[chore] update otel libraries (#3740)

* chore: update otel dependencies

* refactor: combine tracing & metrics in observability package

* chore: update example tracing compose file

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/aggregate.go

@@ -8,7 +8,6 @@ import (
 	"time"
 
 	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
@@ -38,8 +37,8 @@ type Builder[N int64 | float64] struct {
 	// create new exemplar reservoirs for a new seen attribute set.
 	//
 	// If this is not provided a default factory function that returns an
-	// exemplar.Drop reservoir will be used.
-	ReservoirFunc func() exemplar.FilteredReservoir[N]
+	// dropReservoir reservoir will be used.
+	ReservoirFunc func(attribute.Set) FilteredExemplarReservoir[N]
 	// AggregationLimit is the cardinality limit of measurement attributes. Any
 	// measurement for new attributes once the limit has been reached will be
 	// aggregated into a single aggregate for the "otel.metric.overflow"
@@ -50,12 +49,12 @@ type Builder[N int64 | float64] struct {
 	AggregationLimit int
 }
 
-func (b Builder[N]) resFunc() func() exemplar.FilteredReservoir[N] {
+func (b Builder[N]) resFunc() func(attribute.Set) FilteredExemplarReservoir[N] {
 	if b.ReservoirFunc != nil {
 		return b.ReservoirFunc
 	}
 
-	return exemplar.Drop
+	return dropReservoir
 }
 
 type fltrMeasure[N int64 | float64] func(ctx context.Context, value N, fltrAttr attribute.Set, droppedAttr []attribute.KeyValue)

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/drop.go

@@ -0,0 +1,27 @@
+// Copyright The OpenTelemetry Authors
+// SPDX-License-Identifier: Apache-2.0
+
+package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
+
+import (
+	"context"
+
+	"go.opentelemetry.io/otel/attribute"
+	"go.opentelemetry.io/otel/sdk/metric/exemplar"
+)
+
+// dropReservoir returns a [FilteredReservoir] that drops all measurements it is offered.
+func dropReservoir[N int64 | float64](attribute.Set) FilteredExemplarReservoir[N] {
+	return &dropRes[N]{}
+}
+
+type dropRes[N int64 | float64] struct{}
+
+// Offer does nothing, all measurements offered will be dropped.
+func (r *dropRes[N]) Offer(context.Context, N, []attribute.KeyValue) {}
+
+// Collect resets dest. No exemplars will ever be returned.
+func (r *dropRes[N]) Collect(dest *[]exemplar.Exemplar) {
+	clear(*dest) // Erase elements to let GC collect objects
+	*dest = (*dest)[:0]
+}

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/exemplar.go

@@ -6,7 +6,7 @@ package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggreg
 import (
 	"sync"
 
-	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
+	"go.opentelemetry.io/otel/sdk/metric/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
@@ -17,6 +17,7 @@ var exemplarPool = sync.Pool{
 func collectExemplars[N int64 | float64](out *[]metricdata.Exemplar[N], f func(*[]exemplar.Exemplar)) {
 	dest := exemplarPool.Get().(*[]exemplar.Exemplar)
 	defer func() {
+		clear(*dest) // Erase elements to let GC collect objects.
 		*dest = (*dest)[:0]
 		exemplarPool.Put(dest)
 	}()

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/exponential_histogram.go

@@ -12,7 +12,6 @@ import (
 
 	"go.opentelemetry.io/otel"
 	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
@@ -31,7 +30,7 @@ const (
 // expoHistogramDataPoint is a single data point in an exponential histogram.
 type expoHistogramDataPoint[N int64 | float64] struct {
 	attrs attribute.Set
-	res   exemplar.FilteredReservoir[N]
+	res   FilteredExemplarReservoir[N]
 
 	count uint64
 	min   N
@@ -51,16 +50,16 @@ type expoHistogramDataPoint[N int64 | float64] struct {
 
 func newExpoHistogramDataPoint[N int64 | float64](attrs attribute.Set, maxSize int, maxScale int32, noMinMax, noSum bool) *expoHistogramDataPoint[N] {
 	f := math.MaxFloat64
-	max := N(f) // if N is int64, max will overflow to -9223372036854775808
-	min := N(-f)
+	ma := N(f) // if N is int64, max will overflow to -9223372036854775808
+	mi := N(-f)
 	if N(maxInt64) > N(f) {
-		max = N(maxInt64)
-		min = N(minInt64)
+		ma = N(maxInt64)
+		mi = N(minInt64)
 	}
 	return &expoHistogramDataPoint[N]{
 		attrs:    attrs,
-		min:      max,
-		max:      min,
+		min:      ma,
+		max:      mi,
 		maxSize:  maxSize,
 		noMinMax: noMinMax,
 		noSum:    noSum,
@@ -284,7 +283,7 @@ func (b *expoBuckets) downscale(delta int32) {
 // newExponentialHistogram returns an Aggregator that summarizes a set of
 // measurements as an exponential histogram. Each histogram is scoped by attributes
 // and the aggregation cycle the measurements were made in.
-func newExponentialHistogram[N int64 | float64](maxSize, maxScale int32, noMinMax, noSum bool, limit int, r func() exemplar.FilteredReservoir[N]) *expoHistogram[N] {
+func newExponentialHistogram[N int64 | float64](maxSize, maxScale int32, noMinMax, noSum bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *expoHistogram[N] {
 	return &expoHistogram[N]{
 		noSum:    noSum,
 		noMinMax: noMinMax,
@@ -307,7 +306,7 @@ type expoHistogram[N int64 | float64] struct {
 	maxSize  int
 	maxScale int32
 
-	newRes   func() exemplar.FilteredReservoir[N]
+	newRes   func(attribute.Set) FilteredExemplarReservoir[N]
 	limit    limiter[*expoHistogramDataPoint[N]]
 	values   map[attribute.Distinct]*expoHistogramDataPoint[N]
 	valuesMu sync.Mutex
@@ -328,7 +327,7 @@ func (e *expoHistogram[N]) measure(ctx context.Context, value N, fltrAttr attrib
 	v, ok := e.values[attr.Equivalent()]
 	if !ok {
 		v = newExpoHistogramDataPoint[N](attr, e.maxSize, e.maxScale, e.noMinMax, e.noSum)
-		v.res = e.newRes()
+		v.res = e.newRes(attr)
 
 		e.values[attr.Equivalent()] = v
 	}

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/filtered_reservoir.go

@@ -0,0 +1,50 @@
+// Copyright The OpenTelemetry Authors
+// SPDX-License-Identifier: Apache-2.0
+
+package aggregate // import "go.opentelemetry.io/otel/sdk/metric/internal/aggregate"
+
+import (
+	"context"
+	"time"
+
+	"go.opentelemetry.io/otel/attribute"
+	"go.opentelemetry.io/otel/sdk/metric/exemplar"
+)
+
+// FilteredExemplarReservoir wraps a [exemplar.Reservoir] with a filter.
+type FilteredExemplarReservoir[N int64 | float64] interface {
+	// Offer accepts the parameters associated with a measurement. The
+	// parameters will be stored as an exemplar if the filter decides to
+	// sample the measurement.
+	//
+	// The passed ctx needs to contain any baggage or span that were active
+	// when the measurement was made. This information may be used by the
+	// Reservoir in making a sampling decision.
+	Offer(ctx context.Context, val N, attr []attribute.KeyValue)
+	// Collect returns all the held exemplars in the reservoir.
+	Collect(dest *[]exemplar.Exemplar)
+}
+
+// filteredExemplarReservoir handles the pre-sampled exemplar of measurements made.
+type filteredExemplarReservoir[N int64 | float64] struct {
+	filter    exemplar.Filter
+	reservoir exemplar.Reservoir
+}
+
+// NewFilteredExemplarReservoir creates a [FilteredExemplarReservoir] which only offers values
+// that are allowed by the filter.
+func NewFilteredExemplarReservoir[N int64 | float64](f exemplar.Filter, r exemplar.Reservoir) FilteredExemplarReservoir[N] {
+	return &filteredExemplarReservoir[N]{
+		filter:    f,
+		reservoir: r,
+	}
+}
+
+func (f *filteredExemplarReservoir[N]) Offer(ctx context.Context, val N, attr []attribute.KeyValue) {
+	if f.filter(ctx) {
+		// only record the current time if we are sampling this measurement.
+		f.reservoir.Offer(ctx, time.Now(), exemplar.NewValue(val), attr)
+	}
+}
+
+func (f *filteredExemplarReservoir[N]) Collect(dest *[]exemplar.Exemplar) { f.reservoir.Collect(dest) }

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/histogram.go

@@ -11,13 +11,12 @@ import (
 	"time"
 
 	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
 type buckets[N int64 | float64] struct {
 	attrs attribute.Set
-	res   exemplar.FilteredReservoir[N]
+	res   FilteredExemplarReservoir[N]
 
 	counts   []uint64
 	count    uint64
@@ -48,13 +47,13 @@ type histValues[N int64 | float64] struct {
 	noSum  bool
 	bounds []float64
 
-	newRes   func() exemplar.FilteredReservoir[N]
+	newRes   func(attribute.Set) FilteredExemplarReservoir[N]
 	limit    limiter[*buckets[N]]
 	values   map[attribute.Distinct]*buckets[N]
 	valuesMu sync.Mutex
 }
 
-func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func() exemplar.FilteredReservoir[N]) *histValues[N] {
+func newHistValues[N int64 | float64](bounds []float64, noSum bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *histValues[N] {
 	// The responsibility of keeping all buckets correctly associated with the
 	// passed boundaries is ultimately this type's responsibility. Make a copy
 	// here so we can always guarantee this. Or, in the case of failure, have
@@ -94,7 +93,7 @@ func (s *histValues[N]) measure(ctx context.Context, value N, fltrAttr attribute
 		//
 		//   buckets = (-∞, 0], (0, 5.0], (5.0, 10.0], (10.0, +∞)
 		b = newBuckets[N](attr, len(s.bounds)+1)
-		b.res = s.newRes()
+		b.res = s.newRes(attr)
 
 		// Ensure min and max are recorded values (not zero), for new buckets.
 		b.min, b.max = value, value
@@ -109,7 +108,7 @@ func (s *histValues[N]) measure(ctx context.Context, value N, fltrAttr attribute
 
 // newHistogram returns an Aggregator that summarizes a set of measurements as
 // an histogram.
-func newHistogram[N int64 | float64](boundaries []float64, noMinMax, noSum bool, limit int, r func() exemplar.FilteredReservoir[N]) *histogram[N] {
+func newHistogram[N int64 | float64](boundaries []float64, noMinMax, noSum bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *histogram[N] {
 	return &histogram[N]{
 		histValues: newHistValues[N](boundaries, noSum, limit, r),
 		noMinMax:   noMinMax,

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/lastvalue.go

@@ -9,7 +9,6 @@ import (
 	"time"
 
 	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
@@ -17,10 +16,10 @@ import (
 type datapoint[N int64 | float64] struct {
 	attrs attribute.Set
 	value N
-	res   exemplar.FilteredReservoir[N]
+	res   FilteredExemplarReservoir[N]
 }
 
-func newLastValue[N int64 | float64](limit int, r func() exemplar.FilteredReservoir[N]) *lastValue[N] {
+func newLastValue[N int64 | float64](limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *lastValue[N] {
 	return &lastValue[N]{
 		newRes: r,
 		limit:  newLimiter[datapoint[N]](limit),
@@ -33,7 +32,7 @@ func newLastValue[N int64 | float64](limit int, r func() exemplar.FilteredReserv
 type lastValue[N int64 | float64] struct {
 	sync.Mutex
 
-	newRes func() exemplar.FilteredReservoir[N]
+	newRes func(attribute.Set) FilteredExemplarReservoir[N]
 	limit  limiter[datapoint[N]]
 	values map[attribute.Distinct]datapoint[N]
 	start  time.Time
@@ -46,7 +45,7 @@ func (s *lastValue[N]) measure(ctx context.Context, value N, fltrAttr attribute.
 	attr := s.limit.Attributes(fltrAttr, s.values)
 	d, ok := s.values[attr.Equivalent()]
 	if !ok {
-		d.res = s.newRes()
+		d.res = s.newRes(attr)
 	}
 
 	d.attrs = attr
@@ -115,7 +114,7 @@ func (s *lastValue[N]) copyDpts(dest *[]metricdata.DataPoint[N], t time.Time) in
 
 // newPrecomputedLastValue returns an aggregator that summarizes a set of
 // observations as the last one made.
-func newPrecomputedLastValue[N int64 | float64](limit int, r func() exemplar.FilteredReservoir[N]) *precomputedLastValue[N] {
+func newPrecomputedLastValue[N int64 | float64](limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *precomputedLastValue[N] {
 	return &precomputedLastValue[N]{lastValue: newLastValue[N](limit, r)}
 }
 

vendor/go.opentelemetry.io/otel/sdk/metric/internal/aggregate/sum.go

@@ -9,25 +9,24 @@ import (
 	"time"
 
 	"go.opentelemetry.io/otel/attribute"
-	"go.opentelemetry.io/otel/sdk/metric/internal/exemplar"
 	"go.opentelemetry.io/otel/sdk/metric/metricdata"
 )
 
 type sumValue[N int64 | float64] struct {
 	n     N
-	res   exemplar.FilteredReservoir[N]
+	res   FilteredExemplarReservoir[N]
 	attrs attribute.Set
 }
 
 // valueMap is the storage for sums.
 type valueMap[N int64 | float64] struct {
 	sync.Mutex
-	newRes func() exemplar.FilteredReservoir[N]
+	newRes func(attribute.Set) FilteredExemplarReservoir[N]
 	limit  limiter[sumValue[N]]
 	values map[attribute.Distinct]sumValue[N]
 }
 
-func newValueMap[N int64 | float64](limit int, r func() exemplar.FilteredReservoir[N]) *valueMap[N] {
+func newValueMap[N int64 | float64](limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *valueMap[N] {
 	return &valueMap[N]{
 		newRes: r,
 		limit:  newLimiter[sumValue[N]](limit),
@@ -42,7 +41,7 @@ func (s *valueMap[N]) measure(ctx context.Context, value N, fltrAttr attribute.S
 	attr := s.limit.Attributes(fltrAttr, s.values)
 	v, ok := s.values[attr.Equivalent()]
 	if !ok {
-		v.res = s.newRes()
+		v.res = s.newRes(attr)
 	}
 
 	v.attrs = attr
@@ -55,7 +54,7 @@ func (s *valueMap[N]) measure(ctx context.Context, value N, fltrAttr attribute.S
 // newSum returns an aggregator that summarizes a set of measurements as their
 // arithmetic sum. Each sum is scoped by attributes and the aggregation cycle
 // the measurements were made in.
-func newSum[N int64 | float64](monotonic bool, limit int, r func() exemplar.FilteredReservoir[N]) *sum[N] {
+func newSum[N int64 | float64](monotonic bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *sum[N] {
 	return &sum[N]{
 		valueMap:  newValueMap[N](limit, r),
 		monotonic: monotonic,
@@ -142,9 +141,9 @@ func (s *sum[N]) cumulative(dest *metricdata.Aggregation) int {
 }
 
 // newPrecomputedSum returns an aggregator that summarizes a set of
-// observatrions as their arithmetic sum. Each sum is scoped by attributes and
+// observations as their arithmetic sum. Each sum is scoped by attributes and
 // the aggregation cycle the measurements were made in.
-func newPrecomputedSum[N int64 | float64](monotonic bool, limit int, r func() exemplar.FilteredReservoir[N]) *precomputedSum[N] {
+func newPrecomputedSum[N int64 | float64](monotonic bool, limit int, r func(attribute.Set) FilteredExemplarReservoir[N]) *precomputedSum[N] {
 	return &precomputedSum[N]{
 		valueMap:  newValueMap[N](limit, r),
 		monotonic: monotonic,
@@ -152,7 +151,7 @@ func newPrecomputedSum[N int64 | float64](monotonic bool, limit int, r func() ex
 	}
 }
 
-// precomputedSum summarizes a set of observatrions as their arithmetic sum.
+// precomputedSum summarizes a set of observations as their arithmetic sum.
 type precomputedSum[N int64 | float64] struct {
 	*valueMap[N]