# How Amazon SageMaker AI works with IAM
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**Important**  
Custom IAM policies that allow Amazon SageMaker Studio or Amazon SageMaker Studio Classic to create Amazon SageMaker resources must also grant permissions to add tags to those resources. The permission to add tags to resources is required because Studio and Studio Classic automatically tag any resources they create. If an IAM policy allows Studio and Studio Classic to create resources but does not allow tagging, "AccessDenied" errors can occur when trying to create resources. For more information, see [Provide permissions for tagging SageMaker AI resources](security_iam_id-based-policy-examples.md#grant-tagging-permissions).  
[AWS managed policies for Amazon SageMaker AI](security-iam-awsmanpol.md) that give permissions to create SageMaker resources already include permissions to add tags while creating those resources.

Before you use IAM to manage access to SageMaker AI, you should understand what IAM features are available to use with SageMaker AI. To get a high-level view of how SageMaker AI and other AWS services work with IAM, see [AWS Services That Work with IAM](https://docs.aws.amazon.com/service-authorization/latest/reference/reference_aws-services-that-work-with-iam.html) in the *Service Authorization Reference*.

**Topics**
+ [Identity-based policies for Amazon SageMaker AI](#security_iam_service-with-iam-id-based-policies)
+ [Resource-based policies within Amazon SageMaker AI](#security_iam_service-with-iam-resource-based-policies)
+ [Policy actions for Amazon SageMaker AI](#security_iam_service-with-iam-id-based-policies-actions)
+ [Policy resources for Amazon SageMaker AI](#security_iam_service-with-iam-id-based-policies-resources)
+ [Policy condition keys for Amazon SageMaker AI](#security_iam_service-with-iam-id-based-policies-conditionkeys)
+ [Authorization based on SageMaker AI tags](#security_iam_service-with-iam-tags)
+ [SageMaker AI IAM roles](#security_iam_service-with-iam-roles)

## Identity-based policies for Amazon SageMaker AI
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With IAM identity-based policies, you can specify allowed or denied actions and resources as well as the conditions under which actions are allowed or denied. SageMaker AI 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](https://docs.aws.amazon.com/service-authorization/latest/reference/reference_policies_elements.html) in the *Service Authorization Reference*.

## Resource-based policies within Amazon SageMaker AI
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**Supports resource-based policies:** No 

Resource-based policies are JSON policy documents that you attach to a resource. Examples of resource-based policies are IAM *role trust policies* and Amazon S3 *bucket policies*. In services that support resource-based policies, service administrators can use them to control access to a specific resource. For the resource where the policy is attached, the policy defines what actions a specified principal can perform on that resource and under what conditions. You must [specify a principal](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_elements_principal.html) in a resource-based policy. Principals can include accounts, users, roles, federated users, or AWS services.

To enable cross-account access, you can specify an entire account or IAM entities in another account as the principal in a resource-based policy. Adding a cross-account principal to a resource-based policy is only half of establishing the trust relationship. When the principal and the resource are in different AWS accounts, an IAM administrator in the trusted account must also grant the principal entity (user or role) permission to access the resource. They grant permission by attaching an identity-based policy to the entity. However, if a resource-based policy grants access to a principal in the same account, no additional identity-based policy is required. For more information, see [Cross account resource access in IAM](https://docs.aws.amazon.com//IAM/latest/UserGuide/access_policies-cross-account-resource-access.html) in the *IAM User Guide*.

**Note**  
Use [AWS Resource Access Manager](https://docs.aws.amazon.com/ram/latest/userguide/what-is.html) for securely sharing supported SageMaker AI resources. To find the list of sharable resources, see [shareable Amazon SageMaker AI resources](https://docs.aws.amazon.com/ram/latest/userguide/shareable.html#shareable-sagemaker).

## Policy actions for Amazon SageMaker AI
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Administrators can use AWS JSON policies to specify who has access to what. That is, which **principal** can perform **actions** on what **resources**, and under what **conditions**.

The `Action` element of a JSON policy describes the actions that you can use to allow or deny access in a policy. Include actions in a policy to grant permissions to perform the associated operation.

Policy actions in SageMaker AI use the following prefix before the action: `sagemaker:`. For example, to grant someone permission to run a SageMaker AI training job with the SageMaker AI `CreateTrainingJob` API operation, you include the `sagemaker:CreateTrainingJob` action in their policy. Policy statements must include either an `Action` or `NotAction` element. SageMaker AI defines its own set of actions that describe tasks that you can perform with this service.

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

```
"Action": [
      "sagemaker:action1",
      "sagemaker:action2"
]
```

You can specify multiple actions using wildcards (\$1). For example, to specify all actions that begin with the word `Describe`, include the following action:

```
"Action": "sagemaker:Describe*"
```



To see a list of SageMaker AI actions, see [Actions, resources, and condition keys for Amazon SageMaker AI](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemaker.html) in the *Service Authorization Reference*.

