Available on crate features
gen-tonic-messages and metrics only.Modules§
- exemplar
- Nested message and enum types in
Exemplar. - exponential_
histogram_ data_ point - Nested message and enum types in
ExponentialHistogramDataPoint. - metric
- Nested message and enum types in
Metric. - number_
data_ point - Nested message and enum types in
NumberDataPoint. - summary_
data_ point - Nested message and enum types in
SummaryDataPoint.
Structs§
- Exemplar
- 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.
- Exponential
Histogram - ExponentialHistogram represents the type of a metric that is calculated by aggregating as a ExponentialHistogram of all reported double measurements over a time interval.
- Exponential
Histogram Data Point - 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.
- Gauge
- 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.
- Histogram
- Histogram represents the type of a metric that is calculated by aggregating as a Histogram of all reported measurements over a time interval.
- Histogram
Data Point - 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.
- Metric
- Defines a Metric which has one or more timeseries. The following is a brief summary of the Metric data model. For more details, see:
- Metrics
Data - 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.
- Number
Data Point - NumberDataPoint is a single data point in a timeseries that describes the time-varying scalar value of a metric.
- Resource
Metrics - A collection of ScopeMetrics from a Resource.
- Scope
Metrics - A collection of Metrics produced by an Scope.
- Sum
- Sum represents the type of a scalar metric that is calculated as a sum of all reported measurements over a time interval.
- Summary
- 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. Summary metrics do not have an aggregation temporality field. This is because the count and sum fields of a SummaryDataPoint are assumed to be cumulative values.
- Summary
Data Point - SummaryDataPoint is a single data point in a timeseries that describes the time-varying values of a Summary metric. The count and sum fields represent cumulative values.
Enums§
- Aggregation
Temporality - AggregationTemporality defines how a metric aggregator reports aggregated values. It describes how those values relate to the time interval over which they are aggregated.
- Data
Point Flags - 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: