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Move new etcd storage (low level storage) into cacher
In an effort for #29888, we are pushing forward this:
What?
- It changes creating etcd storage.Interface impl into creating config
- In creating cacher storage (StorageWithCacher), it passes config created above and new etcd storage inside.
Why?
- We want to expose the information of (etcd) kv client to cacher. Cacher storage uses this information to talk to remote storage.
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Endpoint controller logs errors during normal cluster behavior
The endpoint controller logs an error when its forbidden from creating new endpoints during namespace termination. This is normal cluster behavior, and therefore should not be logged. This confuses operators administrating the cluster.
Updated to log at a lower level in response to a forbidden message when performing a create operation. In case of an error on the API server side of the house, I continue to requeue the key. It should be ignored in a future syncService call once the service is deleted as part of namespace termination.
See https://bugzilla.redhat.com/show_bug.cgi?id=1347425
/cc @kubernetes/rh-cluster-infra
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Name jobs created by sj deterministically
```release-note
Name the job created by scheduledjob (sj) deterministically with sj's name and a hash of job's scheduled time.
```
@erictune @soltysh
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the observed usage should match those that have hard constraints
in the sync process, the quota will be replenished, the new observed usage will be sumed from each evaluator, if the previousUsed set is not be cleared, the new usage will be dirty, maybe some unusage resource still in , as the code below
newUsage = quota.Mask(newUsage, matchedResources)
for key, value := range newUsage {
usage.Status.Used[key] = value
}
so i think here shoul not set value previousUsed
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[GarbageCollector] measure latency
First commit is #27600.
In e2e tests, I measure the average time an item spend in the eventQueue(~1.5 ms), dirtyQueue(~13ms), and orphanQueue(~37ms). There is no stress test in e2e yet, so the number may not be useful.
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add metrics for workqueues
Adds prometheus metrics to work queues and enables them for the resourcequota controller. It would be easy to add this to all other workqueue based controllers and gather basic responsiveness metrics.
@kubernetes/rh-cluster-infra helps debug quota controller responsiveness problems.
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pkg/controller/garbagecollector: simplify mutexes.
pkg/controller/garbagecollector: simplified synchronization and made idiomatic.
Similar to #29598, we can rely on the zero-value construction behavior
to embed `sync.Mutex` into parent structs.
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HPA: ignore scale targets whose replica count is 0
Disable HPA when the user (or another component) explicitly sets the replicas to 0.
Fixes#28603
@kubernetes/autoscaling @fgrzadkowski @kubernetes/rh-cluster-infra @smarterclayton @ncdc
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Also, fix unit tests to have the same claim and volume sizes in most of the
tests where we don't test matching based on size and test for a specific size
when we do actually test the matching.
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Run goimport for the whole repo
While removing GOMAXPROC and running goimports, I noticed quite a lot of other files also needed a goimport format. Didn't commit `*.generated.go`, `*.deepcopy.go` or files in `vendor`
This is more for testing if it builds.
The only strange thing here is the gopkg.in/gcfg.v1 => github.com/scalingdata/gcfg replace.
cc @jfrazelle @thockin
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optimize conditions of ServiceReplenishmentUpdateFunc to replenish service
Originally, the replenishQuota method didn't focus on the third parameter object even if others transfered to it, i think the function is not efficient and perfect. then i use the third param to get MatchResources, it will be more exact. for example, if the old pod was quota tracked and the new was not, the replenishQuota only focus on usage resource of the old pod, still if the third parameter object is nil, the process will be same as before
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refactor quota calculation for re-use
Refactors quota calculation to allow reuse. This will allow us to do "punch through" calculation inside of admission if a particular quota needs usage stats and allows downstream re-use by moving calculation closer to the evaluators and separating "needs calculation" logic from "do calculation".
@derekwaynecarr
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Rewrite service controller to apply best controller pattern
This PR is a long term solution for #21625:
We apply the same pattern like replication controller to service controller to avoid the potential process order messes in service controller, the change includes:
1. introduce informer controller to watch service changes from kube-apiserver, so that every changes on same service will be kept in serviceStore as the only element.
2. put the service name to be processed to working queue
3. when process service, always get info from serviceStore to ensure the info is up-to-date
4. keep the retry mechanism, sleep for certain interval and add it back to queue.
5. remote the logic of reading last service info from kube-apiserver before processing the LB info as we trust the info from serviceStore.
The UT has been passed, manual test passed after I hardcode the cloud provider as FakeCloud, however I am not able to boot a k8s cluster with any available cloudprovider, so e2e test is not done.
Submit this PR first for review and for triggering a e2e test.
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Fix deployment e2e test: waitDeploymentStatus should error when entering an invalid state
Follow up #28162
1. We should check that max unavailable and max surge aren't violated at all times in e2e tests (didn't check this in deployment scaled rollout yet, but we should wait for it to become valid and then continue do the check until it finishes)
2. Fix some minor bugs in e2e tests
@kubernetes/deployment
