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Merge pull request #111346 from piotrnosek/hpa-tests-2
Add e2e HPA Behavior tests: scale up/down limited by number of Pods / min, scale up/down limited by percentage / min
This commit is contained in:
Kubernetes Prow Robot
GitHub
commit
f0bd02ca5e
@ -30,6 +30,12 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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f := framework.NewDefaultFramework("horizontal-pod-autoscaling")
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f.NamespacePodSecurityEnforceLevel = admissionapi.LevelPrivileged
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hpaName := "consumer"
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podCPURequest := 500
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 110
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fullWindowOfNewUsage := 30 * time.Second
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windowWithOldUsagePasses := 30 * time.Second
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newPodMetricsDelay := 15 * time.Second
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@ -48,16 +54,13 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.Describe("with short downscale stabilization window", func() {
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ginkgo.It("should scale down soon after the stabilization period", func() {
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ginkgo.By("setting up resource consumer and HPA")
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podCPURequest := 500
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 110
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initPods := 1
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initCPUUsageTotal := initPods * usageForSingleReplica
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upScaleStabilization := 0 * time.Minute
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downScaleStabilization := 1 * time.Minute
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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"consumer", f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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@ -92,16 +95,13 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.Describe("with long upscale stabilization window", func() {
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ginkgo.It("should scale up only after the stabilization period", func() {
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ginkgo.By("setting up resource consumer and HPA")
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podCPURequest := 500
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 110
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initPods := 2
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initCPUUsageTotal := initPods * usageForSingleReplica
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upScaleStabilization := 3 * time.Minute
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downScaleStabilization := 0 * time.Minute
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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"consumer", f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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@ -133,24 +133,21 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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})
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})
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ginkgo.Describe("with upscale autoscaling disabled", func() {
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ginkgo.Describe("with autoscaling disabled", func() {
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ginkgo.It("shouldn't scale up", func() {
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ginkgo.By("setting up resource consumer and HPA")
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podCPURequest := 500
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 110
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initPods := 1
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initCPUUsageTotal := initPods * usageForSingleReplica
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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"consumer", f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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defer rc.CleanUp()
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hpa := e2eautoscaling.CreateCPUHorizontalPodAutoscalerWithBehavior(
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rc, int32(targetCPUUtilizationPercent), 1, 10, e2eautoscaling.HPABehaviorWithScaleUpDisabled(),
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rc, int32(targetCPUUtilizationPercent), 1, 10, e2eautoscaling.HPABehaviorWithScaleDisabled(e2eautoscaling.ScaleUpDirection),
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)
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defer e2eautoscaling.DeleteHPAWithBehavior(rc, hpa.Name)
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@ -171,26 +168,21 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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replicas := rc.GetReplicas()
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framework.ExpectEqual(replicas == initPods, true, "had %s replicas, still have %s replicas after time deadline", initPods, replicas)
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})
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})
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ginkgo.Describe("with downscale autoscaling disabled", func() {
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ginkgo.It("shouldn't scale down", func() {
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ginkgo.By("setting up resource consumer and HPA")
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podCPURequest := 500
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 110
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initPods := 3
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initCPUUsageTotal := initPods * usageForSingleReplica
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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"consumer", f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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defer rc.CleanUp()
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hpa := e2eautoscaling.CreateCPUHorizontalPodAutoscalerWithBehavior(
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rc, int32(targetCPUUtilizationPercent), 1, 10, e2eautoscaling.HPABehaviorWithScaleDownDisabled(),
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rc, int32(targetCPUUtilizationPercent), 1, 10, e2eautoscaling.HPABehaviorWithScaleDisabled(e2eautoscaling.ScaleDownDirection),
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)
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defer e2eautoscaling.DeleteHPAWithBehavior(rc, hpa.Name)
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@ -212,6 +204,178 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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replicas := rc.GetReplicas()
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framework.ExpectEqual(replicas == initPods, true, "had %s replicas, still have %s replicas after time deadline", initPods, replicas)
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})
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})
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ginkgo.Describe("with scale limited by number of Pods rate", func() {
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ginkgo.It("should scale up no more than given number of Pods per minute", func() {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 1
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initCPUUsageTotal := initPods * usageForSingleReplica
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limitWindowLength := 1 * time.Minute
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podsLimitPerMinute := 2
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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defer rc.CleanUp()
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hpa := e2eautoscaling.CreateCPUHorizontalPodAutoscalerWithBehavior(
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rc, int32(targetCPUUtilizationPercent), 1, 10,
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e2eautoscaling.HPABehaviorWithScaleLimitedByNumberOfPods(e2eautoscaling.ScaleUpDirection, int32(podsLimitPerMinute), int32(limitWindowLength.Seconds())),
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)
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defer e2eautoscaling.DeleteHPAWithBehavior(rc, hpa.Name)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(5 * usageForSingleReplica)
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waitStart := time.Now()
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rc.WaitForReplicas(3, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor3 := time.Now().Sub(waitStart)
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waitStart = time.Now()
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rc.WaitForReplicas(5, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor5 := time.Now().Sub(waitStart)
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ginkgo.By("verifying time waited for a scale up to 3 replicas")
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deadline := limitWindowLength + maxHPAReactionTime + maxResourceConsumerDelay
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// First scale event can happen right away, as there were no scale events in the past.
