microsoft / microsoft/AzureTRE
When an Azure ML compute instance user resource has public IP, provide `connection_uri`
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Nobody has claimed this yet.
feature
- Dominant language
- Python
- Stars
- 235
- Forks
- 192
- Avg merge
- 1d 23h
- Merged PRs (30d)
- 13
Description
As a researcher when I deploy a public facing Azure Machine learning compute instance user resource I want to be able to connect via the TRE without accessing Azure ML.
When deploy compute instance I would like to chose which URI to publish:
- JupyterLab
- RStudio
- VSCode
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start from the Azure Machine Learning compute instance user resource deployment described in the issue and trace how its public IP is exposed through the TRE. Define how the selected JupyterLab, RStudio, or VSCode URI becomes connection_uri, then verify that the chosen URI is available when the resource has a public IP.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- azure
- Domain
- cloud, infrastructure
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100