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# KEP-5996: Support Default Pod Sysctls in Kubelet Configuration

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- [Release Signoff Checklist](#release-signoff-checklist)
- [Summary](#summary)
- [Motivation](#motivation)
  - [Goals](#goals)
  - [Non-Goals](#non-goals)
- [Proposal](#proposal)
  - [User Stories](#user-stories)
    - [Story 1](#story-1)
  - [Notes/Constraints/Caveats (Optional)](#notesconstraintscaveats-optional)
  - [Risks and Mitigations](#risks-and-mitigations)
- [Design Details](#design-details)
  - [Kubelet Configuration Changes](#kubelet-configuration-changes)
  - [Validation](#validation)
  - [Application Logic](#application-logic)
  - [OCI Runtimes](#oci-runtimes)
  - [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)
    - [Deprecation](#deprecation)
  - [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)
  - [Node Resource Interface (NRI)](#node-resource-interface-nri)
  - [Mutating Admission Webhooks](#mutating-admission-webhooks)
  - [Mutating Admission Policy](#mutating-admission-policy)
<!-- /toc -->

## Release Signoff Checklist

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## Summary

Add support for new field `DefaultPodSysctls` in the Kubelet configuration. This field allows node administrators to define a set of namespaced kernel parameters (sysctls) that will be applied by default to all pods running on the node. These defaults are applied during pod sandbox creation, specifically for sysctls that are namespaced (e.g., within the network or IPC namespaces), provided the pod is not using the host namespace for those subsystems.

## Motivation

Currently, Kubernetes allows users to specify sysctls for individual pods via the [securityContext.sysctls](https://kubernetes.io/docs/tasks/administer-cluster/sysctl-cluster/#setting-sysctls-for-a-pod) field in the Pod spec. However, in many production environments, node administrators often need to enforce consistent kernel parameter tuning across all workloads on a node or within a node pool/group. For example, high-performance networking or messaging applications may require specific `net.*` or `kernel.shm*` values to be set globally for all containers on specialized nodes.
Setting these parameters manually in every Pod spec is error-prone and redundant. Furthermore, cluster operators may wish to manage these defaults at the infrastructure level (e.g., via Kubelet configuration) to ensure performance and stability without requiring application developers to be aware of the underlying host kernel tuning needs.

### Goals

* Add new field `DefaultPodSysctls` to the Kubelet configuration.
* Allow node-level defaulting of namespaced kernel parameters for all pods, including **static** pods.
    * Namespaced sysctls cover both safe and unsafe sysctls.
    * Cover list: `kernel.shm*`, `kernel.msg*`, `kernel.sem`, `fs.mqueue.*`, `net.*`, `kernel.domainname`, `user.*`.
* Ensure that sysctls are only applied if the pod is namespaced for the corresponding subsystem (i.e., not using HostNetwork or HostIPC).

### Non-Goals

* NOT support configuring non-namespaced sysctls in Pods.
* NOT support pod level defaulting of sysctls, i.e. not support additional filtering on Pods to apply default sysctls.
* Configuration changes will only affect new pods; dynamic reconfiguration for existing pods is NOT supported.

## Proposal

We propose adding a new field `DefaultPodSysctls` to the Kubelet configuration. This field will allow operators to specify key-value pairs of sysctls. The Kubelet will merge these defaults into the Pod sandbox configuration during sandbox creation, and thus applied to all Pods.

The precedence for sysctl values will be:
* Pod-level SecurityContext: Values explicitly set in pod `spec.securityContext.sysctls` will always override the Kubelet's default sysctls.
* Kubelet Defaults: Values set in the new kubelet field which will be applied to ALL pods.

The new kubelet field will support all namespaced sysctl (`kernel.shm*`, `kernel.msg*`, `kernel.sem`, `fs.mqueue.*`, `net.*`, `kernel.domainname`, `user.*`), covering both safe and unsafe sysctls. Note, `net.*` sysctl is a bit different, since part of networking sysctls are unnamespaced and cannot be set in pods.

Besides, sysctls inside pods are seen as individual values. Thus, grouping of sysctls needs to be specified explicitly with key and value pairs in the kubelet field map to take effect correctly.

On the other hand, with Kubelet applying sysctls to pod sandbox, no changes in CRI API or container runtime are needed.

### User Stories

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#### Story 1

As a cluster admin, I would like to be able to set namespaced sysctls for all pods to share the same kernel environments. And pods keep the ability to customize specific sysctl in its own namespace.

