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+<!--
+**Note:** When your KEP is complete, all of these comment blocks should be removed.
+
+To get started with this template:
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+  Make sure that the problem space is something the SIG is interested in taking
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+
+**Note:** Any PRs to move a KEP to `implementable`, or significant changes once
+it is marked `implementable`, must be approved by each of the KEP approvers.
+If none of those approvers are still appropriate, then changes to that list
+should be approved by the remaining approvers and/or the owning SIG (or
+SIG Architecture for cross-cutting KEPs).
+-->
+# [KEP-5007](https://github.com/kubernetes/enhancements/issues/5007): DRA Device Attach Before Pod Scheduled
+
+<!--
+This is the title of your KEP. Keep it short, simple, and descriptive. A good
+title can help communicate what the KEP is and should be considered as part of
+any review.
+-->
+
+<!--
+A table of contents is helpful for quickly jumping to sections of a KEP and for
+highlighting any additional information provided beyond the standard KEP
+template.
+
+Ensure the TOC is wrapped with
+  <code>&lt;!-- toc --&rt;&lt;!-- /toc --&rt;</code>
+tags, and then generate with `hack/update-toc.sh`.
+-->
+
+<!-- toc -->
+- [Release Signoff Checklist](#release-signoff-checklist)
+- [Summary](#summary)
+- [Motivation](#motivation)
+  - [Goals](#goals)
+  - [Non-Goals](#non-goals)
+- [Proposal](#proposal)
+  - [User Stories (Optional)](#user-stories-optional)
+    - [Story 1](#story-1)
+    - [Story 2](#story-2)
+  - [Notes/Constraints/Caveats (Optional)](#notesconstraintscaveats-optional)
+  - [Risks and Mitigations](#risks-and-mitigations)
+- [Design Details](#design-details)
+  - [DRA scheduler plugin Design overview](#dra-scheduler-plugin-design-overview)
+  - [Composable Controlelr Design Overview](#composable-controlelr-design-overview)
+    - [Proposal 1: The composable controller publishes ResourceSlices with NodeName set within the pool](#proposal-1-the-composable-controller-publishes-resourceslices-with-nodename-set-within-the-pool)
+    - [Proposal 2: Attached devices are published by the vendor's plugin](#proposal-2-attached-devices-are-published-by-the-vendors-plugin)
+  - [Test Plan](#test-plan)
+      - [Prerequisite testing updates](#prerequisite-testing-updates)
+      - [Unit tests](#unit-tests)
+      - [Integration tests](#integration-tests)
+      - [e2e tests](#e2e-tests)
+  - [Graduation Criteria](#graduation-criteria)
+  - [Upgrade / Downgrade Strategy](#upgrade--downgrade-strategy)
+  - [Version Skew Strategy](#version-skew-strategy)
+- [Production Readiness Review Questionnaire](#production-readiness-review-questionnaire)
+  - [Feature Enablement and Rollback](#feature-enablement-and-rollback)
+  - [Rollout, Upgrade and Rollback Planning](#rollout-upgrade-and-rollback-planning)
+  - [Monitoring Requirements](#monitoring-requirements)
+  - [Dependencies](#dependencies)
+  - [Scalability](#scalability)
+  - [Troubleshooting](#troubleshooting)
+- [Implementation History](#implementation-history)
+- [Drawbacks](#drawbacks)
+- [Alternatives](#alternatives)
+- [Infrastructure Needed (Optional)](#infrastructure-needed-optional)
+<!-- /toc -->
+
+## Release Signoff Checklist
+
+<!--
+**ACTION REQUIRED:** In order to merge code into a release, there must be an
+issue in [kubernetes/enhancements] referencing this KEP and targeting a release
+milestone **before the [Enhancement Freeze](https://git.k8s.io/sig-release/releases)
+of the targeted release**.
+
+For enhancements that make changes to code or processes/procedures in core
+Kubernetes—i.e., [kubernetes/kubernetes], we require the following Release
+Signoff checklist to be completed.
+
+Check these off as they are completed for the Release Team to track. These
+checklist items _must_ be updated for the enhancement to be released.
+-->
+
+Items marked with (R) are required *prior to targeting to a milestone / release*.
+
+- [ ] (R) Enhancement issue in release milestone, which links to KEP dir in [kubernetes/enhancements] (not the initial KEP PR)
+- [ ] (R) KEP approvers have approved the KEP status as `implementable`
+- [ ] (R) Design details are appropriately documented
+- [ ] (R) Test plan is in place, giving consideration to SIG Architecture and SIG Testing input (including test refactors)
+  - [ ] e2e Tests for all Beta API Operations (endpoints)
+  - [ ] (R) Ensure GA e2e tests meet requirements for [Conformance Tests](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-architecture/conformance-tests.md) 
+  - [ ] (R) Minimum Two Week Window for GA e2e tests to prove flake free
+- [ ] (R) Graduation criteria is in place
+  - [ ] (R) [all GA Endpoints](https://github.com/kubernetes/community/pull/1806) must be hit by [Conformance Tests](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-architecture/conformance-tests.md) 
+- [ ] (R) Production readiness review completed
+- [ ] (R) Production readiness review approved
+- [ ] "Implementation History" section is up-to-date for milestone
+- [ ] User-facing documentation has been created in [kubernetes/website], for publication to [kubernetes.io]
+- [ ] Supporting documentation—e.g., additional design documents, links to mailing list discussions/SIG meetings, relevant PRs/issues, release notes
+
+<!--
+**Note:** This checklist is iterative and should be reviewed and updated every time this enhancement is being considered for a milestone.
