The disk size is currently not configurable for SageMaker Endpoints with EBS backed volumes. As a workaround, please use instances with ephemeral storage for your SageMaker endpoint.
Example instance types with ephemeral storage:
- m5d instances: https://aws.amazon.com/ec2/instance-types/m5/
- c5d instances: https://aws.amazon.com/ec2/instance-types/c5/
- r5d instances: https://aws.amazon.com/ec2/instance-types/r5/
The full list of Amazon SageMaker instance types can be accessed here: https://aws.amazon.com/sagemaker/pricing/instance-types/
Thanks! Using a x5d instance solves the issue.
And a quick note: even though I could download the big model to endpoint now, I got timeout error when loading the model in the endpoint. After some trial and error, I solved it by increasing the timeout value and reducing the number of worker by setting the environment variables. To do it, pass this dict
env={"SAGEMAKER_MODEL_SERVER_WORKERS":"1",
"SAGEMAKER_MODEL_SERVER_TIMEOUT":"1800"}
when creating the model object.
Relevant content
- asked 2 years ago
- asked 15 days ago
- Accepted Answerasked 5 months ago
- asked 2 years ago
- AWS OFFICIALUpdated a year ago
- AWS OFFICIALUpdated 10 months ago
- AWS OFFICIALUpdated 9 months ago
- AWS OFFICIALUpdated 2 years ago