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+<!--
+**Note:** When your KEP is complete, all of these comment blocks should be removed.
+
+To get started with this template:
+
+- [x] **Pick a hosting SIG.**
+  Make sure that the problem space is something the SIG is interested in taking
+  up. KEPs should not be checked in without a sponsoring SIG.
+- [x] **Create an issue in kubernetes/enhancements**
+  When filing an enhancement tracking issue, please make sure to complete all
+  fields in that template. One of the fields asks for a link to the KEP. You
+  can leave that blank until this KEP is filed, and then go back to the
+  enhancement and add the link.
+- [x] **Make a copy of this template directory.**
+  Copy this template into the owning SIG's directory and name it
+  `NNNN-short-descriptive-title`, where `NNNN` is the issue number (with no
+  leading-zero padding) assigned to your enhancement above.
+- [x] **Fill out as much of the kep.yaml file as you can.**
+  At minimum, you should fill in the "Title", "Authors", "Owning-sig",
+  "Status", and date-related fields.
+- [ ] **Fill out this file as best you can.**
+  At minimum, you should fill in the "Summary" and "Motivation" sections.
+  These should be easy if you've preflighted the idea of the KEP with the
+  appropriate SIG(s).
+- [ ] **Create a PR for this KEP.**
+  Assign it to people in the SIG who are sponsoring this process.
+- [ ] **Merge early and iterate.**
+  Avoid getting hung up on specific details and instead aim to get the goals of
+  the KEP clarified and merged quickly. The best way to do this is to just
+  start with the high-level sections and fill out details incrementally in
+  subsequent PRs.
+
+Just because a KEP is merged does not mean it is complete or approved. Any KEP
+marked as `provisional` is a working document and subject to change. You can
+denote sections that are under active debate as follows:
+
+```
+<<[UNRESOLVED optional short context or usernames ]>>
+Stuff that is being argued.
+<<[/UNRESOLVED]>>
+```
+
+When editing KEPS, aim for tightly-scoped, single-topic PRs to keep discussions
+focused. If you disagree with what is already in a document, open a new PR
+with suggested changes.
+
+One KEP corresponds to one "feature" or "enhancement" for its whole lifecycle.
+You do not need a new KEP to move from beta to GA, for example. If
+new details emerge that belong in the KEP, edit the KEP. Once a feature has become
+"implemented", major changes should get new KEPs.
+
+The canonical place for the latest set of instructions (and the likely source
+of this file) is [here](/keps/NNNN-kep-template/README.md).
+
+**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-3659: kubectl apply --prune redesign and graduation strategy
+
+<!--
+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)
+- [Background](#background)
+  - [Use case](#use-case)
+  - [Feature history](#feature-history)
+  - [Current implementation](#current-implementation)
+  - [Problems with the current implementation](#problems-with-the-current-implementation)
+    - [Correctness: object leakage](#correctness-object-leakage)
+    - [Scalability](#scalability)
+    - [UX: easy to trigger inadvertent over-selection](#ux-easy-to-trigger-inadvertent-over-selection)
+    - [UX: flag changes affect correctness](#ux-flag-changes-affect-correctness)
+    - [UX: difficult to use with custom resources](#ux-difficult-to-use-with-custom-resources)
+    - [Sustainability: incompatibility with server-side apply](#sustainability-incompatibility-with-server-side-apply)
+- [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)
+  - [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-1)
+  - [Troubleshooting](#troubleshooting)
+- [Implementation History](#implementation-history)
+- [Drawbacks](#drawbacks)
+- [Alternatives](#alternatives)
+- [Infrastructure Needed (Optional)](#infrastructure-needed-optional)
+<!-- /toc -->
+
+## Release Signoff Checklist
+
+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
+-->
+
+When creating objects with `kubectl apply`, it is frequently desired to make changes to the config that remove objects and then re-apply and have those objects deleted. Since Kubernetes v1.5, an alpha-stage `--prune` flag exists to support this workflow: it deletes objects previously applied that no longer exist in the source config. However, the current implementation has fundamental design flaws that limit its performance and lead to surprising behaviours. This KEP proposes a safer and more performant implementation for this feature, along with a plan that will enable it to progress out of alpha while continuing to satisfy the needs of the users who have come to depend on it over the past 20+ releases.
