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<h1><a href="monitoring_v3.html">Stackdriver Monitoring API</a> . <a href="monitoring_v3.projects.html">projects</a> . <a href="monitoring_v3.projects.alertPolicies.html">alertPolicies</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#create">create(name, body, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a new alerting policy.</p>
<p class="toc_element">
  <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes an alerting policy.</p>
<p class="toc_element">
  <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets a single alerting policy.</p>
<p class="toc_element">
  <code><a href="#list">list(name, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None, filter=None)</a></code></p>
<p class="firstline">Lists the existing alerting policies for the project.</p>
<p class="toc_element">
  <code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<p class="toc_element">
  <code><a href="#patch">patch(name, body, updateMask=None, x__xgafv=None)</a></code></p>
<p class="firstline">Updates an alerting policy. You can either replace the entire policy with a new one or replace only certain fields in the current alerting policy by specifying the fields to be updated via updateMask. Returns the updated alerting policy.</p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="create">create(name, body, x__xgafv=None)</code>
  <pre>Creates a new alerting policy.

Args:
  name: string, The project in which to create the alerting policy. The format is projects/[PROJECT_ID].Note that this field names the parent container in which the alerting policy will be written, not the name of the created policy. The alerting policy that is returned will have a name that contains a normalized representation of this name as a prefix but adds a suffix of the form /alertPolicies/[POLICY_ID], identifying the policy in the container. (required)
  body: object, The request body. (required)
    The object takes the form of:

{ # 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. For an overview of alert policies, see Introduction to Alerting.
    "combiner": "A String", # How to combine the results of multiple conditions to determine if an incident should be opened.
    "displayName": "A 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.
    "name": "A String", # Required if the policy exists. The resource name for this policy. The syntax is:
        # projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
        # [ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request.
    "creationRecord": { # Describes a change made to a configuration. # 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.
      "mutatedBy": "A String", # The email address of the user making the change.
      "mutateTime": "A String", # When the change occurred.
    },
    "documentation": { # A content string and a MIME type that describes the content string's format. # Documentation that is included with notifications and incidents related to this policy. Best practice is for the documentation to include information to help responders understand, mitigate, escalate, and correct the underlying problems detected by the alerting policy. Notification channels that have limited capacity might not show this documentation.
      "mimeType": "A String", # The format of the content field. Presently, only the value "text/markdown" is supported. See Markdown (https://en.wikipedia.org/wiki/Markdown) for more information.
      "content": "A String", # The text of the documentation, interpreted according to mime_type. 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.
    },
    "enabled": True or False, # Whether or not the policy is enabled. On write, the default interpretation if unset is that the policy is enabled. On read, clients should not make any assumption about the state if it has not been populated. The field should always be populated on List and Get operations, unless a field projection has been specified that strips it out.
    "userLabels": { # User-supplied key/value data 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.
      "a_key": "A String",
    },
    "notificationChannels": [ # 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 ListNotificationChannels method. The syntax of the entries in this field is:
        # projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]
      "A String",
    ],
    "mutationRecord": { # Describes a change made to a configuration. # A read-only record of the most recent change to the alerting policy. If provided in a call to create or update, this field will be ignored.
      "mutatedBy": "A String", # The email address of the user making the change.
      "mutateTime": "A String", # When the change occurred.
    },
    "conditions": [ # A list of conditions for the policy. The conditions are combined by AND or OR according to the combiner field. If the combined conditions evaluate to true, then an incident is created. A policy can have from one to six conditions.
