActiveLastModified
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Active if last modified <= 1 day",
  "Active if last modified <= 3 days",
  "Active if last modified <= 7 days",
  "Active if last modified <= 14 days",
  "Active if last modified <= 30 days",
  "Active if last modified <= 60 days",
  "Active if last modified <= 90 days",
  "Active if last modified <= 180 days",
  "Active if last modified <= 365 days",
  "Force active if last modified <= 1 day",
  "Force active if last modified <= 3 days",
  "Force active if last modified <= 7 days",
  "Force active if last modified <= 14 days",
  "Force active if last modified <= 30 days",
  "Force active if last modified <= 60 days",
  "Force active if last modified <= 90 days",
  "Force active if last modified <= 180 days",
  "Force active if last modified <= 365 days"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Active if last modified <= 1 day",
    "Active if last modified <= 3 days",
    "Active if last modified <= 7 days",
    "Active if last modified <= 14 days",
    "Active if last modified <= 30 days",
    "Active if last modified <= 60 days",
    "Active if last modified <= 90 days",
    "Active if last modified <= 180 days",
    "Active if last modified <= 365 days",
    "Force active if last modified <= 1 day",
    "Force active if last modified <= 3 days",
    "Force active if last modified <= 7 days",
    "Force active if last modified <= 14 days",
    "Force active if last modified <= 30 days",
    "Force active if last modified <= 60 days",
    "Force active if last modified <= 90 days",
    "Force active if last modified <= 180 days",
    "Force active if last modified <= 365 days"
  ],
  "example": [
    "Active if last modified <= 90 days"
  ],
  "default": "Skip"
}

Azure > Data Factory > Pipeline > Approved

Determine the action to take when an Azure Data Factory pipeline is not approved based on Azure > Data Factory > Pipeline > Approved > * policies.

The Approved control checks the status of the defined Approved sub-policies for the resource. If the resource is not approved according to any of these policies, this control raises an alarm and takes the defined enforcement action.

For any enforcement actions that specify if new, e.g., Enforce: Delete unapproved if new, this control will only take the enforcement actions for resources created within the last 60 minutes.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineApproved
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Check: Approved",
  "Enforce: Delete unapproved if new"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Check: Approved",
    "Enforce: Delete unapproved if new"
  ],
  "example": [
    "Check: Approved"
  ],
  "default": "Skip"
}

Azure > Data Factory > Pipeline > Approved > Custom

Determine whether the Azure Data Factory pipeline is allowed to exist.
This policy will be evaluated by the Approved control. If an Azure Data Factory pipeline is not approved, it will be subject to the action specified in the Azure > Data Factory > Pipeline > Approved policy.
See Approved for more information.

Note: The policy value must be a string with a value of Approved, Not approved or Skip, or in the form of YAML objects. The object(s) must contain the key result with its value as Approved or Not approved. A custom title and message can also be added using the keys title and message respectively.

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineApprovedCustom
Category
Parent
Targets
Schema
{
  "example": [
    "Approved",
    "Not approved",
    "Skip",
    {
      "result": "Approved"
    },
    {
      "title": "string",
      "result": "Not approved"
    },
    {
      "title": "string",
      "result": "Approved",
      "message": "string"
    },
    [
      {
        "title": "string",
        "result": "Approved",
        "message": "string"
      },
      {
        "title": "string",
        "result": "Not approved",
        "message": "string"
      }
    ]
  ],
  "anyOf": [
    {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "title": {
            "type": "string",
            "pattern": "^[\\W\\w]{1,32}$"
          },
          "message": {
            "type": "string",
            "pattern": "^[\\W\\w]{1,128}$"
          },
          "result": {
            "type": "string",
            "pattern": "^(Approved|Not approved|Skip)$"
          }
        },
        "required": [
          "result"
        ],
        "additionalProperties": false
      }
    },
    {
      "type": "object",
      "properties": {
        "title": {
          "type": "string",
          "pattern": "^[\\W\\w]{1,32}$"
        },
        "message": {
          "type": "string",
          "pattern": "^[\\W\\w]{1,128}$"
        },
        "result": {
          "type": "string",
          "pattern": "^(Approved|Not approved|Skip)$"
        }
      },
      "required": [
        "result"
      ],
      "additionalProperties": false
    },
    {
      "type": "string",
      "pattern": "^(Approved|Not approved|Skip)$"
    }
  ],
  "default": "Skip"
}

Azure > Data Factory > Pipeline > Approved > Usage

Determine whether the Azure Data Factory pipeline is allowed to exist.

