otel: go.opentelemetry.io/otel/sdk/metric Index | Examples | Files | Directories

package metric

import "go.opentelemetry.io/otel/sdk/metric"

Package metric implements the OpenTelemetry metric.Meter API. The SDK supports configurable metrics export behavior through a collection of export interfaces that support various export strategies, described below.

The metric.Meter API consists of methods for constructing each of the basic kinds of metric instrument. There are six types of instrument available to the end user, comprised of three basic kinds of metric instrument (Counter, Gauge, Measure) crossed with two kinds of number (int64, float64).

The API assists the SDK by consolidating the variety of metric instruments into a narrower interface, allowing the SDK to avoid repetition of boilerplate. The API and SDK are separated such that an event reaching the SDK has a uniform structure: an instrument, a label set, and a numerical value.

To this end, the API uses a core.Number type to represent either an int64 or a float64, depending on the instrument's definition. A single implementation interface is used for instruments, metric.InstrumentImpl, and a single implementation interface is used for handles, metric.HandleImpl.

There are three entry points for events in the Metrics API: via instrument handles, via direct instrument calls, and via BatchRecord. The SDK is designed with handles as the primary entry point, the other two entry points are implemented in terms of short-lived handles. For example, the implementation of a direct call allocates a handle, operates on the handle, and releases the handle. Similarly, the implementation of RecordBatch uses a short-lived handle for each measurement in the batch.

Internal Structure

The SDK is designed with minimal use of locking, to avoid adding contention for user-level code. For each handle, whether it is held by user-level code or a short-lived device, there exists an internal record managed by the SDK. Each internal record corresponds to a specific instrument and label set combination.

A sync.Map maintains the mapping of current instruments and label sets to internal records. To create a new handle, the SDK consults the Map to locate an existing record, otherwise it constructs a new record. The SDK maintains a count of the number of references to each record, ensuring that records are not reclaimed from the Map while they are still active from the user's perspective.

Metric collection is performed via a single-threaded call to Collect that sweeps through all records in the SDK, checkpointing their state. When a record is discovered that has no references and has not been updated since the prior collection pass, it is marked for reclamation and removed from the Map. There exists, at this moment, a race condition since another goroutine could, in the same instant, obtain a reference to the handle.

The SDK is designed to tolerate this sort of race condition, in the name of reducing lock contention. It is possible for more than one record with identical instrument and label set to exist simultaneously, though only one can be linked from the Map at a time. To avoid lost updates, the SDK maintains two additional linked lists of records, one managed by the collection code path and one managed by the instrumentation code path.

The SDK maintains a current epoch number, corresponding to the number of completed collections. Each record contains the last epoch during which it was collected and updated. These variables allow the collection code path to detect stale records while allowing the instrumentation code path to detect potential reclamations. When the instrumentation code path detects a potential reclamation, it adds itself to the second linked list, where records are saved from reclamation.

Each record has an associated aggregator, which maintains the current state resulting from all metric events since its last checkpoint. Aggregators may be lock-free or they may use locking, but they should expect to be called concurrently. Because of the tolerated race condition described above, aggregators must be capable of merging with another aggregator of the same type.

Export Pipeline

While the SDK serves to maintain a current set of records and coordinate collection, the behavior of a metrics export pipeline is configured through the export types in go.opentelemetry.io/otel/sdk/export/metric. It is important to keep in mind the context these interfaces are called from. There are two contexts, instrumentation context, where a user-level goroutine that enters the SDK resulting in a new record, and collection context, where a system-level thread performs a collection pass through the SDK.

Descriptor is a struct that describes the metric instrument to the export pipeline, containing the name, recommended aggregation keys, units, description, metric kind (counter, gauge, or measure), number kind (int64 or float64), and whether the instrument has alternate semantics or not (i.e., monotonic=false counter, monotonic=true gauge, absolute=false measure). A Descriptor accompanies metric data as it passes through the export pipeline.

The AggregationSelector interface supports choosing the method of aggregation to apply to a particular instrument. Given the Descriptor, this AggregatorFor method returns an implementation of Aggregator. If this interface returns nil, the metric will be disabled. The aggregator should be matched to the capabilities of the exporter. Selecting the aggregator for counter and gauge instruments is relatively straightforward, but for measure instruments there are numerous choices with different cost and quality tradeoffs.

Aggregator is an interface which implements a concrete strategy for aggregating metric updates. Several Aggregator implementations are provided by the SDK. Aggregators may be lock-free or use locking, depending on their structure and semantics. Aggregators implement an Update method, called in instrumentation context, to receive a single metric event. Aggregators implement a Checkpoint method, called in collection context, to save a checkpoint of the current state. Aggregators implement a Merge method, also called in collection context, that combines state from two aggregators into one. Each SDK record has an associated aggregator.

Batcher is an interface which sits between the SDK and an exporter. The Batcher embeds an AggregationSelector, used by the SDK to assign new Aggregators. The Batcher supports a Process() API for submitting checkpointed aggregators to the batcher, and a CheckpointSet() API for producing a complete checkpoint for the exporter. Two default Batcher implementations are provided, the "defaultkeys" Batcher groups aggregate metrics by their recommended Descriptor.Keys(), the "ungrouped" Batcher aggregates metrics at full dimensionality.

LabelEncoder is an optional optimization that allows an exporter to provide the serialization logic for labels. This allows avoiding duplicate serialization of labels, once as a unique key in the SDK (or Batcher) and once in the exporter.

CheckpointSet is an interface between the Batcher and the Exporter. After completing a collection pass, the Batcher.CheckpointSet() method returns a CheckpointSet, which the Exporter uses to iterate over all the updated metrics.

Record is a struct containing the state of an individual exported metric. This is the result of one collection interface for one instrument and one label set.

Labels is a struct containing an ordered set of labels, the corresponding unique encoding, and the encoder that produced it.

Exporter is the final stage of an export pipeline. It is called with a CheckpointSet capable of enumerating all the updated metrics.

Controller is not an export interface per se, but it orchestrates the export pipeline. For example, a "push" controller will establish a periodic timer to regularly collect and export metrics. A "pull" controller will await a pull request before initiating metric collection. Either way, the job of the controller is to call the SDK Collect() method, then read the checkpoint, then invoke the exporter. Controllers are expected to implement the public metric.MeterProvider API, meaning they can be installed as the global Meter provider.



Package Files

doc.go labelencoder.go list.go refcount_mapped.go sdk.go

func DefaultErrorHandler Uses

func DefaultErrorHandler(err error)

func NewDefaultLabelEncoder Uses

func NewDefaultLabelEncoder() export.LabelEncoder

type ErrorHandler Uses

type ErrorHandler func(error)

type SDK Uses

type SDK struct {
    // contains filtered or unexported fields

SDK implements the OpenTelemetry Meter API. The SDK is bound to a single export.Batcher in `New()`.

The SDK supports a Collect() API to gather and export current data. Collect() should be arranged according to the batcher model. Push-based batchers will setup a timer to call Collect() periodically. Pull-based batchers will call Collect() when a pull request arrives.

func New Uses

func New(batcher export.Batcher, labelEncoder export.LabelEncoder) *SDK

New constructs a new SDK for the given batcher. This SDK supports only a single batcher.

The SDK does not start any background process to collect itself periodically, this responsbility lies with the batcher, typically, depending on the type of export. For example, a pull-based batcher will call Collect() when it receives a request to scrape current metric values. A push-based batcher should configure its own periodic collection.


pusher, err := stdout.NewExportPipeline(stdout.Config{
    PrettyPrint:    true,
    DoNotPrintTime: true, // This makes the output deterministic
if err != nil {
    panic(fmt.Sprintln("Could not initialize stdout exporter:", err))
defer pusher.Stop()

ctx := context.Background()

key := key.New("key")
meter := pusher.Meter("example")

counter := meter.NewInt64Counter("a.counter", metric.WithKeys(key))
labels := meter.Labels(key.String("value"))

counter.Add(ctx, 100, labels)


	"updates": [
			"name": "a.counter{key=value}",
			"sum": 100

func (*SDK) Collect Uses

func (m *SDK) Collect(ctx context.Context) int

Collect traverses the list of active records and exports data for each active instrument. Collect() may not be called concurrently.

During the collection pass, the export.Batcher will receive one Export() call per current aggregation.

Returns the number of records that were checkpointed.

func (*SDK) GetDescriptor Uses

func (m *SDK) GetDescriptor(inst metric.InstrumentImpl) *export.Descriptor

GetDescriptor returns the descriptor of an instrument, which is not part of the public metric API.

func (*SDK) Labels Uses

func (m *SDK) Labels(kvs ...core.KeyValue) api.LabelSet

Labels returns a LabelSet corresponding to the arguments. Passed labels are de-duplicated, with last-value-wins semantics.

func (*SDK) NewFloat64Counter Uses

func (m *SDK) NewFloat64Counter(name string, cos ...api.CounterOptionApplier) api.Float64Counter

func (*SDK) NewFloat64Gauge Uses

func (m *SDK) NewFloat64Gauge(name string, gos ...api.GaugeOptionApplier) api.Float64Gauge

func (*SDK) NewFloat64Measure Uses

func (m *SDK) NewFloat64Measure(name string, mos ...api.MeasureOptionApplier) api.Float64Measure

func (*SDK) NewInt64Counter Uses

func (m *SDK) NewInt64Counter(name string, cos ...api.CounterOptionApplier) api.Int64Counter

func (*SDK) NewInt64Gauge Uses

func (m *SDK) NewInt64Gauge(name string, gos ...api.GaugeOptionApplier) api.Int64Gauge

func (*SDK) NewInt64Measure Uses

func (m *SDK) NewInt64Measure(name string, mos ...api.MeasureOptionApplier) api.Int64Measure

func (*SDK) RecordBatch Uses

func (m *SDK) RecordBatch(ctx context.Context, ls api.LabelSet, measurements ...api.Measurement)

RecordBatch enters a batch of metric events.

func (*SDK) SetErrorHandler Uses

func (m *SDK) SetErrorHandler(f ErrorHandler)



Package metric imports 12 packages (graph) and is imported by 4 packages. Updated 2020-02-21. Refresh now. Tools for package owners.