      { # A condition is a true/false test that determines when an alerting policy should open an incident. If a condition evaluates to true, it signifies that something is wrong.
        "conditionThreshold": { # A condition type that compares a collection of time series against a threshold. # A condition that compares a time series against a threshold.
          "comparison": "A 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.
          "denominatorFilter": "A 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.
          "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
            { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
              "groupByFields": [ # 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.
                "A String",
              ],
              "alignmentPeriod": "A 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.
              "perSeriesAligner": "A 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.
              "crossSeriesReducer": "A 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.
            },
          ],
          "filter": "A 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.
          "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
            "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
            "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
          },
          "denominatorAggregations": [ # Specifies the alignment of data points in individual time series selected by denominatorFilter as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resources).When computing ratios, the aggregations and denominator_aggregations fields must use the same alignment period and produce time series that have the same periodicity and labels.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
            { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
              "groupByFields": [ # 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.
                "A String",
              ],
              "alignmentPeriod": "A 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.
              "perSeriesAligner": "A 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.
              "crossSeriesReducer": "A 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.
            },
          ],
          "duration": "A 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.
          "thresholdValue": 3.14, # A value against which to compare the time series.
        },
        "displayName": "A 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": "A String", # Required if the condition exists. 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.When calling the alertPolicies.create method, do not include the name field in the conditions of the requested alerting policy. Stackdriver Monitoring creates the condition identifiers and includes them in the new policy.When calling the alertPolicies.update method to update a policy, including a condition name causes the existing condition to be updated. Conditions without names are added to the updated policy. Existing conditions are deleted if they are not updated.Best practice is to preserve [CONDITION_ID] if you make only small changes, such as those to condition thresholds, durations, or trigger values. Otherwise, treat the change as a new condition and let the existing condition be deleted.
        "conditionAbsent": { # A condition type that checks that monitored resources are reporting data. The configuration defines a metric and a set of monitored resources. The predicate is considered in violation when a time series for the specified metric of a monitored resource does not include any data in the specified duration. # A condition that checks that a time series continues to receive new data points.
          "filter": "A 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.
          "duration": "A 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. 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. The Duration.nanos field is ignored.
          "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations.
            "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
            "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
          },
          "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
            { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
              "groupByFields": [ # 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.
                "A String",
              ],
              "alignmentPeriod": "A 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.
              "perSeriesAligner": "A 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.
              "crossSeriesReducer": "A 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.
            },
          ],
        },
      },
    ],
  }

