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.
ExponentialHistogram represents the type of a metric that is calculated by aggregating
as a ExponentialHistogram of all reported double measurements over a time interval.
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 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.
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.
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.
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.
AggregationTemporality defines how a metric aggregator reports aggregated
values. It describes how those values relate to the time interval over
which they are aggregated.
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: