types

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Documentation

Overview

Original source: https://github.com/open-telemetry/opentelemetry-proto-go/blob/v1.3.1/slim/otlp/common/v1/common.pb.go

Original source: https://github.com/open-telemetry/opentelemetry-proto-go/blob/v1.3.1/slim/otlp/metrics/v1/metrics.pb.go

Original source: https://github.com/open-telemetry/opentelemetry-proto-go/blob/v1.3.1/slim/otlp/collector/metrics/v1/metrics_service.pb.go

Original source: https://github.com/open-telemetry/opentelemetry-proto-go/blob/v1.3.1/slim/otlp/resource/v1/resource.pb.go

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

This section is empty.

Types

type AggregationTemporality 

type AggregationTemporality int32

AggregationTemporality defines how a metric aggregator reports aggregated values. It describes how those values relate to the time interval over which they are aggregated.

type AnyValue 

type AnyValue struct {
	// The value is one of the listed fields. It is valid for all values to be unspecified
	// in which case this AnyValue is considered to be "empty".
	//
	// Types that are assignable to Value:
	//	*AnyValue_StringValue
	//	*AnyValue_BoolValue
	//	*AnyValue_IntValue
	//	*AnyValue_DoubleValue
	//	*AnyValue_ArrayValue
	//	*AnyValue_KvlistValue
	//	*AnyValue_BytesValue
	StringValue string        `json:"stringValue,omitempty"`
	BoolValue   bool          `json:"boolValue,omitempty"`
	IntValue    int64         `json:"intValue,omitempty"`
	DoubleValue float64       `json:"doubleValue,omitempty"`
	ArrayValue  *ArrayValue   `json:"arrayValue,omitempty"`
	KvlistValue *KeyValueList `json:"kvlistValue,omitempty"`
	BytesValue  []byte        `json:"bytesValue,omitempty"`
}

AnyValue is used to represent any type of attribute value. AnyValue may contain a primitive value such as a string or integer or it may contain an arbitrary nested object containing arrays, key-value lists and primitives.

type ArrayValue 

type ArrayValue struct {
	// Array of values. The array may be empty (contain 0 elements).
	Values []*AnyValue `json:"values,omitempty"`
}

ArrayValue is a list of AnyValue messages. We need ArrayValue as a message since oneof in AnyValue does not allow repeated fields.

type Exemplar 

type Exemplar struct {
	// The set of key/value pairs that were filtered out by the aggregator, but
	// recorded alongside the original measurement. Only key/value pairs that were
	// filtered out by the aggregator should be included
	FilteredAttributes []*KeyValue `json:"filtered_attributes,omitempty"`
	// time_unix_nano is the exact time when this exemplar was recorded
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	TimeUnixNano uint64 `json:"time_unix_nano,omitempty"`
	// The value of the measurement that was recorded. An exemplar is
	// considered invalid when one of the recognized value fields is not present
	// inside this oneof.
	//
	// Types that are assignable to Value:
	//	*Exemplar_AsDouble
	//	*Exemplar_AsInt
	AsDouble *Exemplar_AsDouble `json:"asDouble,omitempty"`
	AsInt    *Exemplar_AsInt    `json:"asInt,omitempty"`
	// (Optional) Span ID of the exemplar trace.
	// span_id may be missing if the measurement is not recorded inside a trace
	// or if the trace is not sampled.
	SpanId *SpanID `json:"span_id,omitempty"`
	// (Optional) Trace ID of the exemplar trace.
	// trace_id may be missing if the measurement is not recorded inside a trace
	// or if the trace is not sampled.
	TraceId *TraceID `json:"trace_id,omitempty"`
}

A representation of an exemplar, which is a sample input measurement. Exemplars also hold information about the environment when the measurement was recorded, for example the span and trace ID of the active span when the exemplar was recorded.

type Exemplar_AsDouble 

type Exemplar_AsDouble float64

type Exemplar_AsInt 

type Exemplar_AsInt int64

type ExponentialHistogram 

type ExponentialHistogram struct {
	DataPoints []*ExponentialHistogramDataPoint `json:"data_points,omitempty"`
	// aggregation_temporality describes if the aggregator reports delta changes
	// since last report time, or cumulative changes since a fixed start time.
	AggregationTemporality AggregationTemporality `json:"aggregation_temporality,omitempty"`
}

ExponentialHistogram represents the type of a metric that is calculated by aggregating as a ExponentialHistogram of all reported double measurements over a time interval.

type ExponentialHistogramDataPoint 

type ExponentialHistogramDataPoint struct {
	// The set of key/value pairs that uniquely identify the timeseries from
	// where this point belongs. The list may be empty (may contain 0 elements).
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Attributes []*KeyValue `json:"attributes,omitempty"`
	// StartTimeUnixNano is optional but strongly encouraged, see the
	// the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	StartTimeUnixNano uint64 `json:"start_time_unix_nano,omitempty"`
	// TimeUnixNano is required, see the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	TimeUnixNano uint64 `json:"time_unix_nano,omitempty"`
	// count is the number of values in the population. Must be
	// non-negative. This value must be equal to the sum of the "bucket_counts"
	// values in the positive and negative Buckets plus the "zero_count" field.
	Count uint64 `json:"count,omitempty"`
	// sum of the values in the population. If count is zero then this field
	// must be zero.
	//
	// Note: Sum should only be filled out when measuring non-negative discrete
	// events, and is assumed to be monotonic over the values of these events.
	// Negative events *can* be recorded, but sum should not be filled out when
	// doing so.  This is specifically to enforce compatibility w/ OpenMetrics,
	// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
	Sum *float64 `json:"sum,omitempty"`
	// scale describes the resolution of the histogram.  Boundaries are
	// located at powers of the base, where:
	//
	//   base = (2^(2^-scale))
	//
	// The histogram bucket identified by `index`, a signed integer,
	// contains values that are greater than (base^index) and
	// less than or equal to (base^(index+1)).
	//
	// The positive and negative ranges of the histogram are expressed
	// separately.  Negative values are mapped by their absolute value
	// into the negative range using the same scale as the positive range.
	//
	// scale is not restricted by the protocol, as the permissible
	// values depend on the range of the data.
	Scale int32 `json:"scale,omitempty"`
	// zero_count is the count of values that are either exactly zero or
	// within the region considered zero by the instrumentation at the
	// tolerated degree of precision.  This bucket stores values that
	// cannot be expressed using the standard exponential formula as
	// well as values that have been rounded to zero.
	//
	// Implementations MAY consider the zero bucket to have probability
	// mass equal to (zero_count / count).
	ZeroCount uint64 `json:"zero_count,omitempty"`
	// positive carries the positive range of exponential bucket counts.
	Positive *ExponentialHistogramDataPoint_Buckets `json:"positive,omitempty"`
	// negative carries the negative range of exponential bucket counts.
	Negative *ExponentialHistogramDataPoint_Buckets `json:"negative,omitempty"`
	// Flags that apply to this specific data point.  See DataPointFlags
	// for the available flags and their meaning.
	Flags uint32 `json:"flags,omitempty"`
	// (Optional) List of exemplars collected from
	// measurements that were used to form the data point
	Exemplars []*Exemplar `json:"exemplars,omitempty"`
	// min is the minimum value over (start_time, end_time].
	Min *float64 `json:"min,omitempty"`
	// max is the maximum value over (start_time, end_time].
	Max *float64 `json:"max,omitempty"`
	// ZeroThreshold may be optionally set to convey the width of the zero
	// region. Where the zero region is defined as the closed interval
	// [-ZeroThreshold, ZeroThreshold].
	// When ZeroThreshold is 0, zero count bucket stores values that cannot be
	// expressed using the standard exponential formula as well as values that
	// have been rounded to zero.
	ZeroThreshold float64 `json:"zero_threshold,omitempty"`
}

ExponentialHistogramDataPoint is a single data point in a timeseries that describes the time-varying values of a ExponentialHistogram of double values. A ExponentialHistogram contains summary statistics for a population of values, it may optionally contain the distribution of those values across a set of buckets.

type ExponentialHistogramDataPoint_Buckets 

type ExponentialHistogramDataPoint_Buckets struct {
	// Offset is the bucket index of the first entry in the bucket_counts array.
	//
	// Note: This uses a varint encoding as a simple form of compression.
	Offset int32 `json:"offset,omitempty"`
	// bucket_counts is an array of count values, where bucket_counts[i] carries
	// the count of the bucket at index (offset+i). bucket_counts[i] is the count
	// of values greater than base^(offset+i) and less than or equal to
	// base^(offset+i+1).
	//
	// Note: By contrast, the explicit HistogramDataPoint uses
	// fixed64.  This field is expected to have many buckets,
	// especially zeros, so uint64 has been selected to ensure
	// varint encoding.
	BucketCounts []uint64 `json:"bucket_counts,omitempty"`
}

Buckets are a set of bucket counts, encoded in a contiguous array of counts.

type ExportMetricsServiceRequest 

type ExportMetricsServiceRequest struct {
	// An array of ResourceMetrics.
	// For data coming from a single resource this array will typically contain one
	// element. Intermediary nodes (such as OpenTelemetry Collector) that receive
	// data from multiple origins typically batch the data before forwarding further and
	// in that case this array will contain multiple elements.
	ResourceMetrics []*ResourceMetrics `json:"resource_metrics,omitempty"`
}

type Gauge 

type Gauge struct {
	DataPoints []*NumberDataPoint `json:"data_points,omitempty"`
}

Gauge represents the type of a scalar metric that always exports the "current value" for every data point. It should be used for an "unknown" aggregation.

A Gauge does not support different aggregation temporalities. Given the aggregation is unknown, points cannot be combined using the same aggregation, regardless of aggregation temporalities. Therefore, AggregationTemporality is not included. Consequently, this also means "StartTimeUnixNano" is ignored for all data points.

type Histogram 

type Histogram struct {
	DataPoints []*HistogramDataPoint `json:"data_points,omitempty"`
	// aggregation_temporality describes if the aggregator reports delta changes
	// since last report time, or cumulative changes since a fixed start time.
	AggregationTemporality AggregationTemporality `json:"aggregation_temporality,omitempty"`
}

Histogram represents the type of a metric that is calculated by aggregating as a Histogram of all reported measurements over a time interval.

type HistogramDataPoint 

type HistogramDataPoint struct {
	// The set of key/value pairs that uniquely identify the timeseries from
	// where this point belongs. The list may be empty (may contain 0 elements).
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Attributes []*KeyValue `json:"attributes,omitempty"`
	// StartTimeUnixNano is optional but strongly encouraged, see the
	// the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	StartTimeUnixNano uint64 `json:"start_time_unix_nano,omitempty"`
	// TimeUnixNano is required, see the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	TimeUnixNano uint64 `json:"time_unix_nano,omitempty"`
	// count is the number of values in the population. Must be non-negative. This
	// value must be equal to the sum of the "count" fields in buckets if a
	// histogram is provided.
	Count uint64 `json:"count,omitempty"`
	// sum of the values in the population. If count is zero then this field
	// must be zero.
	//
	// Note: Sum should only be filled out when measuring non-negative discrete
	// events, and is assumed to be monotonic over the values of these events.
	// Negative events *can* be recorded, but sum should not be filled out when
	// doing so.  This is specifically to enforce compatibility w/ OpenMetrics,
	// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#histogram
	Sum *float64 `json:"sum,omitempty"`
	// bucket_counts is an optional field contains the count values of histogram
	// for each bucket.
	//
	// The sum of the bucket_counts must equal the value in the count field.
	//
	// The number of elements in bucket_counts array must be by one greater than
	// the number of elements in explicit_bounds array.
	BucketCounts []uint64 `json:"bucket_counts,omitempty"`
	// explicit_bounds specifies buckets with explicitly defined bounds for values.
	//
	// The boundaries for bucket at index i are:
	//
	// (-infinity, explicit_bounds[i]] for i == 0
	// (explicit_bounds[i-1], explicit_bounds[i]] for 0 < i < size(explicit_bounds)
	// (explicit_bounds[i-1], +infinity) for i == size(explicit_bounds)
	//
	// The values in the explicit_bounds array must be strictly increasing.
	//
	// Histogram buckets are inclusive of their upper boundary, except the last
	// bucket where the boundary is at infinity. This format is intentionally
	// compatible with the OpenMetrics histogram definition.
	ExplicitBounds []float64 `json:"explicit_bounds,omitempty"`
	// (Optional) List of exemplars collected from
	// measurements that were used to form the data point
	Exemplars []*Exemplar `json:"exemplars,omitempty"`
	// Flags that apply to this specific data point.  See DataPointFlags
	// for the available flags and their meaning.
	Flags uint32 `json:"flags,omitempty"`
	// min is the minimum value over (start_time, end_time].
	Min *float64 `json:"min,omitempty"`
	// max is the maximum value over (start_time, end_time].
	Max *float64 `json:"max,omitempty"`
}

HistogramDataPoint is a single data point in a timeseries that describes the time-varying values of a Histogram. A Histogram contains summary statistics for a population of values, it may optionally contain the distribution of those values across a set of buckets.

If the histogram contains the distribution of values, then both "explicit_bounds" and "bucket counts" fields must be defined. If the histogram does not contain the distribution of values, then both "explicit_bounds" and "bucket_counts" must be omitted and only "count" and "sum" are known.

type InstrumentationScope 

type InstrumentationScope struct {
	// An empty instrumentation scope name means the name is unknown.
	Name    string `json:"name,omitempty"`
	Version string `json:"version,omitempty"`
	// Additional attributes that describe the scope. [Optional].
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Attributes             []*KeyValue `json:"attributes,omitempty"`
	DroppedAttributesCount uint32      `json:"dropped_attributes_count,omitempty"`
}

InstrumentationScope is a message representing the instrumentation scope information such as the fully qualified name and version.

type KeyValue 

type KeyValue struct {
	Key   string    `json:"key,omitempty"`
	Value *AnyValue `json:"value,omitempty"`
}

KeyValue is a key-value pair that is used to store Span attributes, Link attributes, etc.

type KeyValueList 

type KeyValueList struct {
	// A collection of key/value pairs of key-value pairs. The list may be empty (may
	// contain 0 elements).
	// The keys MUST be unique (it is not allowed to have more than one
	// value with the same key).
	Values []*KeyValue `json:"values,omitempty"`
}

KeyValueList is a list of KeyValue messages. We need KeyValueList as a message since `oneof` in AnyValue does not allow repeated fields. Everywhere else where we need a list of KeyValue messages (e.g. in Span) we use `repeated KeyValue` directly to avoid unnecessary extra wrapping (which slows down the protocol). The 2 approaches are semantically equivalent.

type Metric 

type Metric struct {
	// name of the metric.
	Name string `json:"name,omitempty"`
	// description of the metric, which can be used in documentation.
	Description string `json:"description,omitempty"`
	// unit in which the metric value is reported. Follows the format
	// described by http://unitsofmeasure.org/ucum.html.
	Unit string `json:"unit,omitempty"`
	// Data determines the aggregation type (if any) of the metric, what is the
	// reported value type for the data points, as well as the relatationship to
	// the time interval over which they are reported.
	//
	// Types that are assignable to Data:
	//	*Metric_Gauge
	//	*Metric_Sum
	//	*Metric_Histogram
	//	*Metric_ExponentialHistogram
	//	*Metric_Summary
	Gauge                *Gauge                `json:"gauge,omitempty"`
	Sum                  *Sum                  `json:"sum,omitempty"`
	Histogram            *Histogram            `json:"histogram,omitempty"`
	ExponentialHistogram *ExponentialHistogram `json:"exponential_histogram,omitempty"`
	Summary              *Summary              `json:"summary,omitempty"`
	// Additional metadata attributes that describe the metric. [Optional].
	// Attributes are non-identifying.
	// Consumers SHOULD NOT need to be aware of these attributes.
	// These attributes MAY be used to encode information allowing
	// for lossless roundtrip translation to / from another data model.
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Metadata []*KeyValue `json:"metadata,omitempty"`
}

Defines a Metric which has one or more timeseries. The following is a brief summary of the Metric data model. For more details, see: 

https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/data-model.md

The data model and relation between entities is shown in the diagram below. Here, "DataPoint" is the term used to refer to any one of the specific data point value types, and "points" is the term used to refer to any one of the lists of points contained in the Metric.

  • Metric is composed of a metadata and data.

  • Metadata part contains a name, description, unit.

  • Data is one of the possible types (Sum, Gauge, Histogram, Summary).

  • DataPoint contains timestamps, attributes, and one of the possible value type fields.

    Metric +------------+ |name | |description | |unit | +------------------------------------+ |data |---> |Gauge, Sum, Histogram, Summary, ... | +------------+ +------------------------------------+

    Data [One of Gauge, Sum, Histogram, Summary, ...] +-----------+ |... | // Metadata about the Data. |points |--+ +-----------+ | | +---------------------------+ | |DataPoint 1 | v |+------+------+ +------+ | +-----+ ||label |label |...|label | | | 1 |-->||value1|value2|...|valueN| | +-----+ |+------+------+ +------+ | | . | |+-----+ | | . | ||value| | | . | |+-----+ | | . | +---------------------------+ | . | . | . | . | . | . | . | +---------------------------+ | . | |DataPoint M | +-----+ |+------+------+ +------+ | | M |-->||label |label |...|label | | +-----+ ||value1|value2|...|valueN| | |+------+------+ +------+ | |+-----+ | ||value| | |+-----+ | +---------------------------+

Each distinct type of DataPoint represents the output of a specific aggregation function, the result of applying the DataPoint's associated function of to one or more measurements.

All DataPoint types have three common fields:

  • Attributes includes key-value pairs associated with the data point
  • TimeUnixNano is required, set to the end time of the aggregation
  • StartTimeUnixNano is optional, but strongly encouraged for DataPoints having an AggregationTemporality field, as discussed below.

Both TimeUnixNano and StartTimeUnixNano values are expressed as UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January 1970.

TimeUnixNano

This field is required, having consistent interpretation across DataPoint types. TimeUnixNano is the moment corresponding to when the data point's aggregate value was captured.

Data points with the 0 value for TimeUnixNano SHOULD be rejected by consumers.

StartTimeUnixNano

StartTimeUnixNano in general allows detecting when a sequence of observations is unbroken. This field indicates to consumers the start time for points with cumulative and delta AggregationTemporality, and it should be included whenever possible to support correct rate calculation. Although it may be omitted when the start time is truly unknown, setting StartTimeUnixNano is strongly encouraged.

type NumberDataPoint 

type NumberDataPoint struct {
	// The set of key/value pairs that uniquely identify the timeseries from
	// where this point belongs. The list may be empty (may contain 0 elements).
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Attributes []*KeyValue `json:"attributes,omitempty"`
	// StartTimeUnixNano is optional but strongly encouraged, see the
	// the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	StartTimeUnixNano uint64 `json:"start_time_unix_nano,omitempty"`
	// TimeUnixNano is required, see the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	TimeUnixNano uint64 `json:"time_unix_nano,omitempty"`
	// The value itself.  A point is considered invalid when one of the recognized
	// value fields is not present inside this oneof.
	//
	// Types that are assignable to Value:
	//	*NumberDataPoint_AsDouble
	//	*NumberDataPoint_AsInt
	AsDouble *NumberDataPoint_AsDouble `json:"asDouble,omitempty"`
	AsInt    *NumberDataPoint_AsInt    `json:"asInt,omitempty"`
	// (Optional) List of exemplars collected from
	// measurements that were used to form the data point
	Exemplars []*Exemplar `json:"exemplars,omitempty"`
	// Flags that apply to this specific data point.  See DataPointFlags
	// for the available flags and their meaning.
	Flags uint32 `json:"flags,omitempty"`
}

NumberDataPoint is a single data point in a timeseries that describes the time-varying scalar value of a metric.

type NumberDataPoint_AsDouble 

type NumberDataPoint_AsDouble float64

type NumberDataPoint_AsInt 

type NumberDataPoint_AsInt int64

type Resource 

type Resource struct {
	// Set of attributes that describe the resource.
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Attributes []*KeyValue `json:"attributes,omitempty"`
	// dropped_attributes_count is the number of dropped attributes. If the value is 0, then
	// no attributes were dropped.
	DroppedAttributesCount uint32 `json:"dropped_attributes_count,omitempty"`
}

Resource information.

type ResourceMetrics 

type ResourceMetrics struct {
	// The resource for the metrics in this message.
	// If this field is not set then no resource info is known.
	Resource *Resource `json:"resource,omitempty"`
	// A list of metrics that originate from a resource.
	ScopeMetrics []*ScopeMetrics `json:"scope_metrics,omitempty"`
	// The Schema URL, if known. This is the identifier of the Schema that the resource data
	// is recorded in. To learn more about Schema URL see
	// https://opentelemetry.io/docs/specs/otel/schemas/#schema-url
	// This schema_url applies to the data in the "resource" field. It does not apply
	// to the data in the "scope_metrics" field which have their own schema_url field.
	SchemaUrl string `json:"schema_url,omitempty"`
}

A collection of ScopeMetrics from a Resource.

type ScopeMetrics 

type ScopeMetrics struct {
	// The instrumentation scope information for the metrics in this message.
	// Semantically when InstrumentationScope isn't set, it is equivalent with
	// an empty instrumentation scope name (unknown).
	Scope *InstrumentationScope `protobuf:"bytes,1,opt,name=scope,proto3" json:"scope,omitempty"`
	// A list of metrics that originate from an instrumentation library.
	Metrics []*Metric `protobuf:"bytes,2,rep,name=metrics,proto3" json:"metrics,omitempty"`
	// The Schema URL, if known. This is the identifier of the Schema that the metric data
	// is recorded in. To learn more about Schema URL see
	// https://opentelemetry.io/docs/specs/otel/schemas/#schema-url
	// This schema_url applies to all metrics in the "metrics" field.
	SchemaUrl string `protobuf:"bytes,3,opt,name=schema_url,json=schemaUrl,proto3" json:"schema_url,omitempty"`
}

A collection of Metrics produced by an Scope.

type SpanID 

type SpanID []byte

func NewSpanID 

func NewSpanID(sid trace.SpanID) *SpanID

func (*SpanID) MarshalJSON 

func (sid *SpanID) MarshalJSON() ([]byte, error)

type Sum 

type Sum struct {
	DataPoints []*NumberDataPoint `json:"data_points,omitempty"`
	// aggregation_temporality describes if the aggregator reports delta changes
	// since last report time, or cumulative changes since a fixed start time.
	AggregationTemporality AggregationTemporality `json:"aggregation_temporality,omitempty"`
	// If "true" means that the sum is monotonic.
	IsMonotonic bool `json:"is_monotonic,omitempty"`
}

Sum represents the type of a scalar metric that is calculated as a sum of all reported measurements over a time interval.

type Summary 

type Summary struct {
	DataPoints []*SummaryDataPoint `json:"data_points,omitempty"`
}

Summary metric data are used to convey quantile summaries, a Prometheus (see: https://prometheus.io/docs/concepts/metric_types/#summary) and OpenMetrics (see: https://github.com/OpenObservability/OpenMetrics/blob/4dbf6075567ab43296eed941037c12951faafb92/protos/prometheus.proto#L45) data type. These data points cannot always be merged in a meaningful way. While they can be useful in some applications, histogram data points are recommended for new applications.

type SummaryDataPoint 

type SummaryDataPoint struct {
	// The set of key/value pairs that uniquely identify the timeseries from
	// where this point belongs. The list may be empty (may contain 0 elements).
	// Attribute keys MUST be unique (it is not allowed to have more than one
	// attribute with the same key).
	Attributes []*KeyValue `json:"attributes,omitempty"`
	// StartTimeUnixNano is optional but strongly encouraged, see the
	// the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	StartTimeUnixNano uint64 `json:"start_time_unix_nano,omitempty"`
	// TimeUnixNano is required, see the detailed comments above Metric.
	//
	// Value is UNIX Epoch time in nanoseconds since 00:00:00 UTC on 1 January
	// 1970.
	TimeUnixNano uint64 `json:"time_unix_nano,omitempty"`
	// count is the number of values in the population. Must be non-negative.
	Count uint64 `json:"count,omitempty"`
	// sum of the values in the population. If count is zero then this field
	// must be zero.
	//
	// Note: Sum should only be filled out when measuring non-negative discrete
	// events, and is assumed to be monotonic over the values of these events.
	// Negative events *can* be recorded, but sum should not be filled out when
	// doing so.  This is specifically to enforce compatibility w/ OpenMetrics,
	// see: https://github.com/OpenObservability/OpenMetrics/blob/main/specification/OpenMetrics.md#summary
	Sum float64 `json:"sum,omitempty"`
	// (Optional) list of values at different quantiles of the distribution calculated
	// from the current snapshot. The quantiles must be strictly increasing.
	QuantileValues []*SummaryDataPoint_ValueAtQuantile `json:"quantile_values,omitempty"`
	// Flags that apply to this specific data point.  See DataPointFlags
	// for the available flags and their meaning.
	Flags uint32 `json:"flags,omitempty"`
}

SummaryDataPoint is a single data point in a timeseries that describes the time-varying values of a Summary metric.

type SummaryDataPoint_ValueAtQuantile 

type SummaryDataPoint_ValueAtQuantile struct {
	// The quantile of a distribution. Must be in the interval
	// [0.0, 1.0].
	Quantile float64 `json:"quantile,omitempty"`
	// The value at the given quantile of a distribution.
	//
	// Quantile values must NOT be negative.
	Value float64 `json:"value,omitempty"`
}

Represents the value at a given quantile of a distribution.

To record Min and Max values following conventions are used: - The 1.0 quantile is equivalent to the maximum value observed. - The 0.0 quantile is equivalent to the minimum value observed.

See the following issue for more context: https://github.com/open-telemetry/opentelemetry-proto/issues/125

type TraceID 

type TraceID []byte

func NewTraceID 

func NewTraceID(tid trace.TraceID) *TraceID

func (*TraceID) MarshalJSON 

func (tid *TraceID) MarshalJSON() ([]byte, error)

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