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Merge pull request #74526 from DXist/feature/hpa-scale-to-zero

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Support scaling HPA to/from zero pods for object/external metrics
This commit is contained in:
Kubernetes Prow Robot 2019-07-16 10:11:24 -07:00 committed by GitHub
commit 5ece88c4c8
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19 changed files with 656 additions and 160 deletions
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6
api/openapi-spec/swagger.json generated
View File

@ -4548,7 +4548,7 @@
"type": "integer"
},
"minReplicas": {
"description": "lower limit for the number of pods that can be set by the autoscaler, default 1.",
"description": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
"format": "int32",
"type": "integer"
},
@ -4851,7 +4851,7 @@
"type": "array"
},
"minReplicas": {
"description": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod.",
"description": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
"format": "int32",
"type": "integer"
},
@ -5291,7 +5291,7 @@
"type": "array"
},
"minReplicas": {
"description": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod.",
"description": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
"format": "int32",
"type": "integer"
},

7
pkg/apis/autoscaling/types.go
View File

@ -76,8 +76,11 @@ type HorizontalPodAutoscalerSpec struct {
// ScaleTargetRef points to the target resource to scale, and is used to the pods for which metrics
// should be collected, as well as to actually change the replica count.
ScaleTargetRef CrossVersionObjectReference
// MinReplicas is the lower limit for the number of replicas to which the autoscaler can scale down.
// It defaults to 1 pod.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
MinReplicas *int32
// MaxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up.

5
pkg/apis/autoscaling/validation/BUILD
View File

@ -13,10 +13,12 @@ go_library(
deps = [
"//pkg/apis/autoscaling:go_default_library",
"//pkg/apis/core/validation:go_default_library",
"//pkg/features:go_default_library",
"//staging/src/k8s.io/apimachinery/pkg/api/validation:go_default_library",
"//staging/src/k8s.io/apimachinery/pkg/api/validation/path:go_default_library",
"//staging/src/k8s.io/apimachinery/pkg/util/sets:go_default_library",
"//staging/src/k8s.io/apimachinery/pkg/util/validation/field:go_default_library",
"//staging/src/k8s.io/apiserver/pkg/util/feature:go_default_library",
],
)
@ -27,8 +29,11 @@ go_test(
deps = [
"//pkg/apis/autoscaling:go_default_library",
"//pkg/apis/core:go_default_library",
"//pkg/features:go_default_library",
"//staging/src/k8s.io/apimachinery/pkg/api/resource:go_default_library",
"//staging/src/k8s.io/apimachinery/pkg/apis/meta/v1:go_default_library",
"//staging/src/k8s.io/apiserver/pkg/util/feature:go_default_library",
"//staging/src/k8s.io/component-base/featuregate/testing:go_default_library",
"//vendor/k8s.io/utils/pointer:go_default_library",
],
)

54
pkg/apis/autoscaling/validation/validation.go
View File

@ -17,14 +17,17 @@ limitations under the License.
package validation
import (
"fmt"
"strings"
apimachineryvalidation "k8s.io/apimachinery/pkg/api/validation"
pathvalidation "k8s.io/apimachinery/pkg/api/validation/path"
"k8s.io/apimachinery/pkg/util/sets"
"k8s.io/apimachinery/pkg/util/validation/field"
utilfeature "k8s.io/apiserver/pkg/util/feature"
"k8s.io/kubernetes/pkg/apis/autoscaling"
apivalidation "k8s.io/kubernetes/pkg/apis/core/validation"
"k8s.io/kubernetes/pkg/features"
)
func ValidateScale(scale *autoscaling.Scale) field.ErrorList {
@ -42,10 +45,12 @@ func ValidateScale(scale *autoscaling.Scale) field.ErrorList {
// Prefix indicates this name will be used as part of generation, in which case trailing dashes are allowed.
var ValidateHorizontalPodAutoscalerName = apivalidation.ValidateReplicationControllerName
func validateHorizontalPodAutoscalerSpec(autoscaler autoscaling.HorizontalPodAutoscalerSpec, fldPath *field.Path) field.ErrorList {
func validateHorizontalPodAutoscalerSpec(autoscaler autoscaling.HorizontalPodAutoscalerSpec, fldPath *field.Path, minReplicasLowerBound int32) field.ErrorList {
allErrs := field.ErrorList{}
if autoscaler.MinReplicas != nil && *autoscaler.MinReplicas < 1 {
allErrs = append(allErrs, field.Invalid(fldPath.Child("minReplicas"), *autoscaler.MinReplicas, "must be greater than 0"))
if autoscaler.MinReplicas != nil && *autoscaler.MinReplicas < minReplicasLowerBound {
allErrs = append(allErrs, field.Invalid(fldPath.Child("minReplicas"), *autoscaler.MinReplicas,
fmt.Sprintf("must be greater than or equal to %d", minReplicasLowerBound)))
}
if autoscaler.MaxReplicas < 1 {
allErrs = append(allErrs, field.Invalid(fldPath.Child("maxReplicas"), autoscaler.MaxReplicas, "must be greater than 0"))
@ -56,7 +61,7 @@ func validateHorizontalPodAutoscalerSpec(autoscaler autoscaling.HorizontalPodAut
if refErrs := ValidateCrossVersionObjectReference(autoscaler.ScaleTargetRef, fldPath.Child("scaleTargetRef")); len(refErrs) > 0 {
allErrs = append(allErrs, refErrs...)
}
if refErrs := validateMetrics(autoscaler.Metrics, fldPath.Child("metrics")); len(refErrs) > 0 {
if refErrs := validateMetrics(autoscaler.Metrics, fldPath.Child("metrics"), autoscaler.MinReplicas); len(refErrs) > 0 {
allErrs = append(allErrs, refErrs...)
}
return allErrs
@ -85,13 +90,34 @@ func ValidateCrossVersionObjectReference(ref autoscaling.CrossVersionObjectRefer
func ValidateHorizontalPodAutoscaler(autoscaler *autoscaling.HorizontalPodAutoscaler) field.ErrorList {
allErrs := apivalidation.ValidateObjectMeta(&autoscaler.ObjectMeta, true, ValidateHorizontalPodAutoscalerName, field.NewPath("metadata"))
allErrs = append(allErrs, validateHorizontalPodAutoscalerSpec(autoscaler.Spec, field.NewPath("spec"))...)
// MinReplicasLowerBound represents a minimum value for minReplicas
// 0 when HPA scale-to-zero feature is enabled
var minReplicasLowerBound int32
if utilfeature.DefaultFeatureGate.Enabled(features.HPAScaleToZero) {
minReplicasLowerBound = 0
} else {
minReplicasLowerBound = 1
}
allErrs = append(allErrs, validateHorizontalPodAutoscalerSpec(autoscaler.Spec, field.NewPath("spec"), minReplicasLowerBound)...)
return allErrs
}
func ValidateHorizontalPodAutoscalerUpdate(newAutoscaler, oldAutoscaler *autoscaling.HorizontalPodAutoscaler) field.ErrorList {
allErrs := apivalidation.ValidateObjectMetaUpdate(&newAutoscaler.ObjectMeta, &oldAutoscaler.ObjectMeta, field.NewPath("metadata"))
allErrs = append(allErrs, validateHorizontalPodAutoscalerSpec(newAutoscaler.Spec, field.NewPath("spec"))...)
// minReplicasLowerBound represents a minimum value for minReplicas
// 0 when HPA scale-to-zero feature is enabled or HPA object already has minReplicas=0
var minReplicasLowerBound int32
if utilfeature.DefaultFeatureGate.Enabled(features.HPAScaleToZero) || (oldAutoscaler.Spec.MinReplicas != nil && *oldAutoscaler.Spec.MinReplicas == 0) {
minReplicasLowerBound = 0
} else {
minReplicasLowerBound = 1
}
allErrs = append(allErrs, validateHorizontalPodAutoscalerSpec(newAutoscaler.Spec, field.NewPath("spec"), minReplicasLowerBound)...)
return allErrs
}
@ -103,14 +129,28 @@ func ValidateHorizontalPodAutoscalerStatusUpdate(newAutoscaler, oldAutoscaler *a
return allErrs
}
func validateMetrics(metrics []autoscaling.MetricSpec, fldPath *field.Path) field.ErrorList {
func validateMetrics(metrics []autoscaling.MetricSpec, fldPath *field.Path, minReplicas *int32) field.ErrorList {
allErrs := field.ErrorList{}
hasObjectMetrics := false
hasExternalMetrics := false
for i, metricSpec := range metrics {
idxPath := fldPath.Index(i)
if targetErrs := validateMetricSpec(metricSpec, idxPath); len(targetErrs) > 0 {
allErrs = append(allErrs, targetErrs...)
}
if metricSpec.Type == autoscaling.ObjectMetricSourceType {
hasObjectMetrics = true
}
if metricSpec.Type == autoscaling.ExternalMetricSourceType {
hasExternalMetrics = true
}
}
if minReplicas != nil && *minReplicas == 0 {
if !hasObjectMetrics && !hasExternalMetrics {
allErrs = append(allErrs, field.Forbidden(fldPath, "must specify at least one Object or External metric to support scaling to zero replicas"))
}
}
return allErrs

