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fix: revise some annnotations and fix fallback check bug #6346

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fix: revise some annnotations and fix fallback check bug #6346

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6ae9874
revise some object name and fix fallback check
ctccxxd Nov 19, 2024
6986e93
add changelog
ctccxxd Nov 19, 2024
55c962b
fix CAHNGELOG.MD
ctccxxd Nov 19, 2024
dfeed82
put new log in CAHNGELOG.MD fix section
ctccxxd Nov 19, 2024
f2ad730
change fallback check
ctccxxd Nov 28, 2024
b115dd4
Merge branch 'main' into checkfallbackvalid
ctccxxd Nov 28, 2024
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -73,6 +73,7 @@ Here is an overview of all new **experimental** features:
### Fixes

- **General**: Paused ScaledObject count is reported correctly after operator restart ([#6321](https://github.com/kedacore/keda/issues/6321))
- **General**: Revise some annotations above function and fix fallback check bug ([#6346](https://github.com/kedacore/keda/pull/6346))

### Deprecations

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8 changes: 4 additions & 4 deletions apis/keda/v1alpha1/scaledobject_types.go
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Expand Up @@ -237,7 +237,7 @@ func (so *ScaledObject) IsUsingModifiers() bool {
return so.Spec.Advanced != nil && !reflect.DeepEqual(so.Spec.Advanced.ScalingModifiers, ScalingModifiers{})
}

// getHPAMinReplicas returns MinReplicas based on definition in ScaledObject or default value if not defined
// GetHPAMinReplicas returns MinReplicas based on definition in ScaledObject or default value if not defined
func (so *ScaledObject) GetHPAMinReplicas() *int32 {
if so.Spec.MinReplicaCount != nil && *so.Spec.MinReplicaCount > 0 {
return so.Spec.MinReplicaCount
Expand All @@ -246,15 +246,15 @@ func (so *ScaledObject) GetHPAMinReplicas() *int32 {
return &tmp
}

// getHPAMaxReplicas returns MaxReplicas based on definition in ScaledObject or default value if not defined
// GetHPAMaxReplicas returns MaxReplicas based on definition in ScaledObject or default value if not defined
func (so *ScaledObject) GetHPAMaxReplicas() int32 {
if so.Spec.MaxReplicaCount != nil {
return *so.Spec.MaxReplicaCount
}
return defaultHPAMaxReplicas
}

// checkReplicaCountBoundsAreValid checks that Idle/Min/Max ReplicaCount defined in ScaledObject are correctly specified
// CheckReplicaCountBoundsAreValid checks that Idle/Min/Max ReplicaCount defined in ScaledObject are correctly specified
// i.e. that Min is not greater than Max or Idle greater or equal to Min
func CheckReplicaCountBoundsAreValid(scaledObject *ScaledObject) error {
min := int32(0)
Expand Down Expand Up @@ -291,7 +291,7 @@ func CheckFallbackValid(scaledObject *ScaledObject) error {
return fmt.Errorf("type is %s , but fallback it is not supported by the CPU & memory scalers", trigger.Type)
}
if trigger.MetricType != autoscalingv2.AverageValueMetricType {
return fmt.Errorf("MetricType=%s, but Fallback can only be enabled for triggers with metric of type AverageValue", trigger.MetricType)
return fmt.Errorf("MetricType=%s, but fallback can only be enabled for triggers with metric of type AverageValue", trigger.MetricType)
}
}
return nil
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2 changes: 1 addition & 1 deletion apis/keda/v1alpha1/scaledobject_webhook.go
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Expand Up @@ -193,7 +193,7 @@ func verifyFallback(incomingSo *ScaledObject, action string, _ bool) error {
scaledobjectlog.WithValues("name", incomingSo.Name).Error(err, "validation error")
metricscollector.RecordScaledObjectValidatingErrors(incomingSo.Namespace, action, "incorrect-fallback")
}
return nil
return err
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this would likely introduce undesired regression on denying SOs with fallback and multiple triggers with at least one being cpu or memory - #5962 (review)

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this would likely introduce undesired regression on denying SOs with fallback and multiple triggers with at least one being cpu or memory - #5962 (review)

so, the code deny trigger which has cpu or memory in function CheckFallbackValid is wrong? so here, it's better to return nil and not take effect?

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@wozniakjan wozniakjan Nov 20, 2024 •
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I think the discussion on this has still not been concluded. Imho it makes sense to allow ScaledObjects that have fallback defined and at least one trigger that is not CPU / memory.

I would go as far as allowing ScaledObjects that have only CPU / memory fallback but throw an Event with type Warning periodically informing the end user that this ScaledObject might not work the way they intended. So this code swallowing the error and just logging it follows that idea.

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@ctccxxd ctccxxd Nov 21, 2024 •
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I see the official website(https://keda.sh/docs/2.16/reference/scaledobject-spec/#fallback) and the code (scaledobject_types.go function CheckFallbackValid), they all forbidden CPU / memory fallback. I think the initial purpose is to forbidden the metric type which is not AverageValue, and I don't know why forbidden CPU / memory fallback? I see that CPU / memory also support type AverageValue. So, if I think there should be a conclusion whether forbidden it. If not forbidden, I think just change code to allow the CPU / memory, but webhook in this part have to take effect to support the value validation. code(maybe just delete this part). If forbidden, so just make it take effect.

Besides, I also make other code contribution, (#6344)
(#6350), and hope you to review, thank you much.

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there is still value in printing the error in this case and maybe we should consider enhancing the user experience by throwing an event too. CPU / memory metrics are not owned by external.metrics.k8s.io API but instead by metrics.k8s.io API. That means KEDA can't fabricate the metric in a way that HPA would scale to fallback numbers.

}

func verifyTriggers(incomingObject interface{}, action string, _ bool) error {
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