How Amazon Glue DataBrew works with IAM - Amazon Glue DataBrew
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How Amazon Glue DataBrew works with IAM

Before you use IAM to manage access to DataBrew, you should understand what IAM features are available to use with DataBrew. To get a high-level view of how DataBrew and other Amazon services work with IAM, see Amazon Services That Work with IAM in the IAM User Guide.

DataBrew identity-based policies

With IAM identity-based policies, you can specify allowed or denied actions and resources, and also the conditions under which actions are allowed or denied. DataBrew supports specific actions, resources, and condition keys. To learn about all of the elements that you use in a JSON policy, see IAM JSON Policy Elements Reference in the IAM User Guide.

Actions

Administrators can use Amazon JSON policies to specify who has access to what. That is, an Amazon JSON policy can specify which principal can perform actions on what resources, and under what conditions.

The Action element of a JSON policy describes the actions to which you can allow or deny access in a policy. Policy actions usually have the same name as the associated Amazon API operation. There are some exceptions, such as permission-only actions that don't have a matching API operation. There are also some operations that require multiple actions in a policy. These additional actions are called dependent actions.

Include actions in a policy to grant permissions to perform the associated operation.

Policy actions in DataBrew use the following prefix before the action: databrew:. For example, to grant someone permission to run an Amazon EC2 instance with the Amazon EC2 RunInstances API operation, you include the ec2:RunInstances action in their policy. Policy statements must include either an Action or NotAction element. DataBrew defines its own set of actions that describe tasks that you can perform with it.

To specify multiple actions in a single statement, separate them with commas as follows.

"Action": [ "databrew:CreateRecipeJob", "databrew:UpdateSchedule"

You can specify multiple actions using wildcards (*). For example, to specify all actions that begin with the word Describe, include the following action.

"Action": "databrew:Describe*"

To see a list of DataBrew actions, see Actions Defined by Amazon Glue DataBrew in the IAM User Guide.

Resources

Administrators can use Amazon JSON policies to specify who has access to what. That is, which principal can perform actions on what resources, and under what conditions.

The Resource JSON policy element specifies the object or objects to which the action applies. Statements must include either a Resource or a NotResource element. As a best practice, specify a resource using its Amazon Resource Name (ARN). You can do this for actions that support a specific resource type, known as resource-level permissions.

For actions that don't support resource-level permissions, such as listing operations, use a wildcard (*) to indicate that the statement applies to all resources.

"Resource": "*"

The following are the DataBrew APIs that don't support resource level permissions:

  • ListDatasets

  • ListJobs

  • ListProjects

  • ListRecipes

  • ListRulesets

  • ListSchedules

The DataBrew dataset resource has the following Amazon Resource Name (ARN).

arn:${Partition}:databrew:${Region}:${Account}:dataset/${Name}

For more information about the format of ARNs, see Amazon Resource Names (ARNs) and Amazon Service Namespaces.

For example, to specify the i-1234567890abcdef0 instance in your statement, use the following ARN.

"Resource": "arn:aws:databrew:us-east-1:123456789012:dataset/my-chess-dataset"

To specify all instances that belong to a specific account, use the wildcard (*).

"Resource": "arn:aws:databrew:us-east-1:123456789012:dataset/*"

You can't perform some DataBrew actions, such as those for creating resources, on a specific resource. In those cases, you must use the wildcard (*).

"Resource": "*"

To see a list of DataBrew resource types and their ARNs, see Resources Defined by Amazon Glue DataBrew in the IAM User Guide. To learn with which actions you can specify the ARN of each resource, see Actions Defined by Amazon Glue DataBrew.

Condition keys

DataBrew doesn't provide any service-specific condition keys, but it does support using some global condition keys. To see all Amazon global condition keys, see Amazon global condition context keys in the IAM User Guide.

Examples

To view examples of DataBrew identity-based policies, see Identity-based policy examples for Amazon Glue DataBrew.

Resource-based policies in DataBrew

DataBrew doesn't support resource-based policies.

DataBrew IAM Roles

An IAM role is an entity within your Amazon account that has specific permissions.

Using temporary credentials with DataBrew

You can use temporary credentials to sign in with federation, assume an IAM role, or to assume a cross-account role. You get temporary security credentials by calling Amazon STS API operations such as AssumeRole or GetFederationToken.

DataBrew supports using temporary credentials.

Service-linked roles

Service-linked roles allow Amazon services to access resources in other services to complete an action on your behalf. Service-linked roles appear in your IAM account and are owned by the service. An administrator can view but not edit the permissions for service-linked roles.

Choosing an IAM role in DataBrew

When you create a dataset resource in DataBrew, you choose an IAM role to allow DataBrew access on your behalf. If you have previously created a service role or service-linked role, then DataBrew provides you with a list of roles to choose from. Make sure to choose a role that allows read access to an Amazon S3 bucket or Amazon Glue Data Catalog resource, as appropriate.