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// This file is @generated by prost-build.
/// MetricsData represents the metrics data that can be stored in a persistent
/// storage, OR can be embedded by other protocols that transfer OTLP metrics
/// data but do not implement the OTLP protocol.
///
/// The main difference between this message and collector protocol is that
/// in this message there will not be any "control" or "metadata" specific to
/// OTLP protocol.
///
/// When new fields are added into this message, the OTLP request MUST be updated
/// as well.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct MetricsData {
/// An array of ResourceMetrics.
/// For data coming from a single resource this array will typically contain
/// one element. Intermediary nodes that receive data from multiple origins
/// typically batch the data before forwarding further and in that case this
/// array will contain multiple elements.
#[prost(message, repeated, tag = "1")]
pub resource_metrics: ::prost::alloc::vec::Vec<ResourceMetrics>,
}
/// A collection of ScopeMetrics from a Resource.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ResourceMetrics {
/// The resource for the metrics in this message.
/// If this field is not set then no resource info is known.
#[prost(message, optional, tag = "1")]
pub resource: ::core::option::Option<super::super::resource::v1::Resource>,
/// A list of metrics that originate from a resource.
#[prost(message, repeated, tag = "2")]
pub scope_metrics: ::prost::alloc::vec::Vec<ScopeMetrics>,
/// 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.
#[prost(string, tag = "3")]
pub schema_url: ::prost::alloc::string::String,
}
/// A collection of Metrics produced by an Scope.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ScopeMetrics {
/// 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).
#[prost(message, optional, tag = "1")]
pub scope: ::core::option::Option<super::super::common::v1::InstrumentationScope>,
/// A list of metrics that originate from an instrumentation library.
#[prost(message, repeated, tag = "2")]
pub metrics: ::prost::alloc::vec::Vec<Metric>,
/// 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.
#[prost(string, tag = "3")]
pub schema_url: ::prost::alloc::string::String,
}
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Metric {
/// name of the metric.
#[prost(string, tag = "1")]
pub name: ::prost::alloc::string::String,
/// description of the metric, which can be used in documentation.
#[prost(string, tag = "2")]
pub description: ::prost::alloc::string::String,
/// unit in which the metric value is reported. Follows the format
/// described by <http://unitsofmeasure.org/ucum.html.>
#[prost(string, tag = "3")]
pub unit: ::prost::alloc::string::String,
/// 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).
#[prost(message, repeated, tag = "12")]
pub metadata: ::prost::alloc::vec::Vec<super::super::common::v1::KeyValue>,
/// 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.
#[prost(oneof = "metric::Data", tags = "5, 7, 9, 10, 11")]
#[cfg_attr(feature = "with-serde", serde(flatten))]
pub data: ::core::option::Option<metric::Data>,
}
/// Nested message and enum types in `Metric`.
pub mod metric {
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Oneof)]
pub enum Data {
#[prost(message, tag = "5")]
Gauge(super::Gauge),
#[prost(message, tag = "7")]
Sum(super::Sum),
#[prost(message, tag = "9")]
Histogram(super::Histogram),
#[prost(message, tag = "10")]
ExponentialHistogram(super::ExponentialHistogram),
#[prost(message, tag = "11")]
Summary(super::Summary),
}
}
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Gauge {
#[prost(message, repeated, tag = "1")]
pub data_points: ::prost::alloc::vec::Vec<NumberDataPoint>,
}
/// Sum represents the type of a scalar metric that is calculated as a sum of all
/// reported measurements over a time interval.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Sum {
#[prost(message, repeated, tag = "1")]
pub data_points: ::prost::alloc::vec::Vec<NumberDataPoint>,
/// aggregation_temporality describes if the aggregator reports delta changes
/// since last report time, or cumulative changes since a fixed start time.
#[prost(enumeration = "AggregationTemporality", tag = "2")]
pub aggregation_temporality: i32,
/// If "true" means that the sum is monotonic.
#[prost(bool, tag = "3")]
pub is_monotonic: bool,
}
/// Histogram represents the type of a metric that is calculated by aggregating
/// as a Histogram of all reported measurements over a time interval.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Histogram {
#[prost(message, repeated, tag = "1")]
pub data_points: ::prost::alloc::vec::Vec<HistogramDataPoint>,
/// aggregation_temporality describes if the aggregator reports delta changes
/// since last report time, or cumulative changes since a fixed start time.
#[prost(enumeration = "AggregationTemporality", tag = "2")]
pub aggregation_temporality: i32,
}
/// ExponentialHistogram represents the type of a metric that is calculated by aggregating
/// as a ExponentialHistogram of all reported double measurements over a time interval.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ExponentialHistogram {
#[prost(message, repeated, tag = "1")]
pub data_points: ::prost::alloc::vec::Vec<ExponentialHistogramDataPoint>,
/// aggregation_temporality describes if the aggregator reports delta changes
/// since last report time, or cumulative changes since a fixed start time.
#[prost(enumeration = "AggregationTemporality", tag = "2")]
pub aggregation_temporality: i32,
}
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Summary {
#[prost(message, repeated, tag = "1")]
pub data_points: ::prost::alloc::vec::Vec<SummaryDataPoint>,
}
/// NumberDataPoint is a single data point in a timeseries that describes the
/// time-varying scalar value of a metric.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct NumberDataPoint {
/// 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).
#[prost(message, repeated, tag = "7")]
pub attributes: ::prost::alloc::vec::Vec<super::super::common::v1::KeyValue>,
/// 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.
#[prost(fixed64, tag = "2")]
#[cfg_attr(
feature = "with-serde",
serde(
serialize_with = "crate::proto::serializers::serialize_u64_to_string",
deserialize_with = "crate::proto::serializers::deserialize_string_to_u64"
)
)]
pub start_time_unix_nano: u64,
/// 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.
#[prost(fixed64, tag = "3")]
#[cfg_attr(
feature = "with-serde",
serde(
serialize_with = "crate::proto::serializers::serialize_u64_to_string",
deserialize_with = "crate::proto::serializers::deserialize_string_to_u64"
)
)]
pub time_unix_nano: u64,
/// (Optional) List of exemplars collected from
/// measurements that were used to form the data point
#[prost(message, repeated, tag = "5")]
pub exemplars: ::prost::alloc::vec::Vec<Exemplar>,
/// Flags that apply to this specific data point. See DataPointFlags
/// for the available flags and their meaning.
#[prost(uint32, tag = "8")]
pub flags: u32,
/// The value itself. A point is considered invalid when one of the recognized
/// value fields is not present inside this oneof.
#[prost(oneof = "number_data_point::Value", tags = "4, 6")]
#[cfg_attr(feature = "with-serde", serde(flatten))]
pub value: ::core::option::Option<number_data_point::Value>,
}
/// Nested message and enum types in `NumberDataPoint`.
pub mod number_data_point {
/// The value itself. A point is considered invalid when one of the recognized
/// value fields is not present inside this oneof.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, Copy, PartialEq, ::prost::Oneof)]
pub enum Value {
#[prost(double, tag = "4")]
AsDouble(f64),
#[prost(sfixed64, tag = "6")]
AsInt(i64),
}
}
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct HistogramDataPoint {
/// 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).
#[prost(message, repeated, tag = "9")]
pub attributes: ::prost::alloc::vec::Vec<super::super::common::v1::KeyValue>,
/// 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.
#[prost(fixed64, tag = "2")]
#[cfg_attr(
feature = "with-serde",
serde(
serialize_with = "crate::proto::serializers::serialize_u64_to_string",
deserialize_with = "crate::proto::serializers::deserialize_string_to_u64"
)
)]
pub start_time_unix_nano: u64,
/// 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.
#[prost(fixed64, tag = "3")]
#[cfg_attr(
feature = "with-serde",
serde(
serialize_with = "crate::proto::serializers::serialize_u64_to_string",
deserialize_with = "crate::proto::serializers::deserialize_string_to_u64"
)
)]
pub time_unix_nano: u64,
/// 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.
#[prost(fixed64, tag = "4")]
pub count: u64,
/// 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>
#[prost(double, optional, tag = "5")]
pub sum: ::core::option::Option<f64>,
/// 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.
#[prost(fixed64, repeated, tag = "6")]
pub bucket_counts: ::prost::alloc::vec::Vec<u64>,
/// 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.
#[prost(double, repeated, tag = "7")]
pub explicit_bounds: ::prost::alloc::vec::Vec<f64>,
/// (Optional) List of exemplars collected from
/// measurements that were used to form the data point
#[prost(message, repeated, tag = "8")]
pub exemplars: ::prost::alloc::vec::Vec<Exemplar>,
/// Flags that apply to this specific data point. See DataPointFlags
/// for the available flags and their meaning.
#[prost(uint32, tag = "10")]
pub flags: u32,
/// min is the minimum value over (start_time, end_time].
#[prost(double, optional, tag = "11")]
pub min: ::core::option::Option<f64>,
/// max is the maximum value over (start_time, end_time].
#[prost(double, optional, tag = "12")]
pub max: ::core::option::Option<f64>,
}
/// 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.
///
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct ExponentialHistogramDataPoint {
/// 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).
#[prost(message, repeated, tag = "1")]
pub attributes: ::prost::alloc::vec::Vec<super::super::common::v1::KeyValue>,
/// 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.
#[prost(fixed64, tag = "2")]
pub start_time_unix_nano: u64,
/// 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.
#[prost(fixed64, tag = "3")]
pub time_unix_nano: u64,
/// 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.
#[prost(fixed64, tag = "4")]
pub count: u64,
/// 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>
#[prost(double, optional, tag = "5")]
pub sum: ::core::option::Option<f64>,
/// 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.
#[prost(sint32, tag = "6")]
pub scale: i32,
/// 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).
#[prost(fixed64, tag = "7")]
pub zero_count: u64,
/// positive carries the positive range of exponential bucket counts.
#[prost(message, optional, tag = "8")]
pub positive: ::core::option::Option<exponential_histogram_data_point::Buckets>,
/// negative carries the negative range of exponential bucket counts.
#[prost(message, optional, tag = "9")]
pub negative: ::core::option::Option<exponential_histogram_data_point::Buckets>,
/// Flags that apply to this specific data point. See DataPointFlags
/// for the available flags and their meaning.
#[prost(uint32, tag = "10")]
pub flags: u32,
/// (Optional) List of exemplars collected from
/// measurements that were used to form the data point
#[prost(message, repeated, tag = "11")]
pub exemplars: ::prost::alloc::vec::Vec<Exemplar>,
/// min is the minimum value over (start_time, end_time].
#[prost(double, optional, tag = "12")]
pub min: ::core::option::Option<f64>,
/// max is the maximum value over (start_time, end_time].
#[prost(double, optional, tag = "13")]
pub max: ::core::option::Option<f64>,
/// 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.
#[prost(double, tag = "14")]
pub zero_threshold: f64,
}
/// Nested message and enum types in `ExponentialHistogramDataPoint`.
pub mod exponential_histogram_data_point {
/// Buckets are a set of bucket counts, encoded in a contiguous array
/// of counts.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Buckets {
/// 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.
#[prost(sint32, tag = "1")]
pub offset: i32,
/// 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.
#[prost(uint64, repeated, tag = "2")]
pub bucket_counts: ::prost::alloc::vec::Vec<u64>,
}
}
/// SummaryDataPoint is a single data point in a timeseries that describes the
/// time-varying values of a Summary metric.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct SummaryDataPoint {
/// 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).
#[prost(message, repeated, tag = "7")]
pub attributes: ::prost::alloc::vec::Vec<super::super::common::v1::KeyValue>,
/// 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.
#[prost(fixed64, tag = "2")]
pub start_time_unix_nano: u64,
/// 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.
#[prost(fixed64, tag = "3")]
pub time_unix_nano: u64,
/// count is the number of values in the population. Must be non-negative.
#[prost(fixed64, tag = "4")]
pub count: u64,
/// 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>
#[prost(double, tag = "5")]
pub sum: f64,
/// (Optional) list of values at different quantiles of the distribution calculated
/// from the current snapshot. The quantiles must be strictly increasing.
#[prost(message, repeated, tag = "6")]
pub quantile_values: ::prost::alloc::vec::Vec<summary_data_point::ValueAtQuantile>,
/// Flags that apply to this specific data point. See DataPointFlags
/// for the available flags and their meaning.
#[prost(uint32, tag = "8")]
pub flags: u32,
}
/// Nested message and enum types in `SummaryDataPoint`.
pub mod summary_data_point {
/// 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>
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, Copy, PartialEq, ::prost::Message)]
pub struct ValueAtQuantile {
/// The quantile of a distribution. Must be in the interval
/// \[0.0, 1.0\].
#[prost(double, tag = "1")]
pub quantile: f64,
/// The value at the given quantile of a distribution.
///
/// Quantile values must NOT be negative.
#[prost(double, tag = "2")]
pub value: f64,
}
}
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, PartialEq, ::prost::Message)]
pub struct Exemplar {
/// 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
#[prost(message, repeated, tag = "7")]
pub filtered_attributes: ::prost::alloc::vec::Vec<
super::super::common::v1::KeyValue,
>,
/// 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.
#[prost(fixed64, tag = "2")]
pub time_unix_nano: u64,
/// (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.
#[prost(bytes = "vec", tag = "4")]
pub span_id: ::prost::alloc::vec::Vec<u8>,
/// (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.
#[prost(bytes = "vec", tag = "5")]
pub trace_id: ::prost::alloc::vec::Vec<u8>,
/// 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.
#[prost(oneof = "exemplar::Value", tags = "3, 6")]
pub value: ::core::option::Option<exemplar::Value>,
}
/// Nested message and enum types in `Exemplar`.
pub mod exemplar {
/// 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.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, Copy, PartialEq, ::prost::Oneof)]
pub enum Value {
#[prost(double, tag = "3")]
AsDouble(f64),
#[prost(sfixed64, tag = "6")]
AsInt(i64),
}
}
/// AggregationTemporality defines how a metric aggregator reports aggregated
/// values. It describes how those values relate to the time interval over
/// which they are aggregated.
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)]
#[repr(i32)]
pub enum AggregationTemporality {
/// UNSPECIFIED is the default AggregationTemporality, it MUST not be used.
Unspecified = 0,
/// DELTA is an AggregationTemporality for a metric aggregator which reports
/// changes since last report time. Successive metrics contain aggregation of
/// values from continuous and non-overlapping intervals.
///
/// The values for a DELTA metric are based only on the time interval
/// associated with one measurement cycle. There is no dependency on
/// previous measurements like is the case for CUMULATIVE metrics.
///
/// For example, consider a system measuring the number of requests that
/// it receives and reports the sum of these requests every second as a
/// DELTA metric:
///
/// 1. The system starts receiving at time=t_0.
/// 2. A request is received, the system measures 1 request.
/// 3. A request is received, the system measures 1 request.
/// 4. A request is received, the system measures 1 request.
/// 5. The 1 second collection cycle ends. A metric is exported for the
/// number of requests received over the interval of time t_0 to
/// t_0+1 with a value of 3.
/// 6. A request is received, the system measures 1 request.
/// 7. A request is received, the system measures 1 request.
/// 8. The 1 second collection cycle ends. A metric is exported for the
/// number of requests received over the interval of time t_0+1 to
/// t_0+2 with a value of 2.
Delta = 1,
/// CUMULATIVE is an AggregationTemporality for a metric aggregator which
/// reports changes since a fixed start time. This means that current values
/// of a CUMULATIVE metric depend on all previous measurements since the
/// start time. Because of this, the sender is required to retain this state
/// in some form. If this state is lost or invalidated, the CUMULATIVE metric
/// values MUST be reset and a new fixed start time following the last
/// reported measurement time sent MUST be used.
///
/// For example, consider a system measuring the number of requests that
/// it receives and reports the sum of these requests every second as a
/// CUMULATIVE metric:
///
/// 1. The system starts receiving at time=t_0.
/// 2. A request is received, the system measures 1 request.
/// 3. A request is received, the system measures 1 request.
/// 4. A request is received, the system measures 1 request.
/// 5. The 1 second collection cycle ends. A metric is exported for the
/// number of requests received over the interval of time t_0 to
/// t_0+1 with a value of 3.
/// 6. A request is received, the system measures 1 request.
/// 7. A request is received, the system measures 1 request.
/// 8. The 1 second collection cycle ends. A metric is exported for the
/// number of requests received over the interval of time t_0 to
/// t_0+2 with a value of 5.
/// 9. The system experiences a fault and loses state.
/// 10. The system recovers and resumes receiving at time=t_1.
/// 11. A request is received, the system measures 1 request.
/// 12. The 1 second collection cycle ends. A metric is exported for the
/// number of requests received over the interval of time t_1 to
/// t_0+1 with a value of 1.
///
/// Note: Even though, when reporting changes since last report time, using
/// CUMULATIVE is valid, it is not recommended. This may cause problems for
/// systems that do not use start_time to determine when the aggregation
/// value was reset (e.g. Prometheus).
Cumulative = 2,
}
impl AggregationTemporality {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
AggregationTemporality::Unspecified => "AGGREGATION_TEMPORALITY_UNSPECIFIED",
AggregationTemporality::Delta => "AGGREGATION_TEMPORALITY_DELTA",
AggregationTemporality::Cumulative => "AGGREGATION_TEMPORALITY_CUMULATIVE",
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"AGGREGATION_TEMPORALITY_UNSPECIFIED" => Some(Self::Unspecified),
"AGGREGATION_TEMPORALITY_DELTA" => Some(Self::Delta),
"AGGREGATION_TEMPORALITY_CUMULATIVE" => Some(Self::Cumulative),
_ => None,
}
}
}
/// DataPointFlags is defined as a protobuf 'uint32' type and is to be used as a
/// bit-field representing 32 distinct boolean flags. Each flag defined in this
/// enum is a bit-mask. To test the presence of a single flag in the flags of
/// a data point, for example, use an expression like:
///
/// (point.flags & DATA_POINT_FLAGS_NO_RECORDED_VALUE_MASK) == DATA_POINT_FLAGS_NO_RECORDED_VALUE_MASK
///
#[cfg_attr(feature = "with-schemars", derive(schemars::JsonSchema))]
#[cfg_attr(feature = "with-serde", derive(serde::Serialize, serde::Deserialize))]
#[cfg_attr(feature = "with-serde", serde(rename_all = "camelCase"))]
#[derive(Clone, Copy, Debug, PartialEq, Eq, Hash, PartialOrd, Ord, ::prost::Enumeration)]
#[repr(i32)]
pub enum DataPointFlags {
/// The zero value for the enum. Should not be used for comparisons.
/// Instead use bitwise "and" with the appropriate mask as shown above.
DoNotUse = 0,
/// This DataPoint is valid but has no recorded value. This value
/// SHOULD be used to reflect explicitly missing data in a series, as
/// for an equivalent to the Prometheus "staleness marker".
NoRecordedValueMask = 1,
}
impl DataPointFlags {
/// String value of the enum field names used in the ProtoBuf definition.
///
/// The values are not transformed in any way and thus are considered stable
/// (if the ProtoBuf definition does not change) and safe for programmatic use.
pub fn as_str_name(&self) -> &'static str {
match self {
DataPointFlags::DoNotUse => "DATA_POINT_FLAGS_DO_NOT_USE",
DataPointFlags::NoRecordedValueMask => {
"DATA_POINT_FLAGS_NO_RECORDED_VALUE_MASK"
}
}
}
/// Creates an enum from field names used in the ProtoBuf definition.
pub fn from_str_name(value: &str) -> ::core::option::Option<Self> {
match value {
"DATA_POINT_FLAGS_DO_NOT_USE" => Some(Self::DoNotUse),
"DATA_POINT_FLAGS_NO_RECORDED_VALUE_MASK" => Some(Self::NoRecordedValueMask),
_ => None,
}
}
}