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Make HPA tolerance a flag

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Fix #18155

Make HPA tolerance configurable as a flag. This change allows us to use
different tolerance values in production/testing.

Signed-off-by: mattjmcnaughton <mattjmcnaughton@gmail.com>
This commit is contained in:
mattjmcnaughton
2017-09-11 09:59:53 -04:00
parent ca712680c7
commit abd46684d4
10 changed files with 37 additions and 19 deletions
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4
pkg/controller/podautoscaler/horizontal.go
View File

@@ -49,10 +49,6 @@ import (
)
var (
// Usage shoud exceed the tolerance before we start downscale or upscale the pods.
// TODO: make it a flag or HPA spec element.
tolerance = 0.1
scaleUpLimitFactor = 2.0
scaleUpLimitMinimum = 4.0
)

5
pkg/controller/podautoscaler/horizontal_test.go
View File

@@ -579,6 +579,7 @@ func (tc *testCase) setupController(t *testing.T) (*HorizontalController, inform
replicaCalc := &ReplicaCalculator{
metricsClient: metricsClient,
podsGetter: testClient.Core(),
tolerance: defaultTestingTolerance,
}
informerFactory := informers.NewSharedInformerFactory(testClient, controller.NoResyncPeriodFunc())
@@ -1525,7 +1526,7 @@ func TestComputedToleranceAlgImplementation(t *testing.T) {
perPodRequested := totalRequestedCPUOfAllPods / startPods
// Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio).
target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01
target := math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .01
finalCPUPercentTarget := int32(target * 100)
resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target)
@@ -1570,7 +1571,7 @@ func TestComputedToleranceAlgImplementation(t *testing.T) {
// Reuse the data structure above, now testing "unscaling".
// Now, we test that no scaling happens if we are in a very close margin to the tolerance
target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004
target = math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .004
finalCPUPercentTarget = int32(target * 100)
tc.CPUTarget = finalCPUPercentTarget
tc.initialReplicas = startPods

5
pkg/controller/podautoscaler/legacy_horizontal_test.go
View File

@@ -484,6 +484,7 @@ func (tc *legacyTestCase) runTest(t *testing.T) {
replicaCalc := &ReplicaCalculator{
metricsClient: metricsClient,
podsGetter: testClient.Core(),
tolerance: defaultTestingTolerance,
}
informerFactory := informers.NewSharedInformerFactory(testClient, controller.NoResyncPeriodFunc())
@@ -965,7 +966,7 @@ func LegacyTestComputedToleranceAlgImplementation(t *testing.T) {
perPodRequested := totalRequestedCPUOfAllPods / startPods
// Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio).
target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01
target := math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .01
finalCPUPercentTarget := int32(target * 100)
resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target)
@@ -1010,7 +1011,7 @@ func LegacyTestComputedToleranceAlgImplementation(t *testing.T) {
// Reuse the data structure above, now testing "unscaling".
// Now, we test that no scaling happens if we are in a very close margin to the tolerance
target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004
target = math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .004
finalCPUPercentTarget = int32(target * 100)
tc.CPUTarget = finalCPUPercentTarget
tc.initialReplicas = startPods

5
pkg/controller/podautoscaler/legacy_replica_calculator_test.go
View File

@@ -188,6 +188,7 @@ func (tc *legacyReplicaCalcTestCase) runTest(t *testing.T) {
replicaCalc := &ReplicaCalculator{
metricsClient: metricsClient,
podsGetter: testClient.Core(),
tolerance: defaultTestingTolerance,
}
selector, err := metav1.LabelSelectorAsSelector(&metav1.LabelSelector{
@@ -603,7 +604,7 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
perPodRequested := totalRequestedCPUOfAllPods / startPods
// Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio).
target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01
target := math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .01
finalCPUPercentTarget := int32(target * 100)
resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target)
@@ -651,7 +652,7 @@ func LegacyTestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
// Reuse the data structure above, now testing "unscaling".
// Now, we test that no scaling happens if we are in a very close margin to the tolerance
target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004
target = math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .004
finalCPUPercentTarget = int32(target * 100)
tc.resource.targetUtilization = finalCPUPercentTarget
tc.currentReplicas = startPods

20
pkg/controller/podautoscaler/replica_calculator.go
View File

@@ -31,15 +31,23 @@ import (
metricsclient "k8s.io/kubernetes/pkg/controller/podautoscaler/metrics"
)
const (
// defaultTestingTolerance is default value for calculating when to
// scale up/scale down.
defaultTestingTolerance = 0.1
)
type ReplicaCalculator struct {
metricsClient metricsclient.MetricsClient
podsGetter v1coreclient.PodsGetter
tolerance float64
}
func NewReplicaCalculator(metricsClient metricsclient.MetricsClient, podsGetter v1coreclient.PodsGetter) *ReplicaCalculator {
func NewReplicaCalculator(metricsClient metricsclient.MetricsClient, podsGetter v1coreclient.PodsGetter, tolerance float64) *ReplicaCalculator {
return &ReplicaCalculator{
metricsClient: metricsClient,
podsGetter: podsGetter,
tolerance: tolerance,
}
}
@@ -105,7 +113,7 @@ func (c *ReplicaCalculator) GetResourceReplicas(currentReplicas int32, targetUti
rebalanceUnready := len(unreadyPods) > 0 && usageRatio > 1.0
if !rebalanceUnready && len(missingPods) == 0 {
if math.Abs(1.0-usageRatio) <= tolerance {
if math.Abs(1.0-usageRatio) <= c.tolerance {
// return the current replicas if the change would be too small
return currentReplicas, utilization, rawUtilization, timestamp, nil
}
@@ -141,7 +149,7 @@ func (c *ReplicaCalculator) GetResourceReplicas(currentReplicas int32, targetUti
return 0, utilization, rawUtilization, time.Time{}, err
}
if math.Abs(1.0-newUsageRatio) <= tolerance || (usageRatio < 1.0 && newUsageRatio > 1.0) || (usageRatio > 1.0 && newUsageRatio < 1.0) {
if math.Abs(1.0-newUsageRatio) <= c.tolerance || (usageRatio < 1.0 && newUsageRatio > 1.0) || (usageRatio > 1.0 && newUsageRatio < 1.0) {
// return the current replicas if the change would be too small,
// or if the new usage ratio would cause a change in scale direction
return currentReplicas, utilization, rawUtilization, timestamp, nil
@@ -218,7 +226,7 @@ func (c *ReplicaCalculator) calcPlainMetricReplicas(metrics metricsclient.PodMet
rebalanceUnready := len(unreadyPods) > 0 && usageRatio > 1.0
if !rebalanceUnready && len(missingPods) == 0 {
if math.Abs(1.0-usageRatio) <= tolerance {
if math.Abs(1.0-usageRatio) <= c.tolerance {
// return the current replicas if the change would be too small
return currentReplicas, utilization, nil
}
@@ -251,7 +259,7 @@ func (c *ReplicaCalculator) calcPlainMetricReplicas(metrics metricsclient.PodMet
// re-run the utilization calculation with our new numbers
newUsageRatio, _ := metricsclient.GetMetricUtilizationRatio(metrics, targetUtilization)
if math.Abs(1.0-newUsageRatio) <= tolerance || (usageRatio < 1.0 && newUsageRatio > 1.0) || (usageRatio > 1.0 && newUsageRatio < 1.0) {
if math.Abs(1.0-newUsageRatio) <= c.tolerance || (usageRatio < 1.0 && newUsageRatio > 1.0) || (usageRatio > 1.0 && newUsageRatio < 1.0) {
// return the current replicas if the change would be too small,
// or if the new usage ratio would cause a change in scale direction
return currentReplicas, utilization, nil
@@ -271,7 +279,7 @@ func (c *ReplicaCalculator) GetObjectMetricReplicas(currentReplicas int32, targe
}
usageRatio := float64(utilization) / float64(targetUtilization)
if math.Abs(1.0-usageRatio) <= tolerance {
if math.Abs(1.0-usageRatio) <= c.tolerance {
// return the current replicas if the change would be too small
return currentReplicas, utilization, timestamp, nil
}

5
pkg/controller/podautoscaler/replica_calculator_test.go
View File

@@ -247,6 +247,7 @@ func (tc *replicaCalcTestCase) runTest(t *testing.T) {
replicaCalc := &ReplicaCalculator{
metricsClient: metricsClient,
podsGetter: testClient.Core(),
tolerance: defaultTestingTolerance,
}
selector, err := metav1.LabelSelectorAsSelector(&metav1.LabelSelector{
@@ -727,7 +728,7 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
perPodRequested := totalRequestedCPUOfAllPods / startPods
// Force a minimal scaling event by satisfying (tolerance < 1 - resourcesUsedRatio).
target := math.Abs(1/(requestedToUsed*(1-tolerance))) + .01
target := math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .01
finalCPUPercentTarget := int32(target * 100)
resourcesUsedRatio := float64(totalUsedCPUOfAllPods) / float64(float64(totalRequestedCPUOfAllPods)*target)
@@ -775,7 +776,7 @@ func TestReplicaCalcComputedToleranceAlgImplementation(t *testing.T) {
// Reuse the data structure above, now testing "unscaling".
// Now, we test that no scaling happens if we are in a very close margin to the tolerance
target = math.Abs(1/(requestedToUsed*(1-tolerance))) + .004
target = math.Abs(1/(requestedToUsed*(1-defaultTestingTolerance))) + .004
finalCPUPercentTarget = int32(target * 100)
tc.resource.targetUtilization = finalCPUPercentTarget
tc.currentReplicas = startPods