AWS Identity and Access Management
User Guide

Actions, Resources, and Condition Keys for Amazon Machine Learning

Amazon Machine Learning (service prefix: machinelearning) provides the following service-specific resources, actions, and condition context keys for use in IAM permission policies.

References:

Actions Defined by Amazon Machine Learning

You can specify the following actions in the Action element of an IAM policy statement. By using policies, you define the permissions for anyone performing an operation in AWS. When you use an action in a policy, you usually allow or deny access to the API operation or CLI command with the same name. However, in some cases, a single action controls access to more than one operation. Alternatively, some operations require several different actions. For details about the columns in the following table, see The Actions Table.

Actions Description Access Level Resource Types (*required) Condition Keys Dependent Actions
AddTags Adds one or more tags to an object, up to a limit of 10. Each tag consists of a key and an optional value Tagging

batchprediction

datasource

evaluation

mlmodel

CreateBatchPrediction Generates predictions for a group of observations Write

batchprediction*

datasource*

mlmodel*

CreateDataSourceFromRDS Creates a DataSource object from an Amazon RDS Write

datasource*

CreateDataSourceFromRedshift Creates a DataSource from a database hosted on an Amazon Redshift cluster Write

datasource*

CreateDataSourceFromS3 Creates a DataSource object from S3 Write

datasource*

CreateEvaluation Creates a new Evaluation of an MLModel Write

datasource*

evaluation*

mlmodel*

CreateMLModel Creates a new MLModel Write

datasource*

mlmodel*

CreateRealtimeEndpoint Creates a real-time endpoint for the MLModel Write

mlmodel*

DeleteBatchPrediction Assigns the DELETED status to a BatchPrediction, rendering it unusable Write

batchprediction*

DeleteDataSource Assigns the DELETED status to a DataSource, rendering it unusable Write

datasource*

DeleteEvaluation Assigns the DELETED status to an Evaluation, rendering it unusable Write

evaluation*

DeleteMLModel Assigns the DELETED status to an MLModel, rendering it unusable Write

mlmodel*

DeleteRealtimeEndpoint Deletes a real time endpoint of an MLModel Write

mlmodel*

DeleteTags Deletes the specified tags associated with an ML object. After this operation is complete, you can't recover deleted tags Tagging

batchprediction

datasource

evaluation

mlmodel

DescribeBatchPredictions Returns a list of BatchPrediction operations that match the search criteria in the request List
DescribeDataSources Returns a list of DataSource that match the search criteria in the request List
DescribeEvaluations Returns a list of DescribeEvaluations that match the search criteria in the request List
DescribeMLModels Returns a list of MLModel that match the search criteria in the request List
DescribeTags Describes one or more of the tags for your Amazon ML object List

batchprediction

datasource

evaluation

mlmodel

GetBatchPrediction Returns a BatchPrediction that includes detailed metadata, status, and data file information Read

batchprediction*

GetDataSource Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource Read

datasource*

GetEvaluation Returns an Evaluation that includes metadata as well as the current status of the Evaluation Read

datasource*

GetMLModel Returns an MLModel that includes detailed metadata, and data source information as well as the current status of the MLModel Read

mlmodel*

Predict Generates a prediction for the observation using the specified ML Model Write

mlmodel*

UpdateBatchPrediction Updates the BatchPredictionName of a BatchPrediction Write

batchprediction*

UpdateDataSource Updates the DataSourceName of a DataSource Write

datasource*

UpdateEvaluation Updates the EvaluationName of an Evaluation Write

evaluation*

UpdateMLModel Updates the MLModelName and the ScoreThreshold of an MLModel Write

mlmodel*

Resources Defined by Machine Learning

The following resource types are defined by this service and can be used in the Resource element of IAM permission policy statements. Each action in the Actions table identifies the resource types that can be specified with that action. A resource type can also define which condition keys you can include in a policy. These keys are displayed in the last column of the table. For details about the columns in the following table, see The Resource Types Table.

Resource Types ARN Condition Keys
batchprediction arn:${Partition}:machinelearning:${Region}:${Account}:batchprediction/${BatchPredictionId}
datasource arn:${Partition}:machinelearning:${Region}:${Account}:datasource/${DatasourceId}
evaluation arn:${Partition}:machinelearning:${Region}:${Account}:evaluation/${EvaluationId}
mlmodel arn:${Partition}:machinelearning:${Region}:${Account}:mlmodel/${MlModelId}

Condition Keys for Amazon Machine Learning

Machine Learning has no service-specific context keys that can be used in the Condition element of policy statements. For the list of the global context keys that are available to all services, see Available Keys for Conditions in the IAM Policy Reference.