google. api
Enumerations
MetricKind
number
The kind of measurement. It describes how the data is reported.
Value 


METRIC_KIND_UNSPECIFIED 
Do not use this default value. 
GAUGE 
An instantaneous measurement of a value. 
DELTA 
The change in a value during a time interval. 
CUMULATIVE 
A value accumulated over a time interval. Cumulative measurements in a time series should have 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. 
MetricKind
number
The kind of measurement. It describes how the data is reported.
Value 


METRIC_KIND_UNSPECIFIED 
Do not use this default value. 
GAUGE 
An instantaneous measurement of a value. 
DELTA 
The change in a value during a time interval. 
CUMULATIVE 
A value accumulated over a time interval. Cumulative measurements in a time series should have 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. 
ValueType
number
The value type of a metric.
Value 


VALUE_TYPE_UNSPECIFIED 
Do not use this default value. 
BOOL 
The value is a boolean. This value type can be used only if the metric kind is 
INT64 
The value is a signed 64bit integer. 
DOUBLE 
The value is a double precision floating point number. 
STRING 
The value is a text string. This value type can be used only if the metric kind is 
DISTRIBUTION 
The value is a 
MONEY 
The value is money. 
ValueType
number
The value type of a metric.
Value 


VALUE_TYPE_UNSPECIFIED 
Do not use this default value. 
BOOL 
The value is a boolean. This value type can be used only if the metric kind is 
INT64 
The value is a signed 64bit integer. 
DOUBLE 
The value is a double precision floating point number. 
STRING 
The value is a text string. This value type can be used only if the metric kind is 
DISTRIBUTION 
The value is a 
MONEY 
The value is money. 
ValueType
number
Value types that can be used as label values.
Value 


STRING 
A variablelength string. This is the default. 
BOOL 
Boolean; true or false. 
INT64 
A 64bit signed integer. 
ValueType
number
Value types that can be used as label values.
Value 


STRING 
A variablelength string. This is the default. 
BOOL 
Boolean; true or false. 
INT64 
A 64bit signed integer. 
Properties
MetricKind
number
The kind of measurement. It describes how the data is reported.
Value 


METRIC_KIND_UNSPECIFIED 
Do not use this default value. 
GAUGE 
An instantaneous measurement of a value. 
DELTA 
The change in a value during a time interval. 
CUMULATIVE 
A value accumulated over a time interval. Cumulative measurements in a time series should have 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. 
MetricKind
number
The kind of measurement. It describes how the data is reported.
Value 


METRIC_KIND_UNSPECIFIED 
Do not use this default value. 
GAUGE 
An instantaneous measurement of a value. 
DELTA 
The change in a value during a time interval. 
CUMULATIVE 
A value accumulated over a time interval. Cumulative measurements in a time series should have 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. 
ValueType
number
The value type of a metric.
Value 


VALUE_TYPE_UNSPECIFIED 
Do not use this default value. 
BOOL 
The value is a boolean. This value type can be used only if the metric kind is 
INT64 
The value is a signed 64bit integer. 
DOUBLE 
The value is a double precision floating point number. 
STRING 
The value is a text string. This value type can be used only if the metric kind is 
DISTRIBUTION 
The value is a 
MONEY 
The value is money. 
ValueType
number
The value type of a metric.
Value 


VALUE_TYPE_UNSPECIFIED 
Do not use this default value. 
BOOL 
The value is a boolean. This value type can be used only if the metric kind is 
INT64 
The value is a signed 64bit integer. 
DOUBLE 
The value is a double precision floating point number. 
STRING 
The value is a text string. This value type can be used only if the metric kind is 
DISTRIBUTION 
The value is a 
MONEY 
The value is money. 
ValueType
number
Value types that can be used as label values.
Value 


STRING 
A variablelength string. This is the default. 
BOOL 
Boolean; true or false. 
INT64 
A 64bit signed integer. 
ValueType
number
Value types that can be used as label values.
Value 