This policy will be evaluated by the Approved control. If an Azure Data Factory pipeline is not approved, it will be subject to the action specified in the Azure > Data Factory > Pipeline > Approved policy.

See Approved for more information.

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineApprovedUsage
Category
Parent
Targets
Valid Value
[
  "Not approved",
  "Approved",
  "Approved if Azure > Data Factory > Enabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Not approved",
    "Approved",
    "Approved if Azure > Data Factory > Enabled"
  ],
  "example": [
    "Not approved"
  ],
  "default": "Approved if Azure > Data Factory > Enabled"
}

Azure > Data Factory > Pipeline > CMDB

Configure whether to record and synchronize details for the Azure Data Factory pipeline into the CMDB.

The CMDB control is responsible for populating and updating all the attributes for that resource type in the Guardrails CMDB.
All policies and controls in Guardrails are based around the resource, so usually the CMDB policy is set to "Enforce: Enabled".

If set to Skip then all changes to the CMDB are paused - no new resources will be discovered, no updates will be made and deleted resources will not be removed.

To cleanup resources and stop tracking changes, set this policy to "Enforce: Disabled".

URI
tmod:@turbot/azure-datafactory#/policy/types/pipelineCmdb
Category
Parent
Targets
Valid Value
[
  "Skip",
  "Enforce: Enabled",
  "Enforce: Enabled if Data Factory provider is Registered",
  "Enforce: Disabled"
]
Schema
{
  "type": "string",
  "enum": [
    "Skip",
    "Enforce: Enabled",
    "Enforce: Enabled if Data Factory provider is Registered",
    "Enforce: Disabled"
  ],
  "example": [
    "Skip"
  ],
  "default": "Enforce: Enabled if Data Factory provider is Registered"
}

Azure > Data Factory > Regions

A list of Azure regions in which Azure Data Factory resources are supported for use.

The expected format is an array of regions names. You may use the '*' and
'?' wildcard characters.

This policy is the default value for all Azure Data Factory resources' Regions policies.

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryRegionsDefault
Category
Parent
Targets
Schema
{
  "allOf": [
    {
      "$ref": "azure#/definitions/regionNameMatcherList"
    },
    {
      "default": [
        "australiaeast",
        "australiasoutheast",
        "brazilsouth",
        "canadacentral",
        "centralindia",
        "centralus",
        "eastasia",
        "eastus",
        "eastus2",
        "francecentral",
        "japaneast",
        "koreacentral",
        "northcentralus",
        "northeurope",
        "southafricanorth",
        "southcentralus",
        "southeastasia",
        "uksouth",
        "usgovtexas",
        "usgovvirginia",
        "westcentralus",
        "westeurope",
        "westus",
        "westus2"
      ]
    }
  ]
}

Azure > Data Factory > Tags Template [Default]

A template used to generate the keys and values for Azure Data Factory resources.

By default, all Data Factory resource Tags > Template policies will use this value.

URI
tmod:@turbot/azure-datafactory#/policy/types/dataFactoryTagsTemplate
Category
Parent
Targets
Default Template Input
"{\n  defaultTags: policyValue(uri:\"tmod:@turbot/azure#/policy/types/defaultTagsTemplate\") {\n    value\n  }\n}\n"
Default Template
"{%- if $.defaultTags.value | length == 0 %} [] {%- elif $.defaultTags.value != undefined %}{{ $.defaultTags.value | dump | safe }}{%- else %}{% for item in $.defaultTags.value %}- {{ item }}{% endfor %}{% endif %}"
Schema

Azure > Turbot > Permissions > Compiled > Levels > @turbot/azure-datafactory

A calculated policy that Guardrails uses to create a compiled list of ALL
permission levels for Azure Data Factory that is used as input to the
stack that manages the Guardrails IAM permissions objects.

URI
tmod:@turbot/azure-datafactory#/policy/types/azureLevelsCompiled
Category
Parent
Targets
Schema

Azure > Turbot > Permissions > Compiled > Service Permissions > @turbot/azure-datafactory

A calculated policy that Guardrails uses to create a compiled list of ALL
permissions for Azure Data Factory that is used as input to the control that manages
the IAM stack.

URI
tmod:@turbot/azure-datafactory#/policy/types/azureCompiledServicePermissions
Category
Parent
Targets
Schema