Review and apply role recommendations for BigQuery datasets

This page explains how to view, understand, and apply IAM role recommendations for BigQuery datasets. Role recommendations help you enforce the principle of least privilege by ensuring that principals have only the permissions that they actually need.

Before you begin

Enable the IAM and Recommender APIs.
Enable the APIs
Understand role recommendations.

Required IAM roles

To get the permissions that you need to manage dataset-level role recommendations, ask your administrator to grant you the following IAM roles:

Role Viewer (roles/iam.roleViewer) on your project
IAM Recommender Admin (roles/recommender.iamAdmin) on your project
BigQuery Data Owner (roles/bigquery.dataOwner) on your dataset

For more information about granting roles, see Manage access to projects, folders, and organizations.

These predefined roles contain the permissions required to manage dataset-level role recommendations. To see the exact permissions that are required, expand the Required permissions section:

Required permissions

The following permissions are required to manage dataset-level role recommendations:

To view recommendations:
- iam.roles.get on your project
- iam.roles.list on your project
- recommender.iamPolicyRecommendations.get on your project
- recommender.iamPolicyRecommendations.list on your project
- recommender.iamPolicyInsights.get on your project
- recommender.iamPolicyInsights.list on your project
- bigquery.datasets.getIamPolicy on your dataset
To apply and dismiss recommendations:
- recommender.iamPolicyRecommendations.update on your project
- bigquery.datasets.setIamPolicy on your dataset

You might also be able to get these permissions with custom roles or other predefined roles.

Review and apply recommendations

You can review and apply dataset-level role recommendations with the Google Cloud CLI and the Recommender API.

gcloud

Review your recommendations:

To list your dataset-level recommendations, run the gcloud recommender recommendations list command, filtering for only BigQuery dataset recommendations:

gcloud recommender recommendations list \
    --location=LOCATION \
    --recommender=google.iam.policy.Recommender \
    --project=PROJECT_ID \
    --format=json \
    --filter="recommenderSubtype:REMOVE_ROLE_BIGQUERY_DATASET OR recommenderSubtype:REPLACE_ROLE_BIGQUERY_DATASET"

Replace the following values:

LOCATION: The region where your Cloud Storage datasets are located—for example, us or us-central1.
PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.

The response is similar to the following example. In this example, all users with the Editor role on the project my-project (projectEditor:my-project) have the BigQuery Data Editor role (roles/bigquery.dataEditor) on the dataset dataset-1. However, this role hasn't been used in the past 90 days. As a result, the role recommendation suggests that you revoke the role:

