microsoft / microsoft/dstoolkit-mlops-v2
Synch - Add Asset Management Workflow for deleting registered Model artifacts using python sdk API's - for Azdo pipleines
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 33
- Forks
- 17
- PR merge metrics
- No merged PRs in 30d
Description
As part of the Issues 148 the new github pipelines were added, so same work has to be synched into creating new azdo pipelines
Details:
Document the process of cleanup of azure AML assets (Data Assets, Experiments(jobs), Registered Model Artifacts) either manually if there is no support of python api or through the workflow to cleanup assets
Add a new workflow for deleting registered model artifacts using python sdk apis
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 by reviewing issue 148 and the existing GitHub pipeline implementation, then read the linked Azure ML Python SDK Model.delete documentation. Done means the cleanup process for Azure ML assets is documented and an Azure DevOps workflow is added for deleting registered model artifacts.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- azure, python
- Domain
- cloud, devops, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100