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framework.ExpectEqual(timeWaitedFor3 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor3, deadline)
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ginkgo.By("verifying time waited for a scale up to 5 replicas")
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// Second scale event needs to respect limit window.
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framework.ExpectEqual(timeWaitedFor5 > limitWindowLength, true, "waited %s, wanted to wait more than %s", timeWaitedFor5, limitWindowLength)
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framework.ExpectEqual(timeWaitedFor5 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor5, deadline)
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})
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ginkgo.It("should scale down no more than given number of Pods per minute", func() {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 6
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initCPUUsageTotal := initPods * usageForSingleReplica
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limitWindowLength := 1 * time.Minute
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podsLimitPerMinute := 2
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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defer rc.CleanUp()
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hpa := e2eautoscaling.CreateCPUHorizontalPodAutoscalerWithBehavior(
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rc, int32(targetCPUUtilizationPercent), 1, 10,
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e2eautoscaling.HPABehaviorWithScaleLimitedByNumberOfPods(e2eautoscaling.ScaleDownDirection, int32(podsLimitPerMinute), int32(limitWindowLength.Seconds())),
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)
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defer e2eautoscaling.DeleteHPAWithBehavior(rc, hpa.Name)
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ginkgo.By("triggering scale down by lowering consumption")
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rc.ConsumeCPU(1 * usageForSingleReplica)
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waitStart := time.Now()
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rc.WaitForReplicas(4, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor4 := time.Now().Sub(waitStart)
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waitStart = time.Now()
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rc.WaitForReplicas(2, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor2 := time.Now().Sub(waitStart)
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ginkgo.By("verifying time waited for a scale down to 4 replicas")
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deadline := limitWindowLength + maxHPAReactionTime + maxResourceConsumerDelay
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// First scale event can happen right away, as there were no scale events in the past.
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framework.ExpectEqual(timeWaitedFor4 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor4, deadline)
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ginkgo.By("verifying time waited for a scale down to 2 replicas")
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// Second scale event needs to respect limit window.
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framework.ExpectEqual(timeWaitedFor2 > limitWindowLength, true, "waited %s, wanted more than %s", timeWaitedFor2, limitWindowLength)
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framework.ExpectEqual(timeWaitedFor2 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor2, deadline)
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})
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})
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ginkgo.Describe("with scale limited by percentage", func() {
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ginkgo.It("should scale up no more than given percentage of current Pods per minute", func() {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 4
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initCPUUsageTotal := initPods * usageForSingleReplica
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limitWindowLength := 1 * time.Minute
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percentageLimitPerMinute := 50
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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defer rc.CleanUp()
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hpa := e2eautoscaling.CreateCPUHorizontalPodAutoscalerWithBehavior(
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rc, int32(targetCPUUtilizationPercent), 1, 10,
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e2eautoscaling.HPABehaviorWithScaleLimitedByPercentage(e2eautoscaling.ScaleUpDirection, int32(percentageLimitPerMinute), int32(limitWindowLength.Seconds())),
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)
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defer e2eautoscaling.DeleteHPAWithBehavior(rc, hpa.Name)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(10 * usageForSingleReplica)
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waitStart := time.Now()
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rc.WaitForReplicas(6, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor6 := time.Now().Sub(waitStart)
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waitStart = time.Now()
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rc.WaitForReplicas(9, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor9 := time.Now().Sub(waitStart)
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ginkgo.By("verifying time waited for a scale up to 6 replicas")
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deadline := limitWindowLength + maxHPAReactionTime + maxResourceConsumerDelay
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// First scale event can happen right away, as there were no scale events in the past.
