The APIs talked about "stale services" and "stale endpoints", but the
thing that is actually "stale" is the conntrack entries, not the
services/endpoints. Fix the names to indicate what they actual keep
track of.
Also, all three fields (2 in the endpoints update object and 1 in the
service update object) are currently UDP-specific, but only the
service one made that clear. Fix that too.
In addition to actually updating their data from the provided list of
changes, EndpointsMap.Update() and ServicePortMap.Update() return a
struct with some information about things that changed because of that
update (eg services with stale conntrack entries).
For some reason, they were also returning information about
HealthCheckNodePorts, but they were returning *static* information
based on the current (post-Update) state of the map, not information
about what had *changed* in the update. Since this doesn't match how
the other data in the struct is used (and since there's no reason to
have the data only be returned when you call Update() anyway) , split
it out.
This is an ugly-but-simple rewrite (particularly involving having to
rewrite "single Endpoints with multiple Subsets" as "multiple
EndpointSlices"). Can be cleaned up more later...
The slice code sorts the results slightly differently from the old
code in two cases, and it was simpler to just reorder the expectations
rather than fixing the comparison code. But other than that, the
expected results are exactly the same as before.
This exposed a bug in the EndpointSlice tracking code, which is that
we didn't properly reset the "last change time" when a slice was
deleted. (This means kube-proxy would report an erroneous value in the
"endpoint programming time" metric if a service was added/updated,
then deleted before kube-proxy processed the add/update, then later
added again.)
TestEndpointsToEndpointsMap tested code that only ran when using
Endpoints tracking rather than EndpointSlice tracking--which is to
say, never, any more. (TestEndpointsMapFromESC in
endpointslicecache_test.go is an equivalent EndpointSlice test.)
iptables-restore requires that if you change any rule in a chain, you
have to rewrite the entire chain. But if you avoid mentioning a chain
at all, it will leave it untouched. Take advantage of this by not
rewriting the SVC, SVL, EXT, FW, and SEP chains for services that have
not changed since the last sync, which should drastically cut down on
the size of each iptables-restore in large clusters.
kube-proxy expose the metric network_programming_duration_seconds,
that is defined as the time it takes to program the network since
a a service or pod has changed. It uses an annotation on the endpoints
/endpointslices to calculate when the endpoint was created, however,
on restarts, kube-proxy process all the endpoints again, no matter
when those were generated, polluting the metrics.
To be safe, kube-proxy will estimate the latency only for those
endpoints that were generated after it started.
* api: structure change
* api: defaulting, conversion, and validation
* [FIX] validation: auto remove second ip/family when service changes to SingleStack
* [FIX] api: defaulting, conversion, and validation
* api-server: clusterIPs alloc, printers, storage and strategy
* [FIX] clusterIPs default on read
* alloc: auto remove second ip/family when service changes to SingleStack
* api-server: repair loop handling for clusterIPs
* api-server: force kubernetes default service into single stack
* api-server: tie dualstack feature flag with endpoint feature flag
* controller-manager: feature flag, endpoint, and endpointSlice controllers handling multi family service
* [FIX] controller-manager: feature flag, endpoint, and endpointSlicecontrollers handling multi family service
* kube-proxy: feature-flag, utils, proxier, and meta proxier
* [FIX] kubeproxy: call both proxier at the same time
* kubenet: remove forced pod IP sorting
* kubectl: modify describe to include ClusterIPs, IPFamilies, and IPFamilyPolicy
* e2e: fix tests that depends on IPFamily field AND add dual stack tests
* e2e: fix expected error message for ClusterIP immutability
* add integration tests for dualstack
the third phase of dual stack is a very complex change in the API,
basically it introduces Dual Stack services. Main changes are:
- It pluralizes the Service IPFamily field to IPFamilies,
and removes the singular field.
- It introduces a new field IPFamilyPolicyType that can take
3 values to express the "dual-stack(mad)ness" of the cluster:
SingleStack, PreferDualStack and RequireDualStack
- It pluralizes ClusterIP to ClusterIPs.
The goal is to add coverage to the services API operations,
taking into account the 6 different modes a cluster can have:
- single stack: IP4 or IPv6 (as of today)
- dual stack: IPv4 only, IPv6 only, IPv4 - IPv6, IPv6 - IPv4
* [FIX] add integration tests for dualstack
* generated data
* generated files
Co-authored-by: Antonio Ojea <aojea@redhat.com>
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.
