Change:
apierrors "k8s.io/apimachinery/pkg/api/errors" metav1 "k8s.io/apimachinery/pkg/apis/meta/v1" "k8s.io/apimachinery/pkg/util/intstr" <ins> "k8s.io/apimachinery/pkg/util/sets" </ins> "k8s.io/apimachinery/pkg/util/wait" clientset "k8s.io/client-go/kubernetes" "k8s.io/kubernetes/test/e2e/framework"

Discussion:
Which jobs are flaking: ci-kubernetes-kind-e2e-parallel pr:pull-kubernetes-e2e-gce pr:pull-kubernetes-e2e-gce-ubuntu-containerd pr:pull-kubernetes-e2e-gce-ubuntu-containerd ci-kubernetes-kind-ipv6-e2e-parallel Which test(s) are flaking: Second flakiest test in the e2e job according to Testgrid link: Reason for failure: Anything else we need to know: /sig network /assign
needs investigation since we're switching kube-proxy to endpointslice in this release
/triage unresolved Comment when the issue is assessed and confirmed. I am a bot run by vllry. ‍
made me think of , but that's in already.
It's possible it's a test timeout that's just too close, but we need verification of that checking the controller and apiserver logs to make sure there isn't a latent bug
Thanks for catching this! It looks like the timeouts are actually associated with waiting for 2 pods to be ready, not actually anything related to EndpointSlice functionality - timeout is here: Given that, it seems like the obvious solution would be to update the Services to set to and update this block to wait for the Pods to have IPs, not for them to be ready. If that sounds reasonable, I'll work on getting a fix in tomorrow.
/remove-triage unresolved
If that is still exercises the same conditions (I vaguely remember publishNotReadyAddresses changing code paths in the endpoints controller... does it do the same in the endpointslice controller?), that seems reasonable to me.
I think the code path is very similar here, the only real difference should be how the EndpointSlice controller calculates readiness. I've gone ahead and filed a PR that uses this approach, hopefully it helps:
This flaked again this morning /reopen
Reopened this issue. <detailsIn response to : This flaked again this morning Instructions for interacting with me using PR comments are available . If you have questions or suggestions related to my behavior, please file an issue against the repository. </details
This should be /priority critical-urgent given
The top level error message does not make this clear but the issue here is that too many EndpointSlices are being created - 3 instead of 2.
Interesting... that condition should not persist for O(minutes), right?

that seems like it might be a bug, not just a test issue
There's potential that it's not consistently merging 2 ports with 1 endpoint into a single slice and instead creating a slice per port. It also could represent a larger bug. Trying to find a way to consistently reproduce this.
Despite my best efforts I have been unable to reproduce this on my own e2e cluster. I've had 10 test runs going at the same time repeatedly without any luck, any ideas for how to reproduce flaky test failures local would be welcome. In the meantime, I've created a follow up PR that will provide more helpful information if/when this test fails again: My leading theory right now is that this could be a caching issue. The EndpointSlice controller runs a sync, sees that we don't have an EndpointSlice for the given port combination in cache and then goes ahead and creates one, even though a matching EndpointSlice already exists and has not been cached yet. That would result in an annoying situation where an essentially duplicate EndpointSlice was created due to a stale cache. I would think the EndpointSliceTracker would resolve this issue for us though, so not sure. Getting the above PR in will help validate this theory. It's worth noting that if this is actually a duplicate EndpointSlice, clients like kube-proxy will handle this seamlessly because they already have to handle potential duplication in EndpointSlices. That would potentially explain why a test failure like this does not seem to be causing other things to break.
It appears that my theory was correct as witnessed here: I create a .

