Package google.monitoring.v3

Index

MetricService (interface)
QueryService (interface)
Aggregation (message)
Aggregation.Aligner (enum)
Aggregation.Reducer (enum)
CreateMetricDescriptorRequest (message)
CreateTimeSeriesError (message)
CreateTimeSeriesRequest (message)
CreateTimeSeriesSummary (message)
CreateTimeSeriesSummary.Error (message)
DeleteMetricDescriptorRequest (message)
DroppedLabels (message)
GetMetricDescriptorRequest (message)
GetMonitoredResourceDescriptorRequest (message)
LabelValue (message)
ListMetricDescriptorsRequest (message)
ListMetricDescriptorsResponse (message)
ListMonitoredResourceDescriptorsRequest (message)
ListMonitoredResourceDescriptorsResponse (message)
ListTimeSeriesRequest (message)
ListTimeSeriesRequest.TimeSeriesView (enum)
ListTimeSeriesResponse (message)
Point (message)
QueryError (message)
QueryErrorList (message)
QueryTimeSeriesRequest (message) (deprecated)
QueryTimeSeriesResponse (message) (deprecated)
SpanContext (message)
TextLocator (message)
TextLocator.Position (message)
TimeInterval (message)
TimeSeries (message)
TimeSeriesData (message)
TimeSeriesData.PointData (message)
TimeSeriesDescriptor (message)
TimeSeriesDescriptor.ValueDescriptor (message)
TypedValue (message)

MetricService

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

CreateMetricDescriptor

CreateMetricDescriptor
`rpc CreateMetricDescriptor(CreateMetricDescriptorRequest) returns (MetricDescriptor)` Creates a new metric descriptor. The creation is executed asynchronously. User-created metric descriptors define custom metrics. The metric descriptor is updated if it already exists, except that metric labels are never removed. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.write` For more information, see the Authentication Overview.

rpc CreateMetricDescriptor(CreateMetricDescriptorRequest) returns (MetricDescriptor)

Creates a new metric descriptor. The creation is executed asynchronously. User-created metric descriptors define custom metrics. The metric descriptor is updated if it already exists, except that metric labels are never removed.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

CreateTimeSeries

CreateTimeSeries
`rpc CreateTimeSeries(CreateTimeSeriesRequest) returns (Empty)` Creates or adds data to one or more time series. The response is empty if all time series in the request were written. If any time series could not be written, a corresponding failure message is included in the error response. This method does not support resource locations constraint of an organization policy. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.write` For more information, see the Authentication Overview.

rpc CreateTimeSeries(CreateTimeSeriesRequest) returns (Empty)

Creates or adds data to one or more time series. The response is empty if all time series in the request were written. If any time series could not be written, a corresponding failure message is included in the error response. This method does not support resource locations constraint of an organization policy.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

DeleteMetricDescriptor

DeleteMetricDescriptor
`rpc DeleteMetricDescriptor(DeleteMetricDescriptorRequest) returns (Empty)` Deletes a metric descriptor. Only user-created custom metrics can be deleted. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` For more information, see the Authentication Overview.

rpc DeleteMetricDescriptor(DeleteMetricDescriptorRequest) returns (Empty)

Deletes a metric descriptor. Only user-created custom metrics can be deleted.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring

For more information, see the Authentication Overview.

GetMetricDescriptor

GetMetricDescriptor
`rpc GetMetricDescriptor(GetMetricDescriptorRequest) returns (MetricDescriptor)` Gets a single metric descriptor. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.read` `https://www.googleapis.com/auth/monitoring.write` For more information, see the Authentication Overview.

rpc GetMetricDescriptor(GetMetricDescriptorRequest) returns (MetricDescriptor)

Gets a single metric descriptor.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.read
https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

