Google Cloud (Stackdriver) Monitoring Alert Policy
This page shows how to write Terraform for Cloud (Stackdriver) Monitoring Alert Policy and write them securely.
google_monitoring_alert_policy (Terraform)
The Alert Policy in Cloud (Stackdriver) Monitoring can be configured in Terraform with the resource name google_monitoring_alert_policy
. The following sections describe 2 examples of how to use the resource and its parameters.
Example Usage from GitHub
resource "google_monitoring_alert_policy" "alert_policy_project_ownership" {
notification_channels = [
google_monitoring_notification_channel.email0.name,
google_monitoring_notification_channel.email1.name ]
display_name = "project-ownership"
combiner = "OR"
resource "google_monitoring_alert_policy" "all_bgp_sessions_down" {
count = var.all_bgp_sessions_down ? 1 : 0
combiner = "OR"
Parameters
-
combiner
required - string
How to combine the results of multiple conditions to determine if an incident should be opened. Possible values: ["AND", "OR", "AND_WITH_MATCHING_RESOURCE"]
-
creation_record
optional computed - list of object
A read-only record of the creation of the alerting policy. If provided in a call to create or update, this field will be ignored.
-
mutate_time
- string -
mutated_by
- string -
display_name
required - string
A short name or phrase used to identify the policy in dashboards, notifications, and incidents. To avoid confusion, don't use the same display name for multiple policies in the same project. The name is limited to 512 Unicode characters.
-
enabled
optional - bool
Whether or not the policy is enabled. The default is true.
The unique resource name for this policy. Its syntax is: projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
-
notification_channels
optional - list of string
Identifies the notification channels to which notifications should be sent when incidents are opened or closed or when new violations occur on an already opened incident. Each element of this array corresponds to the name field in each of the NotificationChannel objects that are returned from the notificationChannels.list method. The syntax of the entries in this field is 'projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]'
-
project
optional computed - string -
user_labels
optional - map from string to string
This field is intended to be used for organizing and identifying the AlertPolicy objects.The field can contain up to 64 entries. Each key and value is limited to 63 Unicode characters or 128 bytes, whichever is smaller. Labels and values can contain only lowercase letters, numerals, underscores, and dashes. Keys must begin with a letter.
-
conditions
list block-
display_name
required - string
A short name or phrase used to identify the condition in dashboards, notifications, and incidents. To avoid confusion, don't use the same display name for multiple conditions in the same policy.
-
name
optional computed - string
The unique resource name for this condition. Its syntax is: projects/[PROJECT_ID]/alertPolicies/[POLICY_ID]/conditions/[CONDITION_ID][CONDITION_ID] is assigned by Stackdriver Monitoring when the condition is created as part of a new or updated alerting policy.
-
condition_absent
list block-
duration
required - string
The amount of time that a time series must fail to report new data to be considered failing. Currently, only values that are a multiple of a minute--e.g. 60s, 120s, or 300s --are supported.
-
filter
optional - string
A filter that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the MetricService.ListTimeSeries request (that call is useful to verify the time series that will be retrieved / processed) and must specify the metric type and optionally may contain restrictions on resource type, resource labels, and metric labels. This field may not exceed 2048 Unicode characters in length.
-
aggregations
list block-
alignment_period
optional - string
The alignment period for per-time series alignment. If present, alignmentPeriod must be at least 60 seconds. After per-time series alignment, each time series will contain data points only on the period boundaries. If perSeriesAligner is not specified or equals ALIGN_NONE, then this field is ignored. If perSeriesAligner is specified and does not equal ALIGN_NONE, then this field must be defined; otherwise an error is returned.
-
cross_series_reducer
optional - string
The approach to be used to combine time series. Not all reducer functions may be applied to all time series, depending on the metric type and the value type of the original time series. Reduction may change the metric type of value type of the time series.Time series data must be aligned in order to perform cross- time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned. Possible values: ["REDUCE_NONE", "REDUCE_MEAN", "REDUCE_MIN", "REDUCE_MAX", "REDUCE_SUM", "REDUCE_STDDEV", "REDUCE_COUNT", "REDUCE_COUNT_TRUE", "REDUCE_COUNT_FALSE", "REDUCE_FRACTION_TRUE", "REDUCE_PERCENTILE_99", "REDUCE_PERCENTILE_95", "REDUCE_PERCENTILE_50", "REDUCE_PERCENTILE_05"]
-
group_by_fields
optional - list of string
The set of fields to preserve when crossSeriesReducer is specified. The groupByFields determine how the time series are partitioned into subsets prior to applying the aggregation function. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The crossSeriesReducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in groupByFields are aggregated away. If groupByFields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If crossSeriesReducer is not defined, this field is ignored.
-
per_series_aligner
optional - string
The approach to be used to align individual time series. Not all alignment functions may be applied to all time series, depending on the metric type and value type of the original time series. Alignment may change the metric type or the value type of the time series.Time series data must be aligned in order to perform cross- time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned. Possible values: ["ALIGN_NONE", "ALIGN_DELTA", "ALIGN_RATE", "ALIGN_INTERPOLATE", "ALIGN_NEXT_OLDER", "ALIGN_MIN", "ALIGN_MAX", "ALIGN_MEAN", "ALIGN_COUNT", "ALIGN_SUM", "ALIGN_STDDEV", "ALIGN_COUNT_TRUE", "ALIGN_COUNT_FALSE", "ALIGN_FRACTION_TRUE", "ALIGN_PERCENTILE_99", "ALIGN_PERCENTILE_95", "ALIGN_PERCENTILE_50", "ALIGN_PERCENTILE_05", "ALIGN_PERCENT_CHANGE"]
-
-
trigger
list block-
count
optional - number
The absolute number of time series that must fail the predicate for the condition to be triggered.
-
percent
optional - number
The percentage of time series that must fail the predicate for the condition to be triggered.
-
-
-
condition_monitoring_query_language
list block-
duration
required - string
The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
-
query
required - string
Monitoring Query Language query that outputs a boolean stream.
-
-
condition_threshold
list block-
comparison
required - string
The comparison to apply between the time series (indicated by filter and aggregation) and the threshold (indicated by threshold_value). The comparison is applied on each time series, with the time series on the left-hand side and the threshold on the right-hand side. Only COMPARISON_LT and COMPARISON_GT are supported currently. Possible values: ["COMPARISON_GT", "COMPARISON_GE", "COMPARISON_LT", "COMPARISON_LE", "COMPARISON_EQ", "COMPARISON_NE"]
-
denominator_filter
optional - string
A filter that identifies a time series that should be used as the denominator of a ratio that will be compared with the threshold. If a denominator_filter is specified, the time series specified by the filter field will be used as the numerator.The filter is similar to the one that is specified in the MetricService.ListTimeSeries request (that call is useful to verify the time series that will be retrieved / processed) and must specify the metric type and optionally may contain restrictions on resource type, resource labels, and metric labels. This field may not exceed 2048 Unicode characters in length.
-
duration
required - string
The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
-
filter
optional - string
A filter that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the MetricService.ListTimeSeries request (that call is useful to verify the time series that will be retrieved / processed) and must specify the metric type and optionally may contain restrictions on resource type, resource labels, and metric labels. This field may not exceed 2048 Unicode characters in length.
-
threshold_value
optional - number
A value against which to compare the time series.
-
aggregations
list block-
alignment_period
optional - string
The alignment period for per-time series alignment. If present, alignmentPeriod must be at least 60 seconds. After per-time series alignment, each time series will contain data points only on the period boundaries. If perSeriesAligner is not specified or equals ALIGN_NONE, then this field is ignored. If perSeriesAligner is specified and does not equal ALIGN_NONE, then this field must be defined; otherwise an error is returned.
-
cross_series_reducer
optional - string
The approach to be used to combine time series. Not all reducer functions may be applied to all time series, depending on the metric type and the value type of the original time series. Reduction may change the metric type of value type of the time series.Time series data must be aligned in order to perform cross- time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned. Possible values: ["REDUCE_NONE", "REDUCE_MEAN", "REDUCE_MIN", "REDUCE_MAX", "REDUCE_SUM", "REDUCE_STDDEV", "REDUCE_COUNT", "REDUCE_COUNT_TRUE", "REDUCE_COUNT_FALSE", "REDUCE_FRACTION_TRUE", "REDUCE_PERCENTILE_99", "REDUCE_PERCENTILE_95", "REDUCE_PERCENTILE_50", "REDUCE_PERCENTILE_05"]
-
group_by_fields
optional - list of string
The set of fields to preserve when crossSeriesReducer is specified. The groupByFields determine how the time series are partitioned into subsets prior to applying the aggregation function. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The crossSeriesReducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in groupByFields are aggregated away. If groupByFields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If crossSeriesReducer is not defined, this field is ignored.
-
per_series_aligner
optional - string
The approach to be used to align individual time series. Not all alignment functions may be applied to all time series, depending on the metric type and value type of the original time series. Alignment may change the metric type or the value type of the time series.Time series data must be aligned in order to perform cross- time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned. Possible values: ["ALIGN_NONE", "ALIGN_DELTA", "ALIGN_RATE", "ALIGN_INTERPOLATE", "ALIGN_NEXT_OLDER", "ALIGN_MIN", "ALIGN_MAX", "ALIGN_MEAN", "ALIGN_COUNT", "ALIGN_SUM", "ALIGN_STDDEV", "ALIGN_COUNT_TRUE", "ALIGN_COUNT_FALSE", "ALIGN_FRACTION_TRUE", "ALIGN_PERCENTILE_99", "ALIGN_PERCENTILE_95", "ALIGN_PERCENTILE_50", "ALIGN_PERCENTILE_05", "ALIGN_PERCENT_CHANGE"]
-
-
denominator_aggregations
list block-
alignment_period
optional - string
The alignment period for per-time series alignment. If present, alignmentPeriod must be at least 60 seconds. After per-time series alignment, each time series will contain data points only on the period boundaries. If perSeriesAligner is not specified or equals ALIGN_NONE, then this field is ignored. If perSeriesAligner is specified and does not equal ALIGN_NONE, then this field must be defined; otherwise an error is returned.
-
cross_series_reducer
optional - string
The approach to be used to combine time series. Not all reducer functions may be applied to all time series, depending on the metric type and the value type of the original time series. Reduction may change the metric type of value type of the time series.Time series data must be aligned in order to perform cross- time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned. Possible values: ["REDUCE_NONE", "REDUCE_MEAN", "REDUCE_MIN", "REDUCE_MAX", "REDUCE_SUM", "REDUCE_STDDEV", "REDUCE_COUNT", "REDUCE_COUNT_TRUE", "REDUCE_COUNT_FALSE", "REDUCE_FRACTION_TRUE", "REDUCE_PERCENTILE_99", "REDUCE_PERCENTILE_95", "REDUCE_PERCENTILE_50", "REDUCE_PERCENTILE_05"]
-
group_by_fields
optional - list of string
The set of fields to preserve when crossSeriesReducer is specified. The groupByFields determine how the time series are partitioned into subsets prior to applying the aggregation function. Each subset contains time series that have the same value for each of the grouping fields. Each individual time series is a member of exactly one subset. The crossSeriesReducer is applied to each subset of time series. It is not possible to reduce across different resource types, so this field implicitly contains resource.type. Fields not specified in groupByFields are aggregated away. If groupByFields is not specified and all the time series have the same resource type, then the time series are aggregated into a single output time series. If crossSeriesReducer is not defined, this field is ignored.
-
per_series_aligner
optional - string
The approach to be used to align individual time series. Not all alignment functions may be applied to all time series, depending on the metric type and value type of the original time series. Alignment may change the metric type or the value type of the time series.Time series data must be aligned in order to perform cross- time series reduction. If crossSeriesReducer is specified, then perSeriesAligner must be specified and not equal ALIGN_NONE and alignmentPeriod must be specified; otherwise, an error is returned. Possible values: ["ALIGN_NONE", "ALIGN_DELTA", "ALIGN_RATE", "ALIGN_INTERPOLATE", "ALIGN_NEXT_OLDER", "ALIGN_MIN", "ALIGN_MAX", "ALIGN_MEAN", "ALIGN_COUNT", "ALIGN_SUM", "ALIGN_STDDEV", "ALIGN_COUNT_TRUE", "ALIGN_COUNT_FALSE", "ALIGN_FRACTION_TRUE", "ALIGN_PERCENTILE_99", "ALIGN_PERCENTILE_95", "ALIGN_PERCENTILE_50", "ALIGN_PERCENTILE_05", "ALIGN_PERCENT_CHANGE"]
-
-
trigger
list block-
count
optional - number
The absolute number of time series that must fail the predicate for the condition to be triggered.
-
percent
optional - number
The percentage of time series that must fail the predicate for the condition to be triggered.
-
-
-
-
documentation
list block-
content
optional - string
The text of the documentation, interpreted according to mimeType. The content may not exceed 8,192 Unicode characters and may not exceed more than 10,240 bytes when encoded in UTF-8 format, whichever is smaller.
-
mime_type
optional - string
The format of the content field. Presently, only the value "text/markdown" is supported.
-
-
timeouts
single block
Explanation in Terraform Registry
A description of the conditions under which some aspect of your system is considered to be "unhealthy" and the ways to notify people or services about this state. To get more information about AlertPolicy, see:
- API documentation
- How-to Guides
Frequently asked questions
What is Google Cloud (Stackdriver) Monitoring Alert Policy?
Google Cloud (Stackdriver) Monitoring Alert Policy is a resource for Cloud (Stackdriver) Monitoring of Google Cloud Platform. Settings can be wrote in Terraform.
Where can I find the example code for the Google Cloud (Stackdriver) Monitoring Alert Policy?
For Terraform, the shudhanshh/Freelance-TF-Project and aliz-ai/terraform-aliz-modules source code examples are useful. See the Terraform Example section for further details.