aws-samples / aws-samples/amazon-sagemaker-pipeline-deploy-manage-100x-models-python-cdk
naming convention for new end point should be the same for updated endpoint for using in production with Lambda function
- Dominant language
- Python
- Stars
- 10
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
Description
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
Contributor guide
Research direction
The issue does not name any files, tests, or deployment entry points. Start by tracing the SageMaker endpoint creation and deletion flow and the Lambda function that accesses the endpoint; clarify the desired naming and update behavior before deciding what completion should mean.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, python
- Domain
- cloud, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100