[
  {
    "associatedInsights": [
      {
        "insight": "projects/1069248613794/locations/us/insightTypes/google.iam.policy.Insight/insights/984eccca-0241-472f-baab-2557dd0d7282"
      }
    ],
    "content": {
      "operationGroups": [
        {
          "operations": [
            {
              "action": "remove",
              "path": "/iamPolicy/bindings/*/members/*",
              "pathFilters": {
                "/iamPolicy/bindings/*/condition/expression": "",
                "/iamPolicy/bindings/*/members/*": "projectEditor:my-project",
                "/iamPolicy/bindings/*/role": "roles/bigquery.dataEditor"
              },
              "resource": "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1",
              "resourceType": "bigquery.googleapis.com/Dataset"
            }
          ]
        }
      ],
      "overview": {
        "addedRoles": [],
        "member": "projectEditor:my-project",
        "minimumObservationPeriodInDays": "0",
        "removedRole": "roles/bigquery.dataEditor",
        "resource": "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1"
      }
    },
    "description": "This role has not been used during the observation window.",
    "etag": "\"3b123bc08d028128\"",
    "lastRefreshTime": "2024-02-04T08:00:00Z",
    "name": "projects/1069248613794/locations/us/recommenders/google.iam.policy.Recommender/recommendations/0e9831fe-6810-476b-b14d-2b64bda17288",
    "primaryImpact": {
      "category": "SECURITY",
      "securityProjection": {
        "details": {
          "revokedIamPermissionsCount": 37
        }
      }
    },
    "priority": "P4",
    "recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET",
    "stateInfo": {
      "state": "ACTIVE"
    },
    "targetResources": [
      "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1"
    ]
  },
  {
    "associatedInsights": [
      {
        "insight": "projects/1069248613794/locations/us/insightTypes/google.iam.policy.Insight/insights/9d11057e-9c71-410f-ad55-fc82d87761d0"
      }
    ],
    "content": {
      "operationGroups": [
        {
          "operations": [
            {
              "action": "remove",
              "path": "/iamPolicy/bindings/*/members/*",
              "pathFilters": {
                "/iamPolicy/bindings/*/condition/expression": "",
                "/iamPolicy/bindings/*/members/*": "user:alicexz@google.com",
                "/iamPolicy/bindings/*/role": "roles/bigquery.dataOwner"
              },
              "resource": "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1",
              "resourceType": "bigquery.googleapis.com/Dataset"
            }
          ]
        }
      ],
      "overview": {
        "addedRoles": [],
        "member": "user:alicexz@google.com",
        "minimumObservationPeriodInDays": "0",
        "removedRole": "roles/bigquery.dataOwner",
        "resource": "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1"
      }
    },
    "description": "This role has not been used during the observation window.",
    "etag": "\"1da285f7aa6438f1\"",
    "lastRefreshTime": "2024-02-04T08:00:00Z",
    "name": "projects/1069248613794/locations/us/recommenders/google.iam.policy.Recommender/recommendations/56013294-cf81-402a-8cde-25489545777c",
    "primaryImpact": {
      "category": "SECURITY",
      "securityProjection": {
        "details": {
          "revokedIamPermissionsCount": 64
        }
      }
    },
    "priority": "P4",
    "recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET",
    "stateInfo": {
      "state": "ACTIVE"
    },
    "targetResources": [
      "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1"
    ]
  }
]

Review each recommendation carefully, and consider how it will change the principal's access to Google Cloud resources. To learn how to review recommendations from the gcloud CLI, see Review recommendations on this page.

To apply a recommendation:

Use the gcloud recommender recommendations mark-claimed command to change the recommendation's state to CLAIMED, which prevents the recommendation from changing while you apply it:
```
gcloud recommender recommendations mark-claimed \
    RECOMMENDATION_ID \
    --location=LOCATION \
    --recommender=google.iam.policy.Recommender \
    --project=PROJECT_ID \
    --format=FORMAT \
    --etag=ETAG \
    --state-metadata=STATE_METADATA
```
Replace the following values:
- RECOMMENDATION_ID: The unique identifier for the recommendation. This value appears at the end of the name field in the recommendation. For example, if the name field is projects/example-project/locations/global/recommenders/google.iam.policy.Recommender/recommendations/fb927dc1-9695-4436-0000-f0f285007c0f, the recommendation ID is fb927dc1-9695-4436-0000-f0f285007c0f.
- LOCATION: The region where your BigQuery dataset is located—for example, us or us-central1.
- PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.
- FORMAT: The format of the response. Use json or yaml.
- ETAG: The value of the etag field in the recommendation, such as "dd0686e7136a4cbb". Note that this value can include quotes.
- STATE_METADATA: Optional. Comma-separated key-value pairs that contain your choice of metadata about the recommendation. For example, --state-metadata=reviewedBy=alice,priority=high. The metadata replaces the stateInfo.stateMetadata field in the recommendation.
If the command succeeds, the response shows the recommendation in a CLAIMED state, as shown in the following example. For clarity, the example omits most fields:
```
...
"priority": "P1",
"recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET",
"stateInfo": {
  "state": "CLAIMED"
}
...
```
Get the allow policy for the dataset, then modify and set the allow policy so that it reflects the recommendation.
Update the recommendation's state to SUCCEEDED, if you were able to apply the recommendation, or FAILED, if you could not apply the recommendation:
```
gcloud recommender recommendations COMMAND \
    RECOMMENDATION_ID \
    --location=LOCATION \
    --recommender=google.iam.policy.Recommender \
    --project=PROJECT_ID \
    --format=FORMAT \
    --etag=ETAG \
    --state-metadata=STATE_METADATA
```
Replace the following values:
- COMMAND: Use mark-succeeded, if you were able to apply the recommendation, or mark-failed, if you could not apply the recommendation.
- RECOMMENDATION_ID: The unique identifier for the recommendation. This value appears at the end of the name field in the recommendation. For example, if the name field is projects/example-project/locations/global/recommenders/google.iam.policy.Recommender/recommendations/fb927dc1-9695-4436-0000-f0f285007c0f, the recommendation ID is fb927dc1-9695-4436-0000-f0f285007c0f.
- LOCATION: The region where your BigQuery dataset is located—for example, us or us-central1.
- PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.
- FORMAT: The format of the response. Use json or yaml.
- ETAG: The value of the etag field in the recommendation, such as "dd0686e7136a4cbb". Note that this value can include quotes.
- STATE_METADATA: Optional. Comma-separated key-value pairs that contain your choice of metadata about the recommendation. For example, --state-metadata=reviewedBy=alice,priority=high. The metadata replaces the stateInfo.stateMetadata field in the recommendation.
For example, if you marked the recommendation as having succeeded, the response shows the recommendation in a SUCCEEDED state. For clarity, this example omits most fields:
```
...
"priority": "P1",
"recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET",
"stateInfo": {
  "state": "SUCCEEDED"
}
...
```

REST

These instructions assume that you have authenticated and set the GOOGLE_APPLICATION_CREDENTIALS environment variable.

Review your recommendations:

To list all available recommendations for your BigQuery datasets, use the Recommender API's recommendations.list method.

Before using any of the request data, make the following replacements:

PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.
LOCATION: The region where your BigQuery datasets are located—for example, us or us-central1.
PAGE_SIZE: Optional. The maximum number of results to return from this request. If not specified, the server will determine the number of results to return. If the number of recommendations is greater than the page size, the response contains a pagination token that you can use to retrieve the next page of results.
PAGE_TOKEN: Optional. The pagination token returned in an earlier response from this method. If specified, the list of recommendations will start where the previous request ended.
PROJECT_ID: Your Google Cloud project ID. Project IDs are alphanumeric strings, like my-project.

HTTP method and URL:

GET https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations?filter=recommenderSubtype%20%3D%20REMOVE_ROLE_BIGQUERY_DATASET%20OR%20recommenderSubtype%20%3D%20REPLACE_ROLE_BIGQUERY_DATASET&pageSize=PAGE_SIZE&pageToken=PAGE_TOKEN

To send your request, expand one of these options:

curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Execute the following command:

curl -X GET \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "x-goog-user-project: PROJECT_ID" \
     "https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations?filter=recommenderSubtype%20%3D%20REMOVE_ROLE_BIGQUERY_DATASET%20OR%20recommenderSubtype%20%3D%20REPLACE_ROLE_BIGQUERY_DATASET&pageSize=PAGE_SIZE&pageToken=PAGE_TOKEN"

PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations?filter=recommenderSubtype%20%3D%20REMOVE_ROLE_BIGQUERY_DATASET%20OR%20recommenderSubtype%20%3D%20REPLACE_ROLE_BIGQUERY_DATASET&pageSize=PAGE_SIZE&pageToken=PAGE_TOKEN" | Select-Object -Expand Content

The response is similar to the following example. In this example, all users with the Editor role on the project `my-project` (projectEditor:my-project) have the BigQuery Data Editor role (roles/bigquery.dataEditor) on the dataset dataset-1. However, this role hasn't been used in the past 90 days. As a result, the role recommendation suggests that you revoke the role:

