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I have two separate deployment - api and svc, both communicating to each other via rabbitmq.
For both dedicated so and ta resources are created.
scaleObject are using dedicated names and scaleTargetRef, but the same trigger type rabbitmq, with the same metadata
metadata:
mode: QueueLength
value: '5'
queueName: que.request
Prior to updates to 2.10 in 2.6, that configuration worked without any issues, scaling both deployments.
With 2.10, that stopper working.
If only one deployment is enabled to use KEDA (only one so is in namespace, it works just fine).
When both deployments are enable, we see warnings with reason: AmbiguousSelector and FailedComputeMetricsReplicas pods by selector one-ofour-label=xxxx are controlled by multiple HPAs: [a-namespace/keda-hpa-svc a-namespace/keda-hpa-api
No errors and no scaling.
Expected Behavior
the configuration to work as in 2.6 release
Actual Behavior
Warnings with reason: AmbiguousSelector and FailedComputeMetricsReplicas pods by selector one-ofour-label=xxxx are controlled by multiple HPAs: [a-namespace/keda-hpa-svc a-namespace/keda-hpa-api
No errors and no scaling.
Hello,
That problem is not related with KEDA, it's a change that Kubernetes introduced in v1.26 for preventing multiple HPA scaling the same workloads: kubernetes/kubernetes#112011
Do you have more than 1 ScaledObject for the same workload? Or a ScaledObject and another external HPA? Other option could be a misconfiguration in labels/labelSelector at deployment level.
The PR I have linked explains both cases. I close this issue because it's not an issue in KEDA, but feel free to reopen it if you still think that there is something related with KEDA
Currently we do not have any other hpa resources besides the ones (2) created by keda out of so. I'll look at the labels/selectors to workaround the dups. if I need details/help, I'll open this ticket maybe with different type (not as a bug)
You can ask here again 😄 I just closed it for not having to enter for checking that it's something in k8s and not a bug, but we will try to help in any case
eliminating label's dups as workaround, resolved the issue. We still consider it as a bug in kubernetes and will be watching kubernetes/kubernetes#116898.
Report
I have two separate deployment - api and svc, both communicating to each other via rabbitmq.
For both dedicated so and ta resources are created.
scaleObject are using dedicated names and scaleTargetRef, but the same trigger type rabbitmq, with the same metadata
metadata:
mode: QueueLength
value: '5'
queueName: que.request
Prior to updates to 2.10 in 2.6, that configuration worked without any issues, scaling both deployments.
With 2.10, that stopper working.
If only one deployment is enabled to use KEDA (only one so is in namespace, it works just fine).
When both deployments are enable, we see warnings with reason: AmbiguousSelector and FailedComputeMetricsReplicas
pods by selector one-ofour-label=xxxx are controlled by multiple HPAs: [a-namespace/keda-hpa-svc a-namespace/keda-hpa-api
No errors and no scaling.
Expected Behavior
the configuration to work as in 2.6 release
Actual Behavior
Warnings with reason: AmbiguousSelector and FailedComputeMetricsReplicas
pods by selector one-ofour-label=xxxx are controlled by multiple HPAs: [a-namespace/keda-hpa-svc a-namespace/keda-hpa-api
No errors and no scaling.
Logs from KEDA operator
KEDA Version
2.10.0
Kubernetes Version
1.26
Platform
Azure
Scaler Details
triggers:: -type: rabbitmq metadata: mode: QueueLength value: '5' queueName: que.request
Anything else?
No response
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