STRING 
A variablelength string. This is the default. 
BOOL 
Boolean; true or false. 
INT64 
A 64bit signed integer. 
Abstract types
BucketOptions
BucketOptions
describes the bucket boundaries used to create a histogram for the distribution. The buckets can be in a linear sequence, an exponential sequence, or each bucket can be specified explicitly.
BucketOptions
does not include the number of values in each bucket.
A bucket has an inclusive lower bound and exclusive upper bound for the values that are counted for that bucket. The upper bound of a bucket must be strictly greater than the lower bound. The sequence of N buckets for a distribution consists of an underflow bucket (number 0), zero or more finite buckets (number 1 through N  2) and an overflow bucket (number N  1). The buckets are contiguous: the lower bound of bucket i (i > 0) is the same as the upper bound of bucket i  1. The buckets span the whole range of finite values: lower bound of the underflow bucket is infinity and the upper bound of the overflow bucket is +infinity. The finite buckets are socalled because both bounds are finite.
Properties
Parameter 


linearBuckets 
Object The linear bucket. This object should have the same structure as Linear 
exponentialBuckets 
Object The exponential buckets. This object should have the same structure as Exponential 
explicitBuckets 
Object The explicit buckets. This object should have the same structure as Explicit 
BucketOptions
BucketOptions
describes the bucket boundaries used to create a histogram for the distribution. The buckets can be in a linear sequence, an exponential sequence, or each bucket can be specified explicitly.
BucketOptions
does not include the number of values in each bucket.
A bucket has an inclusive lower bound and exclusive upper bound for the values that are counted for that bucket. The upper bound of a bucket must be strictly greater than the lower bound. The sequence of N buckets for a distribution consists of an underflow bucket (number 0), zero or more finite buckets (number 1 through N  2) and an overflow bucket (number N  1). The buckets are contiguous: the lower bound of bucket i (i > 0) is the same as the upper bound of bucket i  1. The buckets span the whole range of finite values: lower bound of the underflow bucket is infinity and the upper bound of the overflow bucket is +infinity. The finite buckets are socalled because both bounds are finite.
Properties
Parameter 


linearBuckets 
Object The linear bucket. This object should have the same structure as Linear 
exponentialBuckets 
Object The exponential buckets. This object should have the same structure as Exponential 
explicitBuckets 
Object The explicit buckets. This object should have the same structure as Explicit 
Distribution
Distribution
contains summary statistics for a population of values. It optionally contains a histogram representing the distribution of those values across a set of buckets.
The summary statistics are the count, mean, sum of the squared deviation from the mean, the minimum, and the maximum of the set of population of values. The histogram is based on a sequence of buckets and gives a count of values that fall into each bucket. The boundaries of the buckets are given either explicitly or by formulas for buckets of fixed or exponentially increasing widths.
Although it is not forbidden, it is generally a bad idea to include nonfinite values (infinities or NaNs) in the population of values, as this will render the mean
and sum_of_squared_deviation
fields meaningless.
Properties
Parameter 


count 
number The number of values in the population. Must be nonnegative. This value must equal the sum of the values in 
mean 
number The arithmetic mean of the values in the population. If 
sumOfSquaredDeviation 
number The sum of squared deviations from the mean of the values in the population. For values x_i this is:
Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition describes Welford's method for accumulating this sum in one pass. If 
range 
Object If specified, contains the range of the population values. The field must not be present if the This object should have the same structure as Range 
bucketOptions 
Object Defines the histogram bucket boundaries. If the distribution does not contain a histogram, then omit this field. This object should have the same structure as BucketOptions 
bucketCounts 
Array of number The number of values in each bucket of the histogram, as described in
If present, The order of the values in 
exemplars 
Array of Object Must be in increasing order of This object should have the same structure as Exemplar 
Distribution
Distribution
contains summary statistics for a population of values. It optionally contains a histogram representing the distribution of those values across a set of buckets.
The summary statistics are the count, mean, sum of the squared deviation from the mean, the minimum, and the maximum of the set of population of values. The histogram is based on a sequence of buckets and gives a count of values that fall into each bucket. The boundaries of the buckets are given either explicitly or by formulas for buckets of fixed or exponentially increasing widths.
Although it is not forbidden, it is generally a bad idea to include nonfinite values (infinities or NaNs) in the population of values, as this will render the mean
and sum_of_squared_deviation
fields meaningless.
Properties
Parameter 


count 
number The number of values in the population. Must be nonnegative. This value must equal the sum of the values in 
mean 
number The arithmetic mean of the values in the population. If 
sumOfSquaredDeviation 
number The sum of squared deviations from the mean of the values in the population. For values x_i this is:
Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition describes Welford's method for accumulating this sum in one pass. If 
range 
Object If specified, contains the range of the population values. The field must not be present if the This object should have the same structure as Range 
bucketOptions 
Object Defines the histogram bucket boundaries. If the distribution does not contain a histogram, then omit this field. This object should have the same structure as BucketOptions 
bucketCounts 
Array of number The number of values in each bucket of the histogram, as described in
If present, The order of the values in 
exemplars 
Array of Object Must be in increasing order of This object should have the same structure as Exemplar 
Exemplar
Exemplars are example points that may be used to annotate aggregated distribution values. They are metadata that gives information about a particular value added to a Distribution bucket, such as a trace ID that was active when a value was added. They may contain further information, such as a example values and timestamps, origin, etc.
Properties
Parameter 