165
pkg/apis/autoscaling/validation/validation_test.go
View File

@ -22,8 +22,11 @@ import (
"k8s.io/apimachinery/pkg/api/resource"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
utilfeature "k8s.io/apiserver/pkg/util/feature"
featuregatetesting "k8s.io/component-base/featuregate/testing"
"k8s.io/kubernetes/pkg/apis/autoscaling"
api "k8s.io/kubernetes/pkg/apis/core"
"k8s.io/kubernetes/pkg/features"
utilpointer "k8s.io/utils/pointer"
)
@ -96,6 +99,7 @@ func TestValidateHorizontalPodAutoscaler(t *testing.T) {
if err != nil {
t.Errorf("unable to parse label selector: %v", err)
}
successCases := []autoscaling.HorizontalPodAutoscaler{
{
ObjectMeta: metav1.ObjectMeta{
@ -396,7 +400,7 @@ func TestValidateHorizontalPodAutoscaler(t *testing.T) {
MaxReplicas: 5,
},
},
msg: "must be greater than 0",
msg: "must be greater than or equal to 1",
},
{
horizontalPodAutoscaler: autoscaling.HorizontalPodAutoscaler{
@ -1002,3 +1006,162 @@ func TestValidateHorizontalPodAutoscaler(t *testing.T) {
}
}
}
func prepareMinReplicasCases(t *testing.T, minReplicas int32) []autoscaling.HorizontalPodAutoscaler {
metricLabelSelector, err := metav1.ParseToLabelSelector("label=value")
if err != nil {
t.Errorf("unable to parse label selector: %v", err)
}
minReplicasCases := []autoscaling.HorizontalPodAutoscaler{
{
ObjectMeta: metav1.ObjectMeta{
Name: "myautoscaler",
Namespace: metav1.NamespaceDefault,
ResourceVersion: "theversion",
},
Spec: autoscaling.HorizontalPodAutoscalerSpec{
ScaleTargetRef: autoscaling.CrossVersionObjectReference{
Kind: "ReplicationController",
Name: "myrc",
},
MinReplicas: utilpointer.Int32Ptr(minReplicas),
MaxReplicas: 5,
Metrics: []autoscaling.MetricSpec{
{
Type: autoscaling.ObjectMetricSourceType,
Object: &autoscaling.ObjectMetricSource{
DescribedObject: autoscaling.CrossVersionObjectReference{
Kind: "ReplicationController",
Name: "myrc",
},
Metric: autoscaling.MetricIdentifier{
Name: "somemetric",
},
Target: autoscaling.MetricTarget{
Type: autoscaling.ValueMetricType,
Value: resource.NewMilliQuantity(300, resource.DecimalSI),
},
},
},
},
},
},
{
ObjectMeta: metav1.ObjectMeta{
Name: "myautoscaler",
Namespace: metav1.NamespaceDefault,
ResourceVersion: "theversion",
},
Spec: autoscaling.HorizontalPodAutoscalerSpec{
ScaleTargetRef: autoscaling.CrossVersionObjectReference{
Kind: "ReplicationController",
Name: "myrc",
},
MinReplicas: utilpointer.Int32Ptr(minReplicas),
MaxReplicas: 5,
Metrics: []autoscaling.MetricSpec{
{
Type: autoscaling.ExternalMetricSourceType,
External: &autoscaling.ExternalMetricSource{
Metric: autoscaling.MetricIdentifier{
Name: "somemetric",
Selector: metricLabelSelector,
},
Target: autoscaling.MetricTarget{
Type: autoscaling.AverageValueMetricType,
AverageValue: resource.NewMilliQuantity(300, resource.DecimalSI),
},
},
},
},
},
},
}
return minReplicasCases
}
func TestValidateHorizontalPodAutoscalerScaleToZeroEnabled(t *testing.T) {
// Enable HPAScaleToZero feature gate.
defer featuregatetesting.SetFeatureGateDuringTest(t, utilfeature.DefaultFeatureGate, features.HPAScaleToZero, true)()
zeroMinReplicasCases := prepareMinReplicasCases(t, 0)
for _, successCase := range zeroMinReplicasCases {
if errs := ValidateHorizontalPodAutoscaler(&successCase); len(errs) != 0 {
t.Errorf("expected success: %v", errs)
}
}
}
func TestValidateHorizontalPodAutoscalerScaleToZeroDisabled(t *testing.T) {
// Disable HPAScaleToZero feature gate.
defer featuregatetesting.SetFeatureGateDuringTest(t, utilfeature.DefaultFeatureGate, features.HPAScaleToZero, false)()
zeroMinReplicasCases := prepareMinReplicasCases(t, 0)
errorMsg := "must be greater than or equal to 1"
for _, errorCase := range zeroMinReplicasCases {
errs := ValidateHorizontalPodAutoscaler(&errorCase)
if len(errs) == 0 {
t.Errorf("expected failure for %q", errorMsg)
} else if !strings.Contains(errs[0].Error(), errorMsg) {
t.Errorf("unexpected error: %q, expected: %q", errs[0], errorMsg)
}
}
nonZeroMinReplicasCases := prepareMinReplicasCases(t, 1)
for _, successCase := range nonZeroMinReplicasCases {
successCase.Spec.MinReplicas = utilpointer.Int32Ptr(1)
if errs := ValidateHorizontalPodAutoscaler(&successCase); len(errs) != 0 {
t.Errorf("expected success: %v", errs)
}
}
}
func TestValidateHorizontalPodAutoscalerUpdateScaleToZeroEnabled(t *testing.T) {
// Enable HPAScaleToZero feature gate.
defer featuregatetesting.SetFeatureGateDuringTest(t, utilfeature.DefaultFeatureGate, features.HPAScaleToZero, true)()
zeroMinReplicasCases := prepareMinReplicasCases(t, 0)
nonZeroMinReplicasCases := prepareMinReplicasCases(t, 1)
for i, zeroCase := range zeroMinReplicasCases {
nonZeroCase := nonZeroMinReplicasCases[i]
if errs := ValidateHorizontalPodAutoscalerUpdate(&nonZeroCase, &zeroCase); len(errs) != 0 {
t.Errorf("expected success: %v", errs)
}
if errs := ValidateHorizontalPodAutoscalerUpdate(&zeroCase, &nonZeroCase); len(errs) != 0 {
t.Errorf("expected success: %v", errs)
}
}
}
func TestValidateHorizontalPodAutoscalerScaleToZeroUpdateDisabled(t *testing.T) {
// Disable HPAScaleToZero feature gate.
defer featuregatetesting.SetFeatureGateDuringTest(t, utilfeature.DefaultFeatureGate, features.HPAScaleToZero, false)()
zeroMinReplicasCases := prepareMinReplicasCases(t, 0)
nonZeroMinReplicasCases := prepareMinReplicasCases(t, 1)
errorMsg := "must be greater than or equal to 1"
for i, zeroCase := range zeroMinReplicasCases {
nonZeroCase := nonZeroMinReplicasCases[i]
errs := ValidateHorizontalPodAutoscalerUpdate(&zeroCase, &nonZeroCase)
if len(errs) == 0 {
t.Errorf("expected failure for %q", errorMsg)
} else if !strings.Contains(errs[0].Error(), errorMsg) {
t.Errorf("unexpected error: %q, expected: %q", errs[0], errorMsg)
}
if errs := ValidateHorizontalPodAutoscalerUpdate(&zeroCase, &zeroCase); len(errs) != 0 {
t.Errorf("expected success: %v", errs)
}
if errs := ValidateHorizontalPodAutoscalerUpdate(&nonZeroCase, &zeroCase); len(errs) != 0 {
t.Errorf("expected success: %v", errs)
}
}
}

196
pkg/controller/podautoscaler/horizontal.go
View File

@ -230,16 +230,11 @@ func (a *HorizontalController) processNextWorkItem() bool {
}
// computeReplicasForMetrics computes the desired number of replicas for the metric specifications listed in the HPA,
// returning the maximum of the computed replica counts, a description of the associated metric, and the statuses of
// returning the maximum of the computed replica counts, a description of the associated metric, and the statuses of
// all metrics computed.
func (a *HorizontalController) computeReplicasForMetrics(hpa *autoscalingv2.HorizontalPodAutoscaler, scale *autoscalingv1.Scale,
metricSpecs []autoscalingv2.MetricSpec) (replicas int32, metric string, statuses []autoscalingv2.MetricStatus, timestamp time.Time, err error) {
specReplicas := scale.Spec.Replicas
statusReplicas := scale.Status.Replicas
statuses = make([]autoscalingv2.MetricStatus, len(metricSpecs))
if scale.Status.Selector == "" {
errMsg := "selector is required"
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "SelectorRequired", errMsg)
@ -255,15 +250,23 @@ func (a *HorizontalController) computeReplicasForMetrics(hpa *autoscalingv2.Hori
return 0, "", nil, time.Time{}, fmt.Errorf(errMsg)
}
specReplicas := scale.Spec.Replicas
statusReplicas := scale.Status.Replicas
statuses = make([]autoscalingv2.MetricStatus, len(metricSpecs))
invalidMetricsCount := 0
var invalidMetricError error
var invalidMetricCondition autoscalingv2.HorizontalPodAutoscalerCondition
for i, metricSpec := range metricSpecs {
replicaCountProposal, metricNameProposal, timestampProposal, err := a.computeReplicasForMetric(hpa, metricSpec, specReplicas, statusReplicas, selector, &statuses[i])
replicaCountProposal, metricNameProposal, timestampProposal, condition, err := a.computeReplicasForMetric(hpa, metricSpec, specReplicas, statusReplicas, selector, &statuses[i])
if err != nil {
if invalidMetricsCount <= 0 {
invalidMetricCondition = condition
invalidMetricError = err
}
invalidMetricsCount++
invalidMetricError = err
}
if err == nil && (replicas == 0 || replicaCountProposal > replicas) {
timestamp = timestampProposal
@ -272,62 +275,59 @@ func (a *HorizontalController) computeReplicasForMetrics(hpa *autoscalingv2.Hori
}
}
// If all metrics are invalid or some are invalid and we would scale down,
// return an error and set the condition of the hpa based on the first invalid metric.
// Otherwise set the condition as scaling active as we're going to scale
if invalidMetricsCount >= len(metricSpecs) || (invalidMetricsCount > 0 && replicas < specReplicas) {
return 0, "", statuses, time.Time{}, fmt.Errorf("Invalid metrics (%v invalid out of %v), last error was: %v", invalidMetricsCount, len(metricSpecs), invalidMetricError)
} else {
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionTrue, "ValidMetricFound", "the HPA was able to successfully calculate a replica count from %v", metric)
// If all metrics are invalid return error and set condition on hpa based on first invalid metric.
if invalidMetricsCount >= len(metricSpecs) {
setCondition(hpa, invalidMetricCondition.Type, invalidMetricCondition.Status, invalidMetricCondition.Reason, invalidMetricCondition.Message)
return 0, "", statuses, time.Time{}, fmt.Errorf("Invalid metrics (%v invalid out of %v), first error is: %v", invalidMetricsCount, len(metricSpecs), invalidMetricError)
}
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionTrue, "ValidMetricFound", "the HPA was able to successfully calculate a replica count from %s", metric)
return replicas, metric, statuses, timestamp, nil
}
// computeReplicasForMetric computes the desired number of replicas for for a specific hpa and single metric specification.
// Computes the desired number of replicas for for a specific hpa and metric specification,
// returning the metric status and a proposed condition to be set on the HPA object.
func (a *HorizontalController) computeReplicasForMetric(hpa *autoscalingv2.HorizontalPodAutoscaler, spec autoscalingv2.MetricSpec,
specReplicas, statusReplicas int32, selector labels.Selector, status *autoscalingv2.MetricStatus) (replicaCountProposal int32, metricNameProposal string,
timestampProposal time.Time, err error) {
timestampProposal time.Time, condition autoscalingv2.HorizontalPodAutoscalerCondition, err error) {
switch spec.Type {
case autoscalingv2.ObjectMetricSourceType:
metricSelector, err := metav1.LabelSelectorAsSelector(spec.Object.Metric.Selector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetObjectMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetObjectMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, "", time.Time{}, fmt.Errorf("failed to get object metric value: %v", err)
condition := a.getUnableComputeReplicaCountCondition(hpa, "FailedGetObjectMetric", err)
return 0, "", time.Time{}, condition, fmt.Errorf("failed to get object metric value: %v", err)
}
replicaCountProposal, timestampProposal, metricNameProposal, err = a.computeStatusForObjectMetric(specReplicas, statusReplicas, spec, hpa, selector, status, metricSelector)
replicaCountProposal, timestampProposal, metricNameProposal, condition, err = a.computeStatusForObjectMetric(specReplicas, statusReplicas, spec, hpa, selector, status, metricSelector)
if err != nil {
return 0, "", time.Time{}, fmt.Errorf("failed to get object metric value: %v", err)
return 0, "", time.Time{}, condition, fmt.Errorf("failed to get object metric value: %v", err)
}
case autoscalingv2.PodsMetricSourceType:
metricSelector, err := metav1.LabelSelectorAsSelector(spec.Pods.Metric.Selector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetPodsMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetPodsMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, "", time.Time{}, fmt.Errorf("failed to get pods metric value: %v", err)
condition := a.getUnableComputeReplicaCountCondition(hpa, "FailedGetPodsMetric", err)
return 0, "", time.Time{}, condition, fmt.Errorf("failed to get pods metric value: %v", err)
}
replicaCountProposal, timestampProposal, metricNameProposal, err = a.computeStatusForPodsMetric(specReplicas, spec, hpa, selector, status, metricSelector)
replicaCountProposal, timestampProposal, metricNameProposal, condition, err = a.computeStatusForPodsMetric(specReplicas, spec, hpa, selector, status, metricSelector)
if err != nil {
return 0, "", time.Time{}, fmt.Errorf("failed to get object metric value: %v", err)
return 0, "", time.Time{}, condition, fmt.Errorf("failed to get pods metric value: %v", err)
}
case autoscalingv2.ResourceMetricSourceType:
replicaCountProposal, timestampProposal, metricNameProposal, err = a.computeStatusForResourceMetric(specReplicas, spec, hpa, selector, status)
replicaCountProposal, timestampProposal, metricNameProposal, condition, err = a.computeStatusForResourceMetric(specReplicas, spec, hpa, selector, status)
if err != nil {
return 0, "", time.Time{}, err
return 0, "", time.Time{}, condition, err
}
case autoscalingv2.ExternalMetricSourceType:
replicaCountProposal, timestampProposal, metricNameProposal, err = a.computeStatusForExternalMetric(specReplicas, statusReplicas, spec, hpa, selector, status)
replicaCountProposal, timestampProposal, metricNameProposal, condition, err = a.computeStatusForExternalMetric(specReplicas, statusReplicas, spec, hpa, selector, status)
if err != nil {
return 0, "", time.Time{}, err
return 0, "", time.Time{}, condition, err
}
default:
errMsg := fmt.Sprintf("unknown metric source type %q", string(spec.Type))
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "InvalidMetricSourceType", errMsg)
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "InvalidMetricSourceType", "the HPA was unable to compute the replica count: %v", fmt.Errorf(errMsg))
return 0, "", time.Time{}, fmt.Errorf(errMsg)
err = fmt.Errorf(errMsg)
condition := a.getUnableComputeReplicaCountCondition(hpa, "InvalidMetricSourceType", err)
return 0, "", time.Time{}, condition, err
}
return replicaCountProposal, metricNameProposal, timestampProposal, nil
return replicaCountProposal, metricNameProposal, timestampProposal, autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
}
func (a *HorizontalController) reconcileKey(key string) (deleted bool, err error) {
@ -347,13 +347,12 @@ func (a *HorizontalController) reconcileKey(key string) (deleted bool, err error
}
// computeStatusForObjectMetric computes the desired number of replicas for the specified metric of type ObjectMetricSourceType.
func (a *HorizontalController) computeStatusForObjectMetric(specReplicas, statusReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus, metricSelector labels.Selector) (int32, time.Time, string, error) {
func (a *HorizontalController) computeStatusForObjectMetric(specReplicas, statusReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus, metricSelector labels.Selector) (replicas int32, timestamp time.Time, metricName string, condition autoscalingv2.HorizontalPodAutoscalerCondition, err error) {
