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# KEP-5468: Invariant Testing

<!--
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title can help communicate what the KEP is and should be considered as part of
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<!-- toc -->
- [Release Signoff Checklist](#release-signoff-checklist)
- [Summary](#summary)
- [Motivation](#motivation)
  - [Goals](#goals)
  - [Non-Goals](#non-goals)
- [Proposal](#proposal)
  - [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)
  - [Troubleshooting](#troubleshooting)
- [Implementation History](#implementation-history)
- [Drawbacks](#drawbacks)
- [Alternatives](#alternatives)
  - [Implement outside of test framework](#implement-outside-of-test-framework)
  - [Collect data, and scan for it externally](#collect-data-and-scan-for-it-externally)
- [Infrastructure Needed (Optional)](#infrastructure-needed-optional)
<!-- /toc -->

## Release Signoff Checklist

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Items marked with (R) are required *prior to targeting to a milestone / release*.

- [x] (R) Enhancement issue in release milestone, which links to KEP dir in [kubernetes/enhancements] (not the initial KEP PR)
- [x] (R) KEP approvers have approved the KEP status as `implementable`
- [x] (R) Design details are appropriately documented
- [x] (R) Test plan is in place, giving consideration to SIG Architecture and SIG Testing input (including test refactors)
  - [x] e2e Tests for all Beta API Operations (endpoints)
  - [x] (R) Ensure GA e2e tests meet requirements for [Conformance Tests](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-architecture/conformance-tests.md) 
  - [x] (R) Minimum Two Week Window for GA e2e tests to prove flake free
- [x] (R) Graduation criteria is in place
  - [x] (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) 
- [x] (R) Production readiness review completed
- [x] (R) Production readiness review approved
- [x] "Implementation History" section is up-to-date for milestone
- [x] User-facing documentation has been created in [kubernetes/website], for publication to [kubernetes.io]
- [x] Supporting documentation—e.g., additional design documents, links to mailing list discussions/SIG meetings, relevant PRs/issues, release notes

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[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

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-->

With this KEP, we introduce an approach to testing invariants within the cluster
across the entire end-to-end test run, with rules in place to minimize the risk
of "tragedy of the commons" flakes across CI.


## Motivation

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SIG Testing has received multiple requests to enable testing invariants that span
entire end to end test suite runs, as opposed to being isolated to individual tests.

For example, [declarative validation] introduces a metric which, when incremented,
indicates a mismatch in declarative and imperative validation, indicating a bug.

Because there is concern about flaking tests and "tragedy of the commons" when
a test that spans the entire suite starts to fail in any number of jobs the authors
may not be monitoring, we will formalize the approach in this KEP and introduce
a principled approach with rules and guardrails.

See:

- https://git.k8s.io/enhancements/keps/sig-api-machinery/4153-declarative-validation/README.md
- https://github.com/kubernetes/kubernetes/pull/133013
- https://github.com/kubernetes/kubernetes/pull/132613#discussion_r2244072152
- https://github.com/kubernetes/kubernetes/pull/133844

### Goals

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List the specific goals of the KEP. What is it trying to achieve? How will we
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-->
- Enable end to end tests to check invariants after the rest of the test suite
- Prevent unowned tests
- Allow opting into / out-of this testing
- Prevent flaking, unreliable tests
- Ensure result reporting is structured
- Must not impact the conformance test suite

### Non-Goals

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-->

- Enable completely arbitrary checks
- Targeting integration tests.
  - We are specifically aiming for end to end tests for this purpose.

## Proposal

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First, all invariant **MUST** have clearly documented owners, which will be surfaced
with the failure results.
No invariant tests may roll up to the general test owners.
There is precedent in documenting featuregate and metrics owners.

Similarly, the associated SIG(s) must be registered, for use in tagged related
issues.

A shared system will be introduced to the e2e framework to enable this form of
testing.

All utilities for this will be owned by the SIG Testing Leads and thoroughly
vetted for reliability.

