Package Classes (2.22.1)

Query object for retrieving metric data.

The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Cloud Monitoring. An alerting policy is 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. In addition to using this API, alert policies can also be managed through Cloud Monitoring <https://cloud.google.com/monitoring/docs/>, which can be reached by clicking the "Monitoring" tab in Cloud console <https://console.cloud.google.com/>.

The AlertPolicyService API is used to manage (list, create, delete, edit) alert policies in Cloud Monitoring. An alerting policy is 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. In addition to using this API, alert policies can also be managed through Cloud Monitoring <https://cloud.google.com/monitoring/docs/>, which can be reached by clicking the "Monitoring" tab in Cloud console <https://console.cloud.google.com/>.

A pager for iterating through list_alert_policies requests.

This class thinly wraps an initial ListAlertPoliciesResponse object, and provides an __aiter__ method to iterate through its alert_policies field.

If there are more pages, the __aiter__ method will make additional ListAlertPolicies requests and continue to iterate through the alert_policies field on the corresponding responses.

All the usual ListAlertPoliciesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_alert_policies requests.

This class thinly wraps an initial ListAlertPoliciesResponse object, and provides an __iter__ method to iterate through its alert_policies field.

If there are more pages, the __iter__ method will make additional ListAlertPolicies requests and continue to iterate through the alert_policies field on the corresponding responses.

All the usual ListAlertPoliciesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

The Group API lets you inspect and manage your groups <#google.monitoring.v3.Group>__.

A group is a named filter that is used to identify a collection of monitored resources. Groups are typically used to mirror the physical and/or logical topology of the environment. Because group membership is computed dynamically, monitored resources that are started in the future are automatically placed in matching groups. By using a group to name monitored resources in, for example, an alert policy, the target of that alert policy is updated automatically as monitored resources are added and removed from the infrastructure.

The Group API lets you inspect and manage your groups <#google.monitoring.v3.Group>__.

A group is a named filter that is used to identify a collection of monitored resources. Groups are typically used to mirror the physical and/or logical topology of the environment. Because group membership is computed dynamically, monitored resources that are started in the future are automatically placed in matching groups. By using a group to name monitored resources in, for example, an alert policy, the target of that alert policy is updated automatically as monitored resources are added and removed from the infrastructure.

A pager for iterating through list_group_members requests.

This class thinly wraps an initial ListGroupMembersResponse object, and provides an __aiter__ method to iterate through its members field.

If there are more pages, the __aiter__ method will make additional ListGroupMembers requests and continue to iterate through the members field on the corresponding responses.

All the usual ListGroupMembersResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_group_members requests.

This class thinly wraps an initial ListGroupMembersResponse object, and provides an __iter__ method to iterate through its members field.

If there are more pages, the __iter__ method will make additional ListGroupMembers requests and continue to iterate through the members field on the corresponding responses.

All the usual ListGroupMembersResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_groups requests.

This class thinly wraps an initial ListGroupsResponse object, and provides an __aiter__ method to iterate through its group field.

If there are more pages, the __aiter__ method will make additional ListGroups requests and continue to iterate through the group field on the corresponding responses.

All the usual ListGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_groups requests.

This class thinly wraps an initial ListGroupsResponse object, and provides an __iter__ method to iterate through its group field.

If there are more pages, the __iter__ method will make additional ListGroups requests and continue to iterate through the group field on the corresponding responses.

All the usual ListGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Manages metric descriptors, monitored resource descriptors, and time series data.

Manages metric descriptors, monitored resource descriptors, and time series data.

A pager for iterating through list_metric_descriptors requests.

This class thinly wraps an initial ListMetricDescriptorsResponse object, and provides an __aiter__ method to iterate through its metric_descriptors field.

If there are more pages, the __aiter__ method will make additional ListMetricDescriptors requests and continue to iterate through the metric_descriptors field on the corresponding responses.

All the usual ListMetricDescriptorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_metric_descriptors requests.

This class thinly wraps an initial ListMetricDescriptorsResponse object, and provides an __iter__ method to iterate through its metric_descriptors field.

If there are more pages, the __iter__ method will make additional ListMetricDescriptors requests and continue to iterate through the metric_descriptors field on the corresponding responses.

All the usual ListMetricDescriptorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_monitored_resource_descriptors requests.

This class thinly wraps an initial ListMonitoredResourceDescriptorsResponse object, and provides an __aiter__ method to iterate through its resource_descriptors field.

If there are more pages, the __aiter__ method will make additional ListMonitoredResourceDescriptors requests and continue to iterate through the resource_descriptors field on the corresponding responses.

All the usual ListMonitoredResourceDescriptorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_monitored_resource_descriptors requests.

This class thinly wraps an initial ListMonitoredResourceDescriptorsResponse object, and provides an __iter__ method to iterate through its resource_descriptors field.

If there are more pages, the __iter__ method will make additional ListMonitoredResourceDescriptors requests and continue to iterate through the resource_descriptors field on the corresponding responses.

All the usual ListMonitoredResourceDescriptorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_time_series requests.

