update: source github.com/jsonnet-libs/k8s@84d8d441

Author: strowi

1.6.0/_gen/datadoghq/main.libsonnet 1.18.0/_gen/datadoghq/main.libsonnet1.6.0/_gen/datadoghq/main.libsonnet renamed to 1.18.0/_gen/datadoghq/main.libsonnet

@@ -2,5 +2,6 @@
   local d = (import 'doc-util/main.libsonnet'),
   '#':: d.pkg(name='datadoghq', url='', help=''),
   v1alpha1: (import 'v1alpha1/main.libsonnet'),
+  v1alpha2: (import 'v1alpha2/main.libsonnet'),
   v2alpha1: (import 'v2alpha1/main.libsonnet'),
 }

1.18.0/_gen/datadoghq/v1alpha1/datadogAgentProfile.libsonnet

@@ -56,6 +56,30 @@
     },
     '#options':: d.obj(help='"Options are the optional parameters associated with your monitor"'),
     options: {
+      '#schedulingOptions':: d.obj(help='"Configuration options for scheduling."'),
+      schedulingOptions: {
+        '#customSchedule':: d.obj(help='"Configuration options for the custom schedule. If start is omitted, the monitor creation time will be used."'),
+        customSchedule: {
+          '#recurrence':: d.obj(help='"DatadogMonitorOptionsSchedulingOptionsCustomScheduleRecurrence is a struct of the recurrence definition"'),
+          recurrence: {
+            '#withRrule':: d.fn(help='"The recurrence rule in iCalendar format. For example, `FREQ=MONTHLY;BYMONTHDAY=28,29,30,31;BYSETPOS=-1`."', args=[d.arg(name='rrule', type=d.T.string)]),
+            withRrule(rrule): { spec+: { options+: { schedulingOptions+: { customSchedule+: { recurrence+: { rrule: rrule } } } } } },
+            '#withStart':: d.fn(help='"The start date of the recurrence rule defined in `YYYY-MM-DDThh:mm:ss` format.\\nIf omitted, the monitor creation time will be used."', args=[d.arg(name='start', type=d.T.string)]),
+            withStart(start): { spec+: { options+: { schedulingOptions+: { customSchedule+: { recurrence+: { start: start } } } } } },
+            '#withTimezone':: d.fn(help='"The timezone in `tz database` format, in which the recurrence rule is defined. For example, `America/New_York` or `UTC`."', args=[d.arg(name='timezone', type=d.T.string)]),
+            withTimezone(timezone): { spec+: { options+: { schedulingOptions+: { customSchedule+: { recurrence+: { timezone: timezone } } } } } },
+          },
+        },
+        '#evaluationWindow':: d.obj(help='"Configuration options for the evaluation window. If hour_starts is set, no other fields may be set.\\nOtherwise, day_starts and month_starts must be set together."'),
+        evaluationWindow: {
+          '#withDayStarts':: d.fn(help='"The time of the day at which a one day cumulative evaluation window starts. Must be defined in UTC time in HH:mm format."', args=[d.arg(name='dayStarts', type=d.T.string)]),
+          withDayStarts(dayStarts): { spec+: { options+: { schedulingOptions+: { evaluationWindow+: { dayStarts: dayStarts } } } } },
+          '#withHourStarts':: d.fn(help='"The minute of the hour at which a one hour cumulative evaluation window starts."', args=[d.arg(name='hourStarts', type=d.T.integer)]),
+          withHourStarts(hourStarts): { spec+: { options+: { schedulingOptions+: { evaluationWindow+: { hourStarts: hourStarts } } } } },
+          '#withMonthStarts':: d.fn(help='"The day of the month at which a one month cumulative evaluation window starts."', args=[d.arg(name='monthStarts', type=d.T.integer)]),
+          withMonthStarts(monthStarts): { spec+: { options+: { schedulingOptions+: { evaluationWindow+: { monthStarts: monthStarts } } } } },
+        },
+      },
       '#thresholdWindows':: d.obj(help='"A struct of the alerting time window options."'),
       thresholdWindows: {
         '#withRecoveryWindow':: d.fn(help='"Describes how long an anomalous metric must be normal before the alert recovers."', args=[d.arg(name='recoveryWindow', type=d.T.string)]),