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # 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. For an overview of alert policies, see Introduction to Alerting.
      "combiner": "A String", # How to combine the results of multiple conditions to determine if an incident should be opened.
      "displayName": "A 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.
      "name": "A String", # Required if the policy exists. The resource name for this policy. The syntax is:
          # projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
          # [ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request.
      "creationRecord": { # Describes a change made to a configuration. # 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.
        "mutatedBy": "A String", # The email address of the user making the change.
        "mutateTime": "A String", # When the change occurred.
      },
      "documentation": { # A content string and a MIME type that describes the content string's format. # Documentation that is included with notifications and incidents related to this policy. Best practice is for the documentation to include information to help responders understand, mitigate, escalate, and correct the underlying problems detected by the alerting policy. Notification channels that have limited capacity might not show this documentation.
        "mimeType": "A String", # The format of the content field. Presently, only the value "text/markdown" is supported. See Markdown (https://en.wikipedia.org/wiki/Markdown) for more information.
        "content": "A String", # The text of the documentation, interpreted according to mime_type. 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.
      },
      "enabled": True or False, # Whether or not the policy is enabled. On write, the default interpretation if unset is that the policy is enabled. On read, clients should not make any assumption about the state if it has not been populated. The field should always be populated on List and Get operations, unless a field projection has been specified that strips it out.
      "userLabels": { # User-supplied key/value data 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.
        "a_key": "A String",
      },
      "notificationChannels": [ # 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 ListNotificationChannels method. The syntax of the entries in this field is:
          # projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]
        "A String",
      ],
      "mutationRecord": { # Describes a change made to a configuration. # A read-only record of the most recent change to the alerting policy. If provided in a call to create or update, this field will be ignored.
        "mutatedBy": "A String", # The email address of the user making the change.
        "mutateTime": "A String", # When the change occurred.
      },
      "conditions": [ # A list of conditions for the policy. The conditions are combined by AND or OR according to the combiner field. If the combined conditions evaluate to true, then an incident is created. A policy can have from one to six conditions.
        { # A condition is a true/false test that determines when an alerting policy should open an incident. If a condition evaluates to true, it signifies that something is wrong.
          "conditionThreshold": { # A condition type that compares a collection of time series against a threshold. # A condition that compares a time series against a threshold.
            "comparison": "A 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.
            "denominatorFilter": "A 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.
            "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
            "filter": "A 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.
            "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
              "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
              "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
            },
            "denominatorAggregations": [ # Specifies the alignment of data points in individual time series selected by denominatorFilter as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resources).When computing ratios, the aggregations and denominator_aggregations fields must use the same alignment period and produce time series that have the same periodicity and labels.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
            "duration": "A 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.
            "thresholdValue": 3.14, # A value against which to compare the time series.
          },
          "displayName": "A 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": "A String", # Required if the condition exists. 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.When calling the alertPolicies.create method, do not include the name field in the conditions of the requested alerting policy. Stackdriver Monitoring creates the condition identifiers and includes them in the new policy.When calling the alertPolicies.update method to update a policy, including a condition name causes the existing condition to be updated. Conditions without names are added to the updated policy. Existing conditions are deleted if they are not updated.Best practice is to preserve [CONDITION_ID] if you make only small changes, such as those to condition thresholds, durations, or trigger values. Otherwise, treat the change as a new condition and let the existing condition be deleted.
          "conditionAbsent": { # A condition type that checks that monitored resources are reporting data. The configuration defines a metric and a set of monitored resources. The predicate is considered in violation when a time series for the specified metric of a monitored resource does not include any data in the specified duration. # A condition that checks that a time series continues to receive new data points.
            "filter": "A 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.
            "duration": "A 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. 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. The Duration.nanos field is ignored.
            "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations.
              "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
              "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
            },
            "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
          },
        },
      ],
    }</pre>
</div>

<div class="method">
    <code class="details" id="delete">delete(name, x__xgafv=None)</code>
  <pre>Deletes an alerting policy.

Args:
  name: string, The alerting policy to delete. The format is:
projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
For more information, see AlertPolicy. (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:
      # service Foo {
      #   rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);
      # }
      # The JSON representation for Empty is empty JSON object {}.
  }</pre>
</div>

<div class="method">
    <code class="details" id="get">get(name, x__xgafv=None)</code>
  <pre>Gets a single alerting policy.

Args:
  name: string, The alerting policy to retrieve. The format is
projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
 (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # 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. For an overview of alert policies, see Introduction to Alerting.
      "combiner": "A String", # How to combine the results of multiple conditions to determine if an incident should be opened.
      "displayName": "A 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.
      "name": "A String", # Required if the policy exists. The resource name for this policy. The syntax is:
          # projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
          # [ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request.
      "creationRecord": { # Describes a change made to a configuration. # 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.
        "mutatedBy": "A String", # The email address of the user making the change.
        "mutateTime": "A String", # When the change occurred.
      },
      "documentation": { # A content string and a MIME type that describes the content string's format. # Documentation that is included with notifications and incidents related to this policy. Best practice is for the documentation to include information to help responders understand, mitigate, escalate, and correct the underlying problems detected by the alerting policy. Notification channels that have limited capacity might not show this documentation.
        "mimeType": "A String", # The format of the content field. Presently, only the value "text/markdown" is supported. See Markdown (https://en.wikipedia.org/wiki/Markdown) for more information.
        "content": "A String", # The text of the documentation, interpreted according to mime_type. 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.
      },
      "enabled": True or False, # Whether or not the policy is enabled. On write, the default interpretation if unset is that the policy is enabled. On read, clients should not make any assumption about the state if it has not been populated. The field should always be populated on List and Get operations, unless a field projection has been specified that strips it out.
      "userLabels": { # User-supplied key/value data 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.
        "a_key": "A String",
      },
      "notificationChannels": [ # 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 ListNotificationChannels method. The syntax of the entries in this field is:
          # projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]
        "A String",
      ],
      "mutationRecord": { # Describes a change made to a configuration. # A read-only record of the most recent change to the alerting policy. If provided in a call to create or update, this field will be ignored.
        "mutatedBy": "A String", # The email address of the user making the change.
        "mutateTime": "A String", # When the change occurred.
      },
      "conditions": [ # A list of conditions for the policy. The conditions are combined by AND or OR according to the combiner field. If the combined conditions evaluate to true, then an incident is created. A policy can have from one to six conditions.
        { # A condition is a true/false test that determines when an alerting policy should open an incident. If a condition evaluates to true, it signifies that something is wrong.
          "conditionThreshold": { # A condition type that compares a collection of time series against a threshold. # A condition that compares a time series against a threshold.
            "comparison": "A 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.
            "denominatorFilter": "A 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.
            "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
            "filter": "A 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.
            "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
              "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
              "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
            },
            "denominatorAggregations": [ # Specifies the alignment of data points in individual time series selected by denominatorFilter as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resources).When computing ratios, the aggregations and denominator_aggregations fields must use the same alignment period and produce time series that have the same periodicity and labels.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
            "duration": "A 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.
            "thresholdValue": 3.14, # A value against which to compare the time series.
          },
          "displayName": "A 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": "A String", # Required if the condition exists. 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.When calling the alertPolicies.create method, do not include the name field in the conditions of the requested alerting policy. Stackdriver Monitoring creates the condition identifiers and includes them in the new policy.When calling the alertPolicies.update method to update a policy, including a condition name causes the existing condition to be updated. Conditions without names are added to the updated policy. Existing conditions are deleted if they are not updated.Best practice is to preserve [CONDITION_ID] if you make only small changes, such as those to condition thresholds, durations, or trigger values. Otherwise, treat the change as a new condition and let the existing condition be deleted.
          "conditionAbsent": { # A condition type that checks that monitored resources are reporting data. The configuration defines a metric and a set of monitored resources. The predicate is considered in violation when a time series for the specified metric of a monitored resource does not include any data in the specified duration. # A condition that checks that a time series continues to receive new data points.
            "filter": "A 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.
            "duration": "A 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. 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. The Duration.nanos field is ignored.
            "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations.
              "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
              "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
            },
            "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
          },
        },
      ],
    }</pre>
</div>

<div class="method">
    <code class="details" id="list">list(name, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None, filter=None)</code>
  <pre>Lists the existing alerting policies for the project.

Args:
  name: string, The project whose alert policies are to be listed. The format is
projects/[PROJECT_ID]
Note that this field names the parent container in which the alerting policies to be listed are stored. To retrieve a single alerting policy by name, use the GetAlertPolicy operation, instead. (required)
  orderBy: string, A comma-separated list of fields by which to sort the result. Supports the same set of field references as the filter field. Entries can be prefixed with a minus sign to sort by the field in descending order.For more details, see sorting and filtering.
  pageSize: integer, The maximum number of results to return in a single response.
  pageToken: string, If this field is not empty then it must contain the nextPageToken value returned by a previous call to this method. Using this field causes the method to return more results from the previous method call.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format
  filter: string, If provided, this field specifies the criteria that must be met by alert policies to be included in the response.For more details, see sorting and filtering.

