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Calculate more precise usage for replicas
This commit is contained in:
Pavel Beschetnov
parent
fc002b2f07
commit
456de495ef
@ -37,7 +37,16 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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podCPURequest := 500
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 110
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// usageForReplicas returns usage for (n - 0.5) replicas as if they would consume all CPU
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// under the target. The 0.5 replica reduction is to accommodate for the deviation between
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// the actual consumed cpu and requested usage by the ResourceConsumer.
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// HPA rounds up the recommendations. So, if the usage is e.g. for 3.5 replicas,
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// the recommended replica number will be 4.
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usageForReplicas := func(replicas int) int {
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usagePerReplica := podCPURequest * targetCPUUtilizationPercent / 100
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return replicas*usagePerReplica - usagePerReplica/2
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}
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fullWindowOfNewUsage := 30 * time.Second
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windowWithOldUsagePasses := 30 * time.Second
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@ -58,7 +67,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("should scale down soon after the stabilization period", func(ctx context.Context) {
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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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initCPUUsageTotal := usageForReplicas(initPods)
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upScaleStabilization := 0 * time.Minute
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downScaleStabilization := 1 * time.Minute
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@ -78,11 +87,11 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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// making sure HPA is ready, doing its job and already has a recommendation recorded
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// for stabilization logic before lowering the consumption
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ginkgo.By("triggering scale up to record a recommendation")
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rc.ConsumeCPU(3 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(3))
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rc.WaitForReplicas(ctx, 3, maxHPAReactionTime+maxResourceConsumerDelay+waitBuffer)
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ginkgo.By("triggering scale down by lowering consumption")
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rc.ConsumeCPU(2 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(2))
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waitStart := time.Now()
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rc.WaitForReplicas(ctx, 2, downScaleStabilization+maxHPAReactionTime+maxResourceConsumerDelay+waitBuffer)
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timeWaited := time.Now().Sub(waitStart)
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@ -99,7 +108,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("should scale up only after the stabilization period", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 2
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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upScaleStabilization := 3 * time.Minute
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downScaleStabilization := 0 * time.Minute
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@ -119,11 +128,11 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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// making sure HPA is ready, doing its job and already has a recommendation recorded
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// for stabilization logic before increasing the consumption
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ginkgo.By("triggering scale down to record a recommendation")
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rc.ConsumeCPU(1 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(1))
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rc.WaitForReplicas(ctx, 1, maxHPAReactionTime+maxResourceConsumerDelay+waitBuffer)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(3 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(3))
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waitStart := time.Now()
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rc.WaitForReplicas(ctx, 3, upScaleStabilization+maxHPAReactionTime+maxResourceConsumerDelay+waitBuffer)
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timeWaited := time.Now().Sub(waitStart)
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@ -140,7 +149,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("shouldn't scale up", func(ctx context.Context) {
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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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initCPUUsageTotal := usageForReplicas(initPods)
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rc := e2eautoscaling.NewDynamicResourceConsumer(ctx,
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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@ -157,7 +166,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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waitDeadline := maxHPAReactionTime + maxResourceConsumerDelay + waitBuffer
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ginkgo.By("trying to trigger scale up")
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rc.ConsumeCPU(8 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(8))
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waitStart := time.Now()
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rc.EnsureDesiredReplicasInRange(ctx, initPods, initPods, waitDeadline, hpa.Name)
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@ -175,7 +184,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("shouldn't scale down", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 3
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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rc := e2eautoscaling.NewDynamicResourceConsumer(ctx,
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hpaName, f.Namespace.Name, e2eautoscaling.KindDeployment, initPods,
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@ -193,7 +202,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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waitDeadline := maxHPAReactionTime + maxResourceConsumerDelay + defaultDownscaleStabilisation
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ginkgo.By("trying to trigger scale down")
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rc.ConsumeCPU(1 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(1))
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waitStart := time.Now()
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rc.EnsureDesiredReplicasInRange(ctx, initPods, initPods, waitDeadline, hpa.Name)
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@ -211,14 +220,10 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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})
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ginkgo.Describe("with scale limited by number of Pods rate", func() {
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podCPURequest := 200
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 45
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ginkgo.It("should scale up no more than given number of Pods per minute", func(ctx context.Context) {
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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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initCPUUsageTotal := usageForReplicas(initPods)
