com.pulumi.gcp.monitoring.kotlin.outputs.SloWindowsBasedSliMetricSumInRange.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.monitoring.kotlin.outputs

import kotlin.String
import kotlin.Suppress

/**
 *
 * @property range Range of numerical values. The computed good_service
 * will be the count of values x in the Distribution such
 * that range.min <= x <= range.max. inclusive of min and
 * max. Open ranges can be defined by setting
 * just one of min or max. Summed value `X` should satisfy
 * `range.min <= X <= range.max` for a good window.
 * Structure is documented below.
 * @property timeSeries A [monitoring filter](https://cloud.google.com/monitoring/api/v3/filters)
 * specifying the TimeSeries to use for evaluating window
 * quality. The provided TimeSeries must have
 * ValueType = INT64 or ValueType = DOUBLE and
 * MetricKind = GAUGE.
 * Summed value `X` should satisfy
 * `range.min <= X <= range.max` for a good window.
 */
public data class SloWindowsBasedSliMetricSumInRange(
    public val range: SloWindowsBasedSliMetricSumInRangeRange,
    public val timeSeries: String,
) {
    public companion object {
        public fun toKotlin(javaType: com.pulumi.gcp.monitoring.outputs.SloWindowsBasedSliMetricSumInRange): SloWindowsBasedSliMetricSumInRange = SloWindowsBasedSliMetricSumInRange(
            range = javaType.range().let({ args0 ->
                com.pulumi.gcp.monitoring.kotlin.outputs.SloWindowsBasedSliMetricSumInRangeRange.Companion.toKotlin(args0)
            }),
            timeSeries = javaType.timeSeries(),
        )
    }
}