value 
number Value of the exemplar point. This value determines to which bucket the exemplar belongs. 
timestamp 
Object The observation (sampling) time of the above value. This object should have the same structure as Timestamp 
attachments 
Array of Object Contextual information about the example value. Examples are:
There may be only a single attachment of any given message type in a single exemplar, and this is enforced by the system. This object should have the same structure as Any 
Exemplar
Exemplars are example points that may be used to annotate aggregated distribution values. They are metadata that gives information about a particular value added to a Distribution bucket, such as a trace ID that was active when a value was added. They may contain further information, such as a example values and timestamps, origin, etc.
Properties
Parameter 


value 
number Value of the exemplar point. This value determines to which bucket the exemplar belongs. 
timestamp 
Object The observation (sampling) time of the above value. This object should have the same structure as Timestamp 
attachments 
Array of Object Contextual information about the example value. Examples are:
There may be only a single attachment of any given message type in a single exemplar, and this is enforced by the system. This object should have the same structure as Any 
Explicit
Specifies a set of buckets with arbitrary widths.
There are size(bounds) + 1
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): bounds[i] Lower bound (1 <= i < N); bounds[i  1]
The bounds
field must contain at least one element. If bounds
has only one element, then there are no finite buckets, and that single element is the common boundary of the overflow and underflow buckets.
Property
Parameter 


bounds 
Array of number The values must be monotonically increasing. 
Explicit
Specifies a set of buckets with arbitrary widths.
There are size(bounds) + 1
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): bounds[i] Lower bound (1 <= i < N); bounds[i  1]
The bounds
field must contain at least one element. If bounds
has only one element, then there are no finite buckets, and that single element is the common boundary of the overflow and underflow buckets.
Property
Parameter 


bounds 
Array of number The values must be monotonically increasing. 
Exponential
Specifies an exponential sequence of buckets that have a width that is proportional to the value of the lower bound. Each bucket represents a constant relative uncertainty on a specific value in the bucket.
There are num_finite_buckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): scale (growth_factor ^ i). Lower bound (1 <= i < N): scale (growth_factor ^ (i  1)).
Properties
Parameter 


numFiniteBuckets 
number Must be greater than 0. 
growthFactor 
number Must be greater than 1. 
scale 
number Must be greater than 0. 
Exponential
Specifies an exponential sequence of buckets that have a width that is proportional to the value of the lower bound. Each bucket represents a constant relative uncertainty on a specific value in the bucket.
There are num_finite_buckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): scale (growth_factor ^ i). Lower bound (1 <= i < N): scale (growth_factor ^ (i  1)).
Properties
Parameter 


numFiniteBuckets 
number Must be greater than 0. 
growthFactor 
number Must be greater than 1. 
scale 
number Must be greater than 0. 
LabelDescriptor
A description of a label.
Properties
Parameter 


key 
string The label key. 
valueType 
number The type of data that can be assigned to the label. The number should be among the values of ValueType 
description 
string A humanreadable description for the label. 
LabelDescriptor
A description of a label.
Properties
Parameter 


key 
string The label key. 
valueType 
number The type of data that can be assigned to the label. The number should be among the values of ValueType 
description 
string A humanreadable description for the label. 
Linear
Specifies a linear sequence of buckets that all have the same width (except overflow and underflow). Each bucket represents a constant absolute uncertainty on the specific value in the bucket.
There are num_finite_buckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): offset + (width i). Lower bound (1 <= i < N): offset + (width (i  1)).
Properties
Parameter 


numFiniteBuckets 
number Must be greater than 0. 
width 
number Must be greater than 0. 
offset 
number Lower bound of the first bucket. 
Linear
Specifies a linear sequence of buckets that all have the same width (except overflow and underflow). Each bucket represents a constant absolute uncertainty on the specific value in the bucket.
There are num_finite_buckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): offset + (width i). Lower bound (1 <= i < N): offset + (width (i  1)).
Properties
Parameter 


numFiniteBuckets 
number Must be greater than 0. 
width 
number Must be greater than 0. 
offset 
number Lower bound of the first bucket. 
Metric
A specific metric, identified by specifying values for all of the labels of a MetricDescriptor
.
Properties
Parameter 


type 
string An existing metric type, see google.api.MetricDescriptor. For example, 
labels 
Object with string properties The set of label values that uniquely identify this metric. All labels listed in the 
Metric
A specific metric, identified by specifying values for all of the labels of a MetricDescriptor
.
Properties
Parameter 