+-->
+
+[kubernetes.io]: https://kubernetes.io/
+[kubernetes/enhancements]: https://git.k8s.io/enhancements
+[kubernetes/kubernetes]: https://git.k8s.io/kubernetes
+[kubernetes/website]: https://git.k8s.io/website
+
+## Summary
+
+<!--
+This section is incredibly important for producing high-quality, user-focused
+documentation such as release notes or a development roadmap. It should be
+possible to collect this information before implementation begins, in order to
+avoid requiring implementors to split their attention between writing release
+notes and implementing the feature itself. KEP editors and SIG Docs
+should help to ensure that the tone and content of the `Summary` section is
+useful for a wide audience.
+
+A good summary is probably at least a paragraph in length.
+
+Both in this section and below, follow the guidelines of the [documentation
+style guide]. In particular, wrap lines to a reasonable length, to make it
+easier for reviewers to cite specific portions, and to minimize diff churn on
+updates.
+
+[documentation style guide]: https://github.com/kubernetes/community/blob/master/contributors/guide/style-guide.md
+-->
+
+To achieve efficient management of fabric devices, we propose adding the following features to the Kubernetes scheduler's DRA plugin. Fabric devices are those that are not directly connected to the server and require attachment to the server for use.
+
+In the DRA current implementation, fabric devices are attached after the scheduling decision, which leads to the following issues:
+
+Fabric devices may be contested by other clusters. In scenarios where attachment occurs after scheduling, there is a risk that the resource cannot be attached at the time of attachment, causing the container to remain in the "Container Creating" state.
+
+To address this issue, we propose a feature that allows the DRA scheduler plugin to wait for the device to be attached.
+
+## Motivation
+
+<!--
+This section is for explicitly listing the motivation, goals, and non-goals of
+this KEP.  Describe why the change is important and the benefits to users. The
+motivation section can optionally provide links to [experience reports] to
+demonstrate the interest in a KEP within the wider Kubernetes community.
+
+[experience reports]: https://github.com/golang/go/wiki/ExperienceReports
+-->
+
+As AI and ML become popular in container (K8s) environment, enormous computational resources are required more and more. On the other hand, efforts toward energy efficiency are also required for the realization of a sustainable society. It is expected to achieve the conflicting requirements that providing higher performance and reducing power consumption simultaneously. Recently, a new server architecture called Composable Disaggregated Infrastructure is emerged.
+
+In a traditional server, hardware resources such as CPUs, memory, and GPUs reside within the server. Composable Disaggregated Infrastructure decomposes these hardware resources and makes them available as resource pools. We can combine these resource by software definition so that we can create custom-made servers.
+
+Composable system is composed of resource pool and Composable Manager software. In Resource pool all components are connected to PCIe or CXL switches. Composable Manager controls the switches so as to create composed baremetals by software definition. It has Composable API and Operator or Kubernetes may call the API. Once composed baremetals are created user can install any operating system or container infrastructure.
+
+This flexibility extends further with the use of fabric devices. Fabric devices can be used by multiple Kubernetes clusters, not just a single one. Each cluster expose the device as a ResourceSlice, allowing for efficient utilization of the device.
+
+In this scenario, the ResourceSlice representing a same fabric device might be selected in multiple Kubernetes clusters simultaneously. If the attachment fails in one cluster, the pod will remain in a failed state in kubelet.
+
+By having the scheduler wait for the fabric device to be attached, we can reschedule the pod if the attachment fails. This approach is superior because it avoids unnecessary waiting and allows for immediate rescheduling.
+
+### Goals
+
+<!--
+List the specific goals of the KEP. What is it trying to achieve? How will we
+know that this has succeeded?
+-->
+
+1. **Enhance the DRA Scheduling Process**: 
+Implement a feature that allows the scheduling process to wait for the completion of fabric device attachment. This ensures that pods are only scheduled once the necessary fabric devices are successfully attached, improving reliability and efficiency.
+
+2. **Attribute Information for Fabric Devices**: 
+Add attribute information that clearly distinguishes fabric devices requiring attachment. This will help in accurately identifying and managing these devices within the Kubernetes environment.
+
+3. **Prioritize Device Allocation**:
+Implement a prioritization mechanism for device allocation, favoring devices directly connected to the node over attached fabric devices. This hierarchy ensures optimal performance and resource utilization. For example, the order of preference would be: Node-local devices > Attached fabric devices > Pre-attached fabric devices.
+
+### Non-Goals
+
+<!--
+What is out of scope for this KEP? Listing non-goals helps to focus discussion
+and make progress.
