Lakehouse monitoring integration#156
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arpitjasa-db
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arpitjasa-db
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Some initial comments, but thanks for doing this @s-udhaya !
| resolve the `TODOs` in the ModelValidation task of [model-workflow-resource.yml](./model-workflow-resource.yml). | ||
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| ### Setting up model monitoring |
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| ### Setting up model monitoring | |
| ### Setting up Lakehouse monitoring |
Change elsewhere too please to match our branding
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I understand we are still discussing on this internally. I will update this when we finalize the unified naming convention
- Minor readme changes - Use dafault assets_dir path for monitoring
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- Accept inference table name from CLI - Merge monitoring related resources into a single file - Parametrize the metric and validation threshold
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aravind-segu
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aravind-segu
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Looks good Overall. Thank you for working on this. Left some comments. Can we also do an E2E test on this?
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Where did you find documentation for creating monitors through asset bundles as demonstrated in this PR? I see no documentation in the databricks asset bundle configurations reference, nor the Lakehouse Monitoring page Is this due to the feature being in private preview? |
@RegaCaska the DAB docs might still be generating, you can ask in the CLI GitHub, but if you'd like you can use the Terraform or SDK docs to configure it in DABs since it uses the same structure. |
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This PR integrates lakehouse monitoring, with automatic retraining component into mlops-stack.