type 
string An existing metric type, see google.api.MetricDescriptor. For example, 
labels 
Object with string properties The set of label values that uniquely identify this metric. All labels listed in the 
MetricDescriptor
Defines a metric type and its schema. Once a metric descriptor is created, deleting or altering it stops data collection and makes the metric type's existing data unusable.
Properties
Parameter 


name 
string The resource name of the metric descriptor. 
type 
string
The metric type, including its DNS name prefix. The type is not URLencoded. All userdefined metric types have the DNS name

labels 
Array of Object The set of labels that can be used to describe a specific instance of this metric type. For example, the
This object should have the same structure as LabelDescriptor 
metricKind 
number Whether the metric records instantaneous values, changes to a value, etc. Some combinations of The number should be among the values of MetricKind 
valueType 
number Whether the measurement is an integer, a floatingpoint number, etc. Some combinations of The number should be among the values of ValueType 
unit 
string
The unit in which the metric value is reported. It is only applicable if the
Basic units (UNIT)

description 
string A detailed description of the metric, which can be used in documentation. 
displayName 
string A concise name for the metric, which can be displayed in user interfaces. Use sentence case without an ending period, for example "Request count". This field is optional but it is recommended to be set for any metrics associated with uservisible concepts, such as Quota. 
metadata 
Object Optional. Metadata which can be used to guide usage of the metric. This object should have the same structure as MetricDescriptorMetadata 
MetricDescriptor
Defines a metric type and its schema. Once a metric descriptor is created, deleting or altering it stops data collection and makes the metric type's existing data unusable.
Properties
Parameter 


name 
string The resource name of the metric descriptor. 
type 
string
The metric type, including its DNS name prefix. The type is not URLencoded. All userdefined metric types have the DNS name

labels 
Array of Object The set of labels that can be used to describe a specific instance of this metric type. For example, the
This object should have the same structure as LabelDescriptor 
metricKind 
number Whether the metric records instantaneous values, changes to a value, etc. Some combinations of The number should be among the values of MetricKind 
valueType 
number Whether the measurement is an integer, a floatingpoint number, etc. Some combinations of The number should be among the values of ValueType 
unit 
string
The unit in which the metric value is reported. It is only applicable if the
Basic units (UNIT)

description 
string A detailed description of the metric, which can be used in documentation. 
displayName 
string A concise name for the metric, which can be displayed in user interfaces. Use sentence case without an ending period, for example "Request count". This field is optional but it is recommended to be set for any metrics associated with uservisible concepts, such as Quota. 
metadata 
Object Optional. Metadata which can be used to guide usage of the metric. This object should have the same structure as MetricDescriptorMetadata 
MetricDescriptorMetadata
Additional annotations that can be used to guide the usage of a metric.
Properties
Parameter 


launchStage 
number The launch stage of the metric definition. The number should be among the values of LaunchStage 
samplePeriod 
Object The sampling period of metric data points. For metrics which are written periodically, consecutive data points are stored at this time interval, excluding data loss due to errors. Metrics with a higher granularity have a smaller sampling period. This object should have the same structure as Duration 
ingestDelay 
Object The delay of data points caused by ingestion. Data points older than this age are guaranteed to be ingested and available to be read, excluding data loss due to errors. This object should have the same structure as Duration 
MetricDescriptorMetadata
Additional annotations that can be used to guide the usage of a metric.
Properties
Parameter 


launchStage 
number The launch stage of the metric definition. The number should be among the values of LaunchStage 
samplePeriod 
Object The sampling period of metric data points. For metrics which are written periodically, consecutive data points are stored at this time interval, excluding data loss due to errors. Metrics with a higher granularity have a smaller sampling period. This object should have the same structure as Duration 
ingestDelay 
Object The delay of data points caused by ingestion. Data points older than this age are guaranteed to be ingested and available to be read, excluding data loss due to errors. This object should have the same structure as Duration 
MonitoredResource
An object representing a resource that can be used for monitoring, logging, billing, or other purposes. Examples include virtual machine instances, databases, and storage devices such as disks. The type
field identifies a
MonitoredResourceDescriptor object that describes the resource's schema. Information in the labels
field identifies the actual resource and its attributes according to the schema. For example, a particular Compute Engine
VM instance could be represented by the following object, because the MonitoredResourceDescriptor for "gce_instance"
has labels
"instance_id"
and "zone"
:
{ "type": "gce_instance",
"labels": { "instance_id": "12345678901234",
"zone": "uscentral1a" }}
Properties
Parameter 