GetMonitoredResourceDescriptor

GetMonitoredResourceDescriptor
`rpc GetMonitoredResourceDescriptor(GetMonitoredResourceDescriptorRequest) returns (MonitoredResourceDescriptor)` Gets a single monitored resource descriptor. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.read` `https://www.googleapis.com/auth/monitoring.write` For more information, see the Authentication Overview.

rpc GetMonitoredResourceDescriptor(GetMonitoredResourceDescriptorRequest) returns (MonitoredResourceDescriptor)

Gets a single monitored resource descriptor.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.read
https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

ListMetricDescriptors

ListMetricDescriptors
`rpc ListMetricDescriptors(ListMetricDescriptorsRequest) returns (ListMetricDescriptorsResponse)` Lists metric descriptors that match a filter. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.read` `https://www.googleapis.com/auth/monitoring.write` For more information, see the Authentication Overview.

rpc ListMetricDescriptors(ListMetricDescriptorsRequest) returns (ListMetricDescriptorsResponse)

Lists metric descriptors that match a filter.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.read
https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

ListMonitoredResourceDescriptors

ListMonitoredResourceDescriptors
`rpc ListMonitoredResourceDescriptors(ListMonitoredResourceDescriptorsRequest) returns (ListMonitoredResourceDescriptorsResponse)` Lists monitored resource descriptors that match a filter. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.read` `https://www.googleapis.com/auth/monitoring.write` For more information, see the Authentication Overview.

rpc ListMonitoredResourceDescriptors(ListMonitoredResourceDescriptorsRequest) returns (ListMonitoredResourceDescriptorsResponse)

Lists monitored resource descriptors that match a filter.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.read
https://www.googleapis.com/auth/monitoring.write

For more information, see the Authentication Overview.

ListTimeSeries

ListTimeSeries
`rpc ListTimeSeries(ListTimeSeriesRequest) returns (ListTimeSeriesResponse)` Lists time series that match a filter. Authorization scopes Requires one of the following OAuth scopes: `https://www.googleapis.com/auth/cloud-platform` `https://www.googleapis.com/auth/monitoring` `https://www.googleapis.com/auth/monitoring.read` For more information, see the Authentication Overview.

rpc ListTimeSeries(ListTimeSeriesRequest) returns (ListTimeSeriesResponse)

Lists time series that match a filter.

Authorization scopes

Requires one of the following OAuth scopes:

https://www.googleapis.com/auth/cloud-platform
https://www.googleapis.com/auth/monitoring
https://www.googleapis.com/auth/monitoring.read

For more information, see the Authentication Overview.

QueryService

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.

QueryTimeSeries
This item is deprecated! The method `google.monitoring.v3.QueryService.QueryTimeSeries` is not available in Trusted Cloud by S3NS.

Aggregation

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.

Fields
`alignment_period`	`Duration` The `alignment_period` specifies a time interval, in seconds, that is used to divide the data in all the `time series` into consistent blocks of time. This will be done before the per-series aligner can be applied to the data. The value must be at least 60 seconds. If a per-series aligner other than `ALIGN_NONE` is specified, this field is required or an error is returned. If no per-series aligner is specified, or the aligner `ALIGN_NONE` is specified, then this field is ignored. The maximum value of the `alignment_period` is 104 weeks (2 years) for charts, and 90,000 seconds (25 hours) for alerting policies.
`per_series_aligner`	`Aligner` An `Aligner` describes how to bring the data points in a single time series into temporal alignment. Except for `ALIGN_NONE`, all alignments cause all the data points in an `alignment_period` to be mathematically grouped together, resulting in a single data point for each `alignment_period` with end timestamp at the end of the period. Not all alignment operations may be applied to all time series. The valid choices depend on the `metric_kind` and `value_type` of the original time series. Alignment can change the `metric_kind` or the `value_type` of the time series. Time series data must be aligned in order to perform cross-time series reduction. If `cross_series_reducer` is specified, then `per_series_aligner` must be specified and not equal to `ALIGN_NONE` and `alignment_period` must be specified; otherwise, an error is returned.
`cross_series_reducer`	`Reducer` The reduction operation to be used to combine 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. Not all reducer operations can be applied to all time series. The valid choices depend on the `metric_kind` and the `value_type` of the original time series. Reduction can yield a time series with a different `metric_kind` or `value_type` than the input time series. Time series data must first be aligned (see `per_series_aligner`) in order to perform cross-time series reduction. If `cross_series_reducer` is specified, then `per_series_aligner` must be specified, and must not be `ALIGN_NONE`. An `alignment_period` must also be specified; otherwise, an error is returned.
`group_by_fields[]`	`string` The set of fields to preserve when `cross_series_reducer` is specified. The `group_by_fields` determine how the time series are partitioned into subsets prior to applying the aggregation operation. 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 `cross_series_reducer` 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 `group_by_fields` are aggregated away. If `group_by_fields` 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 `cross_series_reducer` is not defined, this field is ignored.