{
  "recommendations": [
    {
      "name": "projects/1069248613794/locations/us/recommenders/google.iam.policy.Recommender/recommendations/0e9831fe-6810-476b-b14d-2b64bda17288",
      "description": "This role has not been used during the observation window.",
      "lastRefreshTime": "2024-02-02T08:00:00Z",
      "primaryImpact": {
        "category": "SECURITY",
        "securityProjection": {
          "details": {
            "revokedIamPermissionsCount": 37
          }
        }
      },
      "content": {
        "operationGroups": [
          {
            "operations": [
              {
                "action": "remove",
                "resourceType": "bigquery.googleapis.com/Dataset",
                "resource": "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1",
                "path": "/iamPolicy/bindings/*/members/*",
                "pathFilters": {
                  "/iamPolicy/bindings/*/condition/expression": "",
                  "/iamPolicy/bindings/*/members/*": "projectEditor:my-project",
                  "/iamPolicy/bindings/*/role": "roles/bigquery.dataEditor"
                }
              }
            ]
          }
        ],
        "overview": {
          "resource": "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1",
          "member": "projectEditor:my-project",
          "removedRole": "roles/bigquery.dataEditor",
          "addedRoles": [],
          "minimumObservationPeriodInDays": "0"
        }
      },
      "stateInfo": {
        "state": "ACTIVE"
      },
      "etag": "\"d008ad3780bad5e0\"",
      "recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET",
      "associatedInsights": [
        {
          "insight": "projects/1069248613794/locations/us/insightTypes/google.iam.policy.Insight/insights/984eccca-0241-472f-baab-2557dd0d7282"
        }
      ],
      "priority": "P4",
      "targetResources": [
        "//bigquery.googleapis.com/projects/my-project/datasets/dataset-1"
      ]
    }
  ]
}

Review each recommendation carefully, and consider how it will change the principal's access to Google Cloud resources. To learn how to review recommendations from the REST API, see Review recommendations on this page.

To apply a recommendation:

Mark the recommendation as CLAIMED:

To mark a recommendation as CLAIMED, which prevents the recommendation from changing while you apply it, use the Recommender API's recommendations.markClaimed method.

Before using any of the request data, make the following replacements:
- PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.
- LOCATION: The region where your BigQuery dataset is located—for example, us or us-central1.
- RECOMMENDATION_ID: The unique identifier for the recommendation. This value appears at the end of the name field in the recommendation. For example, if the name field is projects/example-project/locations/global/recommenders/google.iam.policy.Recommender/recommendations/fb927dc1-9695-4436-0000-f0f285007c0f, the recommendation ID is fb927dc1-9695-4436-0000-f0f285007c0f.
- ETAG: The value of the etag field in the recommendation, such as "dd0686e7136a4cbb". Use backslashes to escape quotes, for example, "\"df7308cca9719dcc\"".
- STATE_METADATA: Optional. An object that contains key-value pairs with your choice of metadata about the recommendation. For example, {"reviewedBy": "alice", "priority": "high"}. The metadata replaces the stateInfo.stateMetadata field in the recommendation.
HTTP method and URL:
```
POST https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markClaimed
```
Request JSON body:
```
{
  "etag": "ETAG",
  "stateMetadata": {
    "STATE_METADATA"
  }
}
```
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "x-goog-user-project: PROJECT_ID" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markClaimed"
```
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markClaimed" | Select-Object -Expand Content
```
The response shows the recommendation in a CLAIMED state, as shown in the following example. For clarity, this example omits most fields:
```
...
"stateInfo": {
  "state": "CLAIMED"
},
"etag": "\"7caf4103d7669e12\"",
"recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET",
...
```
Get the allow policy for the project, then modify the allow policy so that it reflects the recommendation.
Update the recommendation's state to SUCCEEDED, if you were able to apply the recommendation, or FAILED, if you could not apply the recommendation:
SUCCEEDED

To mark a recommendation as SUCCEEDED, indicating that you were able to apply it, use the Recommender API's recommendations.markSucceeded method.