type 
string Required. The monitored resource type. This field must match the 
labels 
Object with string properties Required. Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels 
MonitoredResource
An object representing a resource that can be used for monitoring, logging, billing, or other purposes. Examples include virtual machine instances, databases, and storage devices such as disks. The type
field identifies a
MonitoredResourceDescriptor object that describes the resource's schema. Information in the labels
field identifies the actual resource and its attributes according to the schema. For example, a particular Compute Engine
VM instance could be represented by the following object, because the MonitoredResourceDescriptor for "gce_instance"
has labels
"instance_id"
and "zone"
:
{ "type": "gce_instance",
"labels": { "instance_id": "12345678901234",
"zone": "uscentral1a" }}
Properties
Parameter 


type 
string Required. The monitored resource type. This field must match the 
labels 
Object with string properties Required. Values for all of the labels listed in the associated monitored resource descriptor. For example, Compute Engine VM instances use the labels 
MonitoredResourceDescriptor
An object that describes the schema of a MonitoredResource object using a type name and a set of labels. For example, the monitored resource descriptor for Google Compute Engine VM instances has a type of
"gce_instance"
and specifies the use of the labels "instance_id"
and
"zone"
to identify particular VM instances.
Different APIs can support different monitored resource types. APIs generally provide a list
method that returns the monitored resource descriptors used by the API.
Properties
Parameter 


name 
string Optional. The resource name of the monitored resource descriptor:

type 
string Required. The monitored resource type. For example, the type

displayName 
string Optional. A concise name for the monitored resource type that might be displayed in user interfaces. It should be a Title Cased Noun Phrase, without any article or other determiners. For example,

description 
string Optional. A detailed description of the monitored resource type that might be used in documentation. 
labels 
Array of Object Required. A set of labels used to describe instances of this monitored resource type. For example, an individual Google Cloud SQL database is identified by values for the labels This object should have the same structure as LabelDescriptor 
MonitoredResourceDescriptor
An object that describes the schema of a MonitoredResource object using a type name and a set of labels. For example, the monitored resource descriptor for Google Compute Engine VM instances has a type of
"gce_instance"
and specifies the use of the labels "instance_id"
and
"zone"
to identify particular VM instances.
Different APIs can support different monitored resource types. APIs generally provide a list
method that returns the monitored resource descriptors used by the API.
Properties
Parameter 


name 
string Optional. The resource name of the monitored resource descriptor:

type 
string Required. The monitored resource type. For example, the type

displayName 
string Optional. A concise name for the monitored resource type that might be displayed in user interfaces. It should be a Title Cased Noun Phrase, without any article or other determiners. For example,

description 
string Optional. A detailed description of the monitored resource type that might be used in documentation. 
labels 
Array of Object Required. A set of labels used to describe instances of this monitored resource type. For example, an individual Google Cloud SQL database is identified by values for the labels This object should have the same structure as LabelDescriptor 
MonitoredResourceMetadata
Auxiliary metadata for a MonitoredResource object. MonitoredResource objects contain the minimum set of information to uniquely identify a monitored resource instance. There is some other useful auxiliary metadata. Monitoring and Logging use an ingestion pipeline to extract metadata for cloud resources of all types, and store the metadata in this message.
Properties
Parameter 


systemLabels 
Object Output only. Values for predefined system metadata labels. System labels are a kind of metadata extracted by Google, including "machine_image", "vpc", "subnet_id", "security_group", "name", etc. System label values can be only strings, Boolean values, or a list of strings. For example:
This object should have the same structure as Struct 
userLabels 
Object with string properties Output only. A map of userdefined metadata labels. 
MonitoredResourceMetadata
Auxiliary metadata for a MonitoredResource object. MonitoredResource objects contain the minimum set of information to uniquely identify a monitored resource instance. There is some other useful auxiliary metadata. Monitoring and Logging use an ingestion pipeline to extract metadata for cloud resources of all types, and store the metadata in this message.
Properties
Parameter 


systemLabels 
Object Output only. Values for predefined system metadata labels. System labels are a kind of metadata extracted by Google, including "machine_image", "vpc", "subnet_id", "security_group", "name", etc. System label values can be only strings, Boolean values, or a list of strings. For example:
This object should have the same structure as Struct 
userLabels 
Object with string properties Output only. A map of userdefined metadata labels. 
Range
The range of the population values.
Properties
Parameter 


min 
number The minimum of the population values. 
max 
number The maximum of the population values. 
Range
The range of the population values.
Properties
Parameter 


min 
number The minimum of the population values. 
max 
number The maximum of the population values. 