AutoscalingConfigArgs

data class AutoscalingConfigArgs(val clusterId: Output<String>? = null, val coolDownDuration: Output<String>? = null, val expander: Output<String>? = null, val gpuUtilizationThreshold: Output<String>? = null, val scaleDownEnabled: Output<Boolean>? = null, val scanInterval: Output<String>? = null, val unneededDuration: Output<String>? = null, val utilizationThreshold: Output<String>? = null) : ConvertibleToJava<AutoscalingConfigArgs>

Constructors

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fun AutoscalingConfigArgs(clusterId: Output<String>? = null, coolDownDuration: Output<String>? = null, expander: Output<String>? = null, gpuUtilizationThreshold: Output<String>? = null, scaleDownEnabled: Output<Boolean>? = null, scanInterval: Output<String>? = null, unneededDuration: Output<String>? = null, utilizationThreshold: Output<String>? = null)

Functions

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open override fun toJava(): AutoscalingConfigArgs

Properties

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val clusterId: Output<String>? = null

The id of kubernetes cluster.

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val coolDownDuration: Output<String>? = null

The cool down duration. Default is 10m. If the delay (cooldown) value is set too long, there could be complaints that the Horizontal Pod Autoscaler is not responsive to workload changes. However, if the delay value is set too short, the scale of the replicas set may keep thrashing as usual.

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val expander: Output<String>? = null

The policy for selecting which node pool to scale. Valid values: least-waste, random, priority. For more information on these policies, see Configure auto scaling

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val gpuUtilizationThreshold: Output<String>? = null

The scale-in threshold for GPU instance. Default is 0.5.

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val scaleDownEnabled: Output<Boolean>? = null

Specify whether to allow the scale-in of nodes. Default is true.

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val scanInterval: Output<String>? = null

The interval at which the cluster is reevaluated for scaling. Default is 30s.

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val unneededDuration: Output<String>? = null

The unneeded duration. Default is 10m.

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val utilizationThreshold: Output<String>? = null

The scale-in threshold. Default is 0.5.