aws / aws/amazon-sagemaker-feedback

[Wish] A different way to see and run notebook instances

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feature-request
Dominant language
No language data
Stars
10
Forks
3
PR merge metrics
No merged PRs in 30d

Description

### Product Version

- [ ] Amazon SageMaker Studio Classic
- [x] Amazon SageMaker Studio
- [ ] It is not related to SageMaker Studio

### Product Category

JupyterLab

### Description

Image

1. The columns are not useful for example, the last run notebook time says 4 days ago which is not really helpful. However if I have information like the GPU memory, no of CPU cores, RAM, NVMe, networking speed in the form of smart drop down I can filter based on that.
2. For every instance type in a SageMaker, keep a notebook ready with a default ephemeral storage that can be changed. Show top 5 frequently used instance type, rest can be paginated based in the smart drop down filters mentioned in 1. Now user comes and says Run, to get a notebook running. For example, I want to try out a model real quick, I select the instance based on the GPU spec I am looking for and hit the run button.

### Other Details

_No response_

Contributor guide

Open the contributing guide

Research direction

No repository files, tests, or implementation entry points are named. Start by reviewing the SageMaker Studio JupyterLab notebook-instance workflow and the requested filtering, prepared instances, storage, pagination, and run behavior. Done would require an agreed product design and implementation scope before coding can begin.

Written by the indexing model from the issue text.

Assessment

Tech stack
aws, jupyter
Domain
cloud, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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