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.

JSON representation
{
  "metric": {
    object(Metric)
  },
  "resource": {
    object(MonitoredResource)
  },
  "metadata": {
    object(MonitoredResourceMetadata)
  },
  "metricKind": enum(MetricKind),
  "valueType": enum(ValueType),
  "points": [
    {
      object(Point)
    }
  ]
}
Fields
metric

object(Metric)

The associated metric. A fully-specified metric used to identify the time series.

resource

object(MonitoredResource)

The associated monitored resource. Custom metrics can use only certain monitored resource types in their time series data.

metadata

object(MonitoredResourceMetadata)

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

enum(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.

valueType

enum(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[]

object(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.

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

string

An existing metric type, see google.api.MetricDescriptor. For example, custom.googleapis.com/invoice/paid/amount.

labels

map (key: string, value: string)

The set of label values that uniquely identify this metric. All labels listed in the MetricDescriptor must be assigned values.

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

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. Google Stackdriver Monitoring & Logging uses an ingestion pipeline to extract metadata for cloud resources of all types , and stores the metadata in this message.

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

object (Struct format)

Output only. Values for predefined system metadata labels. System labels are a kind of metadata extracted by Google Stackdriver. Stackdriver determines what system labels are useful and how to obtain their values. Some examples: "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:

{ "name": "my-test-instance",
  "security_group": ["a", "b", "c"],
  "spot_instance": false }

userLabels

map (key: string, value: string)

Output only. A map of user-defined metadata labels.

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

Point

A single data point in a time series.

JSON representation
{
  "interval": {
    object(TimeInterval)
  },
  "value": {
    object(TypedValue)
  }
}
Fields
interval

object(TimeInterval)

The time interval to which the data point applies. For GAUGE metrics, only the end time of the interval is used. 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

object(TypedValue)

The value of the data point.

TypedValue

A single strongly-typed value.

JSON representation
{

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

boolean

A Boolean value: true or false.

int64Value

string (int64 format)

A 64-bit integer. Its range is approximately ±9.2x1018.

doubleValue

number

A 64-bit double-precision floating-point number. Its magnitude is approximately ±10±300 and it has 16 significant digits of precision.

stringValue

string

A variable-length string value.

distributionValue

object(Distribution)

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 non-finite 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(Range)
  },
  "bucketOptions": {
    object(BucketOptions)
  },
  "bucketCounts": [
    string
  ]
}
Fields
count

string (int64 format)

The number of values in the population. Must be non-negative. This value must equal the sum of the values in bucketCounts if a histogram is provided.

mean

number

The arithmetic mean of the values in the population. If count is zero then this field must be zero.

sumOfSquaredDeviation

number

The sum of squared deviations from the mean of the values in the population. For values x_i this is:

Sum[i=1..n]((x_i - mean)^2)

Knuth, "The Art of Computer Programming", Vol. 2, page 323, 3rd edition describes Welford's method for accumulating this sum in one pass.

If count is zero then this field must be zero.

range

object(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 Stackdriver Monitoring API v3.

bucketOptions

object(BucketOptions)

Required in the Stackdriver Monitoring API v3. Defines the histogram bucket boundaries.

bucketCounts[]

string (int64 format)

Required in the Stackdriver Monitoring API v3. The values for each bucket specified in bucketOptions. The sum of the values in bucketCounts must equal the value in the count field of the Distribution object. The order of the bucket counts follows the numbering schemes described for the three bucket types. The underflow bucket has number 0; the finite buckets, if any, have numbers 1 through N-2; and the overflow bucket has number N-1. The size of bucketCounts must not be greater than N. If the size is less than N, then the remaining buckets are assigned values of zero.

Range

The range of the population values.

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

number

The minimum of the population values.

max

number

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 so-called because both bounds are finite.

JSON representation
{

  // Union field options can be only one of the following:
  "linearBuckets": {
    object(Linear)
  },
  "exponentialBuckets": {
    object(Exponential)
  },
  "explicitBuckets": {
    object(Explicit)
  }
  // End of list of possible types for union field options.
}
Fields
Union field options. Exactly one of these three fields must be set. options can be only one of the following:
linearBuckets

object(Linear)

The linear bucket.

exponentialBuckets

object(Exponential)

The exponential buckets.

explicitBuckets

object(Explicit)

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 < N-1): offset + (width * i). Lower bound (1 <= i < N): offset + (width * (i - 1)).

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

number

Must be greater than 0.

width

number

Must be greater than 0.

offset

number

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 < N-1): scale * (growthFactor ^ i). Lower bound (1 <= i < N): scale * (growthFactor ^ (i - 1)).

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

number

Must be greater than 0.

growthFactor

number

Must be greater than 1.

scale

number

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 < N-1): 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[]

number

The values must be monotonically increasing.

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