Add support for experiments in direct deployment#3669
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shreyas-goenka merged 26 commits intomainfrom Oct 1, 2025
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- Add ResourceExperiment adapter implementing CRUD operations for MLflow experiments - Add experiments to SupportedResources in direct deployment bundle - Add acceptance test for experiment deployment in both terraform and direct modes - Enable creating, updating, and deleting experiments via direct API calls This allows experiments to be deployed using DATABRICKS_BUNDLE_ENGINE=direct-exp, providing an alternative to the terraform-based deployment approach.
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Can we enable acceptance/bundle/deploy/mlops-stacks/ ? |
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denik
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Looks good. Same suggestion on test organization as in https://github.com/databricks/cli/pull/3670/files#r2393785138 (can be a follow up).
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| func (*ResourceExperiment) FieldTriggers() map[string]deployplan.ActionType { | ||
| return map[string]deployplan.ActionType{ | ||
| "name": deployplan.ActionTypeUpdate, |
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a link to corresponding TF code would be helpful there.
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This was referenced Oct 1, 2025
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| @@ -0,0 +1,3 @@ | |||
| update experiments.my_experiment | |||
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| Plan: 0 to add, 1 to change, 0 to delete, 0 unchanged | |||
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Why do we have 'update' for terraform but 'skip' for direct here? @shreyas-goenka
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I think I remember now, terraform shows changes but does not perform the update. Direct also does not do the update for tags but also does not show it in the plan.
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Changes
This PR adds support for ML experiments to direct deployment, keeping the behaviour the same as the current Terraform implementation.
Why
To make migration to direct possible and seamless.
Tests
New integration test.