Aligner

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.

Enums
`ALIGN_NONE`	No alignment. Raw data is returned. Not valid if cross-series reduction is requested. The `value_type` of the result is the same as the `value_type` of the input.
`ALIGN_DELTA`	Align and convert to `DELTA`. The output is `delta = y1 - y0`. This alignment is valid for `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`	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`	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`	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`	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`	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`	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`	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`	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`	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`	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`	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`	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`	Align the time series by using percentile aggregation. 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`	Align the time series by using percentile aggregation. 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`	Align the time series by using percentile aggregation. 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`	Align the time series by using percentile aggregation. 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`	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`.

Reducer

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.

Enums
`REDUCE_NONE`	No cross-time series reduction. The output of the `Aligner` is returned.
`REDUCE_MEAN`	Reduce by computing the mean value across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics with numeric or distribution values. The `value_type` of the output is `DOUBLE`.
`REDUCE_MIN`	Reduce by computing the minimum value across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics with numeric values. The `value_type` of the output is the same as the `value_type` of the input.
`REDUCE_MAX`	Reduce by computing the maximum value across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics with numeric values. The `value_type` of the output is the same as the `value_type` of the input.
`REDUCE_SUM`	Reduce by computing the sum across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics with numeric and distribution values. The `value_type` of the output is the same as the `value_type` of the input.
`REDUCE_STDDEV`	Reduce by computing the standard deviation across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics with numeric or distribution values. The `value_type` of the output is `DOUBLE`.
`REDUCE_COUNT`	Reduce by computing the number of data points across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics of numeric, Boolean, distribution, and string `value_type`. The `value_type` of the output is `INT64`.
`REDUCE_COUNT_TRUE`	Reduce by computing the number of `True`-valued data points across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics of Boolean `value_type`. The `value_type` of the output is `INT64`.
`REDUCE_COUNT_FALSE`	Reduce by computing the number of `False`-valued data points across time series for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics of Boolean `value_type`. The `value_type` of the output is `INT64`.
`REDUCE_FRACTION_TRUE`	Reduce by computing the ratio of the number of `True`-valued data points to the total number of data points for each alignment period. This reducer is valid for `DELTA` and `GAUGE` metrics of Boolean `value_type`. The output value is in the range [0.0, 1.0] and has `value_type` `DOUBLE`.
`REDUCE_PERCENTILE_99`	Reduce by computing the 99th percentile of data points across time series for each alignment period. This reducer is valid for `GAUGE` and `DELTA` metrics of numeric and distribution type. The value of the output is `DOUBLE`.
`REDUCE_PERCENTILE_95`	Reduce by computing the 95th percentile of data points across time series for each alignment period. This reducer is valid for `GAUGE` and `DELTA` metrics of numeric and distribution type. The value of the output is `DOUBLE`.
`REDUCE_PERCENTILE_50`	Reduce by computing the 50th percentile of data points across time series for each alignment period. This reducer is valid for `GAUGE` and `DELTA` metrics of numeric and distribution type. The value of the output is `DOUBLE`.
`REDUCE_PERCENTILE_05`	Reduce by computing the 5th percentile of data points across time series for each alignment period. This reducer is valid for `GAUGE` and `DELTA` metrics of numeric and distribution type. The value of the output is `DOUBLE`.