Returns:
  An object of the form:

    { # The protocol for the ListAlertPolicies response.
    "nextPageToken": "A String", # If there might be more results than were returned, then this field is set to a non-empty value. To see the additional results, use that value as pageToken in the next call to this method.
    "alertPolicies": [ # The returned alert policies.
      { # 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. For an overview of alert policies, see Introduction to Alerting.
          "combiner": "A String", # How to combine the results of multiple conditions to determine if an incident should be opened.
          "displayName": "A 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.
          "name": "A String", # Required if the policy exists. The resource name for this policy. The syntax is:
              # projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
              # [ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request.
          "creationRecord": { # Describes a change made to a configuration. # 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.
            "mutatedBy": "A String", # The email address of the user making the change.
            "mutateTime": "A String", # When the change occurred.
          },
          "documentation": { # A content string and a MIME type that describes the content string's format. # Documentation that is included with notifications and incidents related to this policy. Best practice is for the documentation to include information to help responders understand, mitigate, escalate, and correct the underlying problems detected by the alerting policy. Notification channels that have limited capacity might not show this documentation.
            "mimeType": "A String", # The format of the content field. Presently, only the value "text/markdown" is supported. See Markdown (https://en.wikipedia.org/wiki/Markdown) for more information.
            "content": "A String", # The text of the documentation, interpreted according to mime_type. 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.
          },
          "enabled": True or False, # Whether or not the policy is enabled. On write, the default interpretation if unset is that the policy is enabled. On read, clients should not make any assumption about the state if it has not been populated. The field should always be populated on List and Get operations, unless a field projection has been specified that strips it out.
          "userLabels": { # User-supplied key/value data 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.
            "a_key": "A String",
          },
          "notificationChannels": [ # 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 ListNotificationChannels method. The syntax of the entries in this field is:
              # projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]
            "A String",
          ],
          "mutationRecord": { # Describes a change made to a configuration. # A read-only record of the most recent change to the alerting policy. If provided in a call to create or update, this field will be ignored.
            "mutatedBy": "A String", # The email address of the user making the change.
            "mutateTime": "A String", # When the change occurred.
          },
          "conditions": [ # A list of conditions for the policy. The conditions are combined by AND or OR according to the combiner field. If the combined conditions evaluate to true, then an incident is created. A policy can have from one to six conditions.
            { # A condition is a true/false test that determines when an alerting policy should open an incident. If a condition evaluates to true, it signifies that something is wrong.
              "conditionThreshold": { # A condition type that compares a collection of time series against a threshold. # A condition that compares a time series against a threshold.
                "comparison": "A 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.
                "denominatorFilter": "A 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.
                "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
                  { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                    "groupByFields": [ # 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.
                      "A String",
                    ],
                    "alignmentPeriod": "A 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.
                    "perSeriesAligner": "A 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.
                    "crossSeriesReducer": "A 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.
                  },
                ],
                "filter": "A 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.
                "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
                  "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
                  "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
                },
                "denominatorAggregations": [ # Specifies the alignment of data points in individual time series selected by denominatorFilter as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resources).When computing ratios, the aggregations and denominator_aggregations fields must use the same alignment period and produce time series that have the same periodicity and labels.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
                  { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                    "groupByFields": [ # 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.
                      "A String",
                    ],
                    "alignmentPeriod": "A 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.
                    "perSeriesAligner": "A 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.
                    "crossSeriesReducer": "A 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.
                  },
                ],
                "duration": "A 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.
                "thresholdValue": 3.14, # A value against which to compare the time series.
              },
              "displayName": "A 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": "A String", # Required if the condition exists. 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.When calling the alertPolicies.create method, do not include the name field in the conditions of the requested alerting policy. Stackdriver Monitoring creates the condition identifiers and includes them in the new policy.When calling the alertPolicies.update method to update a policy, including a condition name causes the existing condition to be updated. Conditions without names are added to the updated policy. Existing conditions are deleted if they are not updated.Best practice is to preserve [CONDITION_ID] if you make only small changes, such as those to condition thresholds, durations, or trigger values. Otherwise, treat the change as a new condition and let the existing condition be deleted.
              "conditionAbsent": { # A condition type that checks that monitored resources are reporting data. The configuration defines a metric and a set of monitored resources. The predicate is considered in violation when a time series for the specified metric of a monitored resource does not include any data in the specified duration. # A condition that checks that a time series continues to receive new data points.
                "filter": "A 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.
                "duration": "A 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. 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. The Duration.nanos field is ignored.
                "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations.
                  "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
                  "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
                },
                "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
                  { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                    "groupByFields": [ # 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.
                      "A String",
                    ],
                    "alignmentPeriod": "A 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.
                    "perSeriesAligner": "A 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.
                    "crossSeriesReducer": "A 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.
                  },
                ],
              },
            },
          ],
        },
    ],
  }</pre>
</div>