if metricSpec.Object.Target.Type == autoscalingv2.ValueMetricType {
replicaCountProposal, utilizationProposal, timestampProposal, err := a.replicaCalc.GetObjectMetricReplicas(specReplicas, metricSpec.Object.Target.Value.MilliValue(), metricSpec.Object.Metric.Name, hpa.Namespace, &metricSpec.Object.DescribedObject, selector, metricSelector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetObjectMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetObjectMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, timestampProposal, "", err
condition := a.getUnableComputeReplicaCountCondition(hpa, "FailedGetObjectMetric", err)
return 0, timestampProposal, "", condition, err
}
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.ObjectMetricSourceType,
@ -368,13 +367,12 @@ func (a *HorizontalController) computeStatusForObjectMetric(specReplicas, status
},
},
}
return replicaCountProposal, timestampProposal, fmt.Sprintf("%s metric %s", metricSpec.Object.DescribedObject.Kind, metricSpec.Object.Metric.Name), nil
return replicaCountProposal, timestampProposal, fmt.Sprintf("%s metric %s", metricSpec.Object.DescribedObject.Kind, metricSpec.Object.Metric.Name), autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
} else if metricSpec.Object.Target.Type == autoscalingv2.AverageValueMetricType {
replicaCountProposal, utilizationProposal, timestampProposal, err := a.replicaCalc.GetObjectPerPodMetricReplicas(statusReplicas, metricSpec.Object.Target.AverageValue.MilliValue(), metricSpec.Object.Metric.Name, hpa.Namespace, &metricSpec.Object.DescribedObject, metricSelector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetObjectMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetObjectMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, time.Time{}, "", fmt.Errorf("failed to get %s object metric: %v", metricSpec.Object.Metric.Name, err)
condition := a.getUnableComputeReplicaCountCondition(hpa, "FailedGetObjectMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf("failed to get %s object metric: %v", metricSpec.Object.Metric.Name, err)
}
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.ObjectMetricSourceType,
@ -388,21 +386,20 @@ func (a *HorizontalController) computeStatusForObjectMetric(specReplicas, status
},
},
}
return replicaCountProposal, timestampProposal, fmt.Sprintf("external metric %s(%+v)", metricSpec.Object.Metric.Name, metricSpec.Object.Metric.Selector), nil
return replicaCountProposal, timestampProposal, fmt.Sprintf("external metric %s(%+v)", metricSpec.Object.Metric.Name, metricSpec.Object.Metric.Selector), autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
}
errMsg := "invalid object metric source: neither a value target nor an average value target was set"
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetObjectMetric", errMsg)
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetObjectMetric", "the HPA was unable to compute the replica count: %s", errMsg)
return 0, time.Time{}, "", fmt.Errorf(errMsg)
err = fmt.Errorf(errMsg)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetObjectMetric", err)
return 0, time.Time{}, "", condition, err
}
// computeStatusForPodsMetric computes the desired number of replicas for the specified metric of type PodsMetricSourceType.
func (a *HorizontalController) computeStatusForPodsMetric(currentReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus, metricSelector labels.Selector) (int32, time.Time, string, error) {
func (a *HorizontalController) computeStatusForPodsMetric(currentReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus, metricSelector labels.Selector) (replicaCountProposal int32, timestampProposal time.Time, metricNameProposal string, condition autoscalingv2.HorizontalPodAutoscalerCondition, err error) {
replicaCountProposal, utilizationProposal, timestampProposal, err := a.replicaCalc.GetMetricReplicas(currentReplicas, metricSpec.Pods.Target.AverageValue.MilliValue(), metricSpec.Pods.Metric.Name, hpa.Namespace, selector, metricSelector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetPodsMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetPodsMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, timestampProposal, "", err
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetPodsMetric", err)
return 0, timestampProposal, "", condition, err
}
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.PodsMetricSourceType,
@ -417,20 +414,19 @@ func (a *HorizontalController) computeStatusForPodsMetric(currentReplicas int32,
},
}
return replicaCountProposal, timestampProposal, fmt.Sprintf("pods metric %s", metricSpec.Pods.Metric.Name), nil
return replicaCountProposal, timestampProposal, fmt.Sprintf("pods metric %s", metricSpec.Pods.Metric.Name), autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
}
// computeStatusForResourceMetric computes the desired number of replicas for the specified metric of type ResourceMetricSourceType.
func (a *HorizontalController) computeStatusForResourceMetric(currentReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus) (int32, time.Time, string, error) {
func (a *HorizontalController) computeStatusForResourceMetric(currentReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus) (replicaCountProposal int32, timestampProposal time.Time, metricNameProposal string, condition autoscalingv2.HorizontalPodAutoscalerCondition, err error) {
if metricSpec.Resource.Target.AverageValue != nil {
var rawProposal int64
replicaCountProposal, rawProposal, timestampProposal, err := a.replicaCalc.GetRawResourceReplicas(currentReplicas, metricSpec.Resource.Target.AverageValue.MilliValue(), metricSpec.Resource.Name, hpa.Namespace, selector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetResourceMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetResourceMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, time.Time{}, "", fmt.Errorf("failed to get %s utilization: %v", metricSpec.Resource.Name, err)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetResourceMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf("failed to get %s utilization: %v", metricSpec.Resource.Name, err)
}
metricNameProposal := fmt.Sprintf("%s resource", metricSpec.Resource.Name)
metricNameProposal = fmt.Sprintf("%s resource", metricSpec.Resource.Name)
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.ResourceMetricSourceType,
Resource: &autoscalingv2.ResourceMetricStatus{
@ -440,24 +436,23 @@ func (a *HorizontalController) computeStatusForResourceMetric(currentReplicas in
},
},
}
return replicaCountProposal, timestampProposal, metricNameProposal, nil
return replicaCountProposal, timestampProposal, metricNameProposal, autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
} else {
if metricSpec.Resource.Target.AverageUtilization == nil {
errMsg := "invalid resource metric source: neither a utilization target nor a value target was set"
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetResourceMetric", errMsg)
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetResourceMetric", "the HPA was unable to compute the replica count: %s", errMsg)
return 0, time.Time{}, "", fmt.Errorf(errMsg)
err = fmt.Errorf(errMsg)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetResourceMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf(errMsg)
}
targetUtilization := *metricSpec.Resource.Target.AverageUtilization
var percentageProposal int32
var rawProposal int64
replicaCountProposal, percentageProposal, rawProposal, timestampProposal, err := a.replicaCalc.GetResourceReplicas(currentReplicas, targetUtilization, metricSpec.Resource.Name, hpa.Namespace, selector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetResourceMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetResourceMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, time.Time{}, "", fmt.Errorf("failed to get %s utilization: %v", metricSpec.Resource.Name, err)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetResourceMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf("failed to get %s utilization: %v", metricSpec.Resource.Name, err)
}
metricNameProposal := fmt.Sprintf("%s resource utilization (percentage of request)", metricSpec.Resource.Name)
metricNameProposal = fmt.Sprintf("%s resource utilization (percentage of request)", metricSpec.Resource.Name)
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.ResourceMetricSourceType,
Resource: &autoscalingv2.ResourceMetricStatus{
@ -468,18 +463,17 @@ func (a *HorizontalController) computeStatusForResourceMetric(currentReplicas in
},
},
}
return replicaCountProposal, timestampProposal, metricNameProposal, nil
return replicaCountProposal, timestampProposal, metricNameProposal, autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
}
}