CreateMetricDescriptorRequest

The CreateMetricDescriptor request.

Fields

Fields
`name`	`string` Required. The project on which to execute the request. The format is: 4 projects/[PROJECT_ID_OR_NUMBER]
`metric_descriptor`	`MetricDescriptor` Required. The new custom metric descriptor.

name

string

Required. The project on which to execute the request. The format is: 4 projects/[PROJECT_ID_OR_NUMBER]

metric_descriptor

MetricDescriptor

Required. The new custom metric descriptor.

CreateTimeSeriesError

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

Fields

Fields
`time_series (deprecated)`	`TimeSeries` This item is deprecated! DEPRECATED. Time series ID that resulted in the `status` error.
`status (deprecated)`	`Status` This item is deprecated! DEPRECATED. The status of the requested write operation for `time_series`.

time_series
(deprecated)

TimeSeries

DEPRECATED. Time series ID that resulted in the status error.

status
(deprecated)

Status

DEPRECATED. The status of the requested write operation for time_series.

CreateTimeSeriesRequest

The CreateTimeSeries request.

Fields

name

string

Required. The project on which to execute the request. The format is:

projects/[PROJECT_ID_OR_NUMBER]

time_series[]

TimeSeries

Required. The new data to be added to a list of time series. Adds at most one data point to each of several time series. The new data point must be more recent than any other point in its time series. Each TimeSeries value must fully specify a unique time series by supplying all label values for the metric and the monitored resource.

The maximum number of TimeSeries objects per Create request is 200.

CreateTimeSeriesSummary

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

Fields

Fields
`total_point_count`	`int32` The number of points in the request.
`success_point_count`	`int32` The number of points that were successfully written.
`errors[]`	`Error` The number of points that failed to be written. Order is not guaranteed.

total_point_count

int32

The number of points in the request.

success_point_count

int32

The number of points that were successfully written.

errors[]

Error

The number of points that failed to be written. Order is not guaranteed.

Error

Detailed information about an error category.

Fields

Fields
`status`	`Status` The status of the requested write operation.
`point_count`	`int32` The number of points that couldn't be written because of `status`.

status

Status

The status of the requested write operation.

point_count

int32

The number of points that couldn't be written because of status.

DeleteMetricDescriptorRequest

The DeleteMetricDescriptor request.

Fields

Fields
`name`	`string` Required. The metric descriptor on which to execute the request. The format is: `projects/[PROJECT_ID_OR_NUMBER]/metricDescriptors/[METRIC_ID]` An example of `[METRIC_ID]` is: `"custom.googleapis.com/my_test_metric"`.

name

string

Required. The metric descriptor on which to execute the request. The format is:

projects/[PROJECT_ID_OR_NUMBER]/metricDescriptors/[METRIC_ID]

An example of [METRIC_ID] is: "custom.googleapis.com/my_test_metric".

DroppedLabels

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.

Fields

Fields
`label`	`map<string, string>` Map from label to its value, for all labels dropped in any aggregation.

label

map<string, string>

Map from label to its value, for all labels dropped in any aggregation.

GetMetricDescriptorRequest

The GetMetricDescriptor request.

Fields

Fields
`name`	`string` Required. The metric descriptor on which to execute the request. The format is: `projects/[PROJECT_ID_OR_NUMBER]/metricDescriptors/[METRIC_ID]` An example value of `[METRIC_ID]` is `"compute.googleapis.com/instance/disk/read_bytes_count"`.

name

string

Required. The metric descriptor on which to execute the request. The format is:

projects/[PROJECT_ID_OR_NUMBER]/metricDescriptors/[METRIC_ID]

An example value of [METRIC_ID] is "compute.googleapis.com/instance/disk/read_bytes_count".

GetMonitoredResourceDescriptorRequest

The GetMonitoredResourceDescriptor request.

Fields

Fields
`name`	`string` Required. The monitored resource descriptor to get. The format is: `projects/[PROJECT_ID_OR_NUMBER]/monitoredResourceDescriptors/[RESOURCE_TYPE]` The `[RESOURCE_TYPE]` is a predefined type, such as `cloudsql_database`.

name

string

Required. The monitored resource descriptor to get. The format is:

projects/[PROJECT_ID_OR_NUMBER]/monitoredResourceDescriptors/[RESOURCE_TYPE]

The [RESOURCE_TYPE] is a predefined type, such as cloudsql_database.

LabelValue

A label value.

Fields
Union field `value`. The label value can be a bool, int64, or string. `value` can be only one of the following:
`bool_value`	`bool` A bool label value.
`int64_value`	`int64` An int64 label value.
`string_value`	`string` A string label value.

ListMetricDescriptorsRequest

The ListMetricDescriptors request.

Fields
`name`	`string` Required. The project on which to execute the request. The format is: projects/[PROJECT_ID_OR_NUMBER]
`filter`	`string` Optional. If this field is empty, all custom and system-defined metric descriptors are returned. Otherwise, the filter specifies which metric descriptors are to be returned. For example, the following filter matches all custom metrics: metric.type = starts_with("custom.googleapis.com/")
`page_size`	`int32` Optional. A positive number that is the maximum number of results to return. The default and maximum value is 10,000. If a page_size <= 0 or > 10,000 is submitted, will instead return a maximum of 10,000 results.
`page_token`	`string` Optional. 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 additional results from the previous method call.
`active_only`	`bool` Optional. If true, only metrics and monitored resource types that have recent data (within roughly 25 hours) will be included in the response. - If a metric descriptor enumerates monitored resource types, only the monitored resource types for which the metric type has recent data will be included in the returned metric descriptor, and if none of them have recent data, the metric descriptor will not be returned. - If a metric descriptor does not enumerate the compatible monitored resource types, it will be returned only if the metric type has recent data for some monitored resource type. The returned descriptor will not enumerate any monitored resource types.

ListMetricDescriptorsResponse

The ListMetricDescriptors response.

Fields

Fields
`metric_descriptors[]`	`MetricDescriptor` The metric descriptors that are available to the project and that match the value of `filter`, if present.
`next_page_token`	`string` If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as `page_token` in the next call to this method.

metric_descriptors[]

MetricDescriptor

The metric descriptors that are available to the project and that match the value of filter, if present.

next_page_token

string

If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as page_token in the next call to this method.

ListMonitoredResourceDescriptorsRequest

The ListMonitoredResourceDescriptors request.

Fields
`name`	`string` Required. The project on which to execute the request. The format is: projects/[PROJECT_ID_OR_NUMBER]
`filter`	`string` An optional filter describing the descriptors to be returned. The filter can reference the descriptor's type and labels. For example, the following filter returns only Trusted Cloud Compute Engine descriptors that have an `id` label: `resource.type = starts_with("gce_") AND resource.label:id`
`page_size`	`int32` A positive number that is the maximum number of results to return.
`page_token`	`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 additional results from the previous method call.

ListMonitoredResourceDescriptorsResponse

The ListMonitoredResourceDescriptors response.

Fields

Fields
`resource_descriptors[]`	`MonitoredResourceDescriptor` The monitored resource descriptors that are available to this project and that match `filter`, if present.
`next_page_token`	`string` If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as `page_token` in the next call to this method.

resource_descriptors[]

MonitoredResourceDescriptor

The monitored resource descriptors that are available to this project and that match filter, if present.

next_page_token

string

If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as page_token in the next call to this method.

ListTimeSeriesRequest

The ListTimeSeries request.

Fields
`name`	`string` Required. The project, organization or folder on which to execute the request. The format is: projects/[PROJECT_ID_OR_NUMBER] organizations/[ORGANIZATION_ID] folders/[FOLDER_ID]
`filter`	`string` Required. A monitoring filter that specifies which time series should be returned. The filter must specify a single metric type, and can additionally specify metric labels and other information. For example: metric.type = "compute.googleapis.com/instance/cpu/usage_time" AND metric.labels.instance_name = "my-instance-name"
`interval`	`TimeInterval` Required. The time interval for which results should be returned. Only time series that contain data points in the specified interval are included in the response.
`aggregation`	`Aggregation` Specifies the alignment of data points in individual time series as well as how to combine the retrieved time series across specified labels. By default (if no `aggregation` is explicitly specified), the raw time series data is returned.
`secondary_aggregation`	`Aggregation` Apply a second aggregation after `aggregation` is applied. May only be specified if `aggregation` is specified.
`order_by`	`string` Unsupported: must be left blank. The points in each time series are currently returned in reverse time order (most recent to oldest).
`view`	`TimeSeriesView` Required. Specifies which information is returned about the time series.
`page_size`	`int32` A positive number that is the maximum number of results to return. If `page_size` is empty or more than 100,000 results, the effective `page_size` is 100,000 results. If `view` is set to `FULL`, this is the maximum number of `Points` returned. If `view` is set to `HEADERS`, this is the maximum number of `TimeSeries` returned.
`page_token`	`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 additional results from the previous method call.

TimeSeriesView

Controls which fields are returned by ListTimeSeries*.

Enums
`FULL`	Returns the identity of the metric(s), the time series, and the time series data.
`HEADERS`	Returns the identity of the metric and the time series resource, but not the time series data.

ListTimeSeriesResponse

The ListTimeSeries response.

Fields
`time_series[]`	`TimeSeries` One or more time series that match the filter included in the request.
`next_page_token`	`string` If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as `page_token` in the next call to this method.
`execution_errors[]`	`Status` Query execution errors that may have caused the time series data returned to be incomplete.
`unit`	`string` The unit in which all `time_series` point values are reported. `unit` follows the UCUM format for units as seen in https://unitsofmeasure.org/ucum.html. If different `time_series` have different units (for example, because they come from different metric types, or a unit is absent), then `unit` will be "{not_a_unit}".
`unreachable[]`	`string` Cloud regions that were unreachable which may have caused incomplete data to be returned.

Point

A single data point in a time series.

Fields

Fields
`interval`	`TimeInterval` The time interval to which the data point applies. For `GAUGE` metrics, the start time is optional, but if it is supplied, it must equal the end time. For `DELTA` metrics, the start and end time should specify a non-zero interval, with subsequent points specifying contiguous and non-overlapping intervals. For `CUMULATIVE` metrics, the start and end time should 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.
`value`	`TypedValue` The value of the data point.

interval

TimeInterval

The time interval to which the data point applies. For GAUGE metrics, the start time is optional, but if it is supplied, it must equal the end time. For DELTA metrics, the start and end time should specify a non-zero interval, with subsequent points specifying contiguous and non-overlapping intervals. For CUMULATIVE metrics, the start and end time should 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.

value

TypedValue

The value of the data point.

QueryError

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

Fields

Fields
`locator`	`TextLocator` The location of the time series query language text that this error applies to.
`message`	`string` The error message.

locator

TextLocator

The location of the time series query language text that this error applies to.

message

string

The error message.

QueryErrorList

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

Fields

Fields
`errors[]`	`QueryError` Errors in parsing the time series query language text. The number of errors in the response may be limited.
`error_summary`	`string` A summary of all the errors.

errors[]

QueryError

Errors in parsing the time series query language text. The number of errors in the response may be limited.

error_summary

string

A summary of all the errors.

QueryTimeSeriesRequest

The QueryTimeSeries request. For information about the status of Monitoring Query Language (MQL), see the MQL deprecation notice.

