Multi-container endpoints - Amazon SageMaker AI
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Multi-container endpoints

SageMaker AI multi-container endpoints enable customers to deploy multiple containers, that use different models or frameworks, on a single SageMaker AI endpoint. The containers can be run in a sequence as an inference pipeline, or each container can be accessed individually by using direct invocation to improve endpoint utilization and optimize costs.

For information about invoking the containers in a multi-container endpoint in sequence, see Inference pipelines in Amazon SageMaker AI.

For information about invoking a specific container in a multi-container endpoint, see Invoke a multi-container endpoint with direct invocation

The following policy allows invoke_endpoint requests only when the value of the TargetContainerHostname field matches one of the specified regular expressions.

{ "Version": "2012-10-17", "Statement": [ { "Action": [ "sagemaker:InvokeEndpoint" ], "Effect": "Allow", "Resource": "arn:aws:sagemaker:region:account-id:endpoint/endpoint_name", "Condition": { "StringLike": { "sagemaker:TargetContainerHostname": ["customIps*", "common*"] } } } ] }

The following policy denies invoke_endpoint requests when the value of the TargetContainerHostname field matches one of the specified regular expressions in the Deny statement.

{ "Version": "2012-10-17", "Statement": [ { "Action": [ "sagemaker:InvokeEndpoint" ], "Effect": "Allow", "Resource": "arn:aws:sagemaker:region:account-id:endpoint/endpoint_name", "Condition": { "StringLike": { "sagemaker:TargetContainerHostname": ["*"] } } }, { "Action": [ "sagemaker:InvokeEndpoint" ], "Effect": "Deny", "Resource": "arn:aws:sagemaker:region:account-id:endpoint/endpoint_name", "Condition": { "StringLike": { "sagemaker:TargetContainerHostname": ["special*"] } } } ] }

For information about SageMaker AI condition keys, see Condition Keys for SageMaker AI in the Amazon Identity and Access Management User Guide.