…oghq/v1alpha1/datadogDashboard.libsonnet …oghq/v1alpha1/datadogDashboard.libsonnet1.9.0/_gen/datadoghq/v1alpha1/datadogDashboard.libsonnet renamed to 1.18.0/_gen/datadoghq/v1alpha1/datadogDashboard.libsonnet 1.9.0/_gen/datadoghq/v1alpha1/datadogDashboard.libsonnet renamed to 1.18.0/_gen/datadoghq/v1alpha1/datadogDashboard.libsonnet

@@ -53,17 +53,6 @@
     constraints: {
       '#containers':: d.obj(help='"Containers defines constraints for the containers."'),
       containers: {
-        '#limits':: d.obj(help='"Limits defines the constraints for the limits of the container."'),
-        limits: {
-          '#withMaxAllowed':: d.fn(help='"MaxAllowed is the upper limit for the requests of the container."', args=[d.arg(name='maxAllowed', type=d.T.object)]),
-          withMaxAllowed(maxAllowed): { limits+: { maxAllowed: maxAllowed } },
-          '#withMaxAllowedMixin':: d.fn(help='"MaxAllowed is the upper limit for the requests of the container."\n\n**Note:** This function appends passed data to existing values', args=[d.arg(name='maxAllowed', type=d.T.object)]),
-          withMaxAllowedMixin(maxAllowed): { limits+: { maxAllowed+: maxAllowed } },
-          '#withMinAllowed':: d.fn(help='"MinAllowed is the lower limit for the requests of the container."', args=[d.arg(name='minAllowed', type=d.T.object)]),
-          withMinAllowed(minAllowed): { limits+: { minAllowed: minAllowed } },
-          '#withMinAllowedMixin':: d.fn(help='"MinAllowed is the lower limit for the requests of the container."\n\n**Note:** This function appends passed data to existing values', args=[d.arg(name='minAllowed', type=d.T.object)]),
-          withMinAllowedMixin(minAllowed): { limits+: { minAllowed+: minAllowed } },
-        },
         '#requests':: d.obj(help='"Requests defines the constraints for the requests of the container."'),
         requests: {
           '#withMaxAllowed':: d.fn(help='"MaxAllowed is the upper limit for the requests of the container."', args=[d.arg(name='maxAllowed', type=d.T.object)]),
@@ -75,7 +64,7 @@
           '#withMinAllowedMixin':: d.fn(help='"MinAllowed is the lower limit for the requests of the container."\n\n**Note:** This function appends passed data to existing values', args=[d.arg(name='minAllowed', type=d.T.object)]),
           withMinAllowedMixin(minAllowed): { requests+: { minAllowed+: minAllowed } },
         },
-        '#withEnabled':: d.fn(help='"Enabled false allows to disable resources autoscaling for the container. Default to true."', args=[d.arg(name='enabled', type=d.T.boolean)]),
+        '#withEnabled':: d.fn(help='"Enabled, if false, allows one to disable resource autoscaling for the container. Defaults to true."', args=[d.arg(name='enabled', type=d.T.boolean)]),
         withEnabled(enabled): { enabled: enabled },
         '#withName':: d.fn(help='"Name is the name of the container. Can be \\"*\\" to apply to all containers."', args=[d.arg(name='name', type=d.T.string)]),
         withName(name): { name: name },
@@ -86,7 +75,7 @@
       withContainersMixin(containers): { spec+: { constraints+: { containers+: if std.isArray(v=containers) then containers else [containers] } } },
       '#withMaxReplicas':: d.fn(help='"MaxReplicas is the upper limit for the number of POD replicas. Needs to be >= minReplicas."', args=[d.arg(name='maxReplicas', type=d.T.integer)]),
       withMaxReplicas(maxReplicas): { spec+: { constraints+: { maxReplicas: maxReplicas } } },
-      '#withMinReplicas':: d.fn(help='"MinReplicas is the lower limit for the number of POD replicas. Needs to be >= 1. Default to 1."', args=[d.arg(name='minReplicas', type=d.T.integer)]),
+      '#withMinReplicas':: d.fn(help='"MinReplicas is the lower limit for the number of pod replicas. Needs to be >= 1. Defaults to 1."', args=[d.arg(name='minReplicas', type=d.T.integer)]),
       withMinReplicas(minReplicas): { spec+: { constraints+: { minReplicas: minReplicas } } },
     },
     '#policy':: d.obj(help='"Policy defines how recommendations should be applied."'),
@@ -95,44 +84,44 @@
       downscale: {
         '#rules':: d.obj(help='"Rules is a list of potential scaling polices which can be used during scaling.\\nAt least one policy must be specified, otherwise the DatadogPodAutoscalerScalingPolicy will be discarded as invalid"'),
         rules: {
-          '#withMatch':: d.fn(help='"Match defines if the rule should be considered or not in the calculation.\\nDefault to Always if not set."', args=[d.arg(name='match', type=d.T.string)]),
-          withMatch(match): { match: match },
-          '#withPeriodSeconds':: d.fn(help='"PeriodSeconds specifies the window of time for which the policy should hold true.\\nPeriodSeconds must be greater than zero and less than or equal to 1800 (30 min)."', args=[d.arg(name='periodSeconds', type=d.T.integer)]),
+          '#withPeriodSeconds':: d.fn(help='"PeriodSeconds specifies the window of time for which the policy should hold true.\\nPeriodSeconds must be greater than zero and less than or equal to 3600 (1 hour)."', args=[d.arg(name='periodSeconds', type=d.T.integer)]),
           withPeriodSeconds(periodSeconds): { periodSeconds: periodSeconds },
           '#withType':: d.fn(help='"Type is used to specify the scaling policy."', args=[d.arg(name='type', type=d.T.string)]),
           withType(type): { type: type },
-          '#withValue':: d.fn(help='"Value contains the amount of change which is permitted by the policy.\\nSetting it to 0 will prevent any scaling in this direction and should not be used unless Match is set to IfScalingEvent."', args=[d.arg(name='value', type=d.T.integer)]),
+          '#withValue':: d.fn(help='"Value contains the amount of change which is permitted by the policy.\\nSetting it to 0 will prevent any scaling in this direction."', args=[d.arg(name='value', type=d.T.integer)]),
           withValue(value): { value: value },
         },
         '#withRules':: d.fn(help='"Rules is a list of potential scaling polices which can be used during scaling.\\nAt least one policy must be specified, otherwise the DatadogPodAutoscalerScalingPolicy will be discarded as invalid"', args=[d.arg(name='rules', type=d.T.array)]),
         withRules(rules): { spec+: { policy+: { downscale+: { rules: if std.isArray(v=rules) then rules else [rules] } } } },
         '#withRulesMixin':: d.fn(help='"Rules is a list of potential scaling polices which can be used during scaling.\\nAt least one policy must be specified, otherwise the DatadogPodAutoscalerScalingPolicy will be discarded as invalid"\n\n**Note:** This function appends passed data to existing values', args=[d.arg(name='rules', type=d.T.array)]),
         withRulesMixin(rules): { spec+: { policy+: { downscale+: { rules+: if std.isArray(v=rules) then rules else [rules] } } } },
+        '#withStabilizationWindowSeconds':: d.fn(help='"StabilizationWindowSeconds is the number of seconds the controller should lookback at previous recommendations\\nbefore deciding to apply a new one. Defaults to 0."', args=[d.arg(name='stabilizationWindowSeconds', type=d.T.integer)]),
+        withStabilizationWindowSeconds(stabilizationWindowSeconds): { spec+: { policy+: { downscale+: { stabilizationWindowSeconds: stabilizationWindowSeconds } } } },
         '#withStrategy':: d.fn(help='"Strategy is used to specify which policy should be used.\\nIf not set, the default value Max is used."', args=[d.arg(name='strategy', type=d.T.string)]),
         withStrategy(strategy): { spec+: { policy+: { downscale+: { strategy: strategy } } } },
       },
       '#update':: d.obj(help='"Update defines the policy to update target resource."'),
       update: {
-        '#withStrategy':: d.fn(help='"Mode defines the mode of the update policy."', args=[d.arg(name='strategy', type=d.T.string)]),
+        '#withStrategy':: d.fn(help='"Strategy defines the mode of the update policy."', args=[d.arg(name='strategy', type=d.T.string)]),
         withStrategy(strategy): { spec+: { policy+: { update+: { strategy: strategy } } } },
       },
       '#upscale':: d.obj(help='"Upscale defines the policy to scale up the target resource."'),
       upscale: {
         '#rules':: d.obj(help='"Rules is a list of potential scaling polices which can be used during scaling.\\nAt least one policy must be specified, otherwise the DatadogPodAutoscalerScalingPolicy will be discarded as invalid"'),
         rules: {
-          '#withMatch':: d.fn(help='"Match defines if the rule should be considered or not in the calculation.\\nDefault to Always if not set."', args=[d.arg(name='match', type=d.T.string)]),
-          withMatch(match): { match: match },
-          '#withPeriodSeconds':: d.fn(help='"PeriodSeconds specifies the window of time for which the policy should hold true.\\nPeriodSeconds must be greater than zero and less than or equal to 1800 (30 min)."', args=[d.arg(name='periodSeconds', type=d.T.integer)]),
+          '#withPeriodSeconds':: d.fn(help='"PeriodSeconds specifies the window of time for which the policy should hold true.\\nPeriodSeconds must be greater than zero and less than or equal to 3600 (1 hour)."', args=[d.arg(name='periodSeconds', type=d.T.integer)]),
           withPeriodSeconds(periodSeconds): { periodSeconds: periodSeconds },
           '#withType':: d.fn(help='"Type is used to specify the scaling policy."', args=[d.arg(name='type', type=d.T.string)]),
           withType(type): { type: type },
-          '#withValue':: d.fn(help='"Value contains the amount of change which is permitted by the policy.\\nSetting it to 0 will prevent any scaling in this direction and should not be used unless Match is set to IfScalingEvent."', args=[d.arg(name='value', type=d.T.integer)]),
+          '#withValue':: d.fn(help='"Value contains the amount of change which is permitted by the policy.\\nSetting it to 0 will prevent any scaling in this direction."', args=[d.arg(name='value', type=d.T.integer)]),
           withValue(value): { value: value },
         },
         '#withRules':: d.fn(help='"Rules is a list of potential scaling polices which can be used during scaling.\\nAt least one policy must be specified, otherwise the DatadogPodAutoscalerScalingPolicy will be discarded as invalid"', args=[d.arg(name='rules', type=d.T.array)]),
         withRules(rules): { spec+: { policy+: { upscale+: { rules: if std.isArray(v=rules) then rules else [rules] } } } },
         '#withRulesMixin':: d.fn(help='"Rules is a list of potential scaling polices which can be used during scaling.\\nAt least one policy must be specified, otherwise the DatadogPodAutoscalerScalingPolicy will be discarded as invalid"\n\n**Note:** This function appends passed data to existing values', args=[d.arg(name='rules', type=d.T.array)]),
         withRulesMixin(rules): { spec+: { policy+: { upscale+: { rules+: if std.isArray(v=rules) then rules else [rules] } } } },
+        '#withStabilizationWindowSeconds':: d.fn(help='"StabilizationWindowSeconds is the number of seconds the controller should lookback at previous recommendations\\nbefore deciding to apply a new one. Defaults to 0."', args=[d.arg(name='stabilizationWindowSeconds', type=d.T.integer)]),
+        withStabilizationWindowSeconds(stabilizationWindowSeconds): { spec+: { policy+: { upscale+: { stabilizationWindowSeconds: stabilizationWindowSeconds } } } },
         '#withStrategy':: d.fn(help='"Strategy is used to specify which policy should be used.\\nIf not set, the default value Max is used."', args=[d.arg(name='strategy', type=d.T.string)]),
         withStrategy(strategy): { spec+: { policy+: { upscale+: { strategy: strategy } } } },
       },
@@ -150,37 +139,33 @@
     },
     '#targets':: d.obj(help='"Targets are objectives to reach and maintain for the target resource.\\nDefault to a single target to maintain 80% POD CPU utilization."'),
     targets: {
-      '#containerResource':: d.obj(help='"ContainerResource allows to set a container-level resource target."'),
+      '#containerResource':: d.obj(help='"ContainerResource allows to set a container-level resource objective."'),
       containerResource: {
-        '#value':: d.obj(help='"Value is the value of the target."'),
+        '#value':: d.obj(help='"Value is the value of the objective"'),
         value: {
-          '#withAbsolute':: d.fn(help='"Absolute defines the absolute value of the target (for instance 500 millicores)."', args=[d.arg(name='absolute', type=d.T.any)]),
-          withAbsolute(absolute): { containerResource+: { value+: { absolute: absolute } } },
-          '#withType':: d.fn(help='"Type specifies how the value is expressed (Absolute or Utilization)."', args=[d.arg(name='type', type=d.T.string)]),
+          '#withType':: d.fn(help='"Type specifies how the value is expressed (possible values: Utilization)."', args=[d.arg(name='type', type=d.T.string)]),
           withType(type): { containerResource+: { value+: { type: type } } },
-          '#withUtilization':: d.fn(help='"Utilization defines a percentage of the target compared to requested resource"', args=[d.arg(name='utilization', type=d.T.integer)]),
+          '#withUtilization':: d.fn(help='"Utilization defines a percentage of the target compared to requested workload"', args=[d.arg(name='utilization', type=d.T.integer)]),
           withUtilization(utilization): { containerResource+: { value+: { utilization: utilization } } },
         },
         '#withContainer':: d.fn(help='"Container is the name of the container."', args=[d.arg(name='container', type=d.T.string)]),
         withContainer(container): { containerResource+: { container: container } },
         '#withName':: d.fn(help='"Name is the name of the resource."', args=[d.arg(name='name', type=d.T.string)]),
         withName(name): { containerResource+: { name: name } },
       },
-      '#podResource':: d.obj(help='"PodResource allows to set a POD-level resource target."'),
+      '#podResource':: d.obj(help='"PodResource allows to set a pod-level resource objective."'),
       podResource: {
-        '#value':: d.obj(help='"Value is the value of the target."'),
+        '#value':: d.obj(help='"Value is the value of the objective."'),
         value: {
-          '#withAbsolute':: d.fn(help='"Absolute defines the absolute value of the target (for instance 500 millicores)."', args=[d.arg(name='absolute', type=d.T.any)]),
-          withAbsolute(absolute): { podResource+: { value+: { absolute: absolute } } },
-          '#withType':: d.fn(help='"Type specifies how the value is expressed (Absolute or Utilization)."', args=[d.arg(name='type', type=d.T.string)]),
+          '#withType':: d.fn(help='"Type specifies how the value is expressed (possible values: Utilization)."', args=[d.arg(name='type', type=d.T.string)]),
           withType(type): { podResource+: { value+: { type: type } } },
-          '#withUtilization':: d.fn(help='"Utilization defines a percentage of the target compared to requested resource"', args=[d.arg(name='utilization', type=d.T.integer)]),
+          '#withUtilization':: d.fn(help='"Utilization defines a percentage of the target compared to requested workload"', args=[d.arg(name='utilization', type=d.T.integer)]),
           withUtilization(utilization): { podResource+: { value+: { utilization: utilization } } },
         },
         '#withName':: d.fn(help='"Name is the name of the resource."', args=[d.arg(name='name', type=d.T.string)]),
         withName(name): { podResource+: { name: name } },
       },
-      '#withType':: d.fn(help='"Type sets the type of the target."', args=[d.arg(name='type', type=d.T.string)]),
+      '#withType':: d.fn(help='"Type sets the type of the objective."', args=[d.arg(name='type', type=d.T.string)]),
       withType(type): { type: type },
     },
     '#withOwner':: d.fn(help='"Owner defines the source of truth for this object (local or remote)\\nValue needs to be set when a DatadogPodAutoscaler object is created."', args=[d.arg(name='owner', type=d.T.string)]),