+-->
+
+## Proposal
+
+<!--
+This is where we get down to the specifics of what the proposal actually is.
+This should have enough detail that reviewers can understand exactly what
+you're proposing, but should not include things like API designs or
+implementation. What is the desired outcome and how do we measure success?
+The "Design Details" section below is for the real
+nitty-gritty.
+-->
+
+The basic idea is the following:
+
+1. **Add a Ready Flag to ResourceClaim**:
+   - Add a flag to `ResourceClaim` that indicates the readiness state of the device. The `PreBind` phase will be held until this flag is set to "Ready".
+
+2. **Wait for Device Attachment Completion in the PreBind() Process**:
+   The overall flow of the PreBind() process is as follows:
+
+   - **Update ResourceClaim**:
+     - The scheduler updates the `ResourceClaim` to notify the vendor's driver that the device needs to be prepared. This process is the same as the existing `PreBind`.
+     - After updating the `ResourceClaim`, if the flag is set to "Preparing", the completion of the `PreBind` phase will be held until the flag is set to "Ready".
+
+   - **Monitoring and Preparation by Composable DRA Controllers**:
+     - Composable DRA Controllers monitor the `ResourceClaim`. If a `ResourceSlice` that requires preparation is associated with the `ResourceClaim`, they perform the necessary preparations. Once the preparation is complete, they set the flag to "Ready".
+
+   - **Completion of the PreBind Phase**:
+     - Once the flag is set to "Ready", the `PreBind` phase is completed, and the scheduler proceeds to the next step.
+
+### User Stories (Optional)
+
+<!--
+Detail the things that people will be able to do if this KEP is implemented.
+Include as much detail as possible so that people can understand the "how" of
+the system. The goal here is to make this feel real for users without getting
+bogged down.
+-->
+
+#### Story 1
+
+#### Story 2
+
+### Notes/Constraints/Caveats (Optional)
+
+<!--
+What are the caveats to the proposal?
+What are some important details that didn't come across above?
+Go in to as much detail as necessary here.
+This might be a good place to talk about core concepts and how they relate.
+-->
+
+### Risks and Mitigations
+
+<!--
+What are the risks of this proposal, and how do we mitigate? Think broadly.
+For example, consider both security and how this will impact the larger
+Kubernetes ecosystem.
+
+How will security be reviewed, and by whom?
+
+How will UX be reviewed, and by whom?
+
+Consider including folks who also work outside the SIG or subproject.
+-->
+
+## Design Details
+
+<!--
+This section should contain enough information that the specifics of your
+change are understandable. This may include API specs (though not always
+required) or even code snippets. If there's any ambiguity about HOW your
+proposal will be implemented, this is the place to discuss them.
+-->
+
+
+### DRA scheduler plugin Design overview
+
+Add a flag to the `Device` within `ResourceSlice` to indicate whether it represents a fabric device. This flag will be used by the controller that exposes the `ResourceSlice` to notify whether the device is a fabric device. To avoid impacting existing DRA functionality, the default value of this flag is set to `false`.
+
+```go
+// Device represents one individual hardware instance that can be selected based
+// on its attributes. Besides the name, exactly one field must be set.
+type Device struct {
+	// Name is unique identifier among all devices managed by
+	// the driver in the pool. It must be a DNS label.
+	//
+	// +required
+	Name string
+
+	// Basic defines one device instance.
+	//
+	// +optional
+	// +oneOf=deviceType
+	Basic *BasicDevice
+    
+    // FabricDevice represents whether this device is a fabric device or not.
+    // If true, it indicates that the device is connected via a fabric network.
+    // This flag helps in distinguishing fabric devices from other types of devices.
+    //
+    // +optional
+    FabricDevice string
+}
+```
+
+**Additions to the DRA Scheduler Plugin**
+
+In the current implementation, the `PreBind` phase waits until the `ResourceClaim` update is completed. This proposal adds functionality to block the completion of the `PreBind` phase until the device is attached if a fabric device is included in the `ResourceClaim`. 
+
+To communicate the completion of fabric device attachment to the scheduler, a flag will be added to the `Status` of the `ResourceClaim`.
+
+```go
+// AllocatedDeviceStatus contains the status of an allocated device, if the
+// driver chooses to report it. This may include driver-specific information.
+type AllocatedDeviceStatus struct {
+...
+	// DeviceAttached represents whether the device has been successfully attached.
+	//
+	// +optional
+	DeviceAttached string
+}
+```
+
+This addition ensures that the scheduler only proceeds once the necessary fabric devices are properly attached, enhancing the reliability and efficiency of the scheduling process. 
+
+
+To facilitate the discussion on the KEP, we would like to share the design of the composable controller we are considering as a component utilizing the fabric-oriented scheduler function. By sharing this, we believe we can deepen the discussion on the optimal implementation of the scheduler function. Additionally, we would like to verify whether the controller design matches the DRA design.
+
+### Composable Controlelr Design Overview
+Our controller's philosophy is to efficiently utilize fabric devices. Therefore, we prefer to allocate devices directly connected to the node over attached fabric devices. (e.g., Node-local devices > Attached fabric devices > Pre-attached fabric devices)
+
+This design aims to efficiently utilize fabric devices, prioritizing node-local devices to improve performance. The composable controller manages fabric devices that can be attached and detached. Therefore, it publishes a list of fabric devices as ResourceSlices.
+
+The structure we are considering is as follows:
+
+```yaml
+# composable controller publish this pool
+kind: ResourceSlice
+pool: composable-device
+driver: gpu.nvidia.com
+nodeSelector: fabric1
+devices:
+  - name: device1
+  ...
+  - name: device2
+  ...
+```
+
+The vendor's DRA kubelet plugin will also publish the devices managed by the vendor as ResourceSlices.
+
+```yaml
+# vendor DRA kubelet plugin publish this pool
+kind: ResourceSlice
+pool: Node1
+driver: gpu.nvidia.com
+nodeName: Node1
+devices:
+  - name: device3
+  ...
+```
+
+Here, when the scheduler selects the fabric device `device1`, it waits for the attachment of the fabric device during PreBind. The composable controller performs the attachment operation by checking the flag of the ResourceClaim. After successful attachment, the composable controller changes the flag of the ResourceClaim.
+
+We are considering the following two methods for handling ResourceSlices upon completion of the attachment. We would like to hear your opinions and feasibility on these two composable controller proposals.
+
+#### Proposal 1: The composable controller publishes ResourceSlices with NodeName set within the pool
+
+Multiple ResourceSlices are published with the same pool name. One indicates the devices included in the fabric, and the other indicates the devices attached to the node.
+
+```yaml
+# composable controller publish this pool
+kind: ResourceSlice
+pool: composable-device
+driver: gpu.nvidia.com
+nodeSelector: fabric1
+devices:
+  - name: device2
+  ...
+---
+kind: ResourceSlice
+pool: composable-device
+driver: gpu.nvidia.com
+nodeName: Node1
+devices:
+  - name: device1
+  ...
+```
+
+If the vendor's plugin responds to hotplug, `device1` will appear in the ResourceSlice published by the vendor.
+
+```yaml
+# vendor DRA kubelet plugin publish this pool
+kind: ResourceSlice
+pool: Node1
+driver: gpu.nvidia.com
+nodeName: Node1
+devices:
+  - name: device3
+  ...
+  - name: device1
+  ...
+```
+
+This may cause device duplication issues between ResourceSlices. To prevent multiple ResourceSlices from publishing duplicate devices, we plan to define a deny list and standardize it with DRA.
+
+**Advantages**
+- No need to change the allocationResult by the scheduler or composable controller.
+- Can distinguish attached fabric devices and maintain prioritization.
+
+**Disadvantages**
+- ResourceSlices created by the composable controller may not be understood by the vendor kubelet plugin. (NVIDIA drivers use internal information, so cooperation is needed)
+- Attached and unattached fabric devices are mixed in one pool. (https://github.com/kubernetes/kubernetes/issues/124042#issuecomment-2527279157)
+- A mechanism to prevent device duplication is needed (e.g., deny list).
+
+#### Proposal 2: Attached devices are published by the vendor's plugin
+
+In this case, devices are removed from the composable-device pool.
+
+```yaml
+# composable controller publish this pool
+kind: ResourceSlice
+pool: composable-device
+driver: gpu.nvidia.com
+nodeSelector: fabric1
+devices:
+  - name: device2
+  ...
+```
+
+If the vendor's plugin responds to hotplug, `device1` will appear in the ResourceSlice published by the vendor.
+
+```yaml
+# vendor DRA kubelet plugin publish this pool
+kind: ResourceSlice
+pool: Node1
+driver: gpu.nvidia.com
+nodeName: Node1
+devices:
+  - name: device3
+  ...
+  - name: device1
+  ...
+```
+
+This breaks the linkage between ResourceClaim and ResourceSlice. Therefore, it is necessary to modify the AllocationResult of the ResourceClaim.
+
+**Advantages**
+- Simplifies device management.
+- Centralizes management as the vendor's plugin directly publishes devices.
+- No need for mechanisms to prevent device duplication (e.g., deny list).
+
+**Disadvantages**
+- Cannot distinguish attached fabric devices, making prioritization difficult.
+- Requires modification of the linkage between ResourceClaim and ResourceSlice (expected to be done by the scheduler or DRA controller. Which is more appropriate?).
+- Until the linkage is fixed, the device being used may be published as a ResourceSlice and reserved by other Pods.
+
+
+
+
+
+### Test Plan
+
+<!--
+**Note:** *Not required until targeted at a release.*
+The goal is to ensure that we don't accept enhancements with inadequate testing.
+
+All code is expected to have adequate tests (eventually with coverage
+expectations). Please adhere to the [Kubernetes testing guidelines][testing-guidelines]
+when drafting this test plan.
+
+[testing-guidelines]: https://git.k8s.io/community/contributors/devel/sig-testing/testing.md
+-->
+
+[ ] I/we understand the owners of the involved components may require updates to
+existing tests to make this code solid enough prior to committing the changes necessary
+to implement this enhancement.
+
+##### Prerequisite testing updates
+
+<!--
+Based on reviewers feedback describe what additional tests need to be added prior
+implementing this enhancement to ensure the enhancements have also solid foundations.
+-->
+
+##### Unit tests
+
+<!--
+In principle every added code should have complete unit test coverage, so providing
+the exact set of tests will not bring additional value.
+However, if complete unit test coverage is not possible, explain the reason of it
+together with explanation why this is acceptable.
+-->
+
+<!--
+Additionally, for Alpha try to enumerate the core package you will be touching
+to implement this enhancement and provide the current unit coverage for those
+in the form of:
+- <package>: <date> - <current test coverage>
+The data can be easily read from:
+https://testgrid.k8s.io/sig-testing-canaries#ci-kubernetes-coverage-unit
+
+This can inform certain test coverage improvements that we want to do before
+extending the production code to implement this enhancement.
+-->
+
+- `<package>`: `<date>` - `<test coverage>`
+
+##### Integration tests
+
+<!--
+Integration tests are contained in k8s.io/kubernetes/test/integration.
+Integration tests allow control of the configuration parameters used to start the binaries under test.
+This is different from e2e tests which do not allow configuration of parameters.
+Doing this allows testing non-default options and multiple different and potentially conflicting command line options.
+-->
+
+<!--
+This question should be filled when targeting a release.
+For Alpha, describe what tests will be added to ensure proper quality of the enhancement.
+
+For Beta and GA, add links to added tests together with links to k8s-triage for those tests:
+https://storage.googleapis.com/k8s-triage/index.html
+-->
+
+- <test>: <link to test coverage>
+
+##### e2e tests
+
+<!--
+This question should be filled when targeting a release.
+For Alpha, describe what tests will be added to ensure proper quality of the enhancement.
+
+For Beta and GA, add links to added tests together with links to k8s-triage for those tests:
+https://storage.googleapis.com/k8s-triage/index.html
+
+We expect no non-infra related flakes in the last month as a GA graduation criteria.
+-->
+
+- <test>: <link to test coverage>
+
+### Graduation Criteria
+
+<!--
+**Note:** *Not required until targeted at a release.*
+
+Define graduation milestones.
+
+These may be defined in terms of API maturity, [feature gate] graduations, or as
+something else. The KEP should keep this high-level with a focus on what
+signals will be looked at to determine graduation.
+
+Consider the following in developing the graduation criteria for this enhancement:
+- [Maturity levels (`alpha`, `beta`, `stable`)][maturity-levels]
+- [Feature gate][feature gate] lifecycle
+- [Deprecation policy][deprecation-policy]
+
+Clearly define what graduation means by either linking to the [API doc
+definition](https://kubernetes.io/docs/concepts/overview/kubernetes-api/#api-versioning)
+or by redefining what graduation means.
+
+In general we try to use the same stages (alpha, beta, GA), regardless of how the
+functionality is accessed.
+
+[feature gate]: https://git.k8s.io/community/contributors/devel/sig-architecture/feature-gates.md
+[maturity-levels]: https://git.k8s.io/community/contributors/devel/sig-architecture/api_changes.md#alpha-beta-and-stable-versions
+[deprecation-policy]: https://kubernetes.io/docs/reference/using-api/deprecation-policy/
+
+Below are some examples to consider, in addition to the aforementioned [maturity levels][maturity-levels].
+
+#### Alpha
+
+- Feature implemented behind a feature flag
+- Initial e2e tests completed and enabled
+
+#### Beta
+
+- Gather feedback from developers and surveys
+- Complete features A, B, C
+- Additional tests are in Testgrid and linked in KEP
+
+#### GA
+
+- N examples of real-world usage
+- N installs
+- More rigorous forms of testing—e.g., downgrade tests and scalability tests
+- Allowing time for feedback
+
+**Note:** Generally we also wait at least two releases between beta and
+GA/stable, because there's no opportunity for user feedback, or even bug reports,
+in back-to-back releases.
+
+**For non-optional features moving to GA, the graduation criteria must include
+[conformance tests].**
+
+[conformance tests]: https://git.k8s.io/community/contributors/devel/sig-architecture/conformance-tests.md
+
+#### Deprecation
+
+- Announce deprecation and support policy of the existing flag
+- Two versions passed since introducing the functionality that deprecates the flag (to address version skew)
+- Address feedback on usage/changed behavior, provided on GitHub issues
+- Deprecate the flag
+-->
+
+### Upgrade / Downgrade Strategy
+
+<!--
+If applicable, how will the component be upgraded and downgraded? Make sure
+this is in the test plan.
+
+Consider the following in developing an upgrade/downgrade strategy for this
+enhancement:
+- What changes (in invocations, configurations, API use, etc.) is an existing
+  cluster required to make on upgrade, in order to maintain previous behavior?
+- What changes (in invocations, configurations, API use, etc.) is an existing
+  cluster required to make on upgrade, in order to make use of the enhancement?
+-->
+
+### Version Skew Strategy
+
+<!--
+If applicable, how will the component handle version skew with other
+components? What are the guarantees? Make sure this is in the test plan.
+
+Consider the following in developing a version skew strategy for this
+enhancement:
+- Does this enhancement involve coordinating behavior in the control plane and nodes?
+- How does an n-3 kubelet or kube-proxy without this feature available behave when this feature is used?
+- How does an n-1 kube-controller-manager or kube-scheduler without this feature available behave when this feature is used?
+- Will any other components on the node change? For example, changes to CSI,
+  CRI or CNI may require updating that component before the kubelet.
+-->
+
+## Production Readiness Review Questionnaire
+
+<!--
+
+Production readiness reviews are intended to ensure that features merging into
+Kubernetes are observable, scalable and supportable; can be safely operated in
+production environments, and can be disabled or rolled back in the event they
+cause increased failures in production. See more in the PRR KEP at
+https://git.k8s.io/enhancements/keps/sig-architecture/1194-prod-readiness.
+
+The production readiness review questionnaire must be completed and approved
+for the KEP to move to `implementable` status and be included in the release.
+
+In some cases, the questions below should also have answers in `kep.yaml`. This
+is to enable automation to verify the presence of the review, and to reduce review
+burden and latency.
+
+The KEP must have a approver from the
+[`prod-readiness-approvers`](http://git.k8s.io/enhancements/OWNERS_ALIASES)
+team. Please reach out on the
+[#prod-readiness](https://kubernetes.slack.com/archives/CPNHUMN74) channel if
+you need any help or guidance.
+-->
+
+### Feature Enablement and Rollback
+
+<!--
+This section must be completed when targeting alpha to a release.
+-->
+
+###### How can this feature be enabled / disabled in a live cluster?
+
+<!--
+Pick one of these and delete the rest.
+
+Documentation is available on [feature gate lifecycle] and expectations, as
+well as the [existing list] of feature gates.
+
+[feature gate lifecycle]: https://git.k8s.io/community/contributors/devel/sig-architecture/feature-gates.md
+[existing list]: https://kubernetes.io/docs/reference/command-line-tools-reference/feature-gates/
+-->
+
+- [ ] Feature gate (also fill in values in `kep.yaml`)
+  - Feature gate name:
+  - Components depending on the feature gate:
+- [ ] Other
+  - Describe the mechanism:
+  - Will enabling / disabling the feature require downtime of the control
+    plane?
+  - Will enabling / disabling the feature require downtime or reprovisioning
+    of a node?
+
+###### Does enabling the feature change any default behavior?
+
+<!--
+Any change of default behavior may be surprising to users or break existing
+automations, so be extremely careful here.
+-->
+
+###### Can the feature be disabled once it has been enabled (i.e. can we roll back the enablement)?
+
+<!--
+Describe the consequences on existing workloads (e.g., if this is a runtime
+feature, can it break the existing applications?).
+
+Feature gates are typically disabled by setting the flag to `false` and
+restarting the component. No other changes should be necessary to disable the
+feature.
+
+NOTE: Also set `disable-supported` to `true` or `false` in `kep.yaml`.
+-->
+
+###### What happens if we reenable the feature if it was previously rolled back?
+
+###### Are there any tests for feature enablement/disablement?
+
+<!--
+The e2e framework does not currently support enabling or disabling feature
+gates. However, unit tests in each component dealing with managing data, created
+with and without the feature, are necessary. At the very least, think about
+conversion tests if API types are being modified.
+
+Additionally, for features that are introducing a new API field, unit tests that
+are exercising the `switch` of feature gate itself (what happens if I disable a
+feature gate after having objects written with the new field) are also critical.
+You can take a look at one potential example of such test in:
+https://github.com/kubernetes/kubernetes/pull/97058/files#diff-7826f7adbc1996a05ab52e3f5f02429e94b68ce6bce0dc534d1be636154fded3R246-R282
+-->
+
+### Rollout, Upgrade and Rollback Planning
+
+<!--
+This section must be completed when targeting beta to a release.
+-->
+
+###### How can a rollout or rollback fail? Can it impact already running workloads?
+
+<!--
+Try to be as paranoid as possible - e.g., what if some components will restart
+mid-rollout?
+
+Be sure to consider highly-available clusters, where, for example,
+feature flags will be enabled on some API servers and not others during the
+rollout. Similarly, consider large clusters and how enablement/disablement
+will rollout across nodes.
+-->
+
+###### What specific metrics should inform a rollback?
+
+<!--
+What signals should users be paying attention to when the feature is young
+that might indicate a serious problem?
+-->
+
+###### Were upgrade and rollback tested? Was the upgrade->downgrade->upgrade path tested?
+
+<!--
+Describe manual testing that was done and the outcomes.
+Longer term, we may want to require automated upgrade/rollback tests, but we
+are missing a bunch of machinery and tooling and can't do that now.
+-->
+
+###### Is the rollout accompanied by any deprecations and/or removals of features, APIs, fields of API types, flags, etc.?
+
+<!--
+Even if applying deprecation policies, they may still surprise some users.
+-->
+
+### Monitoring Requirements
+
+<!--
+This section must be completed when targeting beta to a release.
+
+For GA, this section is required: approvers should be able to confirm the
+previous answers based on experience in the field.
+-->
+
+###### How can an operator determine if the feature is in use by workloads?
+
+<!--
+Ideally, this should be a metric. Operations against the Kubernetes API (e.g.,
+checking if there are objects with field X set) may be a last resort. Avoid
+logs or events for this purpose.
+-->
+
+###### How can someone using this feature know that it is working for their instance?
+
+<!--
+For instance, if this is a pod-related feature, it should be possible to determine if the feature is functioning properly
+for each individual pod.
+Pick one more of these and delete the rest.
+Please describe all items visible to end users below with sufficient detail so that they can verify correct enablement
+and operation of this feature.
+Recall that end users cannot usually observe component logs or access metrics.
+-->
+
+- [ ] Events
+  - Event Reason: 
+- [ ] API .status
+  - Condition name: 
+  - Other field: 
+- [ ] Other (treat as last resort)
+  - Details:
+
+###### What are the reasonable SLOs (Service Level Objectives) for the enhancement?
+
+<!--
+This is your opportunity to define what "normal" quality of service looks like
+for a feature.
+
+It's impossible to provide comprehensive guidance, but at the very
+high level (needs more precise definitions) those may be things like:
+  - per-day percentage of API calls finishing with 5XX errors <= 1%
+  - 99% percentile over day of absolute value from (job creation time minus expected
+    job creation time) for cron job <= 10%
+  - 99.9% of /health requests per day finish with 200 code
+
+These goals will help you determine what you need to measure (SLIs) in the next
+question.
+-->
+
+###### What are the SLIs (Service Level Indicators) an operator can use to determine the health of the service?
+
+<!--
+Pick one more of these and delete the rest.
+-->
+
+- [ ] Metrics
+  - Metric name:
+  - [Optional] Aggregation method:
+  - Components exposing the metric:
+- [ ] Other (treat as last resort)
+  - Details:
+
+###### Are there any missing metrics that would be useful to have to improve observability of this feature?
+
+<!--
+Describe the metrics themselves and the reasons why they weren't added (e.g., cost,
+implementation difficulties, etc.).
+-->
+
+### Dependencies
+
+<!--
+This section must be completed when targeting beta to a release.
+-->
+
+###### Does this feature depend on any specific services running in the cluster?
+
+<!--
+Think about both cluster-level services (e.g. metrics-server) as well
+as node-level agents (e.g. specific version of CRI). Focus on external or
+optional services that are needed. For example, if this feature depends on
+a cloud provider API, or upon an external software-defined storage or network
+control plane.
+
+For each of these, fill in the following—thinking about running existing user workloads
+and creating new ones, as well as about cluster-level services (e.g. DNS):
+  - [Dependency name]
+    - Usage description:
+      - Impact of its outage on the feature:
+      - Impact of its degraded performance or high-error rates on the feature:
+-->
+
+### Scalability
+
+<!--
+For alpha, this section is encouraged: reviewers should consider these questions
+and attempt to answer them.
+
+For beta, this section is required: reviewers must answer these questions.
+
+For GA, this section is required: approvers should be able to confirm the
+previous answers based on experience in the field.
+-->
+
+###### Will enabling / using this feature result in any new API calls?
+
+<!--
+Describe them, providing:
+  - API call type (e.g. PATCH pods)
+  - estimated throughput
+  - originating component(s) (e.g. Kubelet, Feature-X-controller)
+Focusing mostly on:
+  - components listing and/or watching resources they didn't before
+  - API calls that may be triggered by changes of some Kubernetes resources
+    (e.g. update of object X triggers new updates of object Y)
+  - periodic API calls to reconcile state (e.g. periodic fetching state,
+    heartbeats, leader election, etc.)
+-->
+
+###### Will enabling / using this feature result in introducing new API types?
+
+<!--
+Describe them, providing:
+  - API type
+  - Supported number of objects per cluster
+  - Supported number of objects per namespace (for namespace-scoped objects)
+-->
+
+###### Will enabling / using this feature result in any new calls to the cloud provider?
+
+<!--
+Describe them, providing:
+  - Which API(s):
+  - Estimated increase:
+-->
+
+###### Will enabling / using this feature result in increasing size or count of the existing API objects?
+
+<!--
+Describe them, providing:
+  - API type(s):
+  - Estimated increase in size: (e.g., new annotation of size 32B)
+  - Estimated amount of new objects: (e.g., new Object X for every existing Pod)
+-->
+
+###### Will enabling / using this feature result in increasing time taken by any operations covered by existing SLIs/SLOs?
+
+<!--
+Look at the [existing SLIs/SLOs].
+
+Think about adding additional work or introducing new steps in between
+(e.g. need to do X to start a container), etc. Please describe the details.
+
+[existing SLIs/SLOs]: https://git.k8s.io/community/sig-scalability/slos/slos.md#kubernetes-slisslos
+-->
+
+###### Will enabling / using this feature result in non-negligible increase of resource usage (CPU, RAM, disk, IO, ...) in any components?
+
+<!--
+Things to keep in mind include: additional in-memory state, additional
+non-trivial computations, excessive access to disks (including increased log
+volume), significant amount of data sent and/or received over network, etc.
+This through this both in small and large cases, again with respect to the
+[supported limits].
+
+[supported limits]: https://git.k8s.io/community//sig-scalability/configs-and-limits/thresholds.md
+-->
+
+###### Can enabling / using this feature result in resource exhaustion of some node resources (PIDs, sockets, inodes, etc.)?
+
+<!--
+Focus not just on happy cases, but primarily on more pathological cases
+(e.g. probes taking a minute instead of milliseconds, failed pods consuming resources, etc.).
+If any of the resources can be exhausted, how this is mitigated with the existing limits
+(e.g. pods per node) or new limits added by this KEP?
+
+Are there any tests that were run/should be run to understand performance characteristics better
+and validate the declared limits?
+-->
+
+### Troubleshooting
+
+<!--
+This section must be completed when targeting beta to a release.
+
+For GA, this section is required: approvers should be able to confirm the
+previous answers based on experience in the field.
+
+The Troubleshooting section currently serves the `Playbook` role. We may consider
+splitting it into a dedicated `Playbook` document (potentially with some monitoring
+details). For now, we leave it here.
+-->
+
+###### How does this feature react if the API server and/or etcd is unavailable?
+
+###### What are other known failure modes?
+
+<!--
+For each of them, fill in the following information by copying the below template:
+  - [Failure mode brief description]
+    - Detection: How can it be detected via metrics? Stated another way:
+      how can an operator troubleshoot without logging into a master or worker node?
+    - Mitigations: What can be done to stop the bleeding, especially for already
+      running user workloads?
+    - Diagnostics: What are the useful log messages and their required logging
+      levels that could help debug the issue?
+      Not required until feature graduated to beta.
+    - Testing: Are there any tests for failure mode? If not, describe why.
+-->
+
+###### What steps should be taken if SLOs are not being met to determine the problem?
+
+## Implementation History
+
+<!--
+Major milestones in the lifecycle of a KEP should be tracked in this section.
+Major milestones might include:
+- the `Summary` and `Motivation` sections being merged, signaling SIG acceptance
+- the `Proposal` section being merged, signaling agreement on a proposed design
+- the date implementation started
+- the first Kubernetes release where an initial version of the KEP was available
+- the version of Kubernetes where the KEP graduated to general availability
+- when the KEP was retired or superseded
+-->
+
+## Drawbacks
+
+<!--
+Why should this KEP _not_ be implemented?
+-->
+
+## Alternatives
+
+<!--
+What other approaches did you consider, and why did you rule them out? These do
+not need to be as detailed as the proposal, but should include enough
+information to express the idea and why it was not acceptable.
+-->
+
+## Infrastructure Needed (Optional)
+
+<!--
+Use this section if you need things from the project/SIG. Examples include a
+new subproject, repos requested, or GitHub details. Listing these here allows a
+SIG to get the process for these resources started right away.
+-->
diff --git a/keps/sig-scheduling/5007-device-attach-before-pod-scheduled/kep.yaml b/keps/sig-scheduling/5007-device-attach-before-pod-scheduled/kep.yaml
new file mode 100644
index 00000000000..de10d155921
--- /dev/null
+++ b/keps/sig-scheduling/5007-device-attach-before-pod-scheduled/kep.yaml
@@ -0,0 +1,46 @@
+title: DRA Device Attach Before Pod Scheduled
+kep-number: 5007
+authors:
+  - "@KobayashiD27"
+owning-sig: sig-scheduling
+#participating-sigs:
+#  - sig-aaa
+#  - sig-bbb
+status: provisional
+#|implementable|implemented|deferred|rejected|withdrawn|replaced
+creation-date: 2024-12-20
+reviewers:
+  - "@pohly"
+approvers:
+  - TBD
+
+see-also:
+  - "/keps/sig-node/4381-dra-structured-parameters"
+  - https://github.com/kubernetes/kubernetes/issues/124042#issuecomment-2548068135
+
+# The target maturity stage in the current dev cycle for this KEP.
+stage: alpha
+#|beta|stable
+
+# The most recent milestone for which work toward delivery of this KEP has been
+# done. This can be the current (upcoming) milestone, if it is being actively
+# worked on.
+latest-milestone: "v1.33"
+
+# The milestone at which this feature was, or is targeted to be, at each stage.
+milestone:
+  alpha: "v1.33"
+  beta: "v1.34"
+  stable: "v1.35"
+
+# The following PRR answers are required at alpha release
+# List the feature gate name and the components for which it must be enabled
+feature-gates:
+  - name: DRADeviceAttachBeforePodScheduled
+    components:
+      - kube-scheduler
+disable-supported: true
+
+# The following PRR answers are required at beta release
+metrics:
+#  - my_feature_metric