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framework.ExpectEqual(timeWaitedFor6 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor6, deadline)
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ginkgo.By("verifying time waited for a scale up to 9 replicas")
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// Second scale event needs to respect limit window.
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framework.ExpectEqual(timeWaitedFor9 > limitWindowLength, true, "waited %s, wanted to wait more than %s", timeWaitedFor9, limitWindowLength)
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framework.ExpectEqual(timeWaitedFor9 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor9, deadline)
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})
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ginkgo.It("should scale down no more than given percentage of current Pods per minute", func() {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 8
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initCPUUsageTotal := initPods * usageForSingleReplica
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limitWindowLength := 1 * time.Minute
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percentageLimitPerMinute := 50
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rc := e2eautoscaling.NewDynamicResourceConsumer(
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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initCPUUsageTotal, 0, 0, int64(podCPURequest), 200,
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f.ClientSet, f.ScalesGetter, e2eautoscaling.Disable, e2eautoscaling.Idle,
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)
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defer rc.CleanUp()
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hpa := e2eautoscaling.CreateCPUHorizontalPodAutoscalerWithBehavior(
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rc, int32(targetCPUUtilizationPercent), 1, 10,
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e2eautoscaling.HPABehaviorWithScaleLimitedByPercentage(e2eautoscaling.ScaleDownDirection, int32(percentageLimitPerMinute), int32(limitWindowLength.Seconds())),
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)
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defer e2eautoscaling.DeleteHPAWithBehavior(rc, hpa.Name)
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ginkgo.By("triggering scale down by lowering consumption")
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rc.ConsumeCPU(1 * usageForSingleReplica)
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waitStart := time.Now()
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rc.WaitForReplicas(4, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor4 := time.Now().Sub(waitStart)
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waitStart = time.Now()
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rc.WaitForReplicas(2, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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timeWaitedFor2 := time.Now().Sub(waitStart)
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ginkgo.By("verifying time waited for a scale down to 4 replicas")
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deadline := limitWindowLength + maxHPAReactionTime + maxResourceConsumerDelay
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// First scale event can happen right away, as there were no scale events in the past.
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framework.ExpectEqual(timeWaitedFor4 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor4, deadline)
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ginkgo.By("verifying time waited for a scale down to 2 replicas")
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// Second scale event needs to respect limit window.
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framework.ExpectEqual(timeWaitedFor2 > limitWindowLength, true, "waited %s, wanted more than %s", timeWaitedFor2, limitWindowLength)
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framework.ExpectEqual(timeWaitedFor2 < deadline, true, "waited %s, wanted less than %s", timeWaitedFor2, deadline)
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})
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})
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})
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@ -78,6 +78,15 @@ var (
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KindReplicaSet = schema.GroupVersionKind{Group: "apps", Version: "v1beta2", Kind: "ReplicaSet"}
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)
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// ScalingDirection identifies the scale direction for HPA Behavior.
