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Merge pull request #4509 from rikatz/lbipmode-to-beta
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KEP-1860 - Propose beta graduation and add missing PRR
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2 changes: 2 additions & 0 deletions keps/prod-readiness/sig-network/1860.yaml
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Expand Up @@ -4,3 +4,5 @@
kep-number: 1860
alpha:
approver: "@wojtek-t"
beta:
approver: "@wojtek-t" # temptative
263 changes: 100 additions & 163 deletions keps/sig-network/1860-kube-proxy-IP-node-binding/README.md
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Expand Up @@ -189,138 +189,125 @@ Yes. It is tested by `TestUpdateServiceLoadBalancerStatus` in pkg/registry/core/

### 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?
As the rollout will enable a feature not being used yet, there is no possible failure
scenario as this feature will then need to be also enabled by the cloud provider on
the services resources.

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.
-->
In case of a rollback, kube-proxy will also rollback to the default behavior, switching
back to VIP mode. This can fail for workloads that may be already relying on the
new behavior (eg. sending traffic to the LoadBalancer expecting some additional
features, like PROXY and TLS Termination as per the Motivations section).

###### 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?
-->
If using kube-proxy, looking at metrics `sync_proxy_rules_duration_seconds` and
`sync_proxy_rules_last_timestamp_seconds` may help identifying problems and indications
of a required 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.
-->
Because this is a feature that depends on CCM/LoadBalancer controller, and none yet
implements it, the scenario is simulated with the upgrade/downgrade/upgrade path being
enabling and disabling the feature flag, and doing the changes on services status subresources.

There is a LoadBalancer running on the environment (metallb) that is responsible for doing the proper
LB ip allocation and announcement, but the rest of the test is related to kube-proxy programming
or not the iptables rules based on this enablement/disablement path

* Initial scenario
* Started with a v1.29 cluster with the feature flag enabled
* Created 3 Deployments:
* web1 - Will be using the new feature
* web2 - Will NOT be using the new feature
* client - "the client"
* Created the loadbalancer for the two web services. By default both LBs are with the default `VIP` value
```yaml
status:
loadBalancer:
ingress:
- ip: 172.18.255.200
ipMode: VIP
```
* With the feature flag enabled but no change on the service resources, tested and both
web deployments were accessible
* Verified that the iptables rule for both LBs exists on all nodes
* Testing the feature ("upgrade")
* Changed the `ipMode` from first LoadBalancer to `Proxy`
* Verified that the iptables rule for the second LB still exists, while the first one didn't
* Because the LoadBalancer of the first service is not aware of this new implementation (metallb), it is
not accessible anymore from the client Pod
* The second service, which `ipMode` is `VIP` is still accessible from the Pods
* Disable the feature flag ("downgrade")
* Edit kube-apiserver manifest and disable the feature flag
* Edit kube-proxy configmap, disable the feature and restart kube-proxy Pods
* Confirmed that both iptables rules are present, even if the `ipMode` field was still
set as `Proxy`, confirming the feature is disabled. Both accesses are working

Additionally, an apiserver and kube-proxy upgrade test was executed as the following:
* Created a KinD cluster with v1.28
* Created the same deployments and services as bellow
* Both loadbalancer are accessible
* Upgraded apiserver and kube-proxy to v1.29, and enabled the feature flag
* Set `ipMode` as `Proxy` on one of the services and execute the same tests as above
* Observed the expected behavior of iptables rule for the changed service
not being created
* Observed that the access of the changed service was not accessible anymore, as
expected
* Disable feature flag
* Rollback kube-apiserver and kube-proxy to v1.28
* Verified that both services are working correctly on v1.28
* Upgraded again to v1.29, keeping the feature flag disabled
* Both loadbalancers worked as expected, the field is still present on
the changed service.


###### 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.
-->
No.

### 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.
-->
If the LB IP works correctly from pods, then the feature is working

###### 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
- [X] API .status
- Condition name:
- Other field:
- [ ] Other (treat as last resort)
- Details:
- Other field: `.status.loadBalancer.ingress.ipMode` not null
- [X] Other:
- Details: To detect if the traffic is being directed to the LoadBalancer and not
directly to another node, the user will need to rely on the LoadBalancer logs,
and the destination workload logs to check if the traffic is coming from one Pod
to the other or from the LoadBalancer.


###### 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.
-->
The quality of service for clouds using this feature is the same as the existing
quality of service for clouds that don't need this feature

###### 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:
N/A

###### 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.).
-->
* On kube-proxy, a metric containing the count of IP programming vs service type would be useful
to determine if the feature is being used, and if there is any drift between nodes

### 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:
-->
- cloud controller manager / LoadBalancer controller
- If there is an outage of the cloud controller manager, the result is the same
as if this feature wasn't in use; the LoadBalancers will get out of sync with Services
- kube-proxy or other Service Proxy that implements this feature
- If there is a service proxy outage, the result is the same as if this feature wasn't in use

### Scalability

Expand All @@ -336,79 +323,34 @@ 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.

###### 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)
-->
- API type: v1/Service
- Estimated increase size: new string field. Supported options at this time are max 6 characters (`Proxy`)
- Estimated amount of new objects: 0

###### 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.
No.

[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
-->
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?
-->
No

### Troubleshooting

Expand All @@ -425,19 +367,14 @@ details). For now, we leave it here.

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

Same for any loadbalancer/cloud controller manager, the new IP and the new status will not be
set.

kube-proxy reacts on the IP status, so the service LoadBalancer IP and configuration will be pending.

###### 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.
-->
N/A

###### What steps should be taken if SLOs are not being met to determine the problem?
N/A
4 changes: 2 additions & 2 deletions keps/sig-network/1860-kube-proxy-IP-node-binding/kep.yaml
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Expand Up @@ -14,9 +14,9 @@ approvers:
- "@thockin"
- "@andrewsykim"

stage: "alpha"
stage: "beta"

latest-milestone: "v1.29"
latest-milestone: "v1.30"

milestone:
alpha: "v1.29"
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