This class thinly wraps an initial ListTimeSeriesResponse object, and provides an __aiter__ method to iterate through its time_series field.

If there are more pages, the __aiter__ method will make additional ListTimeSeries requests and continue to iterate through the time_series field on the corresponding responses.

All the usual ListTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_time_series requests.

This class thinly wraps an initial ListTimeSeriesResponse object, and provides an __iter__ method to iterate through its time_series field.

If there are more pages, the __iter__ method will make additional ListTimeSeries requests and continue to iterate through the time_series field on the corresponding responses.

All the usual ListTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

The Notification Channel API provides access to configuration that controls how messages related to incidents are sent.

The Notification Channel API provides access to configuration that controls how messages related to incidents are sent.

A pager for iterating through list_notification_channel_descriptors requests.

This class thinly wraps an initial ListNotificationChannelDescriptorsResponse object, and provides an __aiter__ method to iterate through its channel_descriptors field.

If there are more pages, the __aiter__ method will make additional ListNotificationChannelDescriptors requests and continue to iterate through the channel_descriptors field on the corresponding responses.

All the usual ListNotificationChannelDescriptorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_notification_channel_descriptors requests.

This class thinly wraps an initial ListNotificationChannelDescriptorsResponse object, and provides an __iter__ method to iterate through its channel_descriptors field.

If there are more pages, the __iter__ method will make additional ListNotificationChannelDescriptors requests and continue to iterate through the channel_descriptors field on the corresponding responses.

All the usual ListNotificationChannelDescriptorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_notification_channels requests.

This class thinly wraps an initial ListNotificationChannelsResponse object, and provides an __aiter__ method to iterate through its notification_channels field.

If there are more pages, the __aiter__ method will make additional ListNotificationChannels requests and continue to iterate through the notification_channels field on the corresponding responses.

All the usual ListNotificationChannelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_notification_channels requests.

This class thinly wraps an initial ListNotificationChannelsResponse object, and provides an __iter__ method to iterate through its notification_channels field.

If there are more pages, the __iter__ method will make additional ListNotificationChannels requests and continue to iterate through the notification_channels field on the corresponding responses.

All the usual ListNotificationChannelsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

The QueryService API is used to manage time series data in Cloud Monitoring. Time series data is a collection of data points that describes the time-varying values of a metric.

The QueryService API is used to manage time series data in Cloud Monitoring. Time series data is a collection of data points that describes the time-varying values of a metric.

A pager for iterating through query_time_series requests.

This class thinly wraps an initial QueryTimeSeriesResponse object, and provides an __aiter__ method to iterate through its time_series_data field.

If there are more pages, the __aiter__ method will make additional QueryTimeSeries requests and continue to iterate through the time_series_data field on the corresponding responses.

All the usual QueryTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through query_time_series requests.

This class thinly wraps an initial QueryTimeSeriesResponse object, and provides an __iter__ method to iterate through its time_series_data field.

If there are more pages, the __iter__ method will make additional QueryTimeSeries requests and continue to iterate through the time_series_data field on the corresponding responses.

All the usual QueryTimeSeriesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

The Cloud Monitoring Service-Oriented Monitoring API has endpoints for managing and querying aspects of a Metrics Scope's services. These include the Service's monitored resources, its Service-Level Objectives, and a taxonomy of categorized Health Metrics.

The Cloud Monitoring Service-Oriented Monitoring API has endpoints for managing and querying aspects of a Metrics Scope's services. These include the Service's monitored resources, its Service-Level Objectives, and a taxonomy of categorized Health Metrics.

A pager for iterating through list_service_level_objectives requests.

This class thinly wraps an initial ListServiceLevelObjectivesResponse object, and provides an __aiter__ method to iterate through its service_level_objectives field.

If there are more pages, the __aiter__ method will make additional ListServiceLevelObjectives requests and continue to iterate through the service_level_objectives field on the corresponding responses.

All the usual ListServiceLevelObjectivesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_service_level_objectives requests.

This class thinly wraps an initial ListServiceLevelObjectivesResponse object, and provides an __iter__ method to iterate through its service_level_objectives field.

If there are more pages, the __iter__ method will make additional ListServiceLevelObjectives requests and continue to iterate through the service_level_objectives field on the corresponding responses.

All the usual ListServiceLevelObjectivesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_services requests.

This class thinly wraps an initial ListServicesResponse object, and provides an __aiter__ method to iterate through its services field.

If there are more pages, the __aiter__ method will make additional ListServices requests and continue to iterate through the services field on the corresponding responses.

All the usual ListServicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_services requests.

This class thinly wraps an initial ListServicesResponse object, and provides an __iter__ method to iterate through its services field.

If there are more pages, the __iter__ method will make additional ListServices requests and continue to iterate through the services field on the corresponding responses.

All the usual ListServicesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

The SnoozeService API is used to temporarily prevent an alert policy from generating alerts. A Snooze is a description of the criteria under which one or more alert policies should not fire alerts for the specified duration.

The SnoozeService API is used to temporarily prevent an alert policy from generating alerts. A Snooze is a description of the criteria under which one or more alert policies should not fire alerts for the specified duration.

A pager for iterating through list_snoozes requests.

This class thinly wraps an initial ListSnoozesResponse object, and provides an __aiter__ method to iterate through its snoozes field.

If there are more pages, the __aiter__ method will make additional ListSnoozes requests and continue to iterate through the snoozes field on the corresponding responses.

All the usual ListSnoozesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_snoozes requests.

This class thinly wraps an initial ListSnoozesResponse object, and provides an __iter__ method to iterate through its snoozes field.

If there are more pages, the __iter__ method will make additional ListSnoozes requests and continue to iterate through the snoozes field on the corresponding responses.

All the usual ListSnoozesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

The UptimeCheckService API is used to manage (list, create, delete, edit) Uptime check configurations in the Cloud Monitoring product. An Uptime check is a piece of configuration that determines which resources and services to monitor for availability. These configurations can also be configured interactively by navigating to the Cloud console, selecting the appropriate project, clicking on "Monitoring" on the left-hand side to navigate to Cloud Monitoring, and then clicking on "Uptime".

The UptimeCheckService API is used to manage (list, create, delete, edit) Uptime check configurations in the Cloud Monitoring product. An Uptime check is a piece of configuration that determines which resources and services to monitor for availability. These configurations can also be configured interactively by navigating to the Cloud console, selecting the appropriate project, clicking on "Monitoring" on the left-hand side to navigate to Cloud Monitoring, and then clicking on "Uptime".

A pager for iterating through list_uptime_check_configs requests.

This class thinly wraps an initial ListUptimeCheckConfigsResponse object, and provides an __aiter__ method to iterate through its uptime_check_configs field.

If there are more pages, the __aiter__ method will make additional ListUptimeCheckConfigs requests and continue to iterate through the uptime_check_configs field on the corresponding responses.

All the usual ListUptimeCheckConfigsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_uptime_check_configs requests.

This class thinly wraps an initial ListUptimeCheckConfigsResponse object, and provides an __iter__ method to iterate through its uptime_check_configs field.

If there are more pages, the __iter__ method will make additional ListUptimeCheckConfigs requests and continue to iterate through the uptime_check_configs field on the corresponding responses.

All the usual ListUptimeCheckConfigsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_uptime_check_ips requests.

This class thinly wraps an initial ListUptimeCheckIpsResponse object, and provides an __aiter__ method to iterate through its uptime_check_ips field.

If there are more pages, the __aiter__ method will make additional ListUptimeCheckIps requests and continue to iterate through the uptime_check_ips field on the corresponding responses.

All the usual ListUptimeCheckIpsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

A pager for iterating through list_uptime_check_ips requests.

This class thinly wraps an initial ListUptimeCheckIpsResponse object, and provides an __iter__ method to iterate through its uptime_check_ips field.

If there are more pages, the __iter__ method will make additional ListUptimeCheckIps requests and continue to iterate through the uptime_check_ips field on the corresponding responses.

All the usual ListUptimeCheckIpsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Describes how to combine multiple time series to provide a different view of the data. Aggregation of time series is done in two steps. First, each time series in the set is aligned to the same time interval boundaries, then the set of time series is optionally reduced in number.

Alignment consists of applying the per_series_aligner operation to each time series after its data has been divided into regular alignment_period time intervals. This process takes all of the data points in an alignment period, applies a mathematical transformation such as averaging, minimum, maximum, delta, etc., and converts them into a single data point per period.

Reduction is when the aligned and transformed time series can optionally be combined, reducing the number of time series through similar mathematical transformations. Reduction involves applying a cross_series_reducer to all the time series, optionally sorting the time series into subsets with group_by_fields, and applying the reducer to each subset.

The raw time series data can contain a huge amount of information from multiple sources. Alignment and reduction transforms this mass of data into a more manageable and representative collection of data, for example "the 95% latency across the average of all tasks in a cluster". This representative data can be more easily graphed and comprehended, and the individual time series data is still available for later drilldown. For more details, see Filtering and aggregation <https://cloud.google.com/monitoring/api/v3/aggregation>__.

The Aligner specifies the operation that will be applied to the data points in each alignment period in a time series. Except for ALIGN_NONE, which specifies that no operation be applied, each alignment operation replaces the set of data values in each alignment period with a single value: the result of applying the operation to the data values. An aligned time series has a single data value at the end of each alignment_period.

An alignment operation can change the data type of the values, too. For example, if you apply a counting operation to boolean values, the data value_type in the original time series is BOOLEAN, but the value_type in the aligned result is INT64.

    This alignment is valid for
    `CUMULATIVE][google.api.MetricDescriptor.MetricKind.CUMULATIVE]`
    and `DELTA` metrics. If the selected alignment period
    results in periods with no data, then the aligned value for
    such a period is created by interpolation. The
    `value_type` of the aligned result is the same as the
    `value_type` of the input.
ALIGN_RATE (2):
    Align and convert to a rate. The result is computed as
    `rate = (y1 - y0)/(t1 - t0)`, or "delta over time". Think
    of this aligner as providing the slope of the line that
    passes through the value at the start and at the end of the
    `alignment_period`.

    This aligner is valid for `CUMULATIVE` and `DELTA`
    metrics with numeric values. If the selected alignment
    period results in periods with no data, then the aligned
    value for such a period is created by interpolation. The
    output is a `GAUGE` metric with `value_type` `DOUBLE`.

    If, by "rate", you mean "percentage change", see the
    `ALIGN_PERCENT_CHANGE` aligner instead.
ALIGN_INTERPOLATE (3):
    Align by interpolating between adjacent points around the
    alignment period boundary. This aligner is valid for
    `GAUGE` metrics with numeric values. The `value_type` of
    the aligned result is the same as the `value_type` of the
    input.
ALIGN_NEXT_OLDER (4):
    Align by moving the most recent data point before the end of
    the alignment period to the boundary at the end of the
    alignment period. This aligner is valid for `GAUGE`
    metrics. The `value_type` of the aligned result is the
    same as the `value_type` of the input.
ALIGN_MIN (10):
    Align the time series by returning the minimum value in each
    alignment period. This aligner is valid for `GAUGE` and
    `DELTA` metrics with numeric values. The `value_type` of
    the aligned result is the same as the `value_type` of the
    input.
ALIGN_MAX (11):
    Align the time series by returning the maximum value in each
    alignment period. This aligner is valid for `GAUGE` and
    `DELTA` metrics with numeric values. The `value_type` of
    the aligned result is the same as the `value_type` of the
    input.
ALIGN_MEAN (12):
    Align the time series by returning the mean value in each
    alignment period. This aligner is valid for `GAUGE` and
    `DELTA` metrics with numeric values. The `value_type` of
    the aligned result is `DOUBLE`.
ALIGN_COUNT (13):
    Align the time series by returning the number of values in
    each alignment period. This aligner is valid for `GAUGE`
    and `DELTA` metrics with numeric or Boolean values. The
    `value_type` of the aligned result is `INT64`.
ALIGN_SUM (14):
    Align the time series by returning the sum of the values in
    each alignment period. This aligner is valid for `GAUGE`
    and `DELTA` metrics with numeric and distribution values.
    The `value_type` of the aligned result is the same as the
    `value_type` of the input.
ALIGN_STDDEV (15):
    Align the time series by returning the standard deviation of
    the values in each alignment period. This aligner is valid
    for `GAUGE` and `DELTA` metrics with numeric values. The
    `value_type` of the output is `DOUBLE`.
ALIGN_COUNT_TRUE (16):
    Align the time series by returning the number of `True`
    values in each alignment period. This aligner is valid for
    `GAUGE` metrics with Boolean values. The `value_type` of
    the output is `INT64`.
ALIGN_COUNT_FALSE (24):
    Align the time series by returning the number of `False`
    values in each alignment period. This aligner is valid for
    `GAUGE` metrics with Boolean values. The `value_type` of
    the output is `INT64`.
ALIGN_FRACTION_TRUE (17):
    Align the time series by returning the ratio of the number
    of `True` values to the total number of values in each
    alignment period. This aligner is valid for `GAUGE`
    metrics with Boolean values. The output value is in the
    range [0.0, 1.0] and has `value_type` `DOUBLE`.
ALIGN_PERCENTILE_99 (18):
    Align the time series by using `percentile
    aggregation <https://en.wikipedia.org/wiki/Percentile>`__.
    The resulting data point in each alignment period is the
    99th percentile of all data points in the period. This
    aligner is valid for `GAUGE` and `DELTA` metrics with
    distribution values. The output is a `GAUGE` metric with
    `value_type` `DOUBLE`.
ALIGN_PERCENTILE_95 (19):
    Align the time series by using `percentile
    aggregation <https://en.wikipedia.org/wiki/Percentile>`__.
    The resulting data point in each alignment period is the
    95th percentile of all data points in the period. This
    aligner is valid for `GAUGE` and `DELTA` metrics with
    distribution values. The output is a `GAUGE` metric with
    `value_type` `DOUBLE`.
ALIGN_PERCENTILE_50 (20):
    Align the time series by using `percentile
    aggregation <https://en.wikipedia.org/wiki/Percentile>`__.
    The resulting data point in each alignment period is the
    50th percentile of all data points in the period. This
    aligner is valid for `GAUGE` and `DELTA` metrics with
    distribution values. The output is a `GAUGE` metric with
    `value_type` `DOUBLE`.
ALIGN_PERCENTILE_05 (21):
    Align the time series by using `percentile
    aggregation <https://en.wikipedia.org/wiki/Percentile>`__.
    The resulting data point in each alignment period is the 5th
    percentile of all data points in the period. This aligner is
    valid for `GAUGE` and `DELTA` metrics with distribution
    values. The output is a `GAUGE` metric with `value_type`
    `DOUBLE`.
ALIGN_PERCENT_CHANGE (23):
    Align and convert to a percentage change. This aligner is
    valid for `GAUGE` and `DELTA` metrics with numeric
    values. This alignment returns
    `((current - previous)/previous) * 100`, where the value
    of `previous` is determined based on the
    `alignment_period`.