Fields
`name`	`string` Required. The project on which to execute the request. The format is: `projects/[PROJECT_ID_OR_NUMBER]`
`query`	`string` Required. The query in the Monitoring Query Language format. The default time zone is in UTC.
`page_size`	`int32` A positive number that is the maximum number of time_series_data to return.
`page_token`	`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 additional results from the previous method call.

QueryTimeSeriesResponse

The QueryTimeSeries response. For information about the status of Monitoring Query Language (MQL), see the MQL deprecation notice.

Fields
`time_series_descriptor`	`TimeSeriesDescriptor` The descriptor for the time series data.
`time_series_data[]`	`TimeSeriesData` The time series data.
`next_page_token`	`string` If there are more results than have been returned, then this field is set to a non-empty value. To see the additional results, use that value as `page_token` in the next call to this method.
`partial_errors[]`	`Status` Query execution errors that may have caused the time series data returned to be incomplete. The available data will be available in the response.

SpanContext

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

It contains the name of a span with format:

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

Fields

Fields
`span_name`	`string` The resource name of the span. The format is: `projects/[PROJECT_ID_OR_NUMBER]/traces/[TRACE_ID]/spans/[SPAN_ID]` `[TRACE_ID]` is a unique identifier for a trace within a project; it is a 32-character hexadecimal encoding of a 16-byte array. `[SPAN_ID]` is a unique identifier for a span within a trace; it is a 16-character hexadecimal encoding of an 8-byte array.

span_name

string

The resource name of the span. The format is:

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

[TRACE_ID] is a unique identifier for a trace within a project; it is a 32-character hexadecimal encoding of a 16-byte array.

[SPAN_ID] is a unique identifier for a span within a trace; it is a 16-character hexadecimal encoding of an 8-byte array.

TextLocator

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".

Fields
`source`	`string` The source of the text. The source may be a field in the request, in which case its format is the format of the google.rpc.BadRequest.FieldViolation.field field in https://documentation.s3ns.fr/apis/design/errors#error_details. It may also be be a source other than the request field (e.g. a macro definition referenced in the text of the query), in which case this is the name of the source (e.g. the macro name).
`start_position`	`Position` The position of the first byte within the text.
`end_position`	`Position` The position of the last byte within the text.
`nested_locator`	`TextLocator` If `source`, `start_position`, and `end_position` describe a call on some object (e.g. a macro in the time series query language text) and a location is to be designated in that object's text, `nested_locator` identifies the location within that object.
`nesting_reason`	`string` When `nested_locator` is set, this field gives the reason for the nesting. Usually, the reason is a macro invocation. In that case, the macro name (including the leading '@') signals the location of the macro call in the text and a macro argument name (including the leading '$') signals the location of the macro argument inside the macro body that got substituted away.

Position

The position of a byte within the text.

Fields

Fields
`line`	`int32` The line, starting with 1, where the byte is positioned.
`column`	`int32` The column within the line, starting with 1, where the byte is positioned. This is a byte index even though the text is UTF-8.

line

int32

The line, starting with 1, where the byte is positioned.

column

int32

The column within the line, starting with 1, where the byte is positioned. This is a byte index even though the text is UTF-8.

TimeInterval

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 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.

Fields

Fields
`end_time`	`Timestamp` Required. The end of the time interval.
`start_time`	`Timestamp` Optional. The beginning of the time interval. The default value for the start time is the end time. The start time must not be later than the end time.

end_time

Timestamp

Required. The end of the time interval.

start_time

Timestamp

Optional. The beginning of the time interval. The default value for the start time is the end time. The start time must not be later than the end time.

TimeSeries

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.

