This includes IPv4 and IPv6 address types and IPVS dual stack support.
Importantly this ensures that EndpointSlices with a FQDN address type
are not processed by kube-proxy.
Computing EndpointChanges is a relatively expensive operation for
kube-proxy when Endpoint Slices are used. This had been computed on
every EndpointSlice update which became quite inefficient at high levels
of scale when multiple EndpointSlice update events would be triggered
before a syncProxyRules call.
Profiling results showed that computing this on each update could
consume ~80% of total kube-proxy CPU utilization at high levels of
scale. This change reduced that to as little as 3% of total kube-proxy
utilization at high levels of scale.
It's worth noting that the difference is minimal when there is a 1:1
relationship between EndpointSlice updates and proxier syncs. This is
primarily beneficial when there are many EndpointSlice updates between
proxier sync loops.
The detectStaleConnections function in kube-proxy is very expensive in
terms of CPU utilization. The results of this function are only actually
used for UDP ports. This adds a protocol attribute to ServicePortName to
make it simple to only run this function for UDP connections. For
clusters with primarily TCP connections this can improve kube-proxy
performance by 2x.