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limitWindowLength := 1 * time.Minute
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podsLimitPerMinute := 1
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@ -236,7 +241,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.DeferCleanup(e2eautoscaling.DeleteHPAWithBehavior, rc, hpa.Name)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(3 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(3))
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waitStart := time.Now()
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rc.WaitForReplicas(ctx, 2, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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@ -260,7 +265,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("should scale down no more than given number of Pods per minute", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 3
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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limitWindowLength := 1 * time.Minute
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podsLimitPerMinute := 1
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@ -278,7 +283,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.DeferCleanup(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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rc.ConsumeCPU(usageForReplicas(1))
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waitStart := time.Now()
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rc.WaitForReplicas(ctx, 2, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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@ -301,14 +306,10 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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})
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ginkgo.Describe("with scale limited by percentage", func() {
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podCPURequest := 200
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targetCPUUtilizationPercent := 25
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usageForSingleReplica := 45
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ginkgo.It("should scale up no more than given percentage of current Pods per minute", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 2
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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limitWindowLength := 1 * time.Minute
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percentageLimitPerMinute := 50
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@ -326,7 +327,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.DeferCleanup(e2eautoscaling.DeleteHPAWithBehavior, rc, hpa.Name)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(8 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(8))
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waitStart := time.Now()
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rc.WaitForReplicas(ctx, 3, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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@ -351,7 +352,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("should scale down no more than given percentage of current Pods per minute", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 7
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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limitWindowLength := 1 * time.Minute
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percentageLimitPerMinute := 25
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@ -369,7 +370,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.DeferCleanup(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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rc.ConsumeCPU(usageForReplicas(1))
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waitStart := time.Now()
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rc.WaitForReplicas(ctx, 5, maxHPAReactionTime+maxResourceConsumerDelay+limitWindowLength)
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@ -398,7 +399,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("should keep recommendation within the range over two stabilization windows", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 2
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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upScaleStabilization := 3 * time.Minute
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downScaleStabilization := 3 * time.Minute
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@ -416,7 +417,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.DeferCleanup(e2eautoscaling.DeleteHPAWithBehavior, rc, hpa.Name)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(4 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(4))
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waitDeadline := upScaleStabilization
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ginkgo.By("verifying number of replicas stay in desired range within stabilisation window")
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@ -431,7 +432,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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gomega.Expect(timeWaited).To(gomega.BeNumerically("<", waitDeadline), "waited %s, wanted less than %s", timeWaited, waitDeadline)
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ginkgo.By("triggering scale down by lowering consumption")
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rc.ConsumeCPU(2 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(2))
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waitDeadline = downScaleStabilization
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ginkgo.By("verifying number of replicas stay in desired range within stabilisation window")
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@ -449,7 +450,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.It("should keep recommendation within the range with stabilization window and pod limit rate", func(ctx context.Context) {
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ginkgo.By("setting up resource consumer and HPA")
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initPods := 2
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initCPUUsageTotal := initPods * usageForSingleReplica
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initCPUUsageTotal := usageForReplicas(initPods)
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downScaleStabilization := 3 * time.Minute
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limitWindowLength := 2 * time.Minute
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podsLimitPerMinute := 1
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@ -470,7 +471,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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ginkgo.DeferCleanup(e2eautoscaling.DeleteHPAWithBehavior, rc, hpa.Name)
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ginkgo.By("triggering scale up by increasing consumption")
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rc.ConsumeCPU(4 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(4))
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waitDeadline := limitWindowLength
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ginkgo.By("verifying number of replicas stay in desired range with pod limit rate")
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@ -485,7 +486,7 @@ var _ = SIGDescribe("[Feature:HPA] [Serial] [Slow] Horizontal pod autoscaling (n
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gomega.Default.Expect(timeWaited).To(gomega.BeNumerically("<", waitDeadline), "waited %s, wanted less than %s", timeWaited, waitDeadline)
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ginkgo.By("triggering scale down by lowering consumption")
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rc.ConsumeCPU(2 * usageForSingleReplica)
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rc.ConsumeCPU(usageForReplicas(2))
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ginkgo.By("verifying number of replicas stay in desired range within stabilisation window")
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waitDeadline = downScaleStabilization
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