Fields
`metric`	`Metric` The associated metric. A fully-specified metric used to identify the time series.
`resource`	`MonitoredResource` The associated monitored resource. Custom metrics can use only certain monitored resource types in their time series data. For more information, see Monitored resources for custom metrics.
`metadata`	`MonitoredResourceMetadata` Output only. The associated monitored resource metadata. When reading a time series, this field will include metadata labels that are explicitly named in the reduction. When creating a time series, this field is ignored.
`metric_kind`	`MetricKind` The metric kind of the time series. When listing time series, this metric kind might be different from the metric kind of the associated metric if this time series is an alignment or reduction of other time series. When creating a time series, this field is optional. If present, it must be the same as the metric kind of the associated metric. If the associated metric's descriptor must be auto-created, then this field specifies the metric kind of the new descriptor and must be either `GAUGE` (the default) or `CUMULATIVE`.
`value_type`	`ValueType` The value type of the time series. When listing time series, this value type might be different from the value type of the associated metric if this time series is an alignment or reduction of other time series. When creating a time series, this field is optional. If present, it must be the same as the type of the data in the `points` field.
`points[]`	`Point` The data points of this time series. When listing time series, points are returned in reverse time order. When creating a time series, this field must contain exactly one point and the point's type must be the same as the value type of the associated metric. If the associated metric's descriptor must be auto-created, then the value type of the descriptor is determined by the point's type, which must be `BOOL`, `INT64`, `DOUBLE`, or `DISTRIBUTION`.
`unit`	`string` The units in which the metric value is reported. It is only applicable if the `value_type` is `INT64`, `DOUBLE`, or `DISTRIBUTION`. The `unit` defines the representation of the stored metric values. This field can only be changed through CreateTimeSeries when it is empty.
`description`	`string` Input only. A detailed description of the time series that will be associated with the `google.api.MetricDescriptor` for the metric. Once set, this field cannot be changed through CreateTimeSeries.

TimeSeriesData

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

Fields

Fields
`label_values[]`	`LabelValue` The values of the labels in the time series identifier, given in the same order as the `label_descriptors` field of the TimeSeriesDescriptor associated with this object. Each value must have a value of the type given in the corresponding entry of `label_descriptors`.
`point_data[]`	`PointData` The points in the time series.

label_values[]

LabelValue

The values of the labels in the time series identifier, given in the same order as the label_descriptors field of the TimeSeriesDescriptor associated with this object. Each value must have a value of the type given in the corresponding entry of label_descriptors.

point_data[]

PointData

The points in the time series.

PointData

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.

Fields

Fields
`values[]`	`TypedValue` The values that make up the point.
`time_interval`	`TimeInterval` The time interval associated with the point.

values[]

TypedValue

The values that make up the point.

time_interval

TimeInterval

The time interval associated with the point.

TimeSeriesDescriptor

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

Fields

Fields
`label_descriptors[]`	`LabelDescriptor` Descriptors for the labels.
`point_descriptors[]`	`ValueDescriptor` Descriptors for the point data value columns.

label_descriptors[]

LabelDescriptor

Descriptors for the labels.

point_descriptors[]

ValueDescriptor

Descriptors for the point data value columns.

ValueDescriptor

A descriptor for the value columns in a data point.

Fields
`key`	`string` The value key.
`value_type`	`ValueType` The value type.
`metric_kind`	`MetricKind` The value stream kind.
`unit`	`string` The unit in which `time_series` point values are reported. `unit` follows the UCUM format for units as seen in https://unitsofmeasure.org/ucum.html. `unit` is only valid if `value_type` is INTEGER, DOUBLE, DISTRIBUTION.

TypedValue

A single strongly-typed value.

Fields
Union field `value`. The typed value field. `value` can be only one of the following:
`bool_value`	`bool` A Boolean value: `true` or `false`.
`int64_value`	`int64` A 64-bit integer. Its range is approximately ±9.2x10¹⁸.
`double_value`	`double` A 64-bit double-precision floating-point number. Its magnitude is approximately ±10^±300 and it has 16 significant digits of precision.
`string_value`	`string` A variable-length string value.
`distribution_value`	`Distribution` A distribution value.