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Add PRR questionnaire to KEP template, require for targeting #1620

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220 changes: 215 additions & 5 deletions keps/NNNN-kep-template/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -93,6 +93,13 @@ tags, and then generate with `hack/update-toc.sh`.
- [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)
Expand All @@ -115,11 +122,15 @@ Check these off as they are completed for the Release Team to track. These
checklist items _must_ be updated for the enhancement to be released.
-->

- [ ] Enhancement issue in release milestone, which links to KEP dir in [kubernetes/enhancements] (not the initial KEP PR)
- [ ] KEP approvers have approved the KEP status as `implementable`
- [ ] Design details are appropriately documented
- [ ] Test plan is in place, giving consideration to SIG Architecture and SIG Testing input
- [ ] Graduation criteria is in place
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
- [ ] (R) Graduation criteria is in place
- [ ] (R) Production readiness review completed
- [ ] 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]
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Are there features where it makes sense to review whether the documentation is good enough, and to have those “good enough” criteria agreed before targeting to a release?

Thinking from the SIG Docs side, there's a range of experience, from features that are well documented in beta and where graduation is a formality, to features that are targeted to go GA in the next release and then there's a bit of a scramble to complete the documentation. And there are also things that go GA and then get properly documented.

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That makes sense to me, but it's orthogonal to PRR effort. I think you should open a separate PR for it and open it for discussion.

- [ ] Supporting documentation e.g., additional design documents, links to mailing list discussions/SIG meetings, relevant PRs/issues, release notes
Expand Down Expand Up @@ -332,6 +343,205 @@ enhancement:
CRI or CNI may require updating that component before the kubelet.
-->

## Production Readiness Review Questionnaire
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<!--

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/20190731-production-readiness-review-process.md

Production readiness review questionnaire must be completed for features in
v1.19 or later, but is non-blocking at this time. That is, approval is not
required in order to be 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 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?**
- [ ] 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).

* **Can the feature be disabled once it has been enabled (i.e. can we rollback
the enablement)?**
Also set `rollback-supported` to `true` or `false` in `kep.yaml`.
Describe the consequences on existing workloads (e.g. if this is runtime
feature, can it break the existing applications?).

* **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 and 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.

### Rollout, Upgrade and Rollback Planning

_This section must be completed when targeting beta graduation to a release._

* **How can a rollout fail? Can it impact already running workloads?**
Try to be as paranoid as possible - e.g. what if some components will restart
in the middle of rollout?

* **What specific metrics should inform a rollback?**

* **Were upgrade and rollback tested? Was 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 do that now.

### Monitoring requirements

_This section must be completed when targeting beta graduation to a release._

* **How can an operator determine if the feature is in use by workloads?**
Ideally, this should be a metrics. Operations against Kubernetes API (e.g.
checking if there are objects with field X set) may be last resort. Avoid
logs or events for this purpose.

* **What are the SLIs (Service Level Indicators) an operator can use to
determine the health of the service?**
- [ ] Metrics
- Metric name:
- [Optional] Aggregation method:
- Components exposing the metric:
- [ ] Other (treat as last resort)
- Details:

* **What are the reasonable SLOs (Service Level Objectives) for the above SLIs?**
At the high-level this usually will be in the form of "high percentile of SLI
per day <= X". It's impossible to provide a comprehensive guidance, but at the very
high level (they 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

* **Are there any missing metrics that would be useful to have to improve
observability if this feature?**
Describe the metrics themselves and the reason they weren't added (e.g. cost,
implementation difficulties, etc.).

### Dependencies

_This section must be completed when targeting beta graduation 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 the fill in the following, thinking both about running user workloads
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missing noun?

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 confirms 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 cloud
provider?**

* **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][]?**
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.

* **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 send and/or received over network, etc.
This through this both in small and large cases, again with respect to the
[supported limits][].

### Troubleshooting

Troubleshooting section serves the `Playbook` role as of now. We may consider
splitting it into a dedicated `Playbook` document (potentially with some monitoring
details). For now we leave it here though.

_This section must be completed when targeting beta graduation to a release._

* **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 loogging into a master or worker node?
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typo in loogging

- 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 debugging 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?**

[supported limits]: https://git.k8s.io/community//sig-scalability/configs-and-limits/thresholds.md
[existing SLIs/SLOs]: https://git.k8s.io/community/sig-scalability/slos/slos.md#kubernetes-slisslos

## Implementation History

<!--
Expand Down
29 changes: 28 additions & 1 deletion keps/NNNN-kep-template/kep.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -13,9 +13,36 @@ reviewers:
- "@alice.doe"
approvers:
- TBD
- "@oscar.doe"
- "@oscar.doe" # PRR Approver
see-also:
- "/keps/sig-aaa/1234-we-heard-you-like-keps"
- "/keps/sig-bbb/2345-everyone-gets-a-kep"
replaces:
- "/keps/sig-ccc/3456-replaced-kep"

# The target maturity stage in the current dev cycle for this KEP.
stage: alpha|beta|stable
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there is no such field in the Proposals structure, causing kepval / make verify to fail:
https://github.com/kubernetes/enhancements/blob/master/pkg/kepval/keps/proposals.go#L49-L76

looks like the template itself is not validated.

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this has since been fixed, thanks


# 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: "v1.19"

# The milestone at which this feature was, or is targeted to be, at each stage.
milestone:
alpha: "v1.19"
beta: "v1.20"
stable: "v1.22"

# The following PRR answers are required at alpha release
# List the feature gate name and the components for which it must be enabled
feature-gate:
name: MyFeature
components:
- kube-apiserver
- kube-controller-manager
rollback-supported: true

# The following PRR answers are required at beta release
metrics:
- my_feature_metric