com.pulumi.gcp.compute.kotlin.inputs.RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs.kt Maven / Gradle / Ivy

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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
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@file:Suppress("NAME_SHADOWING", "DEPRECATION")

package com.pulumi.gcp.compute.kotlin.inputs

import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.gcp.compute.inputs.RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs.builder
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiNullFieldException
import com.pulumi.kotlin.PulumiTagMarker
import kotlin.Double
import kotlin.String
import kotlin.Suppress
import kotlin.jvm.JvmName

/**
 *
 * @property predictiveMethod Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:
 * - NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
 * - OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.
 * @property target The target CPU utilization that the autoscaler should maintain.
 * Must be a float value in the range (0, 1]. If not specified, the
 * default is 0.6.
 * If the CPU level is below the target utilization, the autoscaler
 * scales down the number of instances until it reaches the minimum
 * number of instances you specified or until the average CPU of
 * your instances reaches the target utilization.
 * If the average CPU is above the target utilization, the autoscaler
 * scales up until it reaches the maximum number of instances you
 * specified or until the average utilization reaches the target
 * utilization.
 */
public data class RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs(
    public val predictiveMethod: Output? = null,
    public val target: Output,
) :
    ConvertibleToJava {
    override fun toJava(): com.pulumi.gcp.compute.inputs.RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs =
        com.pulumi.gcp.compute.inputs.RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs.builder()
            .predictiveMethod(predictiveMethod?.applyValue({ args0 -> args0 }))
            .target(target.applyValue({ args0 -> args0 })).build()
}

/**
 * Builder for [RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs].
 */
@PulumiTagMarker
public class RegionAutoscalerAutoscalingPolicyCpuUtilizationArgsBuilder internal constructor() {
    private var predictiveMethod: Output? = null

    private var target: Output? = null

    /**
     * @param value Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:
     * - NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
     * - OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.
     */
    @JvmName("qwfcpqfucahkovdj")
    public suspend fun predictiveMethod(`value`: Output) {
        this.predictiveMethod = value
    }

    /**
     * @param value The target CPU utilization that the autoscaler should maintain.
     * Must be a float value in the range (0, 1]. If not specified, the
     * default is 0.6.
     * If the CPU level is below the target utilization, the autoscaler
     * scales down the number of instances until it reaches the minimum
     * number of instances you specified or until the average CPU of
     * your instances reaches the target utilization.
     * If the average CPU is above the target utilization, the autoscaler
     * scales up until it reaches the maximum number of instances you
     * specified or until the average utilization reaches the target
     * utilization.
     */
    @JvmName("hntsvcpmvuxmfsxo")
    public suspend fun target(`value`: Output) {
        this.target = value
    }

    /**
     * @param value Indicates whether predictive autoscaling based on CPU metric is enabled. Valid values are:
     * - NONE (default). No predictive method is used. The autoscaler scales the group to meet current demand based on real-time metrics.
     * - OPTIMIZE_AVAILABILITY. Predictive autoscaling improves availability by monitoring daily and weekly load patterns and scaling out ahead of anticipated demand.
     */
    @JvmName("gnpruiwvwqrbpqkw")
    public suspend fun predictiveMethod(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.predictiveMethod = mapped
    }

    /**
     * @param value The target CPU utilization that the autoscaler should maintain.
     * Must be a float value in the range (0, 1]. If not specified, the
     * default is 0.6.
     * If the CPU level is below the target utilization, the autoscaler
     * scales down the number of instances until it reaches the minimum
     * number of instances you specified or until the average CPU of
     * your instances reaches the target utilization.
     * If the average CPU is above the target utilization, the autoscaler
     * scales up until it reaches the maximum number of instances you
     * specified or until the average utilization reaches the target
     * utilization.
     */
    @JvmName("tchchxtdaqojduck")
    public suspend fun target(`value`: Double) {
        val toBeMapped = value
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.target = mapped
    }

    internal fun build(): RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs =
        RegionAutoscalerAutoscalingPolicyCpuUtilizationArgs(
            predictiveMethod = predictiveMethod,
            target = target ?: throw PulumiNullFieldException("target"),
        )
}