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Copy file name to clipboardExpand all lines: test/e2e_node/density_test.go
+2-2Lines changed: 2 additions & 2 deletions
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@@ -168,7 +168,7 @@ var _ = SIGDescribe("Density", framework.WithSerial(), framework.WithSlow(), fun
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for_, testArg:=rangedTests {
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itArg:=testArg
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desc:=fmt.Sprintf("latency/resource should be within limit when create %d pods with %v interval [Benchmark][NodeSpecialFeature:Benchmark]", itArg.podsNr, itArg.interval)
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desc:=fmt.Sprintf("latency/resource should be within limit when create %d pods with %v interval [Benchmark]", itArg.podsNr, itArg.interval)
@@ -206,7 +206,7 @@ var _ = SIGDescribe("Density", framework.WithSerial(), framework.WithSlow(), fun
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for_, testArg:=rangedTests {
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itArg:=testArg
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ginkgo.Context("", func() {
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desc:=fmt.Sprintf("latency/resource should be within limit when create %d pods with %v interval (QPS %d) [Benchmark][NodeSpecialFeature:Benchmark]", itArg.podsNr, itArg.interval, itArg.APIQPSLimit)
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desc:=fmt.Sprintf("latency/resource should be within limit when create %d pods with %v interval (QPS %d) [Benchmark]", itArg.podsNr, itArg.interval, itArg.APIQPSLimit)
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// The latency caused by API QPS limit takes a large portion (up to ~33%) of e2e latency.
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// It makes the pod startup latency of Kubelet (creation throughput as well) under-estimated.
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// Here we set API QPS limit from default 5 to 60 in order to test real Kubelet performance.
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