<div class="method">
    <code class="details" id="list_next">list_next(previous_request, previous_response)</code>
  <pre>Retrieves the next page of results.

Args:
  previous_request: The request for the previous page. (required)
  previous_response: The response from the request for the previous page. (required)

Returns:
  A request object that you can call 'execute()' on to request the next
  page. Returns None if there are no more items in the collection.
    </pre>
</div>

<div class="method">
    <code class="details" id="patch">patch(name, body, updateMask=None, x__xgafv=None)</code>
  <pre>Updates an alerting policy. You can either replace the entire policy with a new one or replace only certain fields in the current alerting policy by specifying the fields to be updated via updateMask. Returns the updated alerting policy.

Args:
  name: string, Required if the policy exists. The resource name for this policy. The syntax is:
projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
[ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request. (required)
  body: object, The request body. (required)
    The object takes the form of:

{ # 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. For an overview of alert policies, see Introduction to Alerting.
    "combiner": "A String", # How to combine the results of multiple conditions to determine if an incident should be opened.
    "displayName": "A 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.
    "name": "A String", # Required if the policy exists. The resource name for this policy. The syntax is:
        # projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
        # [ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request.
    "creationRecord": { # Describes a change made to a configuration. # 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.
      "mutatedBy": "A String", # The email address of the user making the change.
      "mutateTime": "A String", # When the change occurred.
    },
    "documentation": { # A content string and a MIME type that describes the content string's format. # Documentation that is included with notifications and incidents related to this policy. Best practice is for the documentation to include information to help responders understand, mitigate, escalate, and correct the underlying problems detected by the alerting policy. Notification channels that have limited capacity might not show this documentation.
      "mimeType": "A String", # The format of the content field. Presently, only the value "text/markdown" is supported. See Markdown (https://en.wikipedia.org/wiki/Markdown) for more information.
      "content": "A String", # The text of the documentation, interpreted according to mime_type. 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.
    },
    "enabled": True or False, # Whether or not the policy is enabled. On write, the default interpretation if unset is that the policy is enabled. On read, clients should not make any assumption about the state if it has not been populated. The field should always be populated on List and Get operations, unless a field projection has been specified that strips it out.
    "userLabels": { # User-supplied key/value data 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.
      "a_key": "A String",
    },
    "notificationChannels": [ # 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 ListNotificationChannels method. The syntax of the entries in this field is:
        # projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]
      "A String",
    ],
    "mutationRecord": { # Describes a change made to a configuration. # A read-only record of the most recent change to the alerting policy. If provided in a call to create or update, this field will be ignored.
      "mutatedBy": "A String", # The email address of the user making the change.
      "mutateTime": "A String", # When the change occurred.
    },
    "conditions": [ # A list of conditions for the policy. The conditions are combined by AND or OR according to the combiner field. If the combined conditions evaluate to true, then an incident is created. A policy can have from one to six conditions.
      { # A condition is a true/false test that determines when an alerting policy should open an incident. If a condition evaluates to true, it signifies that something is wrong.
        "conditionThreshold": { # A condition type that compares a collection of time series against a threshold. # A condition that compares a time series against a threshold.
          "comparison": "A 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.
          "denominatorFilter": "A 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.
          "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
            { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
              "groupByFields": [ # 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.
                "A String",
              ],
              "alignmentPeriod": "A 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.
              "perSeriesAligner": "A 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.
              "crossSeriesReducer": "A 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.
            },
          ],
          "filter": "A 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.
          "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
            "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
            "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
          },
          "denominatorAggregations": [ # Specifies the alignment of data points in individual time series selected by denominatorFilter as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resources).When computing ratios, the aggregations and denominator_aggregations fields must use the same alignment period and produce time series that have the same periodicity and labels.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
            { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
              "groupByFields": [ # 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.
                "A String",
              ],
              "alignmentPeriod": "A 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.
              "perSeriesAligner": "A 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.
              "crossSeriesReducer": "A 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.
            },
          ],
          "duration": "A 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.
          "thresholdValue": 3.14, # A value against which to compare the time series.
        },
        "displayName": "A 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": "A String", # Required if the condition exists. 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.When calling the alertPolicies.create method, do not include the name field in the conditions of the requested alerting policy. Stackdriver Monitoring creates the condition identifiers and includes them in the new policy.When calling the alertPolicies.update method to update a policy, including a condition name causes the existing condition to be updated. Conditions without names are added to the updated policy. Existing conditions are deleted if they are not updated.Best practice is to preserve [CONDITION_ID] if you make only small changes, such as those to condition thresholds, durations, or trigger values. Otherwise, treat the change as a new condition and let the existing condition be deleted.
        "conditionAbsent": { # A condition type that checks that monitored resources are reporting data. The configuration defines a metric and a set of monitored resources. The predicate is considered in violation when a time series for the specified metric of a monitored resource does not include any data in the specified duration. # A condition that checks that a time series continues to receive new data points.
          "filter": "A 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.
          "duration": "A 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. 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. The Duration.nanos field is ignored.
          "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations.
            "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
            "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
          },
          "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
            { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
              "groupByFields": [ # 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.
                "A String",
              ],
              "alignmentPeriod": "A 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.
              "perSeriesAligner": "A 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.
              "crossSeriesReducer": "A 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.
            },
          ],
        },
      },
    ],
  }

  updateMask: string, Optional. A list of alerting policy field names. If this field is not empty, each listed field in the existing alerting policy is set to the value of the corresponding field in the supplied policy (alert_policy), or to the field's default value if the field is not in the supplied alerting policy. Fields not listed retain their previous value.Examples of valid field masks include display_name, documentation, documentation.content, documentation.mime_type, user_labels, user_label.nameofkey, enabled, conditions, combiner, etc.If this field is empty, then the supplied alerting policy replaces the existing policy. It is the same as deleting the existing policy and adding the supplied policy, except for the following:
The new policy will have the same [ALERT_POLICY_ID] as the former policy. This gives you continuity with the former policy in your notifications and incidents.
Conditions in the new policy will keep their former [CONDITION_ID] if the supplied condition includes the name field with that [CONDITION_ID]. If the supplied condition omits the name field, then a new [CONDITION_ID] is created.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # 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. For an overview of alert policies, see Introduction to Alerting.
      "combiner": "A String", # How to combine the results of multiple conditions to determine if an incident should be opened.
      "displayName": "A 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.
      "name": "A String", # Required if the policy exists. The resource name for this policy. The syntax is:
          # projects/[PROJECT_ID]/alertPolicies/[ALERT_POLICY_ID]
          # [ALERT_POLICY_ID] is assigned by Stackdriver Monitoring when the policy is created. When calling the alertPolicies.create method, do not include the name field in the alerting policy passed as part of the request.
      "creationRecord": { # Describes a change made to a configuration. # 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.
        "mutatedBy": "A String", # The email address of the user making the change.
        "mutateTime": "A String", # When the change occurred.
      },
      "documentation": { # A content string and a MIME type that describes the content string's format. # Documentation that is included with notifications and incidents related to this policy. Best practice is for the documentation to include information to help responders understand, mitigate, escalate, and correct the underlying problems detected by the alerting policy. Notification channels that have limited capacity might not show this documentation.
        "mimeType": "A String", # The format of the content field. Presently, only the value "text/markdown" is supported. See Markdown (https://en.wikipedia.org/wiki/Markdown) for more information.
        "content": "A String", # The text of the documentation, interpreted according to mime_type. 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.
      },
      "enabled": True or False, # Whether or not the policy is enabled. On write, the default interpretation if unset is that the policy is enabled. On read, clients should not make any assumption about the state if it has not been populated. The field should always be populated on List and Get operations, unless a field projection has been specified that strips it out.
      "userLabels": { # User-supplied key/value data 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.
        "a_key": "A String",
      },
      "notificationChannels": [ # 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 ListNotificationChannels method. The syntax of the entries in this field is:
          # projects/[PROJECT_ID]/notificationChannels/[CHANNEL_ID]
        "A String",
      ],
      "mutationRecord": { # Describes a change made to a configuration. # A read-only record of the most recent change to the alerting policy. If provided in a call to create or update, this field will be ignored.
        "mutatedBy": "A String", # The email address of the user making the change.
        "mutateTime": "A String", # When the change occurred.
      },
      "conditions": [ # A list of conditions for the policy. The conditions are combined by AND or OR according to the combiner field. If the combined conditions evaluate to true, then an incident is created. A policy can have from one to six conditions.
        { # A condition is a true/false test that determines when an alerting policy should open an incident. If a condition evaluates to true, it signifies that something is wrong.