// computeStatusForExternalMetric computes the desired number of replicas for the specified metric of type ExternalMetricSourceType.
func (a *HorizontalController) computeStatusForExternalMetric(specReplicas, statusReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus) (int32, time.Time, string, error) {
func (a *HorizontalController) computeStatusForExternalMetric(specReplicas, statusReplicas int32, metricSpec autoscalingv2.MetricSpec, hpa *autoscalingv2.HorizontalPodAutoscaler, selector labels.Selector, status *autoscalingv2.MetricStatus) (replicaCountProposal int32, timestampProposal time.Time, metricNameProposal string, condition autoscalingv2.HorizontalPodAutoscalerCondition, err error) {
if metricSpec.External.Target.AverageValue != nil {
replicaCountProposal, utilizationProposal, timestampProposal, err := a.replicaCalc.GetExternalPerPodMetricReplicas(statusReplicas, metricSpec.External.Target.AverageValue.MilliValue(), metricSpec.External.Metric.Name, hpa.Namespace, metricSpec.External.Metric.Selector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetExternalMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetExternalMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, time.Time{}, "", fmt.Errorf("failed to get %s external metric: %v", metricSpec.External.Metric.Name, err)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetExternalMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf("failed to get %s external metric: %v", metricSpec.External.Metric.Name, err)
}
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.ExternalMetricSourceType,
@ -493,14 +487,13 @@ func (a *HorizontalController) computeStatusForExternalMetric(specReplicas, stat
},
},
}
return replicaCountProposal, timestampProposal, fmt.Sprintf("external metric %s(%+v)", metricSpec.External.Metric.Name, metricSpec.External.Metric.Selector), nil
return replicaCountProposal, timestampProposal, fmt.Sprintf("external metric %s(%+v)", metricSpec.External.Metric.Name, metricSpec.External.Metric.Selector), autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
}
if metricSpec.External.Target.Value != nil {
replicaCountProposal, utilizationProposal, timestampProposal, err := a.replicaCalc.GetExternalMetricReplicas(specReplicas, metricSpec.External.Target.Value.MilliValue(), metricSpec.External.Metric.Name, hpa.Namespace, metricSpec.External.Metric.Selector, selector)
if err != nil {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetExternalMetric", err.Error())
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetExternalMetric", "the HPA was unable to compute the replica count: %v", err)
return 0, time.Time{}, "", fmt.Errorf("failed to get external metric %s: %v", metricSpec.External.Metric.Name, err)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetExternalMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf("failed to get external metric %s: %v", metricSpec.External.Metric.Name, err)
}
*status = autoscalingv2.MetricStatus{
Type: autoscalingv2.ExternalMetricSourceType,
@ -514,12 +507,12 @@ func (a *HorizontalController) computeStatusForExternalMetric(specReplicas, stat
},
},
}
return replicaCountProposal, timestampProposal, fmt.Sprintf("external metric %s(%+v)", metricSpec.External.Metric.Name, metricSpec.External.Metric.Selector), nil
return replicaCountProposal, timestampProposal, fmt.Sprintf("external metric %s(%+v)", metricSpec.External.Metric.Name, metricSpec.External.Metric.Selector), autoscalingv2.HorizontalPodAutoscalerCondition{}, nil
}
errMsg := "invalid external metric source: neither a value target nor an average value target was set"
a.eventRecorder.Event(hpa, v1.EventTypeWarning, "FailedGetExternalMetric", errMsg)
setCondition(hpa, autoscalingv2.ScalingActive, v1.ConditionFalse, "FailedGetExternalMetric", "the HPA was unable to compute the replica count: %s", errMsg)
return 0, time.Time{}, "", fmt.Errorf(errMsg)
err = fmt.Errorf(errMsg)
condition = a.getUnableComputeReplicaCountCondition(hpa, "FailedGetExternalMetric", err)
return 0, time.Time{}, "", condition, fmt.Errorf(errMsg)
}
func (a *HorizontalController) recordInitialRecommendation(currentReplicas int32, key string) {
@ -583,9 +576,18 @@ func (a *HorizontalController) reconcileAutoscaler(hpav1Shared *autoscalingv1.Ho
desiredReplicas := int32(0)
rescaleReason := ""
var minReplicas int32
if hpa.Spec.MinReplicas != nil {
minReplicas = *hpa.Spec.MinReplicas
} else {
// Default value
minReplicas = 1
}
rescale := true
if scale.Spec.Replicas == 0 {
if scale.Spec.Replicas == 0 && minReplicas != 0 {
// Autoscaling is disabled for this resource
desiredReplicas = 0
rescale = false
@ -593,12 +595,9 @@ func (a *HorizontalController) reconcileAutoscaler(hpav1Shared *autoscalingv1.Ho
} else if currentReplicas > hpa.Spec.MaxReplicas {
rescaleReason = "Current number of replicas above Spec.MaxReplicas"
desiredReplicas = hpa.Spec.MaxReplicas
} else if hpa.Spec.MinReplicas != nil && currentReplicas < *hpa.Spec.MinReplicas {
} else if currentReplicas < minReplicas {
rescaleReason = "Current number of replicas below Spec.MinReplicas"
desiredReplicas = *hpa.Spec.MinReplicas
} else if currentReplicas == 0 {
rescaleReason = "Current number of replicas must be greater than 0"
desiredReplicas = 1
desiredReplicas = minReplicas
} else {
var metricTimestamp time.Time
metricDesiredReplicas, metricName, metricStatuses, metricTimestamp, err = a.computeReplicasForMetrics(hpa, scale, hpa.Spec.Metrics)
@ -624,7 +623,7 @@ func (a *HorizontalController) reconcileAutoscaler(hpav1Shared *autoscalingv1.Ho
if desiredReplicas < currentReplicas {
rescaleReason = "All metrics below target"
}
desiredReplicas = a.normalizeDesiredReplicas(hpa, key, currentReplicas, desiredReplicas)
desiredReplicas = a.normalizeDesiredReplicas(hpa, key, currentReplicas, desiredReplicas, minReplicas)
rescale = desiredReplicas != currentReplicas
}
@ -679,19 +678,13 @@ func (a *HorizontalController) stabilizeRecommendation(key string, prenormalized
// normalizeDesiredReplicas takes the metrics desired replicas value and normalizes it based on the appropriate conditions (i.e. < maxReplicas, >
// minReplicas, etc...)
func (a *HorizontalController) normalizeDesiredReplicas(hpa *autoscalingv2.HorizontalPodAutoscaler, key string, currentReplicas int32, prenormalizedDesiredReplicas int32) int32 {
func (a *HorizontalController) normalizeDesiredReplicas(hpa *autoscalingv2.HorizontalPodAutoscaler, key string, currentReplicas int32, prenormalizedDesiredReplicas int32, minReplicas int32) int32 {
stabilizedRecommendation := a.stabilizeRecommendation(key, prenormalizedDesiredReplicas)
if stabilizedRecommendation != prenormalizedDesiredReplicas {
setCondition(hpa, autoscalingv2.AbleToScale, v1.ConditionTrue, "ScaleDownStabilized", "recent recommendations were higher than current one, applying the highest recent recommendation")
} else {
setCondition(hpa, autoscalingv2.AbleToScale, v1.ConditionTrue, "ReadyForNewScale", "recommended size matches current size")
}
var minReplicas int32
if hpa.Spec.MinReplicas != nil {
minReplicas = *hpa.Spec.MinReplicas
} else {
minReplicas = 0
}
desiredReplicas, condition, reason := convertDesiredReplicasWithRules(currentReplicas, stabilizedRecommendation, minReplicas, hpa.Spec.MaxReplicas)
@ -704,6 +697,16 @@ func (a *HorizontalController) normalizeDesiredReplicas(hpa *autoscalingv2.Horiz
return desiredReplicas
}
func (a *HorizontalController) getUnableComputeReplicaCountCondition(hpa *autoscalingv2.HorizontalPodAutoscaler, reason string, err error) (condition autoscalingv2.HorizontalPodAutoscalerCondition) {
a.eventRecorder.Event(hpa, v1.EventTypeWarning, reason, err.Error())
return autoscalingv2.HorizontalPodAutoscalerCondition{
Type: autoscalingv2.ScalingActive,
Status: v1.ConditionFalse,
Reason: reason,
Message: fmt.Sprintf("the HPA was unable to compute the replica count: %v", err),
}
}
// convertDesiredReplicas performs the actual normalization, without depending on `HorizontalController` or `HorizontalPodAutoscaler`
func convertDesiredReplicasWithRules(currentReplicas, desiredReplicas, hpaMinReplicas, hpaMaxReplicas int32) (int32, string, string) {
@ -713,13 +716,8 @@ func convertDesiredReplicasWithRules(currentReplicas, desiredReplicas, hpaMinRep
var possibleLimitingCondition string
var possibleLimitingReason string
if hpaMinReplicas == 0 {
minimumAllowedReplicas = 1
possibleLimitingReason = "the desired replica count is zero"
} else {
minimumAllowedReplicas = hpaMinReplicas
possibleLimitingReason = "the desired replica count is less than the minimum replica count"
}
minimumAllowedReplicas = hpaMinReplicas
possibleLimitingReason = "the desired replica count is less than the minimum replica count"
// Do not upscale too much to prevent incorrect rapid increase of the number of master replicas caused by
// bogus CPU usage report from heapster/kubelet (like in issue #32304).