## Policy resources for Amazon SageMaker AI
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**Supports policy resources:** Yes

Administrators can use AWS 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)](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference-arns.html). 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 (\$1) to indicate that the statement applies to all resources.

```
"Resource":  "*"
```

To see a list of Amazon SageMaker AI resource types and their ARNs, see the following references for actions, resource types, and condition keys defined by Amazon SageMaker AI in the *Service Authorization Reference*.
+ [Amazon SageMaker AI](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemaker.html)
+ [Amazon SageMaker geospatial capabilities](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemakergeospatialcapabilities.html)
+ [Amazon SageMaker Ground Truth Synthetic](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemakergroundtruthsynthetic.html)
+ [Amazon SageMaker AI with MLflow](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemakerwithmlflow.html)

To learn with which actions you can specify the ARN of each resource, see [Actions defined by Amazon SageMaker AI](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemaker.html#amazonsagemaker-actions-as-permissions).

## Policy condition keys for Amazon SageMaker AI
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Administrators can use AWS JSON policies to specify who has access to what. That is, which **principal** can perform **actions** on what **resources**, and under what **conditions**.

The `Condition` element specifies when statements execute based on defined criteria. You can create conditional expressions that use [condition operators](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_elements_condition_operators.html), such as equals or less than, to match the condition in the policy with values in the request. To see all AWS global condition keys, see [AWS global condition context keys](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_condition-keys.html) in the *IAM User Guide*.

SageMaker AI defines its own set of condition keys and also supports using some global condition keys. To see all AWS global condition keys, see [AWS Global Condition Context Keys](https://docs.aws.amazon.com/service-authorization/latest/reference/reference_policies_condition-keys.html) in the *Service Authorization Reference*.



SageMaker AI supports a number of service-specific condition keys that you can use for fine-grained access control for the following operations:
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateHyperParameterTuningJob.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateHyperParameterTuningJob.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateNotebookInstance.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateNotebookInstance.html)
+ [https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateNotebookInstance.html](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateNotebookInstance.html)

To see a list of SageMaker AI condition keys, see [Condition keys for Amazon SageMaker AI ](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemaker.html#amazonsagemaker-policy-keys) in the *Service Authorization Reference*. To learn with which actions and resources you can use a condition key, see [Actions defined by Amazon SageMaker AI](https://docs.aws.amazon.com/service-authorization/latest/reference/list_amazonsagemaker.html#amazonsagemaker-actions-as-permissions).

For examples of using SageMaker AI condition keys, see the following: [Control creation of SageMaker AI resources with condition keys](security_iam_id-based-policy-examples.md#sagemaker-condition-examples).

### Examples
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To view examples of SageMaker AI identity-based policies, see [Amazon SageMaker AI identity-based policy examples](security_iam_id-based-policy-examples.md).

## Authorization based on SageMaker AI tags
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You can attach tags to SageMaker AI resources or pass tags in a request to SageMaker AI. To control access based on tags, you provide tag information in the [condition element](https://docs.aws.amazon.com/service-authorization/latest/reference/reference_policies_elements_condition.html) of a policy using the `sagemaker:ResourceTag/key-name`, `aws:RequestTag/key-name`, or `aws:TagKeys` condition keys. For more information about tagging SageMaker AI resources, see [Control access to SageMaker AI resources by using tags](security_iam_id-based-policy-examples.md#access-tag-policy).

To view an example identity-based policy for limiting access to a resource based on the tags on that resource, see [Control access to SageMaker AI resources by using tags](security_iam_id-based-policy-examples.md#access-tag-policy).

## SageMaker AI IAM roles
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An [IAM role](https://docs.aws.amazon.com/service-authorization/latest/reference/id_roles.html) is an entity within your AWS account that has specific permissions.

### Using temporary credentials with SageMaker AI
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You can use temporary credentials to sign in with federation, assume an IAM role, or to assume a cross-account role. You obtain temporary security credentials by calling AWS STS API operations such as [AssumeRole](https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRole.html) or [GetFederationToken](https://docs.aws.amazon.com/STS/latest/APIReference/API_GetFederationToken.html). 

SageMaker AI supports using temporary credentials.

### Service-linked roles
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SageMaker AI partially supports [service-linked roles](https://docs.aws.amazon.com/service-authorization/latest/reference/id_roles_terms-and-concepts.html#iam-term-service-linked-role). Service-linked roles are currently available for SageMaker Studio Classic.

### Service roles
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This feature allows a service to assume a [service role](https://docs.aws.amazon.com/service-authorization/latest/reference/id_roles_terms-and-concepts.html#iam-term-service-role) on your behalf. This role allows the service to access resources in other services to complete an action on your behalf. Service roles appear in your IAM account and are owned by the account. This means that an IAM administrator can change the permissions for this role. However, doing so might break the functionality of the service.

SageMaker AI supports service roles.

### Choosing an IAM role in SageMaker AI
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When you create a notebook instance, processing job, training job, hosted endpoint, or batch transform job resource in SageMaker AI, you must choose a role to allow SageMaker AI to access SageMaker AI on your behalf. If you have previously created a service role or service-linked role, then SageMaker AI provides you with a list of roles to choose from. It's important to choose a role that allows access to the AWS operations and resources you need. For more information, see [How to use SageMaker AI execution roles](sagemaker-roles.md).