When calling a SageMaker deploy_endpoint function with an a1.small instance, I'm given an error that I can't open a m5.xlarge instance

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So while executing through a notebook generated by Autopilot, I went to execute the final code cell:

pipeline_model.deploy(initial_instance_count=1,
                      instance_type='a1.small',
                      endpoint_name=pipeline_model.name,
                      wait=True)

I get this error

ResourceLimitExceeded: An error occurred (ResourceLimitExceeded) when calling the CreateEndpoint operation: The account-level service limit 'ml.m5.2xlarge for endpoint usage' is 0 Instances, with current utilization of 0 Instances and a request delta of 1 Instances. Please contact AWS support to request an increase for this limit.

The most important part of that is the last line where it mentions resource limits. I'm not trying to open the type of instance it's giving me an error about opening.

Does the endpoint NEED to be on an ml.m5.2xlarge instance? Or is the code acting up?

Thanks in advance guys and gals.

amazon-sagemaker boto3 python
1 Answers

You should use one of on-demand ML hosting instances supported as detailed at this link. I think non-valid instance_type='a1.small' is replaced by a valid one (ml.m5.2xlarge), and that is not in your AWS service quota. The weird part is that seeing instance_type='a1.small' was generated by SageMaker Autopilot.

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