By using AWS re:Post, you agree to the Terms of Use
/SageMaker AutoML generates ExpiredTokenException/

SageMaker AutoML generates ExpiredTokenException



I can train models using different AWS SageMaker estimators, but when I use SageMaker AutoML Python SDK the following error occurs about 15 minutes into the model training process:

"botocore.exceptions.ClientError: An error occurred (ExpiredTokenException) when calling the DescribeAutoMLJob operation: The security token included in the request is expired"

The role used to create the AutoML object is associated with the following AWS pre-defined policies as well as one inline policy. Can you please let me know what I’m missing that's causing this ExpiredTokenException error?

AmazonS3FullAccess AWSCloud9Administrator AWSCloud9User AmazonSageMakerFullAccess

Inline policy: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "iam:PassRole" , "Resource": "", "Condition": { "StringEquals": { "iam:PassedToService": "" } } }, { "Effect": "Allow", "Action": "sagemaker:DescribeEndpointConfig", "sagemaker:DescribeModel", "sagemaker:InvokeEndpoint", "sagemaker:ListTags", "sagemaker:DescribeEndpoint", "sagemaker:CreateModel", "sagemaker:CreateEndpointConfig", "sagemaker:CreateEndpoint", "sagemaker:DeleteModel", "sagemaker:DeleteEndpointConfig", "sagemaker:DeleteEndpoint", "cloudwatch:PutMetricData", "logs:CreateLogStream", "logs:PutLogEvents", "logs:CreateLogGroup", "logs:DescribeLogStreams", "s3:GetObject", "s3:PutObject", "s3:ListBucket", "ecr:GetAuthorizationToken", "ecr:BatchCheckLayerAvailability", "ecr:GetDownloadUrlForLayer", "ecr:BatchGetImage" , "Resource": "" } ] }

Thanks, Stefan