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OSDOCS 17854 Upstream KEDA 2.18.1 changes #104664

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OSDOCS 17854 Upstream KEDA 2.18.1 changes
Jan 12, 2026
600c02b
Added note that fallback is not supported for CPU and memory triggers
Jan 13, 2026
203a068
Fix build error
Jan 26, 2026
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82 changes: 46 additions & 36 deletions modules/nodes-cma-autoscaling-custom-creating-workload.adoc
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Original file line number Diff line number Diff line change
Expand Up @@ -76,19 +76,22 @@ apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
annotations:
autoscaling.keda.sh/paused-replicas: "0" <1>
name: scaledobject <2>
autoscaling.keda.sh/paused <1>
autoscaling.keda.sh/paused-replicas: "0" <2>
autoscaling.keda.sh/paused-scale-in: "true" <3>
autoscaling.keda.sh/paused-scale-out: "true" <4>
name: scaledobject <5>
namespace: my-namespace
spec:
scaleTargetRef:
apiVersion: apps/v1 <3>
name: example-deployment <4>
kind: Deployment <5>
envSourceContainerName: .spec.template.spec.containers[0] <6>
cooldownPeriod: 200 <7>
maxReplicaCount: 100 <8>
minReplicaCount: 0 <9>
metricsServer: <10>
apiVersion: apps/v1 <6>
name: example-deployment <7>
kind: Deployment <8>
envSourceContainerName: .spec.template.spec.containers[0] <9>
cooldownPeriod: 200 <10>
maxReplicaCount: 100 <11>
minReplicaCount: 0 <12>
metricsServer: <13>
auditConfig:
logFormat: "json"
logOutputVolumeClaim: "persistentVolumeClaimName"
Expand All @@ -101,57 +104,64 @@ spec:
maxAge: "2"
maxBackup: "1"
maxSize: "50"
fallback: <11>
fallback: <14>
failureThreshold: 3
replicas: 6
behavior: static <12>
pollingInterval: 30 <13>
behavior: static <15>
pollingInterval: 30 <16>
advanced:
restoreToOriginalReplicaCount: false <14>
restoreToOriginalReplicaCount: false <17>
horizontalPodAutoscalerConfig:
name: keda-hpa-scale-down <15>
behavior: <16>
name: keda-hpa-scale-down <18>
behavior: <19>
scaleDown:
stabilizationWindowSeconds: 300
policies:
- type: Percent
value: 100
periodSeconds: 15
triggers:
- type: prometheus <17>
- type: prometheus <20>
metadata:
serverAddress: https://thanos-querier.openshift-monitoring.svc.cluster.local:9092
namespace: kedatest
metricName: http_requests_total
threshold: '5'
query: sum(rate(http_requests_total{job="test-app"}[1m]))
authModes: basic
authenticationRef: <18>
authenticationRef: <21>
name: prom-triggerauthentication
kind: TriggerAuthentication
----
<1> Optional: Specifies that the Custom Metrics Autoscaler Operator is to scale the replicas to the specified value and stop autoscaling, as described in the "Pausing the custom metrics autoscaler for a workload" section.
<2> Specifies a name for this custom metrics autoscaler.
<3> Optional: Specifies the API version of the target resource. The default is `apps/v1`.
<4> Specifies the name of the object that you want to scale.
<5> Specifies the `kind` as `Deployment`, `StatefulSet` or `CustomResource`.
<6> Optional: Specifies the name of the container in the target resource, from which the custom metrics autoscaler gets environment variables holding secrets and so forth. The default is `.spec.template.spec.containers[0]`.
<7> Optional. Specifies the period in seconds to wait after the last trigger is reported before scaling the deployment back to `0` if the `minReplicaCount` is set to `0`. The default is `300`.
<8> Optional: Specifies the maximum number of replicas when scaling up. The default is `100`.
<9> Optional: Specifies the minimum number of replicas when scaling down.
<10> Optional: Specifies the parameters for audit logs. as described in the "Configuring audit logging" section.
<11> Optional: Specifies the number of replicas to fall back to if a scaler fails to get metrics from the source for the number of times defined by the `failureThreshold` parameter. For more information on fallback behavior, see the link:https://keda.sh/docs/latest/reference/scaledobject-spec/#fallback[KEDA documentation].
<12> Optional: Specifies the replica count to be used if a fallback occurs. Enter one of the following options or omit the parameter:
<1> Optional: Specifies that the Custom Metrics Autoscaler Operator should pause scaling immediately and maintain the current instance count.
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@mburke5678 mburke5678 Jan 13, 2026

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REVIEWERS: Call outs <1>, <3>, and <4> are new. All other call out text is unchanged, except where noted. Updated the numbering only.
Will remove callouts in separate PR.

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🤖 [error] AsciiDocDITA.CalloutList: Callouts are not supported in DITA.

<2> Optional: Specifies that the Custom Metrics Autoscaler Operator is to scale the replicas to the specified value and stop autoscaling, as described in the "Pausing the custom metrics autoscaler for a workload" section.
<3> Optional: Specifies whether the Custom Metrics Autoscaler Operator pauses scale down for the object, while allowing the object to scale up.
* If `true`, scaling down is disabled, even if the current number of pods is above the `minReplicaCount`.
* If `false`, scaling down is enabled, and scaling is restored to the original configuration.
<4> Optional: Specifies whether the Custom Metrics Autoscaler Operator pauses scale up for the object, while allowing the object to scale down.
* If `true`, scaling up is disabled, even if the current number of pods is above the `minReplicaCount`.
* If `false`, scaling down is enabled, and scaling is restored to the original configuration.
<5> Specifies a name for this custom metrics autoscaler.
<6> Optional: Specifies the API version of the target resource. The default is `apps/v1`.
<7> Specifies the name of the object that you want to scale.
<8> Specifies the `kind` as `Deployment`, `StatefulSet` or `CustomResource`.
<9> Optional: Specifies the name of the container in the target resource, from which the custom metrics autoscaler gets environment variables holding secrets and so forth. The default is `.spec.template.spec.containers[0]`.
<10> Optional. Specifies the period in seconds to wait after the last trigger is reported before scaling the deployment back to `0` if the `minReplicaCount` is set to `0`. The default is `300`.
<11> Optional: Specifies the maximum number of replicas when scaling up. The default is `100`.
<12> Optional: Specifies the minimum number of replicas when scaling down.
<13> Optional: Specifies the parameters for audit logs. as described in the "Configuring audit logging" section.
<14> Optional: Specifies the number of replicas to fall back to if a scaler fails to get metrics from the source for the number of times defined by the `failureThreshold` parameter. Not supported for CPU or memory triggers. For more information on fallback behavior, see the link:https://keda.sh/docs/latest/reference/scaledobject-spec/#fallback[KEDA documentation].
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@qe: This sentence is new: Not supported for CPU or memory triggers. Picked it up from here.

<15> Optional: Specifies the replica count to be used if a fallback occurs. Enter one of the following options or omit the parameter:
* Enter `static` to use the number of replicas specified by the `fallback.replicas` parameter. This is the default.
* Enter `currentReplicas` to maintain the current number of replicas.
* Enter `currentReplicasIfHigher` to maintain the current number of replicas, if that number is higher than the `fallback.replicas` parameter. If the current number of replicas is lower than the `fallback.replicas` parameter, use the `fallback.replicas` value.
* Enter `currentReplicasIfLower` to maintain the current number of replicas, if that number is lower than the `fallback.replicas` parameter. If the current number of replicas is higher than the `fallback.replicas` parameter, use the `fallback.replicas` value.
<13> Optional: Specifies the interval in seconds to check each trigger on. The default is `30`.
<14> Optional: Specifies whether to scale back the target resource to the original replica count after the scaled object is deleted. The default is `false`, which keeps the replica count as it is when the scaled object is deleted.
<15> Optional: Specifies a name for the horizontal pod autoscaler. The default is `keda-hpa-{scaled-object-name}`.
<16> Optional: Specifies a scaling policy to use to control the rate to scale pods up or down, as described in the "Scaling policies" section.
<17> Specifies the trigger to use as the basis for scaling, as described in the "Understanding the custom metrics autoscaler triggers" section. This example uses {product-title} monitoring.
<18> Optional: Specifies a trigger authentication or a cluster trigger authentication. For more information, see _Understanding the custom metrics autoscaler trigger authentication_ in the _Additional resources_ section.
<16> Optional: Specifies the interval in seconds to check each trigger on. The default is `30`.
<17> Optional: Specifies whether to scale back the target resource to the original replica count after the scaled object is deleted. The default is `false`, which keeps the replica count as it is when the scaled object is deleted.
<18> Optional: Specifies a name for the horizontal pod autoscaler. The default is `keda-hpa-{scaled-object-name}`.
<19> Optional: Specifies a scaling policy to use to control the rate to scale pods up or down, as described in the "Scaling policies" section.
<20> Specifies the trigger to use as the basis for scaling, as described in the "Understanding the custom metrics autoscaler triggers" section. This example uses {product-title} monitoring.
<21> Optional: Specifies a trigger authentication or a cluster trigger authentication. For more information, see _Understanding the custom metrics autoscaler trigger authentication_ in the _Additional resources_ section.
* Enter `TriggerAuthentication` to use a trigger authentication. This is the default.
* Enter `ClusterTriggerAuthentication` to use a cluster trigger authentication.

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20 changes: 14 additions & 6 deletions modules/nodes-cma-autoscaling-custom-trigger-kafka.adoc
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🤖 [error] AsciiDocDITA.TaskContents: The '.Procedure' block title is missing.

Original file line number Diff line number Diff line change
Expand Up @@ -41,9 +41,11 @@ spec:
allowIdleConsumers: true <8>
scaleToZeroOnInvalidOffset: false <9>
excludePersistentLag: false <10>
version: '1.0.0' <11>
partitionLimitation: '1,2,10-20,31' <12>
tls: enable <13>
ensureEvenDistributionOfPartitions: 'false' <11>
limitToPartitionsWithLag <12>
version: '1.0.0' <13>
partitionLimitation: '1,2,10-20,31' <14>
tls: enable <15>
----
<1> Specifies Kafka as the trigger type.
<2> Specifies the name of the Kafka topic on which Kafka is processing the offset lag.
Expand All @@ -61,6 +63,12 @@ spec:
<10> Optional: Specifies whether the trigger includes or excludes partition lag for partitions whose current offset is the same as the current offset of the previous polling cycle.
* If `true`, the scaler excludes partition lag in these partitions.
* If `false`, the trigger includes all consumer lag in all partitions. This is the default.
<11> Optional: Specifies the version of your Kafka brokers. Must be specified as a quoted string value. The default is `1.0.0`.
<12> Optional: Specifies a comma-separated list of partition IDs to scope the scaling on. If set, only the listed IDs are considered when calculating lag. Must be specified as a quoted string value. The default is to consider all partitions.
<13> Optional: Specifies whether to use TSL client authentication for Kafka. The default is `disable`. For information on configuring TLS, see "Understanding custom metrics autoscaler trigger authentications".
<11> Optional: Specifies whether the trigger ensures that replicas are spread evenly across the topic partitions.
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REVIEWERS: Call outs <11> and <12> are new. All other call out text is unchanged, except where noted. Updated the numbering only.
Will remove callouts in separate PR.

* If `true`, the replicas are scaled evenly across the partitions.
* If `false`, the replicas are scaled based on the calculated lag and the lag threshold, and are not distributed evenly across partitions. This is the default.
<12> Optional: Specifies whether the number of replicas can exceed the number of partitions that are experiencing lag.
* If `true`, the number of replicas cannot exceed the number of partitions having lag. The `topic` parameter must be specified and the `allowIdleConsumers` must be `false`.
* If `false`, the number of replicas can exceed the number of partitions having lag. This is the default.
<13> Optional: Specifies the version of your Kafka brokers. Must be specified as a quoted string value. The default is `1.0.0`.
<14> Optional: Specifies a comma-separated list of partition IDs to scope the scaling on. If set, only the listed IDs are considered when calculating lag. Must be specified as a quoted string value. The default is to consider all partitions.
<15> Optional: Specifies whether to use TSL client authentication for Kafka. The default is `disable`. For information on configuring TLS, see "Understanding custom metrics autoscaler trigger authentications".