+
+
+## Motivation
+
+### Goals
+
+- MUST use a pruning set identification algorithm that remains accurate regardless of what has changed between the previous and current sets
+- MUST use a pruning set identification algorithm that scales to thousands of resources across hundreds of types
+- MUST natively support custom resources
+- MUST provide a way to accurately preview which objects will be deleted
+- MUST support namespaced and non-namespaced resources; SHOULD support them within the same operation
+<!--
+List the specific goals of the KEP. What is it trying to achieve? How will we
+know that this has succeeded?
+-->
+
+### Non-Goals
+
+- MUST NOT formalize the grouping of objects under management (i.e. it is a just a set of objects, not an "application" or other high-level construct) or require the user to do so to use the feature
+- MUST NOT require server-side API changes
+- MUST NOT require third-party CRDs to be installed
+- MAY still have limited performance when used to manage thousands of resources of hundreds of types in a single operation (MUST NOT be expected to overcome performance limitations of issuing many individual deletion requests, for example)
+
+## Background
+
+### Use case
+
+The pruning feature enables kubectl to automatically clean up previously applied objects that have been removed from the current configuration set.
+
+Adding the `--prune` flag to kubectl apply adds a deletion step after objects are applied, removing all objects that were previously applied AND are not currently being applied: `{objects to prune (delete)} = {previously applied objects} - {currently applied objects}`.
+
+In the illustration below, we initially apply a configuration set containing two objects: Object A and Object B. Then, we remove Object A from our configuration and add Object C. When we re-apply our configuration with pruning enabled, we expect Object A to be deleted (pruned), Object B to be updated, and Object C to be created. This basic use case works as expected today.
+
+<img src=initial-apply.png width=500px>
+<img src=subsequent-apply.png width=500px>
+
+### Feature history
+
+The `--prune` flag (and dependent `--prune-whitelist` and `--all` flags) were added to `kubectl apply` back in [Kubernetes v1.5](https://github.com/kubernetes/kubernetes/commit/56a22f925f6f1fd774ad1ae9e04bcf8d75bbde63). Twenty releases later, this feature is still in alpha, as documented in `kubectl apply -h` (though interestingly not on the flag doc string itself, or during usage):
+
+<details>
+<summary>Relevant portion of `kubectl apply -h`</summary>
+
+```shell
+$ kubectl version --client --short
+Client Version: v1.25.2
+
+$ kubectl apply -h
+Apply a configuration to a resource by file name or stdin. The resource name must be specified. This resource will be
+created if it doesn't exist yet. To use 'apply', always create the resource initially with either 'apply' or 'create
+--save-config'.
+
+ JSON and YAML formats are accepted.
+
+ Alpha Disclaimer: the --prune functionality is not yet complete. Do not use unless you are aware of what the current
+state is. See https://issues.k8s.io/34274.
+
+Examples:
+  # Note: --prune is still in Alpha
+  # Apply the configuration in manifest.yaml that matches label app=nginx and delete all other resources that are not in
+the file and match label app=nginx
+  kubectl apply --prune -f manifest.yaml -l app=nginx
+
+  # Apply the configuration in manifest.yaml and delete all the other config maps that are not in the file
+  kubectl apply --prune -f manifest.yaml --all --prune-whitelist=core/v1/ConfigMap
+
+Options:
+    --all=false:
+	Select all resources in the namespace of the specified resource types.
+    --prune=false:
+	Automatically delete resource objects, that do not appear in the configs and are created by either apply or
+	create --save-config. Should be used with either -l or --all.
+    --prune-whitelist=[]:
+	Overwrite the default whitelist with <group/version/kind> for --prune
+    -l, --selector='':
+	Selector (label query) to filter on, supports '=', '==', and '!='.(e.g. -l key1=value1,key2=value2). Matching
+	objects must satisfy all of the specified label constraints.
+```
+</details>
+
+The reason for this stagnation is that the implementation has fundamental limitations that limit performance and cause unexpected behaviours.