    If the values of `current` and `previous` are both 0,
    then the returned value is 0. If only `previous` is 0, the
    returned value is infinity.

    A 10-minute moving mean is computed at each point of the
    alignment period prior to the above calculation to smooth
    the metric and prevent false positives from very short-lived
    spikes. The moving mean is only applicable for data whose
    values are `>= 0`. Any values `< 0` are treated as a
    missing datapoint, and are ignored. While `DELTA` metrics
    are accepted by this alignment, special care should be taken
    that the values for the metric will always be positive. The
    output is a `GAUGE` metric with `value_type` `DOUBLE`.

A Reducer operation describes how to aggregate data points from multiple time series into a single time series, where the value of each data point in the resulting series is a function of all the already aligned values in the input time series.

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 <https://cloud.google.com/monitoring/alerts/>__.

Control over how the notification channels in notification_channels are notified when this alert fires.

Control over how the notification channels in notification_channels are notified when this alert fires, on a per-channel basis.

Control over the rate of notifications sent to this alert policy's notification channels.

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

A condition control that determines how metric-threshold conditions are evaluated when data stops arriving. This control doesn't affect metric-absence policies.

A condition type that checks whether a log message in the scoping project <https://cloud.google.com/monitoring/api/v3#project_name>__ satisfies the given filter. Logs from other projects in the metrics scope are not evaluated.

The abstract base class for a message.

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 type that compares a collection of time series against a threshold.

Options used when forecasting the time series and testing the predicted value against the threshold.

A condition type that allows alert policies to be defined using Monitoring Query Language <https://cloud.google.com/monitoring/mql>__.

A condition type that allows alert policies to be defined using Prometheus Query Language (PromQL) <https://prometheus.io/docs/prometheus/latest/querying/basics/>__.

The PrometheusQueryLanguageCondition message contains information from a Prometheus alerting rule and its associated rule group.

A Prometheus alerting rule is described here <https://prometheus.io/docs/prometheus/latest/configuration/alerting_rules/>. The semantics of a Prometheus alerting rule is described here <https://prometheus.io/docs/prometheus/latest/configuration/recording_rules/#rule>.

A Prometheus rule group is described here <https://prometheus.io/docs/prometheus/latest/configuration/recording_rules/>. The semantics of a Prometheus rule group is described here <https://prometheus.io/docs/prometheus/latest/configuration/recording_rules/#rule_group>.

Because Cloud Alerting has no representation of a Prometheus rule group resource, we must embed the information of the parent rule group inside each of the conditions that refer to it. We must also update the contents of all Prometheus alerts in case the information of their rule group changes.

The PrometheusQueryLanguageCondition protocol buffer combines the information of the corresponding rule group and alerting rule. The structure of the PrometheusQueryLanguageCondition protocol buffer does NOT mimic the structure of the Prometheus rule group and alerting rule YAML declarations. The PrometheusQueryLanguageCondition protocol buffer may change in the future to support future rule group and/or alerting rule features. There are no new such features at the present time (2023-06-26).

The abstract base class for a message.

Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Operators for combining conditions.

Documentation that is included in the notifications and incidents pertaining to this policy.

Links to content such as playbooks, repositories, and other resources.

An enumeration of possible severity level for an Alert Policy.

The abstract base class for a message.

An SLI measuring performance on a well-known service type. Performance will be computed on the basis of pre-defined metrics. The type of the service_resource determines the metrics to use and the service_resource.labels and metric_labels are used to construct a monitoring filter to filter that metric down to just the data relevant to this service.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Future parameters for the availability SLI.

Parameters for a latency threshold SLI.

Specifies an ordering relationship on two arguments, called left and right.

The protocol for the CreateAlertPolicy request.

The CreateGroup request.

The CreateMetricDescriptor request.

The CreateNotificationChannel request.

The CreateServiceLevelObjective request.

The CreateService request.

The message definition for creating a Snooze. Users must provide the body of the Snooze to be created but must omit the Snooze field, name.

DEPRECATED. Used to hold per-time-series error status.

The CreateTimeSeries request.

Summary of the result of a failed request to write data to a time series.

Detailed information about an error category.

The protocol for the CreateUptimeCheckConfig request.

The protocol for the DeleteAlertPolicy request.

The DeleteGroup request. The default behavior is to be able to delete a single group without any descendants.

The DeleteMetricDescriptor request.

The DeleteNotificationChannel request.

The DeleteServiceLevelObjective request.

The DeleteService request.

The protocol for the DeleteUptimeCheckConfig request.

A DistributionCut defines a TimeSeries and thresholds used for measuring good service and total service. The TimeSeries must have ValueType = DISTRIBUTION and MetricKind = DELTA or MetricKind = CUMULATIVE. The computed good_service will be the estimated count of values in the Distribution that fall within the specified min and max.

A set of (label, value) pairs that were removed from a Distribution time series during aggregation and then added as an attachment to a Distribution.Exemplar.

The full label set for the exemplars is constructed by using the dropped pairs in combination with the label values that remain on the aggregated Distribution time series. The constructed full label set can be used to identify the specific entity, such as the instance or job, which might be contributing to a long-tail. However, with dropped labels, the storage requirements are reduced because only the aggregated distribution values for a large group of time series are stored.

Note that there are no guarantees on ordering of the labels from exemplar-to-exemplar and from distribution-to-distribution in the same stream, and there may be duplicates. It is up to clients to resolve any ambiguities.

The abstract base class for a message.

The protocol for the GetAlertPolicy request.

The GetGroup request.

The GetMetricDescriptor request.

The GetMonitoredResourceDescriptor request.

The GetNotificationChannelDescriptor response.

The GetNotificationChannel request.

The GetNotificationChannelVerificationCode request.

The GetNotificationChannelVerificationCode request.

The GetServiceLevelObjective request.

The GetService request.

The message definition for retrieving a Snooze. Users must specify the field, name, which identifies the Snooze.

The protocol for the GetUptimeCheckConfig request.

The description of a dynamic collection of monitored resources. Each group has a filter that is matched against monitored resources and their associated metadata. If a group's filter matches an available monitored resource, then that resource is a member of that group. Groups can contain any number of monitored resources, and each monitored resource can be a member of any number of groups.

Groups can be nested in parent-child hierarchies. The parentName field identifies an optional parent for each group. If a group has a parent, then the only monitored resources available to be matched by the group's filter are the resources contained in the parent group. In other words, a group contains the monitored resources that match its filter and the filters of all the group's ancestors. A group without a parent can contain any monitored resource.

For example, consider an infrastructure running a set of instances with two user-defined tags: "environment" and "role". A parent group has a filter, environment="production". A child of that parent group has a filter, role="transcoder". The parent group contains all instances in the production environment, regardless of their roles. The child group contains instances that have the transcoder role and are in the production environment.

The monitored resources contained in a group can change at any moment, depending on what resources exist and what filters are associated with the group and its ancestors.

The supported resource types that can be used as values of group_resource.resource_type. INSTANCE includes gce_instance and aws_ec2_instance resource types. The resource types gae_app and uptime_url are not valid here because group checks on App Engine modules and URLs are not allowed.

An internal checker allows Uptime checks to run on private/internal GCP resources.

Operational states for an internal checker.

A label value.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The protocol for the ListAlertPolicies request.

The protocol for the ListAlertPolicies response.

The ListGroupMembers request.

The ListGroupMembers response.

The ListGroup request.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The ListGroups response.

The ListMetricDescriptors request.

The ListMetricDescriptors response.

The ListMonitoredResourceDescriptors request.

The ListMonitoredResourceDescriptors response.

The ListNotificationChannelDescriptors request.

The ListNotificationChannelDescriptors response.

The ListNotificationChannels request.

The ListNotificationChannels response.

The ListServiceLevelObjectives request.

The ListServiceLevelObjectives response.

The ListServices request.

The ListServices response.

The message definition for listing Snooze\ s associated with the given parent, satisfying the optional filter.

The results of a successful ListSnoozes call, containing the matching Snooze\ s.

The ListTimeSeries request.

Controls which fields are returned by ListTimeSeries*.

The ListTimeSeries response.

The protocol for the ListUptimeCheckConfigs request.

The protocol for the ListUptimeCheckConfigs response.

The protocol for the ListUptimeCheckIps request.

The protocol for the ListUptimeCheckIps response.

Describes a change made to a configuration.

A NotificationChannel is a medium through which an alert is delivered when a policy violation is detected. Examples of channels include email, SMS, and third-party messaging applications. Fields containing sensitive information like authentication tokens or contact info are only partially populated on retrieval.

The abstract base class for a message.

The abstract base class for a message.

Indicates whether the channel has been verified or not. It is illegal to specify this field in a [CreateNotificationChannel][google.monitoring.v3.NotificationChannelService.CreateNotificationChannel] or an [UpdateNotificationChannel][google.monitoring.v3.NotificationChannelService.UpdateNotificationChannel] operation.

A description of a notification channel. The descriptor includes the properties of the channel and the set of labels or fields that must be specified to configure channels of a given type.

A single data point in a time series.

An error associated with a query in the time series query language format.

This is an error detail intended to be used with INVALID_ARGUMENT errors.

The QueryTimeSeries request.

The QueryTimeSeries response.

Range of numerical values within min and max.

Service Level Indicators for which atomic units of service are counted directly.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The SendNotificationChannelVerificationCode request.

A Service is a discrete, autonomous, and network-accessible unit, designed to solve an individual concern (Wikipedia <https://en.wikipedia.org/wiki/Service-orientation>__). In Cloud Monitoring, a Service acts as the root resource under which operational aspects of the service are accessible.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

App Engine service. Learn more at https://cloud.google.com/appengine.

A well-known service type, defined by its service type and service labels. Documentation and examples here <https://cloud.google.com/stackdriver/docs/solutions/slo-monitoring/api/api-structures#basic-svc-w-basic-sli>__.

The abstract base class for a message.

Cloud Endpoints service. Learn more at https://cloud.google.com/endpoints.

Cloud Run service. Learn more at https://cloud.google.com/run.

Istio service scoped to a single Kubernetes cluster. Learn more at https://istio.io. Clusters running OSS Istio will have their services ingested as this type.

Use a custom service to designate a service that you want to monitor when none of the other service types (like App Engine, Cloud Run, or a GKE type) matches your intended service.

GKE Namespace. The field names correspond to the resource metadata labels on monitored resources that fall under a namespace (for example, k8s_container or k8s_pod).

GKE Service. The "service" here represents a Kubernetes service object <https://kubernetes.io/docs/concepts/services-networking/service>. The field names correspond to the resource labels on `k8s_service monitored resources https://cloud.google.com/monitoring/api/resources#tag_k8s_service`.

A GKE Workload (Deployment, StatefulSet, etc). The field names correspond to the metadata labels on monitored resources that fall under a workload (for example, k8s_container or k8s_pod).

Canonical service scoped to an Istio mesh. Anthos clusters running ASM >= 1.6.8 will have their services ingested as this type.

Istio service scoped to an Istio mesh. Anthos clusters running ASM < 1.6.8 will have their services ingested as this type.

Configuration for how to query telemetry on a Service.

The abstract base class for a message.

A Service-Level Indicator (SLI) describes the "performance" of a service. For some services, the SLI is well-defined. In such cases, the SLI can be described easily by referencing the well-known SLI and providing the needed parameters. Alternatively, a "custom" SLI can be defined with a query to the underlying metric store. An SLI is defined to be good_service / total_service over any queried time interval. The value of performance always falls into the range 0 <= performance <= 1. A custom SLI describes how to compute this ratio, whether this is by dividing values from a pair of time series, cutting a Distribution into good and bad counts, or counting time windows in which the service complies with a criterion. For separation of concerns, a single Service-Level Indicator measures performance for only one aspect of service quality, such as fraction of successful queries or fast-enough queries.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

A Service-Level Objective (SLO) describes a level of desired good service. It consists of a service-level indicator (SLI), a performance goal, and a period over which the objective is to be evaluated against that goal. The SLO can use SLIs defined in a number of different manners. Typical SLOs might include "99% of requests in each rolling week have latency below 200 milliseconds" or "99.5% of requests in each calendar month return successfully."

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The abstract base class for a message.

ServiceLevelObjective.View determines what form of ServiceLevelObjective is returned from GetServiceLevelObjective, ListServiceLevelObjectives, and ListServiceLevelObjectiveVersions RPCs.

The tier of service for a Metrics Scope. Please see the service tiers documentation <https://cloud.google.com/monitoring/workspaces/tiers>__ for more details.

A Snooze will prevent any alerts from being opened, and close any that are already open. The Snooze will work on alerts that match the criteria defined in the Snooze. The Snooze will be active from interval.start_time through interval.end_time.

Criteria specific to the AlertPolicy\ s that this Snooze applies to. The Snooze will suppress alerts that come from one of the AlertPolicy\ s whose names are supplied.

The context of a span. This is attached to an Exemplar][google.api.Distribution.Exemplar] in Distribution][google.api.Distribution] values during aggregation.

It contains the name of a span with format:

::

projects/[PROJECT_ID_OR_NUMBER]/traces/[TRACE_ID]/spans/[SPAN_ID]

Describes a Synthetic Monitor to be invoked by Uptime.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

A Synthetic Monitor deployed to a Cloud Functions V2 instance.

A locator for text. Indicates a particular part of the text of a request or of an object referenced in the request.

For example, suppose the request field text contains:

text: "The quick brown fox jumps over the lazy dog."

Then the locator:

source: "text" start_position { line: 1 column: 17 } end_position { line: 1 column: 19 }

refers to the part of the text: "fox".

The position of a byte within the text.

Describes a time interval:

• Reads: A half-open time interval. It includes the end time but excludes the start time: (startTime, endTime]. The start time must be specified, must be earlier than the end time, and should be no older than the data retention period for the metric.

• Writes: A closed time interval. It extends from the start time to the end time, and includes both: [startTime, endTime]. Valid time intervals depend on the `MetricKind https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.metricDescriptors#MetricKind`__ of the metric value. The end time must not be earlier than the start time, and the end time must not be more than 25 hours in the past or more than five minutes in the future.