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type ScalingDirection int
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const (
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DirectionUnknown ScalingDirection = iota
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ScaleUpDirection
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ScaleDownDirection
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)
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/*
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ResourceConsumer is a tool for testing. It helps create specified usage of CPU or memory (Warning: memory not supported)
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typical use case:
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@ -725,38 +734,65 @@ func HPABehaviorWithScaleUpAndDownRules(scaleUpRule, scaleDownRule *autoscalingv
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}
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}
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func HPAStabilizationWindowScalingRule(stabilizationDuration int32) *autoscalingv2.HPAScalingRules {
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func HPABehaviorWithScalingRuleInDirection(scalingDirection ScalingDirection, rule *autoscalingv2.HPAScalingRules) *autoscalingv2.HorizontalPodAutoscalerBehavior {
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var scaleUpRule, scaleDownRule *autoscalingv2.HPAScalingRules
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if scalingDirection == ScaleUpDirection {
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scaleUpRule = rule
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}
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if scalingDirection == ScaleDownDirection {
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scaleDownRule = rule
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}
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return HPABehaviorWithScaleUpAndDownRules(scaleUpRule, scaleDownRule)
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}
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func HPAScalingRuleWithStabilizationWindow(stabilizationDuration int32) *autoscalingv2.HPAScalingRules {
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return &autoscalingv2.HPAScalingRules{
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StabilizationWindowSeconds: &stabilizationDuration,
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}
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}
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func HPAPolicyDisabledScalingRule() *autoscalingv2.HPAScalingRules {
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func HPAScalingRuleWithPolicyDisabled() *autoscalingv2.HPAScalingRules {
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disabledPolicy := autoscalingv2.DisabledPolicySelect
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return &autoscalingv2.HPAScalingRules{
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SelectPolicy: &disabledPolicy,
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}
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}
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func HPAScalingRuleWithScalingPolicy(policyType autoscalingv2.HPAScalingPolicyType, value, periodSeconds int32) *autoscalingv2.HPAScalingRules {
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stabilizationWindowDisabledDuration := int32(0)
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selectPolicy := autoscalingv2.MaxChangePolicySelect
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return &autoscalingv2.HPAScalingRules{
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Policies: []autoscalingv2.HPAScalingPolicy{
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{
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Type: policyType,
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Value: value,
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PeriodSeconds: periodSeconds,
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},
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},
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SelectPolicy: &selectPolicy,
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StabilizationWindowSeconds: &stabilizationWindowDisabledDuration,
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}
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}
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func HPABehaviorWithStabilizationWindows(upscaleStabilization, downscaleStabilization time.Duration) *autoscalingv2.HorizontalPodAutoscalerBehavior {
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return HPABehaviorWithScaleUpAndDownRules(
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/*scaleUpRule=*/ HPAStabilizationWindowScalingRule(int32(upscaleStabilization.Seconds())),
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/*scaleDownRule=*/ HPAStabilizationWindowScalingRule(int32(downscaleStabilization.Seconds())),
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)
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scaleUpRule := HPAScalingRuleWithStabilizationWindow(int32(upscaleStabilization.Seconds()))
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scaleDownRule := HPAScalingRuleWithStabilizationWindow(int32(downscaleStabilization.Seconds()))
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return HPABehaviorWithScaleUpAndDownRules(scaleUpRule, scaleDownRule)
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}
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func HPABehaviorWithScaleUpDisabled() *autoscalingv2.HorizontalPodAutoscalerBehavior {
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return HPABehaviorWithScaleUpAndDownRules(
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/*scaleUpRule=*/ HPAPolicyDisabledScalingRule(),
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/*scaleDownRule=*/ nil,
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)
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func HPABehaviorWithScaleDisabled(scalingDirection ScalingDirection) *autoscalingv2.HorizontalPodAutoscalerBehavior {
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scalingRule := HPAScalingRuleWithPolicyDisabled()
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return HPABehaviorWithScalingRuleInDirection(scalingDirection, scalingRule)
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}
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|
||||
func HPABehaviorWithScaleDownDisabled() *autoscalingv2.HorizontalPodAutoscalerBehavior {
|
||||
return HPABehaviorWithScaleUpAndDownRules(
|
||||
/*scaleUpRule=*/ nil,
|
||||
/*scaleDownRule=*/ HPAPolicyDisabledScalingRule(),
|
||||
)
|
||||
func HPABehaviorWithScaleLimitedByNumberOfPods(scalingDirection ScalingDirection, numberOfPods, periodSeconds int32) *autoscalingv2.HorizontalPodAutoscalerBehavior {
|
||||
scalingRule := HPAScalingRuleWithScalingPolicy(autoscalingv2.PodsScalingPolicy, numberOfPods, periodSeconds)
|
||||
return HPABehaviorWithScalingRuleInDirection(scalingDirection, scalingRule)
|
||||
}
|
||||
|
||||
func HPABehaviorWithScaleLimitedByPercentage(scalingDirection ScalingDirection, percentage, periodSeconds int32) *autoscalingv2.HorizontalPodAutoscalerBehavior {
|
||||
scalingRule := HPAScalingRuleWithScalingPolicy(autoscalingv2.PercentScalingPolicy, percentage, periodSeconds)
|
||||
return HPABehaviorWithScalingRuleInDirection(scalingDirection, scalingRule)
|
||||
}
|
||||
|
||||
func DeleteHPAWithBehavior(rc *ResourceConsumer, autoscalerName string) {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user