The key points I've noticed so far: 1 EndpointSlice references pod2 (example-named-port-f7vq5) 2 EndpointSlices reference pod1 (example-named-port-fkgcc and example-named-port-vfp2q) 2 EndpointSlices were created at "2020-07-28T04:57:51Z": example-named-port-f7vq5 (references pod2) example-named-port-vfp2q (references pod1) 1 EndpointSlice was created 1 second later ("2020-07-28T04:57:52Z") example-named-port-fkgcc (references pod1) All 3 EndpointSlices are: On generation 1 - no updates have occurred With a state of ready: true The 2 EndpointSlices referencing pod1 are effectively identical  Of course this is something the EndpointSliceTracker should be handling for us, but even that approach seems less than ideal here. It wouldn't actually prevent the duplicate EndpointSlices from being created, it should just be cleaning up duplicates after they happen. This combined with the race conditions referenced in make me think we may want to find a way to slow down the sync cycle for each Service here. This also feels at least tangentially related to the need for better rate limiting in both this and the Endpoints controller discussed in . /cc
Hmm - actually I don't understand why this is happening. Maybe I'm missing something, but I don't think slowing down controller is needed to solve this problem. Even though the controller usually is not lagging my more than 1s, it is possible that it can be lagging by a minute or more in pathological cases. So we can't just rely on the fact that it's guaranteed to be synced. Can you explain it a bit deeper why this is happening? i.e. some more detailed timeline like: T1: state of cache is XYZ T2: controller computes the ES x1, x2 T3: state of cache in ABC T4: controller computes ES y1 [why?]
Agree, I'm not in favor of slowing down the controller globally to address this. Delaying resync of a particular service until we observe the existence of new endpointslices we know we created (with some max delay) could be reasonable.

That's exactly where I was hoping to end up here, although I'm not quite sure how to do that cleanly yet. To be clear, this is not just to fix this flaky test. This flaky test is a symptom of a much larger and more annoying issue with the current implementation. The EndpointSlice controller is consistently running into errors where it's trying to update EndpointSlices that are stale. This is caused by follow up calls to running before the informer cache is up to date, which happens all the time during rolling updates where rapid churn of EndpointSlices is expected. Although this eventually resolves itself, it's causing a lot more load on API Server than necessary and can potentially result in some bad states where an update fails but a delete succeeds. In this specific instance, it looks like a syncService run is occurring after the first 2 EndpointSlices have been created but before the one referencing pod1 is in the informer cache. That results in the controller creating a new EndpointSlice to reference pod1 and thus we end up with a duplicate. If anything in the future triggers another syncService call that would be resolved. I'd initially thought that EndpointSliceTracker would be thing to trigger that follow up syncService, but I was wrong. That tracker just tracks the latest resource version for each EndpointSlice the controller has created/updated and compares that with EndpointSlices received through create/update events. If the controller doesn't think that EndpointSlice should exist or the controller's resource version for that slice does not match it triggers another syncService. In this case neither of those conditions would be met so no additional syncService call would be triggered. So that's a long way of saying that I think our best possible solution here is to introduce some delay between when Services can be synced. I think the easiest solution that would solve 99% of our problems would be to add something like a 1s delay in between syncs simply by delaying when was called. This would not be ideal, but it would result in an immediate improvement and be easy to backport. It's worth noting that although duplicate EndpointSlices like this or even attempts to update a stale EndpointSlice are not ideal, they are not actually invalid and will eventually resolve themselves. Consumers of this API already have to do some form of deduping.

With that said, I'm hopeful that there's a clean way to implement a solution that actually waited for each EndpointSlice change the controller has made to be reflected in the cache because that would be a better solution. I'll spend some time looking into possible implementations here.
I've created a draft PR that contains my initial progress towards the approach I described above. I don't particularly love this approach so I'm very open to other ways we could solve this issue. It's also still very much a WIP and has significant work remaining. I opened the PR early just so I could get some initial feedback on the direction and potentially inspire other ideas around approaches we could take here.
is still the best approach I can come up with here. It is ready for review if anyone has time to take a look.
Quick update here, I've limited the scope here to the following changes as discussed in Update the flaky test to consider duplicate EndpointSlices valid. Update the docs to make it very clear that consumers of the EndpointSlice API will have to do deduplication (as kube-proxy already does). Update the controller error handling to return immediately if a create, update, or delete errors (in that order). Reviews would be appreciated on all of the above.
Reopening since is not yet merged.
Thanks for catching that Closing now that is merged. /close
Closing this issue. <detailsIn response to : Thanks for catching that Closing now that is merged. Instructions for interacting with me using PR comments are available . If you have questions or suggestions related to my behavior, please file an issue against the repository. </details