Training: Add documentation for the MultiKueue and spec.managedBy API #3956
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| title = "How to manage Jobs in multi-cluster environment" | ||||||
| Desciption = "Using managedBy feild for MultiKueue" | ||||||
| weight = 10 | ||||||
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| ## Overview | ||||||
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| The `spec.runPolicy.managedBy` field is a new feature introduced for MultiQueue support in the Kubeflow Training Operator. This field allows for more robust management of multi-cluster job dispatching by specifying the managing entity. | ||||||
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| ## Prerequisites | ||||||
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| 1. Ensure that you have the latest version of the Kubeflow Training Operator installed. | ||||||
| 2. Make sure Kueue is compiled against the new operator to leverage the `spec.runPolicy.managedBy` field. | ||||||
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There was a problem hiding this comment. Should we say the version of Kubeflow Training Operator and Kueue that needs to be installed ? There was a problem hiding this comment. Yess that would make sense |
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| ## Usage | ||||||
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| To use the `spec.runPolicy.managedBy` field in your training jobs, include it in the job specification as shown below: | ||||||
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| ```yaml | ||||||
| apiVersion: "kubeflow.org/v1" | ||||||
| kind: "TFJob" | ||||||
| metadata: | ||||||
| name: "example-tfjob" | ||||||
| spec: | ||||||
| runPolicy: | ||||||
| managedBy: "kueue.x-k8s.io/multikueue" | ||||||
| tfReplicaSpecs: | ||||||
| ... | ||||||
| ``` | ||||||
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| Example | ||||||
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| Here is a complete example of a TensorFlow job using the spec.managedBy field: | ||||||
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| ```YAML | ||||||
| apiVersion: "kubeflow.org/v1" | ||||||
| kind: "TFJob" | ||||||
| metadata: | ||||||
| name: "example-tfjob" | ||||||
| spec: | ||||||
| runPolicy: | ||||||
| managedBy: "kueue.x-k8s.io/multikueue" | ||||||
| tfReplicaSpecs: | ||||||
| Chief: | ||||||
| replicas: 1 | ||||||
| template: | ||||||
| spec: | ||||||
| containers: | ||||||
| - name: tensorflow | ||||||
| image: tensorflow/tensorflow:latest | ||||||
| args: ["python", "model.py"] | ||||||
| Worker: | ||||||
| replicas: 2 | ||||||
| template: | ||||||
| spec: | ||||||
| containers: | ||||||
| - name: tensorflow | ||||||
| image: tensorflow/tensorflow:latest | ||||||
| args: ["python", "model.py"] | ||||||
| ``` | ||||||
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| ## More Details | ||||||
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| For more details on setting up and using MultiQueue with the Kubeflow Training Operator, refer to the following documentation pages: | ||||||
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| - [Kueue/Kubeflow](https://kueue.sigs.k8s.io/docs/tasks/run/multikueue/kubeflow/) | ||||||
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Can we explain in overview that we leverage MultiKueue capability in Kueue project for this feature?
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I think we have provided the Cross-references/More details for that purpose, so that the user interested can have a brief there
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Yeah, but the goal of overview section is to provide brief description on what is that feature.
It might be important to say that we leverage Kueue for that capability.
WDYT @Garvit-77 @mimowo @mszadkow ?
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It allows this feature of MultiKueue to be applied for Kubeflow, yes, I think it make sense to mention that
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I think that we can just point https://kueue.sigs.k8s.io/docs/concepts/multikueue/ document here to describe what is MultiKueue.