  • For GAUGE metrics, the startTime value is technically optional; if no value is specified, the start time defaults to the value of the end time, and the interval represents a single point in time. If both start and end times are specified, they must be identical. Such an interval is valid only for GAUGE metrics, which are point-in-time measurements. The end time of a new interval must be at least a millisecond after the end time of the previous interval.
  • For DELTA metrics, the start time and end time must specify a non-zero interval, with subsequent points specifying contiguous and non-overlapping intervals. For DELTA metrics, the start time of the next interval must be at least a millisecond after the end time of the previous interval.
  • For CUMULATIVE metrics, the start time and end time must specify a non-zero interval, with subsequent points specifying the same start time and increasing end times, until an event resets the cumulative value to zero and sets a new start time for the following points. The new start time must be at least a millisecond after the end time of the previous interval.
  • The start time of a new interval must be at least a millisecond after the end time of the previous interval because intervals are closed. If the start time of a new interval is the same as the end time of the previous interval, then data written at the new start time could overwrite data written at the previous end time.

A collection of data points that describes the time-varying values of a metric. A time series is identified by a combination of a fully-specified monitored resource and a fully-specified metric. This type is used for both listing and creating time series.

Represents the values of a time series associated with a TimeSeriesDescriptor.

A point's value columns and time interval. Each point has one or more point values corresponding to the entries in point_descriptors field in the TimeSeriesDescriptor associated with this object.

A descriptor for the labels and points in a time series.

A descriptor for the value columns in a data point.

A TimeSeriesRatio specifies two TimeSeries to use for computing the good_service / total_service ratio. The specified TimeSeries must have ValueType = DOUBLE or ValueType = INT64 and must have MetricKind = DELTA or MetricKind = CUMULATIVE. The TimeSeriesRatio must specify exactly two of good, bad, and total, and the relationship good_service + bad_service = total_service will be assumed.

A single strongly-typed value.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The protocol for the UpdateAlertPolicy request.

The UpdateGroup request.

The UpdateNotificationChannel request.

The UpdateServiceLevelObjective request.

The UpdateService request.

The message definition for updating a Snooze. The field, snooze.name identifies the Snooze to be updated. The remainder of snooze gives the content the Snooze in question will be assigned.

What fields can be updated depends on the start time and end time of the Snooze.

• end time is in the past: These Snooze\ s are considered read-only and cannot be updated.
• start time is in the past and end time is in the future: display_name and interval.end_time can be updated.
• start time is in the future: display_name, interval.start_time and interval.end_time can be updated.

The protocol for the UpdateUptimeCheckConfig request.

This message configures which resources and services to monitor for availability.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

What kind of checkers are available to be used by the check.

Optional. Used to perform content matching. This allows matching based on substrings and regular expressions, together with their negations. Only the first 4 MB of an HTTP or HTTPS check's response (and the first 1 MB of a TCP check's response) are examined for purposes of content matching.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Options to perform content matching.

Information needed to perform a JSONPath content match. Used for ContentMatcherOption::MATCHES_JSON_PATH and ContentMatcherOption::NOT_MATCHES_JSON_PATH.

Options to perform JSONPath content matching.

Information involved in an HTTP/HTTPS Uptime check request.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

The authentication parameters to provide to the specified resource or URL that requires a username and password. Currently, only Basic HTTP authentication <https://tools.ietf.org/html/rfc7617>__ is supported in Uptime checks.

Header options corresponding to the content type of a HTTP request body.

The abstract base class for a message.

The HTTP request method options.

A status to accept. Either a status code class like "2xx", or an integer status code like "200".

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

An HTTP status code class.

Contains information needed for generating an OpenID Connect token <https://developers.google.com/identity/protocols/OpenIDConnect>__. The OIDC token will be generated for the Monitoring service agent service account.

Type of authentication.

Information involved in sending ICMP pings alongside public HTTP/TCP checks. For HTTP, the pings are performed for each part of the redirect chain.

The resource submessage for group checks. It can be used instead of a monitored resource, when multiple resources are being monitored.

Information required for a TCP Uptime check request.

The abstract base class for a message.

Contains the region, location, and list of IP addresses where checkers in the location run from.

The regions from which an Uptime check can be run.

The VerifyNotificationChannel request.

A WindowsBasedSli defines good_service as the count of time windows for which the provided service was of good quality. Criteria for determining if service was good are embedded in the window_criterion.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

A MetricRange is used when each window is good when the value x of a single TimeSeries satisfies range.min <= x <= range.max. The provided TimeSeries must have ValueType = INT64 or ValueType = DOUBLE and MetricKind = GAUGE.

A PerformanceThreshold is used when each window is good when that window has a sufficiently high performance.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

Time series query for the Google Stackdriver Monitoring API (V3)_.

.. _Google Stackdriver Monitoring API (V3): https://cloud.google.com/monitoring/api/ref_v3/rest/v3/ projects.timeSeries/list

API documentation for monitoring_v3.services.alert_policy_service.pagers module.

API documentation for monitoring_v3.services.group_service.pagers module.

API documentation for monitoring_v3.services.metric_service.pagers module.

API documentation for monitoring_v3.services.notification_channel_service.pagers module.

API documentation for monitoring_v3.services.query_service.pagers module.

API documentation for monitoring_v3.services.service_monitoring_service.pagers module.

API documentation for monitoring_v3.services.snooze_service.pagers module.

API documentation for monitoring_v3.services.uptime_check_service.pagers module.