Before using any of the request data, make the following replacements:
- PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.
- LOCATION: The region where your BigQuery dataset is located—for example, us or us-central1.
- RECOMMENDATION_ID: The unique identifier for the recommendation. This value appears at the end of the name field in the recommendation. For example, if the name field is projects/example-project/locations/global/recommenders/google.iam.policy.Recommender/recommendations/fb927dc1-9695-4436-0000-f0f285007c0f, the recommendation ID is fb927dc1-9695-4436-0000-f0f285007c0f.
- ETAG: The value of the etag field in the recommendation, such as "dd0686e7136a4cbb". Use backslashes to escape quotes, for example, "\"df7308cca9719dcc\"".
- STATE_METADATA: Optional. An object that contains key-value pairs with your choice of metadata about the recommendation. For example, {"reviewedBy": "alice", "priority": "high"}. The metadata replaces the stateInfo.stateMetadata field in the recommendation.
HTTP method and URL:
POST https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markSucceeded
Request JSON body:
{ "etag": "ETAG", "stateMetadata": { "STATE_METADATA" } }
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markSucceeded"
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markSucceeded" | Select-Object -Expand Content
The response shows the recommendation in a SUCCEEDED state, as shown in the following example. For clarity, this example omits most fields:
... "stateInfo": { "state": "SUCCEEDED" }, "etag": "\"7caf4103d7669e12\"", "recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET", ...
FAILED

To mark a recommendation as FAILED, indicating that you were not able to apply it, use the Recommender API's recommendations.markFailed method.

Before using any of the request data, make the following replacements:
- PROJECT_ID: The ID of the Google Cloud project that contains your BigQuery datasets. Project IDs are alphanumeric strings, like my-project.
- LOCATION: The region where your BigQuery dataset is located—for example, us or us-central1.
- RECOMMENDATION_ID: The unique identifier for the recommendation. This value appears at the end of the name field in the recommendation. For example, if the name field is projects/example-project/locations/global/recommenders/google.iam.policy.Recommender/recommendations/fb927dc1-9695-4436-0000-f0f285007c0f, the recommendation ID is fb927dc1-9695-4436-0000-f0f285007c0f.
- ETAG: The value of the etag field in the recommendation, such as "dd0686e7136a4cbb". Use backslashes to escape quotes, for example, "\"df7308cca9719dcc\"".
- STATE_METADATA: Optional. An object that contains key-value pairs with your choice of metadata about the recommendation. For example, {"reviewedBy": "alice", "priority": "high"}. The metadata replaces the stateInfo.stateMetadata field in the recommendation.
HTTP method and URL:
POST https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markFailed
Request JSON body:
{ "etag": "ETAG", "stateMetadata": { "STATE_METADATA" } }
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: PROJECT_ID" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markFailed"
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "PROJECT_ID" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://recommender.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/recommenders/google.iam.policy.Recommender/recommendations/RECOMMENDATION_ID:markFailed" | Select-Object -Expand Content
The response shows the recommendation in a FAILED state, as shown in the following example. For clarity, this example omits most fields:
... "stateInfo": { "state": "FAILED" }, "etag": "\"7caf4103d7669e12\"", "recommenderSubtype": "REMOVE_ROLE_BIGQUERY_DATASET", ...

Understand recommendations

Each recommendation includes information to help you understand why the recommendation was made.

For details on the fields of a recommendation, see the Recommendation reference.

To see the permission usage that this recommendation is based on, view the policy insights that are associated with the recommendation. These insights are listed in the associatedInsights field. To view a policy insight that is associated with the recommendation, do the following:

Copy the associated insight's ID. The ID is everything after insights/ in the insight field. For example, if the insight field reads projects/123456789012/locations/us/insightTypes/google.iam.policy.Insight/insights/7849add9-73c0-419e-b169-42b3671173fb, the insight ID is 7849add9-73c0-419e-b169-42b3671173fb.
Follow the instructions to get a policy insight, using the insight ID you copied.

What's next

Learn more about Recommender.
Learn how to use allow policy insights for BigQuery datasets.

Review and apply role recommendations for BigQuery datasets

Before you begin

Required IAM roles

Required permissions

Review and apply recommendations

gcloud

REST

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

`SUCCEEDED`

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

`FAILED`

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

Understand recommendations

What's next