New invariants will be tested many times before merge, and may be demoted
at any time by tagging the associated sentinel test `[Flaky]`. Failure to respond
to flaking invariant tests in a timeline fashion will result in demoting or
removing them.

### Risks and Mitigations

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-->

If implemented poorly, this could result in tests flaking in any number of e2e
test CI jobs that are now running these tests.

We will mitigate this by thoroughly reviewing and testing the invariant checking utilities, 
and by limiting to only portable, reliable mechanisms.

If not run in many CI jobs, there will be limited benefit to the signal.
We will aim to generally introduce these as default selected tests.


## Design Details

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[Ginkgo], which we use for the e2e tests, does not have a facility for 
"this test must run after all other tests". It does have ordering, but only
within a group of tests. Alternatively we can run arbitrary code after the
suite, but that does not suit our ability to opt-in/out of the tests.

We will introduce a package under `test/e2e` that contains sentinel test(s) which
do nothing other than register to Ginkgo that they have run, if selected.

These tests can be labeled appropriately, allowing the existing test selection
mechanisms to select / skip them.

We can then use `ginkgo.ReportAfterSuite` to inspect which, if any, of these 
sentinel invariant tests ran, and run the *actual* test logic, reporting pass/fail.

This allows us the flexibility of treating them like regular tests while ensuring
that the actual invariant check occurs _after_ all other tests.

It also ensures that while default-enabled, these tests will not impact
conformance testing, since the sentinel tests will not be tagged `[Conformance]`
and therefore will not run, in turn disabling the actual after-suite checks.

Invariant checks will be limited to read-only, such as fetching metrics.
Invariant checks should be simple, reliable, cheap code.
They ideally run in most e2e test runs for useful coverage.

Failure logs for these invariant checks will include instructions about how
to handle the test failure and who to report bugs to, from the documented owners.

Something like this, for the failure message:
> Invariant failed for missing metric: <metric-name>
>
> If this failed on a pull request, please check if the PR changes may be related
> to the failure, if not, you can also search for an existing GitHub issue before
> filing a new issue.
>
> If this failed in a periodic CI, please file a bug and assign the owners.
>
> Owners for this metric: <github-handles>
> Associated Special Interest Groups: <sig-foo>


### 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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Based on reviewers feedback describe what additional tests need to be added prior
implementing this enhancement to ensure the enhancements have also solid foundations.
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This KEP is itself entirely testing updates.

##### Unit tests

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Not applicable, these are e2e tests.

##### Integration tests

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Not applicable, these are e2e tests.

##### e2e tests

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We expect no non-infra related flakes in the last month as a GA graduation criteria.
If e2e tests are not necessary or useful, explain why.
-->

TBD: We will need to settle on the tests and names.

To start we will add something to cover the declarative validation metric.


### Graduation Criteria

N/A. Alpha/Beta/GA does not apply to a KEP of this nature.
This KEP is about decision making around the e2e tests, it does not have
any feature-gated changes or user-facing API changes.

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Define graduation milestones.

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#### Beta

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- All functionality completed
- All security enforcement completed
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- All testing requirements completed
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**Note:** Beta criteria must include all functional, security, monitoring, and testing requirements along with resolving all issues and gaps identified

#### GA

- N examples of real-world usage
- N installs
- Allowing time for feedback
- All issues and gaps identified as feedback during beta are resolved

**Note:** GA criteria must not include any functional, security, monitoring, or testing requirements.  Those must be beta requirements.

**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

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### Upgrade / Downgrade Strategy

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Not applicable.

### 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?
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  CRI or CNI may require updating that component before the kubelet.
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Not applicable.

## Production Readiness Review Questionnaire

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This entire section is N/A, this is not in a production cluster component.

### Feature Enablement and Rollback

<!--
This section must be completed when targeting alpha to a release.
-->

Not applicable. Does not exist in a cluster component.

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

<!--
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Documentation is available on [feature gate lifecycle] and expectations, as
well as the [existing list] of feature gates.

