PRR approval request for KEPs:

  1287-in-place-update-pod-resources
  2273-kubelet-container-resources-cri-api-changes

Author: vinaykul

keps/prod-readiness/sig-node/1287.yaml

@@ -0,0 +1,3 @@
+kep-number: 1287
+alpha:
+  approver: "@ehashman"

keps/prod-readiness/sig-node/2273.yaml

@@ -0,0 +1,3 @@
+kep-number: 2273
+alpha:
+  approver: "@ehashman"

keps/sig-node/1287-in-place-update-pod-resources/README.md

@@ -33,9 +33,17 @@
   - [Alpha](#alpha)
   - [Beta](#beta)
   - [Stable](#stable)
+- [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)
 <!-- /toc -->
 
+
 ## Summary
 
 This proposal aims at allowing Pod resource requests & limits to be updated
@@ -629,6 +637,203 @@ TODO: Identify more cases
 - No major bugs reported for three months.
 - Pod-scoped resources are handled if that KEP is past alpha
 
+## 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/20190731-production-readiness-review-process.md.
+
+The 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 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?**
+  - [x] Feature gate (also fill in values in `kep.yaml`)
+    - Feature gate name: InPlacePodVerticalScaling
+    - Components depending on the feature gate: kubelet
+  - [ ] 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?** No
+
+* **Can the feature be disabled once it has been enabled (i.e. can we roll back
+  the enablement)?** Yes
+
+* **What happens if we reenable the feature if it was previously rolled back?**
+
+* **Are there any tests for feature enablement/disablement?** Unit tests
+
+### 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
+   mid-rollout?
+
+* **What specific metrics should inform a rollback?**
+
+* **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 graduation to a release._
+
+* **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.
+
+* **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 a high level, this usually will be in the form of "high percentile of SLI
+  per day <= X". 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
+
+* **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 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 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?**
+
+* **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 sent and/or received over network, etc.
+  This through this both in small and large cases, again with respect to the
+  [supported limits].
+
+### Troubleshooting
+
+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.
+
+_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 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?**
+
+[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
 
 - 2018-11-06 - initial KEP draft created

keps/sig-node/1287-in-place-update-pod-resources/kep.yaml

@@ -23,12 +23,26 @@ approvers:
   - "@mwielgus"
 editor: TBD
 creation-date: 2018-11-06
-last-updated: 2020-01-14
+last-updated: 2021-02-05
 status: implementable
 see-also:
   - "/keps/sig-node/2273-kubelet-container-resources-cri-api-changes"
 replaces:
 superseded-by:
 
+# PRR
+prr-approvers:
+  - "@ehashman"
+feature-gates:
+  - name: InPlacePodVerticalScaling
+    components:
+      - kube-apiserver
+      - kube-scheduler
+      - kubelet
+disable-supported: true
+milestone:
+  alpha: "v1.22"
+  beta: "v1.23"
+  stable: "v1.24"
 latest-milestone: "0.0"
 stage: "alpha"