          "conditionThreshold": { # A condition type that compares a collection of time series against a threshold. # A condition that compares a time series against a threshold.
            "comparison": "A 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.
            "denominatorFilter": "A 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.
            "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
            "filter": "A 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.
            "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
              "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
              "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
            },
            "denominatorAggregations": [ # Specifies the alignment of data points in individual time series selected by denominatorFilter as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resources).When computing ratios, the aggregations and denominator_aggregations fields must use the same alignment period and produce time series that have the same periodicity and labels.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
            "duration": "A 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.
            "thresholdValue": 3.14, # A value against which to compare the time series.
          },
          "displayName": "A 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": "A String", # Required if the condition exists. 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.When calling the alertPolicies.create method, do not include the name field in the conditions of the requested alerting policy. Stackdriver Monitoring creates the condition identifiers and includes them in the new policy.When calling the alertPolicies.update method to update a policy, including a condition name causes the existing condition to be updated. Conditions without names are added to the updated policy. Existing conditions are deleted if they are not updated.Best practice is to preserve [CONDITION_ID] if you make only small changes, such as those to condition thresholds, durations, or trigger values. Otherwise, treat the change as a new condition and let the existing condition be deleted.
          "conditionAbsent": { # A condition type that checks that monitored resources are reporting data. The configuration defines a metric and a set of monitored resources. The predicate is considered in violation when a time series for the specified metric of a monitored resource does not include any data in the specified duration. # A condition that checks that a time series continues to receive new data points.
            "filter": "A 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.
            "duration": "A 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. 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. The Duration.nanos field is ignored.
            "trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations.
              "count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
              "percent": 3.14, # The percentage of time series that must fail the predicate for the condition to be triggered.
            },
            "aggregations": [ # Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series together (such as when aggregating multiple streams on each resource to a single stream for each resource or when aggregating streams across all members of a group of resrouces). Multiple aggregations are applied in the order specified.This field is similar to the one in the MetricService.ListTimeSeries request. It is advisable to use the ListTimeSeries method when debugging this field.
              { # Describes how to combine multiple time series to provide different views of the data. Aggregation consists of an alignment step on individual time series (alignment_period and per_series_aligner) followed by an optional reduction step of the data across the aligned time series (cross_series_reducer and group_by_fields). For more details, see Aggregation.
                "groupByFields": [ # 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.
                  "A String",
                ],
                "alignmentPeriod": "A 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.
                "perSeriesAligner": "A 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.
                "crossSeriesReducer": "A 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.
              },
            ],
          },
        },
      ],
    }</pre>
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