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The following metrics can be used to see if the introduction of this change resulted in a significantly
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large number of traffic to the apiserver.
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###### Were upgrade and rollback tested? Was the upgrade->downgrade->upgrade path tested?
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@@ -228,21 +248,29 @@ on how the new conditions are being used.
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###### What are the SLIs (Service Level Indicators) an operator can use to determine the health of the service?
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Metrics will be added for total endpoints with the `serving` and `terminating` condition set.
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The existing SLI can be used to determine the health of this feature:
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```
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Latency of programming in-cluster load balancing mechanism (e.g. iptables), measured from when service spec or list of its Ready pods change to when it is reflected in load balancing mechanism, measured as 99th percentile over last 5 minutes aggregated across all programmers
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```
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###### What are the reasonable SLOs (Service Level Objectives) for the above SLIs?
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N/A
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It's hard to gauge an exact number here, because the existing SLI does not have a target SLO yet.
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However, we should assume that the addition of the `serving` and `terminating` conditions do not
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significantly impact the latency of kube-proxy syncing load balancer rules.
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###### Are there any missing metrics that would be useful to have to improve observability of this feature?
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N/A
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Adapting the existing endpoint slice controller metrics to also include endpoint conditions
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as a label could be useful since a user can distinguish if the endpoint churn is happening due
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to the addition of terminating endpoints or for another reason.
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### Dependencies
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###### Does this feature depend on any specific services running in the cluster?
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N/A
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None aside from the existing core Kubernetes components, specifically kube-apiserver and kube-controller-manager.
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