+
+Acknowledging that pruning could not be progressed out of alpha in its current form, SIG CLI created a proof of concept for an alternative implmentation in the [cli-utils](https://github.com/kubernetes-sigs/cli-utils) repo in 2019 (initially [moved over](https://github.com/kubernetes-sigs/cli-utils/pull/1) from [cli-experimental#13](https://github.com/kubernetes-sigs/cli-experimental/pull/13)). This implementation was proposed in [KEP 810](https://github.com/kubernetes/enhancements/pull/810/files), which did not reach consensus and was ultimately closed. In the subsequent three years, work continued on the proof of concept, and other ecosystem tools (notably `kpt live apply`) have been using it successfully while the canoncial implementation in k/k has continued to stagnate.
+
+### Current implementation
+
+The implementation of this feature is not as simple as the illustration above might suggest at first glance. The core of the reason is that the previously applied set is not specifically encoded anywhere by the previous apply operation, and therefore that set needs to be dynamically discovered.
+
+Several different factors are used to select the set of objects to be pruned:
+
+1. **GVK allowlist**: A user-provided ( via `--prune-whitelist` until v1.26, `--prune-allowlist` in v1.26+) or defaulted list of GVK strings identifying which resources kubectl will consider for pruning. The default list is hardcoded. [[code](https://github.com/kubernetes/kubernetes/blob/e39a0af5ce0a836b30bd3cce237778fb4557f0cb/staging/src/k8s.io/kubectl/pkg/util/prune/prune.go#L28-L50)]
+1. **namespace** (for namespaced resources): `kubectl` keeps track of which namespaces it has "visited" during the apply operation and considers both them and the objects they contain for pruning. [[code](https://github.com/kubernetes/kubernetes/blob/master/staging/src/k8s.io/kubectl/pkg/cmd/apply/prune.go#L78)]
+1. **the `kubectl.kubernetes.io/last-applied-configuration` annotation**: kubectl uses this as the signal that the object was created with `apply` as opposed to by another kubectl command or entity. Only objects created by apply are considered for pruning. [[code](https://github.com/kubernetes/kubernetes/blob/master/staging/src/k8s.io/kubectl/pkg/cmd/apply/prune.go#L117-L120)]
+1. **labels**: pruning forces users to specify either `--all` or `-l/--selector`, and in the latter case, the query selecting resources for pruning will be constrained by the provided labels (note that this flag also constrains the resources applied in the main operation) [[code](https://github.com/kubernetes/kubernetes/blob/master/staging/src/k8s.io/kubectl/pkg/cmd/apply/prune.go#L99)]
+
+For a more detailed walkthrough of the implementation along with examples, please see [kubectl apply/prune: implementation and limitations](https://docs.google.com/document/d/1y747qL3GYMDDYHR8SqJ-6iWjQEdCJwK_n0z_KHcwa3I/edit#) by @seans3.
+
+### Problems with the current implementation
+
+#### Correctness: object leakage
+
+ If an object is supposed to be pruned, but it is not, then it is leaked. This situation occurs when the set of previously applied objects selected is incomplete. There are two main ways this can happen:
+ - **GVK allowlist mismatch**: the allowlist is hardcoded (either by kubectl or by the user) and as such it is not tied in any way to the list of kinds we actually need to manage to prune effectively. For example, the default allowlist will never prune PDBs, regardless of whether current or previous operations created them.
+ - **namespace mismatch**: the namespace list is constructed dynamically from the _current_ set of objects, which causes object leakage when the current operation touches fewer namespaces than the previous one did. For example, if the initial operation touched namespaces A and B, and the second touched only B, nothing in namespace A will be pruned.
+
+ TODO: link issues
+
+#### UX: flag changes affect correctness
+
+If the user changes the `--prune-allowlist` or `--selector` flags used with the apply command, this may radically change the scoping of the pruning operation, causing it over- or under-select resources. For example, if they add a new label to all their resources and adjust the `--selector` accordingly, this will have the side-effect of leaking ALL resources that should have been deleted during the operation (nothing will be pruned). On the contrary, if `--prune-allowlist` is expanded to include additional types or `--selector` is made more general, any objects that have been manually applied by other actors in the system may automatically get scoped in.
+
+TODO: link issues
+
+#### Scalability
+
+To discover the set of resources to be pruned, kubectl makes a LIST query to every GVR on the allowlist, for every namespace (if applicable): `GVR(namespaced)*Ns + GVR(global)`. For example, with the default list and one target namespace, this is 14 requests; with the default list and two namespaces, it jumps to 26. An obvious fix for some of the correctness issues described would be to get the full list of GVRs from discovery and query ALL of them, ensuring all previous objects are discovered. Indeed some tools do this, and pass the resulting list to kubectl's allowlist. But this strategy is clearly not performant, and many of the additional queries are wasted, as the GVRs in question are extremely unlikely to have resources managed via kubectl.
+
+A related issue is that the identifier of ownership for pruning is the last-applied annotation, which is not something that can be queried on. This means we cannot avoid retrieving irrelevant resources in the LIST requests we make.
+
+TODO: link issues
+
+#### UX: easy to trigger inadvertent over-selection
+
+The default allowlist, in addition to being incomplete, is unintuitive. Notably, it includes the cluster-scoped Namespace and PersistentVolume resources, and will prune these resources even if the `--namespace` flag is used. Given that Namespace deletion cascades to all the contents of the namespaces, this is particularly catastropic.
+
+Because every `apply` operation uses the same identity for the purposes of pruning (i.e. has the same last-applied annotation), it is easy to make a small change to the scoping of the command that will inadvertantly cover resources managed by other operations, with potentially disasterous effects.
+
+TODO: link issues
+
+#### UX: difficult to use with custom resources
+
+Because the default allowlist is hard-coded in the kubectl codebase, it inherently does not include any custom resources. Users who want to prune custom resources necessarily need to specify their own allowlist and keep it up to date.
+
+TODO: link issues
+
+#### Sustainability: incompatibility with server-side apply
+
+While it is not disabled, pruning does not work correctly with server-side apply today. If the objects being managed were created with server-side apply, or were migrated to server-side apply using a custom field manager, they will never be pruned. If they were created with client-side apply and migrated to server-side using the default field manager, they will be pruned as needed. The worst case is that the managed set includes objects in multiple of these states, leading to inconsistent behaviour.
+
+One solution to this would be to use the presence of the current field manager as the indicator of eligibility for pruning. However, field managers cannot be queried on any more than annotations can, so are not a great for an identifier we want to select on. It can also be considered problematic that the default state for server-side applied objects includes at least two field managers, which are then all taken to be object owners for the purposes of pruning, regardless of their intent to use this power. In other words, we end up introducing the possibilty of multiple owners without the possiblity of conflict detection.
+
+## 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.
+-->
+
+### 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.
+-->
+
+### 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
+
+<!--
+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
+  in the kubelet? How does an n-2 kubelet 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? (Do not assume `Dynamic Kubelet Config` feature is enabled).
+
+###### 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
+-->
+
+### 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-cli/3659-kubectl-apply-prune/initial-apply.png b/keps/sig-cli/3659-kubectl-apply-prune/initial-apply.png
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diff --git a/keps/sig-cli/3659-kubectl-apply-prune/kep.yaml b/keps/sig-cli/3659-kubectl-apply-prune/kep.yaml
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index 00000000000..86b18f4613a
--- /dev/null
+++ b/keps/sig-cli/3659-kubectl-apply-prune/kep.yaml
@@ -0,0 +1,40 @@
+title: KEP Template
+kep-number: 3659
+authors:
+  - "@KnVerey"
+owning-sig: sig-cli
+participating-sigs: []
+status: provisional
+creation-date: 2022-11-15
+reviewers:
+  - @soltysh
+  - @seans3
+  - @eddiezane
+approvers:
+  - @soltysh
+
+see-also:
+  - "https://github.com/kubernetes/enhancements/issues/128"
+  - "https://github.com/kubernetes/enhancements/pull/810"
+
+# The target maturity stage in the current dev cycle for this KEP.
+stage: alpha
+
+# 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: "v1.27"
+
+# The milestone at which this feature was, or is targeted to be, at each stage.
+milestone:
+  alpha: "v1.27"
+  beta: "TBD"
+  stable: "TBD"
+
+# 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: []
+disable-supported: true
+
+# The following PRR answers are required at beta release
+metrics: []
diff --git a/keps/sig-cli/3659-kubectl-apply-prune/subsequent-apply.png b/keps/sig-cli/3659-kubectl-apply-prune/subsequent-apply.png
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