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when new data added and new endpoint created , is new end point created with the same name as old point
since it end point used in lambda function to access end point from local computer
then end point name should not be changed
but by default , for sagemaker new end point can not be created with the same name as old point
and end point configuration should be deleted
naming convention for new end point should be the same for updated endpoint for using in production with Lambda function
as you wrote
Start SM Pipeline Stack: Designed to respond to new training data uploaded to the specified S3 bucket. It utilizes a Lambda function to trigger the SageMaker pipeline, ensuring that your machine learning models are updated with the latest data automatically
The text was updated successfully, but these errors were encountered:
when new data added and new endpoint created , is new end point created with the same name as old point
since it end point used in lambda function to access end point from local computer
then end point name should not be changed
but by default , for sagemaker new end point can not be created with the same name as old point
and end point configuration should be deleted
naming convention for new end point should be the same for updated endpoint for using in production with Lambda function
as you wrote
Start SM Pipeline Stack: Designed to respond to new training data uploaded to the specified S3 bucket. It utilizes a Lambda function to trigger the SageMaker pipeline, ensuring that your machine learning models are updated with the latest data automatically
The text was updated successfully, but these errors were encountered: