 JSON representation
 Metric
 MonitoredResourceMetadata
 Point
 TypedValue
 Distribution
 Range
 BucketOptions
 Linear
 Exponential
 Explicit
 Exemplar
A collection of data points that describes the timevarying values of a metric. A time series is identified by a combination of a fullyspecified monitored resource and a fullyspecified metric. This type is used for both listing and creating time series.
JSON representation  

{ "metric": { object ( 
Fields  

metric 
The associated metric. A fullyspecified metric used to identify the time series. 
resource 
The associated monitored resource. Custom metrics can use only certain monitored resource types in their time series data. 
metadata 
Output only. The associated monitored resource metadata. When reading a a timeseries, this field will include metadata labels that are explicitly named in the reduction. When creating a timeseries, this field is ignored. 
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 autocreated, then this field specifies the metric kind of the new descriptor and must be either 
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[] 
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 autocreated, then the value type of the descriptor is determined by the point's type, which must be 
Metric
A specific metric, identified by specifying values for all of the labels of a
.MetricDescriptor
JSON representation  

{ "type": string, "labels": { string: string, ... } } 
Fields  

type 
An existing metric type, see 
labels 
The set of label values that uniquely identify this metric. All labels listed in the An object containing a list of 
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.
JSON representation  

{ "systemLabels": { object }, "userLabels": { string: string, ... } } 
Fields  

systemLabels 
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:

userLabels 
Output only. A map of userdefined metadata labels. An object containing a list of 
Point
A single data point in a time series.
JSON representation  

{ "interval": { object ( 
Fields  

interval 
The time interval to which the data point applies. For 
value 
The value of the data point. 
TypedValue
A single stronglytyped value.
JSON representation  

{ // Union field 
Fields  

Union field value . The typed value field. value can be only one of the following: 

boolValue 
A Boolean value: 

int64Value 
A 64bit integer. Its range is approximately ±9.2x10^{18}. 

doubleValue 
A 64bit doubleprecision floatingpoint number. Its magnitude is approximately ±10^{±300} and it has 16 significant digits of precision. 

stringValue 
A variablelength string value. 

distributionValue 
A distribution value. 
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 sumOfSquaredDeviation
fields meaningless.
JSON representation  

{ "count": string, "mean": number, "sumOfSquaredDeviation": number, "range": { object ( 
Fields  

count 
The number of values in the population. Must be nonnegative. This value must equal the sum of the values in 
mean 
The arithmetic mean of the values in the population. If 
sumOfSquaredDeviation 
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 
If specified, contains the range of the population values. The field must not be present if the count is zero. This field is presently ignored by the Cloud Monitoring API v3. 
bucketOptions 
Required in the Cloud Monitoring API v3. Defines the histogram bucket boundaries. 
bucketCounts[] 
Required in the Cloud Monitoring API v3. The values for each bucket specified in 
exemplars[] 
Must be in increasing order of 
Range
The range of the population values.
JSON representation  

{ "min": number, "max": number } 
Fields  

min 
The minimum of the population values. 
max 
The maximum of the population values. 
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.
JSON representation  

{ // Union field 
Fields  

Union field options . Exactly one of these three fields must be set. options can be only one of the following: 

linearBuckets 
The linear bucket. 

exponentialBuckets 
The exponential buckets. 

explicitBuckets 
The explicit buckets. 
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 numFiniteBuckets + 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)).
JSON representation  

{ "numFiniteBuckets": integer, "width": number, "offset": number } 
Fields  

numFiniteBuckets 
Must be greater than 0. 
width 
Must be greater than 0. 
offset 
Lower bound of the first bucket. 
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 numFiniteBuckets + 2
(= N) buckets. Bucket i
has the following boundaries:
Upper bound (0 <= i < N1): scale * (growthFactor ^ i). Lower bound (1 <= i < N): scale * (growthFactor ^ (i  1)).
JSON representation  

{ "numFiniteBuckets": integer, "growthFactor": number, "scale": number } 
Fields  

numFiniteBuckets 
Must be greater than 0. 
growthFactor 
Must be greater than 1. 
scale 
Must be greater than 0. 
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.
JSON representation  

{ "bounds": [ number ] } 
Fields  

bounds[] 
The values must be monotonically increasing. 
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.
JSON representation  

{ "value": number, "timestamp": string, "attachments": [ { "@type": string, field1: ..., ... } ] } 
Fields  

value 
Value of the exemplar point. This value determines to which bucket the exemplar belongs. 
timestamp 
The observation (sampling) time of the above value. A timestamp in RFC3339 UTC "Zulu" format, accurate to nanoseconds. Example: 
attachments[] 
Contextual information about the example value. Examples are: Trace: type.googleapis.com/google.monitoring.v3.SpanContext Literal string: type.googleapis.com/google.protobuf.StringValue Labels dropped during aggregation: type.googleapis.com/google.monitoring.v3.DroppedLabels There may be only a single attachment of any given message type in a single exemplar, and this is enforced by the system. An object containing fields of an arbitrary type. An additional field 