MetricValueSet

Represents a set of metric values in the same metric. Each metric value in the set should have a unique combination of start time, end time, and label values.

JSON representation 
{
  "metricName": string,
  "metricValues": [
    {
      object (MetricValue)
    }
  ]
}
Fields
metricName

string

The metric name defined in the service configuration.
metricValues[]

object (MetricValue)

The values in this metric.

MetricValue

Represents a single metric value.

JSON representation 
{
  "labels": {
    string: string,
    ...
  },
  "startTime": string,
  "endTime": string,

  // Union field value can be only one of the following:
  "boolValue": boolean,
  "int64Value": string,
  "doubleValue": number,
  "stringValue": string,
  "distributionValue": {
    object (Distribution)
  }
  // End of list of possible types for union field value.
}
Fields
labels

map (key: string, value: string)

The labels describing the metric value. See comments on google.api.servicecontrol.v1.Operation.labels for the overriding relationship. Note that this map must not contain monitored resource labels.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
startTime

string (Timestamp format)

The start of the time period over which this metric value's measurement applies. The time period has different semantics for different metric types (cumulative, delta, and gauge). See the metric definition documentation in the service configuration for details. If not specified, google.api.servicecontrol.v1.Operation.start_time will be used.

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
endTime

string (Timestamp format)

The end of the time period over which this metric value's measurement applies. If not specified, google.api.servicecontrol.v1.Operation.end_time will be used.

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
Union field value. The value. The type of value used in the request must agree with the metric definition in the service configuration, otherwise the MetricValue is rejected. value can be only one of the following:
boolValue

boolean

A boolean value.
int64Value

string (int64 format)

A signed 64-bit integer value.
doubleValue

number

A double precision floating point value.
stringValue

string

A text string value.
distributionValue

object (Distribution)

A distribution value.

Distribution

Distribution represents a frequency distribution of double-valued sample points. It contains the size of the population of sample points plus additional optional information:

  • the arithmetic mean of the samples
  • the minimum and maximum of the samples
  • the sum-squared-deviation of the samples, used to compute variance
  • a histogram of the values of the sample points
JSON representation 
{
  "count": string,
  "mean": number,
  "minimum": number,
  "maximum": number,
  "sumOfSquaredDeviation": number,
  "bucketCounts": [
    string
  ],
  "exemplars": [
    {
      object (Exemplar)
    }
  ],

  // Union field bucket_option can be only one of the following:
  "linearBuckets": {
    object (LinearBuckets)
  },
  "exponentialBuckets": {
    object (ExponentialBuckets)
  },
  "explicitBuckets": {
    object (ExplicitBuckets)
  }
  // End of list of possible types for union field bucket_option.
}
Fields
count

string (int64 format)

The total number of samples in the distribution. Must be >= 0.
mean

number

The arithmetic mean of the samples in the distribution. If count is zero then this field must be zero.
minimum

number

The minimum of the population of values. Ignored if count is zero.
maximum

number

The maximum of the population of values. Ignored if count is zero.
sumOfSquaredDeviation

number

The sum of squared deviations from the mean: Sum[i=1..count]((x_i - mean)^2) where each x_i is a sample values. If count is zero then this field must be zero, otherwise validation of the request fails.
bucketCounts[]

string (int64 format)

The number of samples in each histogram bucket. bucketCounts are optional. If present, they must sum to the count value.

The buckets are defined below in bucket_option. There are N buckets. bucketCounts[0] is the number of samples in the underflow bucket. bucketCounts[1] to bucketCounts[N-1] are the numbers of samples in each of the finite buckets. And bucketCounts[N] is the number of samples in the overflow bucket. See the comments ofbucket_option` below for more details.

Any suffix of trailing zeros may be omitted.
exemplars[]

object (Exemplar)

Example points. Must be in increasing order of value field.

Union field bucket_option. Defines the buckets in the histogram. bucket_option and bucket_counts must be both set, or both unset.

Buckets are numbered in the range of [0, N], with a total of N+1 buckets. There must be at least two buckets (a single-bucket histogram gives no information that isn't already provided by count).

The first bucket is the underflow bucket which has a lower bound of -inf. The last bucket is the overflow bucket which has an upper bound of +inf. All other buckets (if any) are called "finite" buckets because they have finite lower and upper bounds. As described below, there are three ways to define the finite buckets.

(1) Buckets with constant width. (2) Buckets with exponentially growing widths. (3) Buckets with arbitrary user-provided widths.

In all cases, the buckets cover the entire real number line (-inf, +inf). Bucket upper bounds are exclusive and lower bounds are inclusive. The upper bound of the underflow bucket is equal to the lower bound of the smallest finite bucket; the lower bound of the overflow bucket is equal to the upper bound of the largest finite bucket. bucket_option can be only one of the following:
linearBuckets

object (LinearBuckets)

Buckets with constant width.
exponentialBuckets

object (ExponentialBuckets)

Buckets with exponentially growing width.
explicitBuckets

object (ExplicitBuckets)

Buckets with arbitrary user-provided width.

LinearBuckets

Describing buckets with constant width.

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

integer

The number of finite buckets. With the underflow and overflow buckets, the total number of buckets is numFiniteBuckets + 2. See comments on bucketOptions for details.
width

number

The i'th linear bucket covers the interval [offset + (i-1) * width, offset + i * width) where i ranges from 1 to numFiniteBuckets, inclusive. Must be strictly positive.
offset

number

The i'th linear bucket covers the interval [offset + (i-1) * width, offset + i * width) where i ranges from 1 to numFiniteBuckets, inclusive.

ExponentialBuckets

Describing buckets with exponentially growing width.

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

integer

The number of finite buckets. With the underflow and overflow buckets, the total number of buckets is numFiniteBuckets + 2. See comments on bucketOptions for details.
growthFactor

number

The i'th exponential bucket covers the interval [scale * growthFactor^(i-1), scale * growthFactor^i) where i ranges from 1 to numFiniteBuckets inclusive. Must be larger than 1.0.
scale

number

The i'th exponential bucket covers the interval [scale * growthFactor^(i-1), scale * growthFactor^i) where i ranges from 1 to numFiniteBuckets inclusive. Must be > 0.

ExplicitBuckets

Describing buckets with arbitrary user-provided width.

JSON representation 
{
  "bounds": [
    number
  ]
}
Fields
bounds[]

number

'bound' is a list of strictly increasing boundaries between buckets. Note that a list of length N-1 defines N buckets because of fenceposting. See comments on bucketOptions for details.

The i'th finite bucket covers the interval [bound[i-1], bound[i]) where i ranges from 1 to bound_size() - 1. Note that there are no finite buckets at all if 'bound' only contains a single element; in that special case the single bound defines the boundary between the underflow and overflow buckets.

bucket number lower bound upper bound i == 0 (underflow) -inf bound[i] 0 < i < bound_size() bound[i-1] bound[i] i == bound_size() (overflow) bound[i-1] +inf

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

number

Value of the exemplar point. This value determines to which bucket the exemplar belongs.
timestamp

string (Timestamp format)

The observation (sampling) time of the above value.

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
attachments[]

object

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 "@type" contains a URI identifying the type. Example: { "id": 1234, "@type": "types.example.com/standard/id" }.