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[existing list]: https://kubernetes.io/docs/reference/command-line-tools-reference/feature-gates/
-->

Not applicable. Does not exist in a cluster component.

###### 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.
-->

Not applicable. Does not exist in a cluster component.

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

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-->

Not applicable. Does not exist in a cluster component.

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

Not applicable. Does not exist in a cluster component.

###### Are there any tests for feature enablement/disablement?

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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
-->

Not applicable. Does not exist in a cluster component.

### Rollout, Upgrade and Rollback Planning

<!--
This section must be completed when targeting beta to a release.
-->

Not applicable. Does not exist in a cluster component.

###### How can a rollout or rollback fail? Can it impact already running workloads?

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Be sure to consider highly-available clusters, where, for example,
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rollout. Similarly, consider large clusters and how enablement/disablement
will rollout across nodes.
-->

Not applicable. Does not exist in a cluster component.

###### 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?
-->

Not applicable. Does not exist in a cluster component.

###### 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.
-->

Not applicable. Does not exist in a cluster component.

###### 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.
-->

Not applicable. Does not exist in a cluster component.

### 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.
-->

Not applicable. Does not exist in a cluster component.

###### 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.
-->

Not applicable. Does not exist in a cluster component.

###### How can someone using this feature know that it is working for their instance?

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For instance, if this is a pod-related feature, it should be possible to determine if the feature is functioning properly
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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.
-->

Not applicable. Does not exist in a cluster component.

###### 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
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  - 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.
-->

Not applicable. Does not exist in a cluster component.

###### 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.
-->

Not applicable. Does not exist in a cluster component.

###### 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.).
-->

Not applicable. Does not exist in a cluster component.

### Dependencies

<!--
This section must be completed when targeting beta to a release.
-->

None.

###### 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
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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:
-->

Not applicable. Does not exist in a cluster component.

### Scalability

<!--
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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
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###### 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.)
-->
Not applicable. Does not exist in a cluster component.

###### 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)
-->
Not applicable. Does not exist in a cluster component.

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

<!--
Describe them, providing:
  - Which API(s):
  - Estimated increase:
-->
Not applicable. Does not exist in a cluster component.

###### 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)
-->
Not applicable. Does not exist in a cluster component.

###### 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
-->
Not applicable. Does not exist in a cluster component.

###### 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
-->
Not applicable. Does not exist in a cluster component.

###### 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 applicable. Does not exist in a cluster component.

### Troubleshooting

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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.
-->

Not applicable. Does not exist in a cluster component.

###### How does this feature react if the API server and/or etcd is unavailable?

Not applicable. Does not exist in a cluster component.

###### 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.
-->
Not applicable. Does not exist in a cluster component.

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

Not applicable. Does not exist in a cluster component.

## 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
-->

- Proposal 2025-08-06: https://github.com/kubernetes/enhancements/issues/5468
- Proposal Merged 2025-09-30: https://github.com/kubernetes/enhancements/pull/5514
- Code + Tests Merged 2025-10-02: https://github.com/kubernetes/kubernetes/pull/133394

## Drawbacks

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

It introduces additional complexity and a risk for flaking tests.
I believe we can sufficiently mitigate these.

## 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.
-->

### Implement outside of test framework

We could implement checks in some specific CI jobs, outside of the e2e test framework.
This would give us less coverage, and be less maintainable.

### Collect data, and scan for it externally

We could make sure CI jobs are exporting relevant metrics and other invariant data
to persisted CI results, and then scan those in some external process.

This was discussed and considered, but deemed redundant to our existing CI result
pipelines and dashboards, which already need more active maintainers 
(testgrid, triage, prow, gcsweb ...). It is also difficult to do efficiently,
and we've already tackled that problem with collecting JUnit results from the
test runs.

## 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.
-->

[declarative validation]: https://git.k8s.io/enhancements/keps/sig-api-machinery/4153-declarative-validation/README.md
[Ginkgo]: https://onsi.github.io/ginkgo/