For example, I plan to run a large-scale data processing pipeline or a distributed machine learning training workload, which
involves significant inter-pod network communication, transferring large volumes of data. To improve data transfer speed and reduce overall job completion time, I need to increase `net.ipv4.tcp_rmem` and `net.ipv4.tcp_wmem` for all pods to increase the TCP buffer sizes.

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### Risks and Mitigations

* Overwriting critical host settings if a global sysctl is accidentally specified.
    * The application logic strictly enforces namespacing. Global (non-namespaced) sysctls specified in `DefaultPodSysctls` will be ignored if they cannot be applied in a namespace context, adhering to underlying OCI Runtimes (eg., `runc` and `crun`) restrictions. However, some `net.*` sysctls are unnamespaced, and would lead to `FailedCreatePodSandBox` failure. Users need to ensure that the `net` sysctls are namespaced.

* The provided sysctl keys or values are invalid.
    * The OCI Runtimes (eg., `runc` and `crun`) handles the direct application of sysctl configurations by writing to the appropriate files within `/proc/sys/`. The Linux Kernel handles validation on value type and range. Consequently, if a sysctl key is invalid or the provided value is unsupported, the operation will fail. This failure prevents the Kubelet from successfully creating the pod sandbox, resulting in a `FailedCreatePodSandBox` error. Therefore cluster admin needs to verify that all provided sysctl keys and values are accurate and valid to avoid the pod failure.

## Design Details

### Kubelet Configuration Changes

The `KubeletConfiguration` struct will be updated to include a new field:

```
type KubeletConfiguration struct {
    // Existing fields: A comma separated allowlist of unsafe sysctls or sysctl patterns. Users are allowed to set them in pod securityContext.sysctls.
    AllowedUnsafeSysctls []string

    // New field: DefaultPodSysctls is a list of sysctls that will be applied inside all pods running on this node by default.
    // +optional
    DefaultPodSysctls map[string]string
}
```

### Validation

The field will be guarded by a new feature gate called `DefaultPodSysctls` added in [kube_features.go](https://github.com/kubernetes/kubernetes/blob/master/pkg/features/kube_features.go).

The namespace-level verification will be performed while applying to pods in `Application Logic` below, since it depends on the pod namespace information. Unnamespaced flags will be ignored to avoid failure. There will be log messages containing all applied sysctls.

Besides, we will NOT perform exhaustive validation on the specific sysctl keys or values within the field, similar to [AllowedUnsafeSysctls](https://github.com/kubernetes/kubernetes/blob/master/pkg/kubelet/apis/config/types.go#L408), considering the large amount of parameters. Linux kernel defines handlers for each category of sysctls and validates on parameter type and ranges. For example, [net.ipv4.*](https://github.com/torvalds/linux/blob/9147566d801602c9e7fc7f85e989735735bf38ba/net/ipv4/sysctl_net_ipv4.c) defines the handler to check integer type and min/max values. Thus the cluster admin needs to ensure the provided keys and values are valid.

### Application Logic
The field will be called in the `generatePodSandboxLinuxConfig` function in [kuberuntime](https://github.com/kubernetes/kubernetes/blob/master/pkg/kubelet/kuberuntime/kuberuntime_sandbox.go#L179) before `securityContext.sysctls` is applied, and parsed to linux config (as below) to start [PodSandbox](https://github.com/kubernetes/kubernetes/blob/master/pkg/kubelet/kuberuntime/kuberuntime_sandbox.go#L67). 

```
// NamespaceOption provides options for Linux namespaces.
message PodSandboxConfig {
    PodSandboxMetadata metadata = 1;
    // Hostname of the sandbox. Hostname could only be empty when the pod
    // network namespace is NODE.
    string hostname = 2;
    ...
    LinuxPodSandboxConfig linux = 8;
    // Optional configurations specific to Windows hosts.
    WindowsPodSandboxConfig windows = 9;
}

// LinuxPodSandboxConfig holds platform-specific configurations for Linux
// host platforms and Linux-based containers.
message LinuxPodSandboxConfig {
    // Parent cgroup of the PodSandbox.
    // The cgroupfs style syntax will be used, but the container runtime can
    // convert it to systemd semantics if needed.
    string cgroup_parent = 1;
    // LinuxSandboxSecurityContext holds sandbox security attributes.
    LinuxSandboxSecurityContext security_context = 2;
    // Sysctls holds linux sysctls config for the sandbox.
    map<string, string> sysctls = 3;
    ...
}
```

