feat(runtime): support dataset auto-create policy

[jakharmonika364]

Ⅰ. Describe what this PR does

• Adds a runtime annotation fluid.io/dataset-policy: "auto-create" to let a Runtime start without a pre-created Dataset.
• When this annotation is set and the matching Dataset is missing, the shared RuntimeReconciler auto-creates a minimal Dataset with the same name/namespace and keeps the existing binding flow unchanged for other cases.

---

Ⅱ. Does this pull request fix one issue?

fixes #4518

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Ⅲ. List the added test cases (unit test/integration test) if any, please explain if no tests are needed.

No new tests in this PR. The change is confined to the shared controller logic; I’ve verified the basic flow manually as described below and can add unit tests around RuntimeReconciler in a follow-up if preferred.

---

Ⅳ. Describe how to verify it

1. Deploy Fluid built from this branch.
2. Create a JuiceFSRuntime (or another supported runtime) without a Dataset:

   apiVersion: data.fluid.io/v1alpha1
   kind: JuiceFSRuntime
   metadata:
     name: demo-juicefs
     namespace: default
     annotations:
       fluid.io/dataset-policy: "auto-create"
   spec:
     # minimal valid spec

3. Check that Dataset demo-juicefs is created in default and has metadata.annotations["fluid.io/dataset-policy"] = "auto-create".
4. Confirm the runtime reconciles as usual (ownerReferences/finalizers set, engine created) and DataLoad/DataMigrate still work on the auto-created Dataset.

---

Ⅴ. Special notes for reviews

• The behavior is opt-in and only affects runtimes annotated with fluid.io/dataset-policy: "auto-create"; existing users see no change by default.

[fluid-e2e-bot]

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[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the Fluid runtime controller by enabling the automatic creation of Datasets. It simplifies the deployment process for users by removing the prerequisite of manually creating a Dataset before a Runtime. The change streamlines the workflow for new Runtimes, making them more self-sufficient in their initial setup.

Highlights

• Dataset Auto-Creation Policy: Introduced a new runtime annotation, fluid.io/dataset-policy: "auto-create", allowing a Runtime to be created without a pre-existing Dataset.
• Automated Dataset Provisioning: When the auto-create annotation is present and a matching Dataset is not found, the RuntimeReconciler automatically creates a minimal Dataset with the same name and namespace, ensuring the Runtime can proceed with its binding flow.
• Opt-in Behavior: This new functionality is opt-in, meaning existing Runtimes without the specific annotation will behave as before, ensuring no breaking changes for current users.

Changelog

• pkg/common/constants.go
  • Defined a new constant DatasetPolicyAutoCreate to represent the 'auto-create' policy value.
• pkg/common/label.go
  • Added a new constant AnnotationDatasetPolicy for the fluid.io/dataset-policy annotation key.
• pkg/controllers/runtime_controller.go
  • Imported the apierrors package for Kubernetes API error handling.
  • Modified the ReconcileInternal method to check for the fluid.io/dataset-policy annotation on the Runtime.
  • Implemented logic within ReconcileInternal to call a new ensureDatasetForRuntime function if the auto-create policy is set and the corresponding Dataset is not found.
  • Updated logging messages to provide more context when a Dataset is not found, especially when the auto-create policy is active.
  • Added a new private method ensureDatasetForRuntime responsible for creating a minimal Dataset object, copying relevant annotations, and setting its TypeMeta and ObjectMeta.

Activity

• No new automated tests were added in this PR, as the change is confined to shared controller logic.
• The author manually verified the basic flow as described in the PR body.
• The author indicated that unit tests around RuntimeReconciler could be added in a follow-up PR if preferred.

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[fluid-e2e-bot]

Hi @jakharmonika364. Thanks for your PR.

I'm waiting for a fluid-cloudnative member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.

Once the patch is verified, the new status will be reflected by the ok-to-test label.

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Details

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[gemini-code-assist]

Code Review

This pull request introduces a useful feature for auto-creating datasets when a runtime is deployed with a specific annotation. The overall implementation is sound, but I've identified a critical issue that could lead to resource leaks. The auto-created dataset lacks an owner reference to the runtime, which means it won't be garbage collected when the runtime is deleted. I've provided a high-severity comment with a code suggestion to fix this. I also found a minor opportunity to refactor a piece of code for better readability and have included a medium-severity suggestion for that. Given the nature of these changes, I strongly recommend adding unit tests, as you've also noted, to ensure the correctness of the auto-creation logic and prevent future regressions, especially around resource lifecycle management.

[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud