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# KEP-5978: DRA: ClusterResourceClaimTemplate

**NOTE:** This KEP was withdrawn in favor of [the Out-of-Tree Synchronization Controller alternative](#out-of-tree-alternative).

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<!-- 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: Exposing and Consuming Specialized Hardware Cluster-Wide](#story-1-exposing-and-consuming-specialized-hardware-cluster-wide)
  - [Notes/Constraints/Caveats (Optional)](#notesconstraintscaveats-optional)
  - [Risks and Mitigations](#risks-and-mitigations)
- [Design Details](#design-details)
  - [API Changes](#api-changes)
  - [ResourceClaim Controller Changes](#resourceclaim-controller-changes)
  - [Admission &amp; Validation](#admission--validation)
  - [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)
    - [Alpha](#alpha)
    - [Beta](#beta)
    - [GA](#ga)
  - [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

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- [ ] (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)
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  - [ ] (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) within one minor version of promotion to GA
- [ ] (R) Production readiness review completed
- [ ] (R) Production readiness review approved
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## Summary

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We propose introducing a new cluster-scoped API resource,
ClusterResourceClaimTemplate, to allow cluster administrators to define
standard Dynamic Resource Allocation (DRA) templates once at the cluster level.
Any workload (via Pod or PodGroup) in any namespace can reference these templates. During Pod or PodGroup
scheduling/admission, the control plane's resource claim controller resolves the
cluster template and automatically generates a namespace-local ResourceClaim
under the Pod's or PodGroup's namespace.

## Motivation

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Currently, ResourceClaimTemplate is namespace-scoped. Administrators managing
clusters with specialized hardware (GPUs, FPGAs, high-performance network
devices) must deploy and synchronize identical ResourceClaimTemplate resources
across all active namespaces. This namespace pollution makes cluster management
complex, especially in dynamic, multi-tenant clusters. Cluster-scoped templates
solve this by allowing a single central template definition.

### Goals

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- **Reduce administrative overhead**: Eliminate the need to replicate and
  synchronize identical DRA templates across multiple namespaces.
- **Simplify workload configuration**: Allow Pods and PodGroups in any namespace
  to easily consume centrally managed hardware templates.
- **Preserve namespace isolation**: Ensure cluster-scoped templates do not
  introduce privilege escalation or cross-namespace risks.

### Non-Goals

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- Changing how namespace-local ResourceClaimTemplate behaves.
- Dynamically shadowing namespaced templates with cluster templates (resolution
  must be explicit).
- Direct cluster-wide sharing of a single namespaced ResourceClaim instance
  (claims remain isolated per namespace).

## Proposal

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We propose introducing a new cluster-scoped API resource,
ClusterResourceClaimTemplate, which serves as a cluster-wide template for
generating ResourceClaims. Along with this, we propose adding a new
`clusterResourceClaimTemplateName` field to `PodResourceClaim` and `PodGroupResourceClaim` alongside the
existing `resourceClaimName` and `resourceClaimTemplateName` fields. 

When `clusterResourceClaimTemplateName` is populated in a Pod or PodGroup specification, the
ResourceClaim controller fetches the referenced ClusterResourceClaimTemplate
and generates a corresponding ResourceClaim in the Pod's or PodGroup's namespace,
maintaining standard resource ownership and garbage collection semantics.

### User Stories (Optional)

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#### Story 1: Exposing and Consuming Specialized Hardware Cluster-Wide
As a cluster administrator of an AI training platform, I want to expose
high-performance GPUs (e.g., NVIDIA H100) to all research groups across the
cluster without managing templates in every individual namespace.

1. The administrator defines a single ClusterResourceClaimTemplate named
   `nvidia-h100-80gb` at the cluster scope.
2. A developer/researcher in a newly provisioned namespace (e.g.,
   `project-alpha`) creates a Pod that references this template. The ephemeral
   resource claim controller automatically generates the namespaced
   ResourceClaim in `project-alpha` with the spec defined in
   `nvidia-h100-80gb`:

```yaml
apiVersion: v1
kind: Pod
metadata:
  name: gpu-pod
  namespace: project-alpha
spec:
  containers:
  - name: training
    image: my-training-image
    resources:
      claims:
        - name: gpu
  resourceClaims:
  - name: gpu
    clusterResourceClaimTemplateName: nvidia-h100-80gb
```

### Notes/Constraints/Caveats (Optional)

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### Risks and Mitigations

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## Design Details

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### API Changes

We will introduce a new cluster-scoped resource ClusterResourceClaimTemplate
in `resource.k8s.io`:

```go
// ClusterResourceClaimTemplate is used to produce ResourceClaim objects.
// Cluster scoped.
type ClusterResourceClaimTemplate struct {
	metav1.TypeMeta   `json:""`
  // Standard object metadata
  // +optional
  metav1.ObjectMeta `json:"metadata,omitempty" protobuf:"bytes,1,opt,name=metadata"`

  // Describes the ResourceClaim that is to be generated.
  //
  // This field is immutable. A ResourceClaim will get created by the
  // control plane for a Pod when needed and then not get updated
  // anymore.
  // +optional
  Spec ClusterResourceClaimTemplateSpec `json:"spec" protobuf:"bytes,2,name=spec"`
}

// ClusterResourceClaimTemplateSpec contains the metadata and fields for a ResourceClaim.
type ClusterResourceClaimTemplateSpec struct {
  // ObjectMeta may contain labels and annotations that will be copied into the ResourceClaim
  // when creating it. No other fields are allowed and will be rejected during validation.
  // +optional
  metav1.ObjectMeta `json:"metadata,omitempty" protobuf:"bytes,1,opt,name=metadata"`

  // Spec for the ResourceClaim. The entire content is copied unchanged
  // into the ResourceClaim that gets created from this template. The
  // same fields as in a ResourceClaim are also valid here.
  // +optional
  Spec ResourceClaimSpec `json:"spec" protobuf:"bytes,2,name=spec"`
}
```

We will add `ClusterResourceClaimTemplateName` to `PodResourceClaim` in `k8s.io/api/core/v1`:

```go
type PodResourceClaim struct {
  Name string `json:"name" protobuf:"bytes,1,name=name"`
  ResourceClaimName *string `json:"resourceClaimName,omitempty" protobuf:"bytes,3,opt,name=resourceClaimName"`
  ResourceClaimTemplateName *string `json:"resourceClaimTemplateName,omitempty" protobuf:"bytes,4,opt,name=resourceClaimTemplateName"`

  // ClusterResourceClaimTemplateName is the name of a ClusterResourceClaimTemplate
  // object in the cluster.
  //
  // The template will be used to create a new ResourceClaim in the same
  // namespace as the Pod, which will be bound to this Pod. Except for the
  // cluster scope, it behaves identically to ResourceClaimTemplateName.
  //
  // This field is immutable and no changes will be made to the
  // corresponding ResourceClaim by the control plane after creating the
  // ResourceClaim.
  //
  // Exactly one of ResourceClaimName, ResourceClaimTemplateName, and
  // ClusterResourceClaimTemplateName must be set.
  ClusterResourceClaimTemplateName *string `json:"clusterResourceClaimTemplateName,omitempty" protobuf:"bytes,5,opt,name=clusterResourceClaimTemplateName"`
}
```

We will also add `ClusterResourceClaimTemplateName` to `PodGroupResourceClaim`
in `k8s.io/api/scheduling/v1alpha3` (or the appropriate API group for
PodGroups):

```go
type PodGroupResourceClaim struct {
  Name string `json:"name"`
  ResourceClaimName *string `json:"resourceClaimName,omitempty"`
  ResourceClaimTemplateName *string `json:"resourceClaimTemplateName,omitempty"`

  // ClusterResourceClaimTemplateName is the name of a ClusterResourceClaimTemplate
  // object in the cluster.
  //
  // The template will be used to create a new ResourceClaim in the same
  // namespace as this PodGroup, which will be bound to this PodGroup. Except for the
  // cluster scope, it behaves identically to ResourceClaimTemplateName.
  //
  // This field is immutable and no changes will be made to the
  // corresponding ResourceClaim by the control plane after creating the
  // ResourceClaim.
  //
  // Exactly one of ResourceClaimName, ResourceClaimTemplateName, and
  // ClusterResourceClaimTemplateName must be set.
  ClusterResourceClaimTemplateName *string `json:"clusterResourceClaimTemplateName,omitempty"`
}
```

### ResourceClaim Controller Changes

`ResourceClaimController` will be updated to:
- Fetch ClusterResourceClaimTemplate resources using a cluster-level template
  informer.
- When a `PodResourceClaim` references a `ClusterResourceClaimTemplateName`,
  create a namespaced ResourceClaim in the Pod's namespace using the ClusterResourceClaimTemplate's
  `Spec.Spec`, and attach standard OwnerReferences mapping it to the
  Pod.
- When a `PodGroupResourceClaim` references a `ClusterResourceClaimTemplateName`,
  create a namespaced ResourceClaim in the PodGroup's namespace using the ClusterResourceClaimTemplate's
  `Spec.Spec`, and attach standard OwnerReferences mapping it to the
  PodGroup.

### Admission & Validation

A Pod or PodGroup reference to a cluster-scoped template does not require explicit reference
authorization checks (such as SubjectAccessReview) during Pod or PodGroup admission. This
is consistent with other cluster-scoped templates and class resources like
StorageClass or RuntimeClass.

Because a ClusterResourceClaimTemplate is a template containing a declarative
`ResourceClaimSpec` and does not grant any special capabilities on its own, a
user could always copy the template's content and create an equivalent
namespaced ResourceClaimTemplate or inline ResourceClaim. Enforcing access
control on the actual underlying hardware or scheduling resources must be done
at the resource driver level or via namespace resource quotas/limits.

During admission, the API server will perform standard structural validation on
the `clusterResourceClaimTemplateName` field in both `PodResourceClaim` and `PodGroupResourceClaim` (e.g. checking that only one of the
template/claim name fields is populated).

### Test Plan

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[x] 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
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None.

##### Unit tests
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- `k8s.io/kubernetes/pkg/apis/core/validation`: `85.5%`
- `k8s.io/kubernetes/pkg/apis/scheduling/validation`: `90.6%`
- `k8s.io/kubernetes/pkg/apis/resource/validation`: `96.6%`
- `k8s.io/kubernetes/pkg/controller/resourceclaim`: `75.0%`
- `k8s.io/dynamic-resource-allocation/resourceclaim`: `90.6%`

##### Integration tests
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Integration tests will verify:
- Successful generation of namespaced ResourceClaims from
  ClusterResourceClaimTemplate resources when a Pod or PodGroup is created.
- Correct `ownerReferences` on the generated ResourceClaims and matching
  garbage collection when Pods or PodGroups are deleted.
- API validation ensuring that only one of `resourceClaimName`,
  `resourceClaimTemplateName`, and `clusterResourceClaimTemplateName` is set on
  Pod or PodGroup creation.
- Proper behavior in edge cases (e.g. non-existent templates, updates to
  templates, and multi-namespace references).

##### e2e tests
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If e2e tests are not necessary or useful, explain why.
-->

E2E tests will verify:
- Complete scheduling lifecycle of a Pod or PodGroup referencing a
  ClusterResourceClaimTemplate using a test DRA resource driver (successful
  allocation, execution, and deallocation/clean-up).
- Correct resource isolation and independent allocation across multiple
  namespaces referencing the same cluster-scoped template.

### Graduation Criteria

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#### Alpha

- API fields added and gate `ClusterResourceClaimTemplates` introduced.
- Controller logic implemented for resolving cluster templates.
- Tests added and enabled.

#### Beta

- API types graduated to beta.
- Feature gate enabled by default.
- Gather feedback.

#### GA

- API types graduated to GA.
- Feature gate locked to true.

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### Upgrade / Downgrade Strategy

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  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?
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- **Upgrade**: Enabling the `ClusterResourceClaimTemplates` feature gate
  registers the ClusterResourceClaimTemplate API. The feature is opt-in and
  does not affect existing workloads.
- **Downgrade**: Disabling the feature gate will prevent the creation of new
  ClusterResourceClaimTemplate objects, and Pod or PodGroup creation requests referencing
  them will be rejected. Already-generated, namespaced ResourceClaims remain
  unaffected and continue to function as standard claims.

### Version Skew Strategy

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- 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.
-->

- **Kube-apiserver / Kube-controller-manager skew**: If `kube-apiserver` is
  upgraded but `kube-controller-manager` is not, Pods or PodGroups referencing a cluster
  template will be admitted but remain in `Pending` state indefinitely because
  the claim controller won't generate the namespaced ResourceClaims.
- **Kubelet skew**: The kubelet only interacts with standard, namespaced
  ResourceClaim objects. Since the cluster-scoped template resolution is
  performed entirely by the control plane, there is no dependency or version
  skew concerns with older Kubelets.

## Production Readiness Review Questionnaire

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### Feature Enablement and Rollback

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###### How can this feature be enabled / disabled in a live cluster?

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- [x] Feature gate (also fill in values in `kep.yaml`)
  - Feature gate name: `ClusterResourceClaimTemplates`
  - Components depending on the feature gate: `kube-apiserver`, `kube-controller-manager`
- [ ] 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.
-->

No.

###### 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`.
-->

Yes. If disabled, new Pod or PodGroup specifications with `clusterResourceClaimTemplateName`
set will be rejected during API validation. Existing Pods or PodGroups with the field
populated will fail validation on any subsequent updates. Generated
ResourceClaim resources already created will continue to exist and be bound,
but further template resolution will be disabled.

###### What happens if we reenable the feature if it was previously rolled back?

The `kube-apiserver` and `kube-controller-manager` will resume resolving
ClusterResourceClaimTemplate references and generating corresponding local
ResourceClaim resources for any new or updated Pods or PodGroups.

###### 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
-->

We will cover feature enablement/disablement in both unit tests and integration tests.

### 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.
-->

During upgrade, if a new `kube-apiserver` is upgraded and admits a Pod or PodGroup with
`clusterResourceClaimTemplateName` but `kube-controller-manager` has not yet
been upgraded or does not have the feature gate enabled, the Pod or PodGroup will remain
pending indefinitely because the claim controller won't create the namespaced
ResourceClaim. Already running workloads are unaffected.

###### 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?
-->

- An increase in the number of Pods or PodGroups stuck in `Pending` state with unscheduled
  ResourceClaims.
- High error rates in `kube-controller-manager` logs related to ResourceClaim
  creation.

###### 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.
-->

To be completed at Beta stage.

###### 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.
-->

No.

### 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.
-->

An operator can list ClusterResourceClaimTemplate objects or query
`kube-apiserver` request metrics for `clusterresourceclaimtemplates`.

###### 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: 
- [x] API .status
  - Condition name: ResourceClaim transitions to `status.allocation` set.
  - Other field: Pod's `status.resourceClaims` list, and the existence of the generated namespaced ResourceClaim owned by the Pod or PodGroup.
- [ ] 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.
-->

99% of local ResourceClaim creations corresponding to a
ClusterResourceClaimTemplate should succeed within 1 second of the Pod or PodGroup being
admitted.

###### 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.
-->

- [x] Metrics
  - Metric name: `controller_runtime_reconcile_errors_total` (filtered by `resourceclaim` controller)
  - [Optional] Aggregation method: `sum`
  - Components exposing the metric: `kube-controller-manager`
- [ ] 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.).
-->

No. Standard API server request latency/error metrics and controller-runtime
metrics are sufficient.


### 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:
-->

No.

### 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.)
-->

Yes:
- `kube-controller-manager` will list and watch ClusterResourceClaimTemplates
  (cluster-wide informer index).
- Throughput is bounded by Pod or PodGroup creation/admission rates that use these
  templates.

###### 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)
-->

Yes, ClusterResourceClaimTemplate.

###### Will enabling / using this feature result in any new calls to the cloud provider?

<!--
Describe them, providing:
  - Which API(s):
  - Estimated increase:
-->

No.

###### 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)
-->

Yes, Pod or PodGroup specifications referencing a cluster template will have one extra field
(`clusterResourceClaimTemplateName`) set.

###### 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
-->

No additional checks or operations are performed during Pod or PodGroup admission that
would impact existing SLIs/SLOs.

###### 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
-->

No. The new informer in `kube-controller-manager` caches only
ClusterResourceClaimTemplates which are highly static and low in count.

###### 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?
-->

No.

### 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?

Admission/creation of Pods or PodGroups using the templates, as well as the creation, update,
or deletion of the ClusterResourceClaimTemplate resources themselves, is blocked,
similar to other Kubernetes resources.

###### 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.
-->

- **Template Reference Resolution Failure**: A Pod or PodGroup specifies a non-existent
  `clusterResourceClaimTemplateName`.
  - Detection: Pod or PodGroup remains `Pending` (or unscheduled) with a status event indicating that
    template resolution failed.
  - Mitigations: Correct the Pod or PodGroup specification to use a valid template or create
    the referenced ClusterResourceClaimTemplate.
  - Diagnostics: Look at events on the Pod/PodGroup and logs of
    `kube-controller-manager`.

###### What steps should be taken if SLOs are not being met to determine the problem?

Verify that `kube-controller-manager` has connection to `kube-apiserver`. Check
`kube-controller-manager` logs and the rate of reconcile errors for the
`resourceclaim` controller.


## 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
-->

- **2026-06-02**: Initial KEP drafted and proposed targeting v1.37 Alpha.
- **2026-06-16**: KEP withdrawn in favor of an out-of-tree controller solution.

## Drawbacks

<!--
Why should this KEP _not_ be implemented?
-->

Introducing ClusterResourceClaimTemplate adds another API resource to
`resource.k8s.io` and expands the `PodResourceClaim` API structure. However,
this is justified by the significant simplification it brings to cluster-scoped
DRA configuration and resource control.

## 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.
-->

- **Shadowing / Fallback Resolution**: Allow `resourceClaimTemplateName` to
  resolve to a cluster-scoped resource if the namespaced template is not found.
  - *Why Rejected*: Shadowing leads to unpredictable resolution behavior and
    silent failures. An administrator creating a namespaced template would
    silently override/shadow the cluster-scoped template, changing Pod
    provisioning paths without explicit audit trails. Dedicated fields make
    references completely explicit and easily auditable.

<a id="out-of-tree-alternative"></a>
- **Out-of-Tree Synchronization Controller / CRD**: Create an out-of-tree
  controller (for example, in a `kubernetes-sigs` repository) that automatically
  generates namespaced `ResourceClaimTemplate` objects in target namespaces. This
  could be driven either by a `ClusterResourceClaimTemplate` CRD or by publishing
  master `ResourceClaimTemplate` objects in a centralized controller namespace
  using a special naming convention or annotation mapping. Pods would then
  refer to the generated namespaced templates by name.
  - *Trade-offs / Motivation for Withdrawal*: While this approach involves certain
    trade-offs compared to an in-tree API:
    - **Race Conditions**: When a new namespace is created, Pods referencing the
      template might be rejected or fail to deploy if they are created before the
      out-of-tree controller finishes copying the template into the new namespace.
    - **Resource Proliferation and Overhead**: Duplicating identical template
      objects across tens or hundreds of namespaces creates unnecessary `etcd`
      storage overhead and additional API server load.

    Despite these trade-offs, the SIG decided to withdraw this KEP in favor of this
    out-of-tree controller approach. The alternative is considered good enough to
    fulfill the target use cases, and implementing an in-tree solution does not
    justify the required engineering effort and the expansion of the core
    Kubernetes API surface.

## 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.
-->

None.

