Change factories_config type in FAST and project/vpc factory modules, add YAML schema validation (#3728)
* stage 0 * stage 1 * networking * security * pf stage * tfdoc * align schemas * inventory * fix observability * pf module * pf module budgets * align fast stages * align project subfactories * tfdoc * schema validation * add missing schemas * Fix observability types --------- Co-authored-by: Julio Castillo <jccb@google.com>
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Ludovico Magnocavallo
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@@ -45,12 +45,14 @@ locals {
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condition_absent = !can(c.condition_absent) ? null : {
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duration = c.condition_absent.duration
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filter = try(c.condition_absent.filter, null)
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aggregations = !can(c.condition_absent.aggregations) ? null : {
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per_series_aligner = try(c.condition_absent.aggregations.per_series_aligner, null)
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group_by_fields = try(c.condition_absent.aggregations.group_by_fields, null)
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cross_series_reducer = try(c.condition_absent.aggregations.cross_series_reducer, null)
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alignment_period = try(c.condition_absent.aggregations.alignment_period, null)
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}
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aggregations = !can(c.condition_absent.aggregations) ? null : [
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for a in c.condition_absent.aggregations : {
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per_series_aligner = try(a.per_series_aligner, null)
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group_by_fields = try(a.group_by_fields, null)
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cross_series_reducer = try(a.cross_series_reducer, null)
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alignment_period = try(a.alignment_period, null)
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}
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]
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trigger = !can(c.condition_absent.trigger) ? null : {
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count = try(c.condition_absent.trigger.count, null)
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percent = try(c.condition_absent.trigger.percent, null)
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@@ -85,18 +87,22 @@ locals {
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evaluation_missing_data = try(c.condition_threshold.evaluation_missing_data, null)
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filter = try(c.condition_threshold.filter, null)
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threshold_value = try(c.condition_threshold.threshold_value, null)
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aggregations = !can(c.condition_threshold.aggregations) ? null : {
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per_series_aligner = try(c.condition_threshold.aggregations.per_series_aligner, null)
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group_by_fields = try(c.condition_threshold.aggregations.group_by_fields, null)
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cross_series_reducer = try(c.condition_threshold.aggregations.cross_series_reducer, null)
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alignment_period = try(c.condition_threshold.aggregations.alignment_period, null)
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}
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denominator_aggregations = !can(c.condition_threshold.denominator_aggregations) ? null : {
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per_series_aligner = try(c.condition_threshold.denominator_aggregations.per_series_aligner, null)
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group_by_fields = try(c.condition_threshold.denominator_aggregations.group_by_fields, null)
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cross_series_reducer = try(c.condition_threshold.denominator_aggregations.cross_series_reducer, null)
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alignment_period = try(c.condition_threshold.denominator_aggregations.alignment_period, null)
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}
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aggregations = !can(c.condition_threshold.aggregations) ? null : [
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for a in c.condition_threshold.aggregations : {
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per_series_aligner = try(a.per_series_aligner, null)
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group_by_fields = try(a.group_by_fields, null)
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cross_series_reducer = try(a.cross_series_reducer, null)
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alignment_period = try(a.alignment_period, null)
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}
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]
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denominator_aggregations = !can(c.condition_threshold.denominator_aggregations) ? null : [
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for a in c.condition_threshold.denominator_aggregations : {
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per_series_aligner = try(a.per_series_aligner, null)
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group_by_fields = try(a.group_by_fields, null)
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cross_series_reducer = try(a.cross_series_reducer, null)
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alignment_period = try(a.alignment_period, null)
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}
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]
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forecast_options = !can(c.condition_threshold.forecast_options) ? null : {
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forecast_horizon = c.condition_threshold.forecast_options.forecast_horizon
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}
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@@ -173,7 +179,7 @@ resource "google_monitoring_alert_policy" "alerts" {
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duration = condition_absent.value.duration
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filter = condition_absent.value.filter
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dynamic "aggregations" {
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for_each = condition_absent.value.aggregations[*]
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for_each = coalesce(condition_absent.value.aggregations, [])
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content {
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alignment_period = aggregations.value.alignment_period
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cross_series_reducer = aggregations.value.cross_series_reducer
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@@ -235,7 +241,7 @@ resource "google_monitoring_alert_policy" "alerts" {
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filter = condition_threshold.value.filter
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threshold_value = condition_threshold.value.threshold_value
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dynamic "aggregations" {
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for_each = condition_threshold.value.aggregations[*]
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for_each = coalesce(condition_threshold.value.aggregations, [])
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content {
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alignment_period = aggregations.value.alignment_period
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cross_series_reducer = aggregations.value.cross_series_reducer
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@@ -244,7 +250,7 @@ resource "google_monitoring_alert_policy" "alerts" {
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}
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}
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dynamic "denominator_aggregations" {
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for_each = condition_threshold.value.denominator_aggregations[*]
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for_each = coalesce(condition_threshold.value.denominator_aggregations, [])
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content {
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alignment_period = denominator_aggregations.value.alignment_period
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cross_series_reducer = denominator_aggregations.value.cross_series_reducer
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@@ -478,23 +478,26 @@
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]
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},
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"aggregations": {
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"type": "object",
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"additionalProperties": false,
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"properties": {
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"per_series_aligner": {
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"type": "string"
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},
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"group_by_fields": {
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"type": "array",
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"items": {
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"type": "array",
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"items": {
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"type": "object",
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"additionalProperties": false,
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"properties": {
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"per_series_aligner": {
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"type": "string"
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},
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"group_by_fields": {
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"type": "array",
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"items": {
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"type": "string"
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}
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},
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"cross_series_reducer": {
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"type": "string"
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},
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"alignment_period": {
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"type": "string"
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}
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},
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"cross_series_reducer": {
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"type": "string"
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},
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"alignment_period": {
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"type": "string"
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}
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}
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},
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@@ -511,4 +514,4 @@
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}
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}
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}
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}
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}
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@@ -39,12 +39,12 @@ variable "alerts" {
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condition_absent = optional(object({
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duration = string
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filter = optional(string)
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aggregations = optional(object({
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aggregations = optional(list(object({
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per_series_aligner = optional(string)
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group_by_fields = optional(list(string))
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cross_series_reducer = optional(string)
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alignment_period = optional(string)
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}))
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})))
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trigger = optional(object({
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count = optional(number)
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percent = optional(number)
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@@ -79,18 +79,18 @@ variable "alerts" {
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evaluation_missing_data = optional(string)
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filter = optional(string)
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threshold_value = optional(number)
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aggregations = optional(object({
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aggregations = optional(list(object({
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per_series_aligner = optional(string)
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group_by_fields = optional(list(string))
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cross_series_reducer = optional(string)
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alignment_period = optional(string)
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}))
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denominator_aggregations = optional(object({
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})))
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denominator_aggregations = optional(list(object({
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per_series_aligner = optional(string)
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group_by_fields = optional(list(string))
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cross_series_reducer = optional(string)
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alignment_period = optional(string)
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}))
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})))
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forecast_options = optional(object({
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forecast_horizon = string
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}))
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