Fix replica calculation at start of HPA scaling policy period
When calculating the scale-up/scale-down limit, the number of replicas at the start of the scaling policy period is calculated correctly by taken into account the number of scaled-up and scaled-down replicas. Signed-off-by: Olivier Michaelis <38879457+oliviermichaelis@users.noreply.github.com>
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@ -929,7 +929,7 @@ func (a *HorizontalController) convertDesiredReplicasWithBehaviorRate(args Norma
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var possibleLimitingReason, possibleLimitingMessage string
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if args.DesiredReplicas > args.CurrentReplicas {
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scaleUpLimit := calculateScaleUpLimitWithScalingRules(args.CurrentReplicas, a.scaleUpEvents[args.Key], args.ScaleUpBehavior)
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scaleUpLimit := calculateScaleUpLimitWithScalingRules(args.CurrentReplicas, a.scaleUpEvents[args.Key], a.scaleDownEvents[args.Key], args.ScaleUpBehavior)
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if scaleUpLimit < args.CurrentReplicas {
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// We shouldn't scale up further until the scaleUpEvents will be cleaned up
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scaleUpLimit = args.CurrentReplicas
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@ -947,7 +947,7 @@ func (a *HorizontalController) convertDesiredReplicasWithBehaviorRate(args Norma
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return maximumAllowedReplicas, possibleLimitingReason, possibleLimitingMessage
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}
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} else if args.DesiredReplicas < args.CurrentReplicas {
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scaleDownLimit := calculateScaleDownLimitWithBehaviors(args.CurrentReplicas, a.scaleDownEvents[args.Key], args.ScaleDownBehavior)
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scaleDownLimit := calculateScaleDownLimitWithBehaviors(args.CurrentReplicas, a.scaleUpEvents[args.Key], a.scaleDownEvents[args.Key], args.ScaleDownBehavior)
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if scaleDownLimit > args.CurrentReplicas {
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// We shouldn't scale down further until the scaleDownEvents will be cleaned up
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scaleDownLimit = args.CurrentReplicas
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@ -1032,7 +1032,7 @@ func getLongestPolicyPeriod(scalingRules *autoscalingv2.HPAScalingRules) int32 {
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}
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// calculateScaleUpLimitWithScalingRules returns the maximum number of pods that could be added for the given HPAScalingRules
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func calculateScaleUpLimitWithScalingRules(currentReplicas int32, scaleEvents []timestampedScaleEvent, scalingRules *autoscalingv2.HPAScalingRules) int32 {
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func calculateScaleUpLimitWithScalingRules(currentReplicas int32, scaleUpEvents, scaleDownEvents []timestampedScaleEvent, scalingRules *autoscalingv2.HPAScalingRules) int32 {
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var result int32
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var proposed int32
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var selectPolicyFn func(int32, int32) int32
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@ -1046,8 +1046,9 @@ func calculateScaleUpLimitWithScalingRules(currentReplicas int32, scaleEvents []
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selectPolicyFn = max // Use the default policy otherwise to produce a highest possible change
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}
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for _, policy := range scalingRules.Policies {
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replicasAddedInCurrentPeriod := getReplicasChangePerPeriod(policy.PeriodSeconds, scaleEvents)
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periodStartReplicas := currentReplicas - replicasAddedInCurrentPeriod
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replicasAddedInCurrentPeriod := getReplicasChangePerPeriod(policy.PeriodSeconds, scaleUpEvents)
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replicasDeletedInCurrentPeriod := getReplicasChangePerPeriod(policy.PeriodSeconds, scaleDownEvents)
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periodStartReplicas := currentReplicas - replicasAddedInCurrentPeriod + replicasDeletedInCurrentPeriod
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if policy.Type == autoscalingv2.PodsScalingPolicy {
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proposed = periodStartReplicas + policy.Value
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} else if policy.Type == autoscalingv2.PercentScalingPolicy {
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@ -1060,7 +1061,7 @@ func calculateScaleUpLimitWithScalingRules(currentReplicas int32, scaleEvents []
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}
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// calculateScaleDownLimitWithBehavior returns the maximum number of pods that could be deleted for the given HPAScalingRules
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func calculateScaleDownLimitWithBehaviors(currentReplicas int32, scaleEvents []timestampedScaleEvent, scalingRules *autoscalingv2.HPAScalingRules) int32 {
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func calculateScaleDownLimitWithBehaviors(currentReplicas int32, scaleUpEvents, scaleDownEvents []timestampedScaleEvent, scalingRules *autoscalingv2.HPAScalingRules) int32 {
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var result int32
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var proposed int32
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var selectPolicyFn func(int32, int32) int32
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@ -1074,8 +1075,9 @@ func calculateScaleDownLimitWithBehaviors(currentReplicas int32, scaleEvents []t
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selectPolicyFn = min // Use the default policy otherwise to produce a highest possible change
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}
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for _, policy := range scalingRules.Policies {
