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// Copyright The OpenTelemetry Authors
// SPDX-License-Identifier: Apache-2.0
package runtime // import "go.opentelemetry.io/contrib/instrumentation/runtime"
import (
"context"
"errors"
"math"
"runtime/metrics"
"sync"
"time"
"go.opentelemetry.io/otel/attribute"
"go.opentelemetry.io/otel/sdk/instrumentation"
"go.opentelemetry.io/otel/sdk/metric"
"go.opentelemetry.io/otel/sdk/metric/metricdata"
)
var startTime time.Time
func init() {
startTime = time.Now()
}
var histogramMetrics = []string{goSchedLatencies}
// Producer is a metric.Producer, which provides precomputed histogram metrics from the go runtime.
type Producer struct {
lock sync.Mutex
collector *goCollector
}
var _ metric.Producer = (*Producer)(nil)
// NewProducer creates a Producer which provides precomputed histogram metrics from the go runtime.
func NewProducer(opts ...ProducerOption) *Producer {
c := newProducerConfig(opts...)
return &Producer{
collector: newCollector(c.MinimumReadMemStatsInterval, histogramMetrics),
}
}
// Produce returns precomputed histogram metrics from the go runtime, or an error if unsuccessful.
func (p *Producer) Produce(context.Context) ([]metricdata.ScopeMetrics, error) {
p.lock.Lock()
p.collector.refresh()
schedHist := p.collector.getHistogram(goSchedLatencies)
p.lock.Unlock()
// Use the last collection time (which may or may not be now) for the timestamp.
histDp := convertRuntimeHistogram(schedHist, p.collector.lastCollect)
if len(histDp) == 0 {
return nil, errors.New("unable to obtain go.schedule.duration metric from the runtime")
}
return []metricdata.ScopeMetrics{
{
Scope: instrumentation.Scope{
Name: ScopeName,
Version: Version(),
},
Metrics: []metricdata.Metrics{
{
Name: "go.schedule.duration",
Description: "The time goroutines have spent in the scheduler in a runnable state before actually running.",
Unit: "s",
Data: metricdata.Histogram[float64]{
Temporality: metricdata.CumulativeTemporality,
DataPoints: histDp,
},
},
},
},
}, nil
}
var emptySet = attribute.EmptySet()
func convertRuntimeHistogram(runtimeHist *metrics.Float64Histogram, ts time.Time) []metricdata.HistogramDataPoint[float64] {
if runtimeHist == nil {
return nil
}
bounds := runtimeHist.Buckets
counts := runtimeHist.Counts
if len(bounds) < 2 {
// runtime histograms are guaranteed to have at least two bucket boundaries.
return nil
}
// trim the first bucket since it is a lower bound. OTel histogram boundaries only have an upper bound.
bounds = bounds[1:]
if bounds[len(bounds)-1] == math.Inf(1) {
// trim the last bucket if it is +Inf, since the +Inf boundary is implicit in OTel.
bounds = bounds[:len(bounds)-1]
} else {
// if the last bucket is not +Inf, append an extra zero count since
// the implicit +Inf bucket won't have any observations.
counts = append(counts, 0)
}
count := uint64(0)
sum := float64(0)
for i, c := range counts {
count += c
// This computed sum is an underestimate, since it assumes each
// observation happens at the bucket's lower bound.
if i > 0 && count != 0 {
sum += bounds[i-1] * float64(count)
}
}
return []metricdata.HistogramDataPoint[float64]{
{
StartTime: startTime,
Count: count,
Sum: sum,
Time: ts,
Bounds: bounds,
BucketCounts: counts,
Attributes: *emptySet,
},
}
}
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