`Containerd` doesn’t have any validation on sysctl settings, while the underlying OCI Runtimes (eg., `runc` and `crun`) have. A filtering function consistent with `runc` will be applied in Kubelet to ensure following sysctls are applied in the required namespaces:
* kernel.shm* => IPC namespace, not HostIPC
* kernel.msg* => IPC
* kernel.sem => IPC
* fs.mqueue.* => IPC
* kernel.domainname => UTS 
    * kernel.hostname is explicitly denied even in UTS ns
* net.*  => Net, not HostNetwork
* user.* => User (recently supported in PR last year)

### OCI Runtimes
Containerd uses `runc` by default to actually spawn and run the containers on Linux. `runc` serves as a low-level, lightweight container runtime, acting as a bridge between high-level container orchestration tools (like Containerd) and the underlying operating system. Kubelet applies the same application logic as `runc` to avoid `FailedCreatePodSandBox` failure caused by namespace checks. However the failure could still happen if the sysctl keys or values are invalid while in [WriteSysctls function](https://github.com/opencontainers/runc/blob/main/internal/sys/sysctl_linux.go#L25) (denied by kernel).

On the other hand, Containerd can also use `crun` for the same scenario. `crun` applies similar validation to `runc` on namespace checks in the [validate_sysctl](https://github.com/containers/crun/blob/main/src/libcrun/linux.c#L3667) function. The only difference is that `crun` doesn’t support `user.*` params, which was recently added in `runc`. 

An alternative of Containerd is `CRI-O`, which also applies similar validation on sysctl namespaces in [CRI-O code](https://github.com/cri-o/cri-o/blob/main/pkg/config/sysctl.go#L83), called when creating podsandbox. The only difference is that it doesn’t support `kernel.domainname` and `user.*`.

### Test Plan

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##### Prerequisite testing updates

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- `pkg/kubelet/kuberuntime`: 2026-04-09 - 70.9%
- `pkg/kubelet/apis/config/validation/`: 2026-04-09 - 91.7%

These data is obtained by running `go test -cover` based on commit [f5c7b422749303542baa17f1322d95250df9b0b5](https://github.com/kubernetes/kubernetes/commit/f5c7b422749303542baa17f1322d95250df9b0b5).

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N/A. This feature requires e2e tests.

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- Test sysctls set in `DefaultPodSysctls` field are applied to ALL pods, including static pods.
- Test pod level sysctl set in `spec.securityContext.sysctls` could override sysctls set in `DefaultPodSysctls`.
- Test unnamespaced sysctls are ignored instead of leading to failures.

### Graduation Criteria

#### Alpha

* Implement the `DefaultPodSysctls` field in Kubelet configuration behind the feature flag.
* Implement the validating and merging logic in kuberuntime.
* Add unit tests for merging precedence.

#### Beta

* Enable the feature gate by default.
* Add E2E tests covering various namespaced sysctls.

#### GA

* Gather feedback from users running specialized workloads.
* Documentation completed on kubernetes.io.

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### Upgrade / Downgrade Strategy

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- **Upgrade:**
  - Upgrading the Kubelet does not change any default behavior, as the feature
    is disabled by default during Alpha.
  - To make use of the feature after upgrade, operators must enable the
    `DefaultPodSysctls` feature gate and specify the default sysctls in the
    KubeletConfiguration (`defaultPodSysctls`).
  - Pods that are already running prior to the upgrade will continue running
    unaffected. Only new pods created post-upgrade will have default sysctls
    applied.

- **Downgrade:**
  - Before downgrading the Kubelet to a version where the feature is not
    supported or when disabling the feature gate, any `defaultPodSysctls`
    field in the KubeletConfiguration must be removed to prevent validation
    failures during Kubelet startup.
  - Active workloads constructed prior to the rollback/downgrade will keep
    running with their set sysctl values. Any new sandboxes created after the
    downgrade will not receive default sysctl configurations.

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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: `DefaultPodSysctls`
  - Components depending on the feature gate: Kubelet
- [x] Kubelet configuration parameter
  - Field: `defaultPodSysctls` under KubeletConfiguration

###### Does enabling the feature change any default behavior?

No. Enabling the feature gate exposes the config field and does not alter pod behavior unless `DefaultPodSysctls` is populated in the Kubelet configuration.

###### Can the feature be disabled once it has been enabled (i.e. can we roll back the enablement)?

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Yes. To disable the feature, turn off the `DefaultPodSysctls` feature gate, or remove the `DefaultPodSysctls` map from the Kubelet configuration, and restart the Kubelet. Workloads running on existing pod sandboxes will be unaffected.

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

New pods will have default sysctl settings applied based on the configured `DefaultPodSysctls` field. Existing running pods will continue to run with the sysctls configured at their sandbox creation time.

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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.
-->

- **Rollout Failure:**
  - **Pod Sandbox Creation Failure:** If a sysctl configured in `DefaultPodSysctls` is invalid (e.g., value out of bounds, key not recognized by the host kernel), OCI runtimes (like `runc`) will fail to write to `/proc/sys/`. This causes pod sandbox creation to fail with a `FailedCreatePodSandBox` warning event, and new pods will remain in the `Pending` state.

- **Rollback Failure:**
  - If disabling the feature, omitting to cleanse the KubeletConfiguration files of the `defaultPodSysctls` field on older downgraded Kubelet binaries will lead to startup failures due to unrecognized fields.

- **Impact on Running Workloads:**
  - Already running workloads are **not** impacted by a rollout or rollback. Defaults are applied only when a new pod sandbox is created.
  - If a running pod restarts (e.g., due to container crash or rescheduled node), the pod sandbox is reconstructed, which would then apply the updated configurations and could fail to start if the configuration is invalid.

###### 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.
-->

Check Kubelet logs to see if the feature gate is enabled and kubelet configuration is set.

###### 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:
-->

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.)
-->

No.

###### 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)
-->

No. But a new kubelet configuration will be added.

###### 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)
-->

No.

###### 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.

###### 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.

###### 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?
-->

Not likely.

### 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?

This feature is enabled in Kubelet alone.

###### 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.
-->

* Invalid Sysctl keys or values leading to WriteSysctl failure.
* Unnamespaced sysctls (some `net.` params) failed to be set in pods.

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

* Kubelet `configz` endpoint

The new kubelet field `DefaultPodSysctls` can be inspected from `configz` endpoint following [guidance](https://kubernetes.io/docs/tasks/administer-cluster/kubelet-config-file/#viewing-the-kubelet-configuration).

* Check failure in events

When starting a new pod, examine the pod status and events to verify if anything fails. If sysctl fails to apply, the pod will remain in `Pending` status, and the event contains `FailedCreatePodSandBox` failure. For example,

```
kubectl describe pod <pod-name> -n <namespace>
(Or "kubectl get events -n <namespace>")

Name:           my-sysctl-pod
Namespace:      default
Priority:       0
Node:           gke-my-cluster-node-1/10.128.0.1
Status:         Pending
...
Events:
  Type     Reason                  Age                From               Message
  ----     ------                  ----               ----               -------
  Normal   Scheduled               2m                 default-scheduler  Successfully assigned default/my-sysctl-pod to gke-my-cluster-node-1
  Warning  FailedCreatePodSandBox  30s (x5 over 2m)   kubelet            Failed to create pod sandbox: rpc error: code = Unknown desc = failed to create containerd task: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: error during container init: error applying sysctl options: failed to write net.ipv4.tcp_tw_reuse = "bad-value": Invalid argument
```

* Check sysctl in pod

To check detailed sysctl settings inside a running Kubernetes pod, you can use `kubectl exec` to run commands within one of the pod's containers. For example,

```
# start an interactive shell session within a container in the pod.
kubectl exec --stdin --tty <pod-name> -n <namespace> -- /bin/sh 

# Inside the pod's container shell:
/ # sysctl net.ipv4.ip_forward
net.ipv4.ip_forward = 0
/ # sysctl -a
... (all sysctls)
```

## 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

### Node Resource Interface (NRI)

An NRI plugin could be used to inject sysctls into pod sandboxes by adding native sysctl support to the NRI framework (https://github.com/containerd/nri/pull/248) or using OCI hooks. While NRI might offer a faster implementation path for new features, especially those with unique requirements, integrating directly into Kubernetes is generally the superior long-term approach for general-purpose improvements, like sysctl management enhancement here. The direct Kubernetes support, achieved through the upstream KEP process, results in a more streamlined architecture with reduced maintenance efforts. 

### Mutating Admission Webhooks

Injecting sysctls at admission time with [mutating webhook](https://kubernetes.io/docs/reference/access-authn-authz/admission-controllers/#mutatingadmissionwebhook) is possible but requires a running control plane component, which also requires much internal maintenance efforts. And we may require duplicate validation logic to enable “safe” sysctls in the webhooks. Besides, it doesn't allow for node-specific or node-pool-specific defaults without complex logic based on node labels.

### Mutating Admission Policy

Mutating admission policy ([GA in 1.36](https://kubernetes.io/docs/reference/access-authn-authz/mutating-admission-policy/)) is better than mutating admission webhooks since it does not require an additional control plane component. However other restrictions still apply.