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replicasDeletedInCurrentPeriod := getReplicasChangePerPeriod(policy.PeriodSeconds, scaleEvents)
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periodStartReplicas := currentReplicas + replicasDeletedInCurrentPeriod
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replicasAddedInCurrentPeriod := getReplicasChangePerPeriod(policy.PeriodSeconds, scaleUpEvents)
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replicasDeletedInCurrentPeriod := getReplicasChangePerPeriod(policy.PeriodSeconds, scaleDownEvents)
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periodStartReplicas := currentReplicas - replicasAddedInCurrentPeriod + replicasDeletedInCurrentPeriod
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if policy.Type == autoscalingv2.PodsScalingPolicy {
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proposed = periodStartReplicas - policy.Value
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} else if policy.Type == autoscalingv2.PercentScalingPolicy {
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@ -3029,7 +3029,7 @@ func TestConvertDesiredReplicasWithRules(t *testing.T) {
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func TestCalculateScaleUpLimitWithScalingRules(t *testing.T) {
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policy := autoscalingv2.MinChangePolicySelect
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calculated := calculateScaleUpLimitWithScalingRules(1, []timestampedScaleEvent{}, &autoscalingv2.HPAScalingRules{
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calculated := calculateScaleUpLimitWithScalingRules(1, []timestampedScaleEvent{}, []timestampedScaleEvent{}, &autoscalingv2.HPAScalingRules{
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StabilizationWindowSeconds: utilpointer.Int32Ptr(300),
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SelectPolicy: &policy,
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Policies: []autoscalingv2.HPAScalingPolicy{
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@ -3051,7 +3051,7 @@ func TestCalculateScaleUpLimitWithScalingRules(t *testing.T) {
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func TestCalculateScaleDownLimitWithBehaviors(t *testing.T) {
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policy := autoscalingv2.MinChangePolicySelect
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calculated := calculateScaleDownLimitWithBehaviors(5, []timestampedScaleEvent{}, &autoscalingv2.HPAScalingRules{
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calculated := calculateScaleDownLimitWithBehaviors(5, []timestampedScaleEvent{}, []timestampedScaleEvent{}, &autoscalingv2.HPAScalingRules{
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StabilizationWindowSeconds: utilpointer.Int32Ptr(300),
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SelectPolicy: &policy,
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Policies: []autoscalingv2.HPAScalingPolicy{
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@ -3480,6 +3480,18 @@ func TestScalingWithRules(t *testing.T) {
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expectedReplicas: 255, // (100 - 15) + 200%
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expectedCondition: "ScaleUpLimit",
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},
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{
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name: "scaleUp with percent policy and previous scale up and down events",
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scaleUpEvents: generateEventsUniformDistribution([]int{4}, 120),
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scaleDownEvents: generateEventsUniformDistribution([]int{2}, 120),
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specMinReplicas: 1,
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specMaxReplicas: 1000,
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scaleUpRules: generateScalingRules(0, 0, 300, 300, 0),
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currentReplicas: 6,
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prenormalizedDesiredReplicas: 24,
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expectedReplicas: 16,
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expectedCondition: "ScaleUpLimit",
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},
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// ScaleDown with PeriodSeconds usage
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{
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name: "scaleDown with default policy and previous events",
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@ -3546,6 +3558,18 @@ func TestScalingWithRules(t *testing.T) {
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expectedReplicas: 56, // (100 + 12) - 50%
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expectedCondition: "ScaleDownLimit",
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},
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{
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name: "scaleDown with percent policy and previous scale up and down events",
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scaleUpEvents: generateEventsUniformDistribution([]int{2}, 120),
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scaleDownEvents: generateEventsUniformDistribution([]int{4}, 120),
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specMinReplicas: 1,
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specMaxReplicas: 1000,
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scaleDownRules: generateScalingRules(0, 0, 50, 180, 0),
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currentReplicas: 10,
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prenormalizedDesiredReplicas: 1,
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expectedReplicas: 6,
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expectedCondition: "ScaleDownLimit",
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},
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{
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// corner case for calculating the scaleDownLimit, when we changed pod or percent policy after a lot of scaleDown events
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// in this case we shouldn't allow scale down, though, the naive formula will suggest that scaleDownlimit is more then CurrentReplicas (100+30-10% > 100)
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