274
pkg/controller/podautoscaler/horizontal_test.go
View File

@ -1066,6 +1066,68 @@ func TestScaleUpCMObject(t *testing.T) {
tc.runTest(t)
}
func TestScaleUpFromZeroCMObject(t *testing.T) {
targetValue := resource.MustParse("15.0")
tc := testCase{
minReplicas: 0,
maxReplicas: 6,
initialReplicas: 0,
expectedDesiredReplicas: 2,
CPUTarget: 0,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: autoscalingv2.ObjectMetricSourceType,
Object: &autoscalingv2.ObjectMetricSource{
DescribedObject: autoscalingv2.CrossVersionObjectReference{
APIVersion: "apps/v1",
Kind: "Deployment",
Name: "some-deployment",
},
Metric: autoscalingv2.MetricIdentifier{
Name: "qps",
},
Target: autoscalingv2.MetricTarget{
Value: &targetValue,
},
},
},
},
reportedLevels: []uint64{20000},
}
tc.runTest(t)
}
func TestScaleUpFromZeroIgnoresToleranceCMObject(t *testing.T) {
targetValue := resource.MustParse("1.0")
tc := testCase{
minReplicas: 0,
maxReplicas: 6,
initialReplicas: 0,
expectedDesiredReplicas: 1,
CPUTarget: 0,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: autoscalingv2.ObjectMetricSourceType,
Object: &autoscalingv2.ObjectMetricSource{
DescribedObject: autoscalingv2.CrossVersionObjectReference{
APIVersion: "apps/v1",
Kind: "Deployment",
Name: "some-deployment",
},
Metric: autoscalingv2.MetricIdentifier{
Name: "qps",
},
Target: autoscalingv2.MetricTarget{
Value: &targetValue,
},
},
},
},
reportedLevels: []uint64{1000},
}
tc.runTest(t)
}
func TestScaleUpPerPodCMObject(t *testing.T) {
targetAverageValue := resource.MustParse("10.0")
tc := testCase{
@ -1163,6 +1225,67 @@ func TestScaleDown(t *testing.T) {
tc.runTest(t)
}
func TestScaleUpOneMetricInvalid(t *testing.T) {
tc := testCase{
minReplicas: 2,
maxReplicas: 6,
initialReplicas: 3,
expectedDesiredReplicas: 4,
CPUTarget: 30,
verifyCPUCurrent: true,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: "CheddarCheese",
},
},
reportedLevels: []uint64{300, 400, 500},
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
}
tc.runTest(t)
}
func TestScaleUpFromZeroOneMetricInvalid(t *testing.T) {
tc := testCase{
minReplicas: 0,
maxReplicas: 6,
initialReplicas: 0,
expectedDesiredReplicas: 4,
CPUTarget: 30,
verifyCPUCurrent: true,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: "CheddarCheese",
},
},
reportedLevels: []uint64{300, 400, 500},
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
recommendations: []timestampedRecommendation{},
}
tc.runTest(t)
}
func TestScaleUpBothMetricsEmpty(t *testing.T) { // Switch to missing
tc := testCase{
minReplicas: 2,
maxReplicas: 6,
initialReplicas: 3,
expectedDesiredReplicas: 3,
CPUTarget: 0,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: "CheddarCheese",
},
},
reportedLevels: []uint64{},
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
expectedConditions: []autoscalingv1.HorizontalPodAutoscalerCondition{
{Type: autoscalingv1.AbleToScale, Status: v1.ConditionTrue, Reason: "SucceededGetScale"},
{Type: autoscalingv1.ScalingActive, Status: v1.ConditionFalse, Reason: "InvalidMetricSourceType"},
},
}
tc.runTest(t)
}
func TestScaleDownStabilizeInitialSize(t *testing.T) {
tc := testCase{
minReplicas: 2,
@ -1249,6 +1372,39 @@ func TestScaleDownCMObject(t *testing.T) {
tc.runTest(t)
}
func TestScaleDownToZeroCMObject(t *testing.T) {
targetValue := resource.MustParse("20.0")
tc := testCase{
minReplicas: 0,
maxReplicas: 6,
initialReplicas: 5,
expectedDesiredReplicas: 0,
CPUTarget: 0,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: autoscalingv2.ObjectMetricSourceType,
Object: &autoscalingv2.ObjectMetricSource{
DescribedObject: autoscalingv2.CrossVersionObjectReference{
APIVersion: "apps/v1",
Kind: "Deployment",
Name: "some-deployment",
},
Metric: autoscalingv2.MetricIdentifier{
Name: "qps",
},
Target: autoscalingv2.MetricTarget{
Value: &targetValue,
},
},
},
},
reportedLevels: []uint64{0},
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
recommendations: []timestampedRecommendation{},
}
tc.runTest(t)
}
func TestScaleDownPerPodCMObject(t *testing.T) {
targetAverageValue := resource.MustParse("20.0")
tc := testCase{
@ -1308,6 +1464,32 @@ func TestScaleDownCMExternal(t *testing.T) {
tc.runTest(t)
}
func TestScaleDownToZeroCMExternal(t *testing.T) {
tc := testCase{
minReplicas: 0,
maxReplicas: 6,
initialReplicas: 5,
expectedDesiredReplicas: 0,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: autoscalingv2.ExternalMetricSourceType,
External: &autoscalingv2.ExternalMetricSource{
Metric: autoscalingv2.MetricIdentifier{
Name: "qps",
Selector: &metav1.LabelSelector{},
},
Target: autoscalingv2.MetricTarget{
Value: resource.NewMilliQuantity(14400, resource.DecimalSI),
},
},
},
},
reportedLevels: []uint64{0},
recommendations: []timestampedRecommendation{},
}
tc.runTest(t)
}
func TestScaleDownPerPodCMExternal(t *testing.T) {
tc := testCase{
minReplicas: 2,
@ -1352,6 +1534,62 @@ func TestScaleDownIncludeUnreadyPods(t *testing.T) {
tc.runTest(t)
}
func TestScaleDownOneMetricInvalid(t *testing.T) {
tc := testCase{
minReplicas: 2,
maxReplicas: 6,
initialReplicas: 5,
expectedDesiredReplicas: 3,
CPUTarget: 50,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: "CheddarCheese",
},
},
reportedLevels: []uint64{100, 300, 500, 250, 250},
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
useMetricsAPI: true,
recommendations: []timestampedRecommendation{},
}
tc.runTest(t)
}
func TestScaleDownOneMetricEmpty(t *testing.T) {
tc := testCase{
minReplicas: 2,
maxReplicas: 6,
initialReplicas: 5,
expectedDesiredReplicas: 3,
CPUTarget: 50,
metricsTarget: []autoscalingv2.MetricSpec{
{
Type: autoscalingv2.ExternalMetricSourceType,
External: &autoscalingv2.ExternalMetricSource{
Metric: autoscalingv2.MetricIdentifier{
Name: "qps",
Selector: &metav1.LabelSelector{},
},
Target: autoscalingv2.MetricTarget{
Type: autoscalingv2.AverageValueMetricType,
AverageValue: resource.NewMilliQuantity(1000, resource.DecimalSI),
},
},
},
},
reportedLevels: []uint64{100, 300, 500, 250, 250},
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
useMetricsAPI: true,
recommendations: []timestampedRecommendation{},
}
_, _, _, testEMClient, _ := tc.prepareTestClient(t)
testEMClient.PrependReactor("list", "*", func(action core.Action) (handled bool, ret runtime.Object, err error) {
return true, &emapi.ExternalMetricValueList{}, fmt.Errorf("something went wrong")
})
tc.testEMClient = testEMClient
tc.runTest(t)
}
func TestScaleDownIgnoreHotCpuPods(t *testing.T) {
tc := testCase{
minReplicas: 2,
@ -1610,6 +1848,26 @@ func TestMinReplicas(t *testing.T) {
tc.runTest(t)
}
func TestZeroMinReplicasDesiredZero(t *testing.T) {
tc := testCase{
minReplicas: 0,
maxReplicas: 5,
initialReplicas: 3,
expectedDesiredReplicas: 0,
CPUTarget: 90,
reportedLevels: []uint64{0, 0, 0},
reportedCPURequests: []resource.Quantity{resource.MustParse("0.9"), resource.MustParse("1.0"), resource.MustParse("1.1")},
useMetricsAPI: true,
expectedConditions: statusOkWithOverrides(autoscalingv2.HorizontalPodAutoscalerCondition{
Type: autoscalingv2.ScalingLimited,
Status: v1.ConditionFalse,
Reason: "DesiredWithinRange",
}),
recommendations: []timestampedRecommendation{},
}
tc.runTest(t)
}
func TestMinReplicasDesiredZero(t *testing.T) {
tc := testCase{
minReplicas: 2,
@ -2553,9 +2811,9 @@ func TestConvertDesiredReplicasWithRules(t *testing.T) {
expectedDesiredReplicas: 0,
hpaMinReplicas: 0,
hpaMaxReplicas: 10,
expectedConvertedDesiredReplicas: 1,
expectedCondition: "TooFewReplicas",
annotation: "1 is minLimit because hpaMinReplicas < 1",
expectedConvertedDesiredReplicas: 0,
expectedCondition: "DesiredWithinRange",
annotation: "prenormalized desired replicas within range",
},
{
currentReplicas: 20,
@ -2717,8 +2975,9 @@ func TestNoScaleDownOneMetricInvalid(t *testing.T) {
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
useMetricsAPI: true,
expectedConditions: []autoscalingv1.HorizontalPodAutoscalerCondition{
{Type: autoscalingv1.AbleToScale, Status: v1.ConditionTrue, Reason: "SucceededGetScale"},
{Type: autoscalingv1.ScalingActive, Status: v1.ConditionFalse, Reason: "InvalidMetricSourceType"},
{Type: autoscalingv1.AbleToScale, Status: v1.ConditionTrue, Reason: "ScaleDownStabilized"},
{Type: autoscalingv1.ScalingActive, Status: v1.ConditionTrue, Reason: "ValidMetricFound"},
{Type: autoscalingv1.ScalingLimited, Status: v1.ConditionFalse, Reason: "DesiredWithinRange"},
},
}
@ -2750,8 +3009,9 @@ func TestNoScaleDownOneMetricEmpty(t *testing.T) {
reportedCPURequests: []resource.Quantity{resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0"), resource.MustParse("1.0")},
useMetricsAPI: true,
expectedConditions: []autoscalingv1.HorizontalPodAutoscalerCondition{
{Type: autoscalingv1.AbleToScale, Status: v1.ConditionTrue, Reason: "SucceededGetScale"},
{Type: autoscalingv1.ScalingActive, Status: v1.ConditionFalse, Reason: "FailedGetExternalMetric"},
{Type: autoscalingv1.AbleToScale, Status: v1.ConditionTrue, Reason: "ScaleDownStabilized"},
{Type: autoscalingv1.ScalingActive, Status: v1.ConditionTrue, Reason: "ValidMetricFound"},
{Type: autoscalingv1.ScalingLimited, Status: v1.ConditionFalse, Reason: "DesiredWithinRange"},
},
}
_, _, _, testEMClient, _ := tc.prepareTestClient(t)

48
pkg/controller/podautoscaler/replica_calculator.go
View File

@ -241,20 +241,30 @@ func (c *ReplicaCalculator) GetObjectMetricReplicas(currentReplicas int32, targe
}
usageRatio := float64(utilization) / float64(targetUtilization)
if math.Abs(1.0-usageRatio) <= c.tolerance {
// return the current replicas if the change would be too small
return currentReplicas, utilization, timestamp, nil
replicaCount, timestamp, err = c.getUsageRatioReplicaCount(currentReplicas, usageRatio, namespace, selector)
return replicaCount, utilization, timestamp, err
}
// getUsageRatioReplicaCount calculates the desired replica count based on usageRatio and ready pods count.
// For currentReplicas=0 doesn't take into account ready pods count and tolerance to support scaling to zero pods.
func (c *ReplicaCalculator) getUsageRatioReplicaCount(currentReplicas int32, usageRatio float64, namespace string, selector labels.Selector) (replicaCount int32, timestamp time.Time, err error) {
if currentReplicas != 0 {
if math.Abs(1.0-usageRatio) <= c.tolerance {
// return the current replicas if the change would be too small
return currentReplicas, timestamp, nil
}
readyPodCount := int64(0)
readyPodCount, err = c.getReadyPodsCount(namespace, selector)
if err != nil {
return 0, time.Time{}, fmt.Errorf("unable to calculate ready pods: %s", err)
}
replicaCount = int32(math.Ceil(usageRatio * float64(readyPodCount)))
} else {
// Scale to zero or n pods depending on usageRatio
replicaCount = int32(math.Ceil(usageRatio))
}
readyPodCount, err := c.getReadyPodsCount(namespace, selector)
if err != nil {
return 0, 0, time.Time{}, fmt.Errorf("unable to calculate ready pods: %s", err)
}
replicaCount = int32(math.Ceil(usageRatio * float64(readyPodCount)))
return replicaCount, utilization, timestamp, nil
return replicaCount, timestamp, err
}
// GetObjectPerPodMetricReplicas calculates the desired replica count based on a target metric utilization (as a milli-value)
@ -316,19 +326,9 @@ func (c *ReplicaCalculator) GetExternalMetricReplicas(currentReplicas int32, tar
utilization = utilization + val
}
readyPodCount, err := c.getReadyPodsCount(namespace, podSelector)
if err != nil {
return 0, 0, time.Time{}, fmt.Errorf("unable to calculate ready pods: %s", err)
}
usageRatio := float64(utilization) / float64(targetUtilization)
if math.Abs(1.0-usageRatio) <= c.tolerance {
// return the current replicas if the change would be too small
return currentReplicas, utilization, timestamp, nil
}
return int32(math.Ceil(usageRatio * float64(readyPodCount))), utilization, timestamp, nil
replicaCount, timestamp, err = c.getUsageRatioReplicaCount(currentReplicas, usageRatio, namespace, podSelector)
return replicaCount, utilization, timestamp, err
}
// GetExternalPerPodMetricReplicas calculates the desired replica count based on a

7
pkg/features/kube_features.go
View File

@ -54,6 +54,12 @@ const (
// Enables support for Device Plugins
DevicePlugins featuregate.Feature = "DevicePlugins"
// owner: @dxist
// alpha: v1.16
//
// Enables support of HPA scaling to zero pods when an object or custom metric is configured.
HPAScaleToZero featuregate.Feature = "HPAScaleToZero"
// owner: @Huang-Wei
// beta: v1.13
//
@ -549,4 +555,5 @@ var defaultKubernetesFeatureGates = map[featuregate.Feature]featuregate.FeatureS
// features that enable backwards compatibility but are scheduled to be removed
// ...
HPAScaleToZero: {Default: false, PreRelease: featuregate.Alpha},
}

6
staging/src/k8s.io/api/autoscaling/v1/generated.proto
View File

@ -141,7 +141,11 @@ message HorizontalPodAutoscalerSpec {
// and will set the desired number of pods by using its Scale subresource.
optional CrossVersionObjectReference scaleTargetRef = 1;
// lower limit for the number of pods that can be set by the autoscaler, default 1.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
optional int32 minReplicas = 2;

8
staging/src/k8s.io/api/autoscaling/v1/types.go
View File

@ -17,7 +17,7 @@ limitations under the License.
package v1
import (
"k8s.io/api/core/v1"
v1 "k8s.io/api/core/v1"
"k8s.io/apimachinery/pkg/api/resource"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
)
@ -38,7 +38,11 @@ type HorizontalPodAutoscalerSpec struct {
// reference to scaled resource; horizontal pod autoscaler will learn the current resource consumption
// and will set the desired number of pods by using its Scale subresource.
ScaleTargetRef CrossVersionObjectReference `json:"scaleTargetRef" protobuf:"bytes,1,opt,name=scaleTargetRef"`
// lower limit for the number of pods that can be set by the autoscaler, default 1.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
MinReplicas *int32 `json:"minReplicas,omitempty" protobuf:"varint,2,opt,name=minReplicas"`
// upper limit for the number of pods that can be set by the autoscaler; cannot be smaller than MinReplicas.

2
staging/src/k8s.io/api/autoscaling/v1/types_swagger_doc_generated.go generated
View File

@ -99,7 +99,7 @@ func (HorizontalPodAutoscalerList) SwaggerDoc() map[string]string {
var map_HorizontalPodAutoscalerSpec = map[string]string{
"": "specification of a horizontal pod autoscaler.",
"scaleTargetRef": "reference to scaled resource; horizontal pod autoscaler will learn the current resource consumption and will set the desired number of pods by using its Scale subresource.",
"minReplicas": "lower limit for the number of pods that can be set by the autoscaler, default 1.",
"minReplicas": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
"maxReplicas": "upper limit for the number of pods that can be set by the autoscaler; cannot be smaller than MinReplicas.",
"targetCPUUtilizationPercentage": "target average CPU utilization (represented as a percentage of requested CPU) over all the pods; if not specified the default autoscaling policy will be used.",
}

7
staging/src/k8s.io/api/autoscaling/v2beta1/generated.proto
View File

@ -146,8 +146,11 @@ message HorizontalPodAutoscalerSpec {
// should be collected, as well as to actually change the replica count.
optional CrossVersionObjectReference scaleTargetRef = 1;
// minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down.
// It defaults to 1 pod.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
optional int32 minReplicas = 2;

9
staging/src/k8s.io/api/autoscaling/v2beta1/types.go
View File

@ -17,7 +17,7 @@ limitations under the License.
package v2beta1
import (
"k8s.io/api/core/v1"
v1 "k8s.io/api/core/v1"
"k8s.io/apimachinery/pkg/api/resource"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
)
@ -38,8 +38,11 @@ type HorizontalPodAutoscalerSpec struct {
// scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics
// should be collected, as well as to actually change the replica count.
ScaleTargetRef CrossVersionObjectReference `json:"scaleTargetRef" protobuf:"bytes,1,opt,name=scaleTargetRef"`
// minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down.
// It defaults to 1 pod.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
MinReplicas *int32 `json:"minReplicas,omitempty" protobuf:"varint,2,opt,name=minReplicas"`
// maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up.

2
staging/src/k8s.io/api/autoscaling/v2beta1/types_swagger_doc_generated.go generated
View File

@ -99,7 +99,7 @@ func (HorizontalPodAutoscalerList) SwaggerDoc() map[string]string {
var map_HorizontalPodAutoscalerSpec = map[string]string{
"": "HorizontalPodAutoscalerSpec describes the desired functionality of the HorizontalPodAutoscaler.",
"scaleTargetRef": "scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics should be collected, as well as to actually change the replica count.",
"minReplicas": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod.",
"minReplicas": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
"maxReplicas": "maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas.",
"metrics": "metrics contains the specifications for which to use to calculate the desired replica count (the maximum replica count across all metrics will be used). The desired replica count is calculated multiplying the ratio between the target value and the current value by the current number of pods. Ergo, metrics used must decrease as the pod count is increased, and vice-versa. See the individual metric source types for more information about how each type of metric must respond.",
}

7
staging/src/k8s.io/api/autoscaling/v2beta2/generated.proto
View File

@ -123,8 +123,11 @@ message HorizontalPodAutoscalerSpec {
// should be collected, as well as to actually change the replica count.
optional CrossVersionObjectReference scaleTargetRef = 1;
// minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down.
// It defaults to 1 pod.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
optional int32 minReplicas = 2;

9
staging/src/k8s.io/api/autoscaling/v2beta2/types.go
View File

@ -19,7 +19,7 @@ limitations under the License.
package v2beta2
import (
"k8s.io/api/core/v1"
v1 "k8s.io/api/core/v1"
"k8s.io/apimachinery/pkg/api/resource"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
)
@ -52,8 +52,11 @@ type HorizontalPodAutoscalerSpec struct {
// scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics
// should be collected, as well as to actually change the replica count.
ScaleTargetRef CrossVersionObjectReference `json:"scaleTargetRef" protobuf:"bytes,1,opt,name=scaleTargetRef"`
// minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down.
// It defaults to 1 pod.
// minReplicas is the lower limit for the number of replicas to which the autoscaler
// can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the
// alpha feature gate HPAScaleToZero is enabled and at least one Object or External
// metric is configured. Scaling is active as long as at least one metric value is
// available.
// +optional
MinReplicas *int32 `json:"minReplicas,omitempty" protobuf:"varint,2,opt,name=minReplicas"`
// maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up.

2
staging/src/k8s.io/api/autoscaling/v2beta2/types_swagger_doc_generated.go generated
View File

@ -95,7 +95,7 @@ func (HorizontalPodAutoscalerList) SwaggerDoc() map[string]string {
var map_HorizontalPodAutoscalerSpec = map[string]string{
"": "HorizontalPodAutoscalerSpec describes the desired functionality of the HorizontalPodAutoscaler.",
"scaleTargetRef": "scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics should be collected, as well as to actually change the replica count.",
"minReplicas": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod.",
"minReplicas": "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
"maxReplicas": "maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas.",
"metrics": "metrics contains the specifications for which to use to calculate the desired replica count (the maximum replica count across all metrics will be used). The desired replica count is calculated multiplying the ratio between the target value and the current value by the current number of pods. Ergo, metrics used must decrease as the pod count is increased, and vice-versa. See the individual metric source types for more information about how each type of metric must respond. If not set, the default metric will be set to 80% average CPU utilization.",
}

2
staging/src/k8s.io/apiextensions-apiserver/pkg/generated/openapi/zz_generated.openapi.go generated
View File

@ -381,7 +381,7 @@ func schema_k8sio_api_autoscaling_v1_HorizontalPodAutoscalerSpec(ref common.Refe
},
"minReplicas": {
SchemaProps: spec.SchemaProps{
Description: "lower limit for the number of pods that can be set by the autoscaler, default 1.",
Description: "minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.",
Type: []string{"integer"},
Format: "int32",
},