Instrumentation
Instrumentation is the act of adding observability code to an app yourself.
If you’re instrumenting an app, you need to use the OpenTelemetry SDK for your language. You’ll then use the SDK to initialize OpenTelemetry and the API to instrument your code. This will emit telemetry from your app, and any library you installed that also comes with instrumentation.
If you’re instrumenting a library, only install the OpenTelemetry API package for your language. Your library will not emit telemetry on its own. It will only emit telemetry when it is part of an app that uses the OpenTelemetry SDK. For more on instrumenting libraries, see Libraries.
For more information about the OpenTelemetry API and SDK, see the specification.
Note
OpenTelemetry C++ doesn’t support automatic instrumentation when the source code of the library you want to instrument isn’t available.Setup
Follow the instructions in the Getting Started Guide to build OpenTelemetry C++.
Traces
Initialize tracing
auto provider = opentelemetry::trace::Provider::GetTracerProvider();
auto tracer = provider->GetTracer("foo_library", "1.0.0");
The TracerProvider
acquired in the first step is a singleton object that is
usually provided by the OpenTelemetry C++ SDK. It is used to provide specific
implementations for API interfaces. In case no SDK is used, the API provides a
default no-op implementation of a TracerProvider
.
The Tracer
acquired in the second step is needed to create and start Spans.
Start a span
auto span = tracer->StartSpan("HandleRequest");
This creates a span, sets its name to "HandleRequest"
, and sets its start time
to the current time. Refer to the API documentation for other operations that
are available to enrich spans with additional data.
Mark a span as active
auto scope = tracer->WithActiveSpan(span);
This marks a span as active and returns a Scope
object. The scope object
controls how long a span is active. The span remains active for the lifetime of
the scope object.
The concept of an active span is important, as any span that is created without explicitly specifying a parent is parented to the currently active span. A span without a parent is called root span.
Create nested spans
auto outer_span = tracer->StartSpan("Outer operation");
auto outer_scope = tracer->WithActiveSpan(outer_span);
{
auto inner_span = tracer->StartSpan("Inner operation");
auto inner_scope = tracer->WithActiveSpan(inner_span);
// ... perform inner operation
inner_span->End();
}
// ... perform outer operation
outer_span->End();
Spans can be nested, and have a parent-child relationship with other spans. When a given span is active, the newly created span inherits the active span’s trace ID, and other context attributes.
Context propagation
// set global propagator
opentelemetry::context::propagation::GlobalTextMapPropagator::SetGlobalPropagator(
nostd::shared_ptr<opentelemetry::context::propagation::TextMapPropagator>(
new opentelemetry::trace::propagation::HttpTraceContext()));
// get global propagator
HttpTextMapCarrier<opentelemetry::ext::http::client::Headers> carrier;
auto propagator =
opentelemetry::context::propagation::GlobalTextMapPropagator::GetGlobalPropagator();
//inject context to headers
auto current_ctx = opentelemetry::context::RuntimeContext::GetCurrent();
propagator->Inject(carrier, current_ctx);
//Extract headers to context
auto current_ctx = opentelemetry::context::RuntimeContext::GetCurrent();
auto new_context = propagator->Extract(carrier, current_ctx);
auto remote_span = opentelemetry::trace::propagation::GetSpan(new_context);
Context
contains the metadata of the currently active Span including Span ID,
Trace ID, and flags. Context Propagation is an important mechanism in
distributed tracing to transfer this Context across service boundary often
through HTTP headers. OpenTelemetry provides a text-based approach to propagate
context to remote services using the W3C Trace Context HTTP headers.
Further reading
Metrics
Initialize exporter and reader
Initialize an exporter and a reader. In this case, you initialize an OStream Exporter which prints to stdout by default. The reader periodically collects metrics from the Aggregation Store and exports them.
std::unique_ptr<opentelemetry::sdk::metrics::MetricExporter> exporter{new opentelemetry::exporters::OStreamMetricExporter};
std::unique_ptr<opentelemetry::sdk::metrics::MetricReader> reader{
new opentelemetry::sdk::metrics::PeriodicExportingMetricReader(std::move(exporter), options)};
Initialize a meter provider
Initialize a MeterProvider and add the reader. Use this to obtain Meter objects in the future.
auto provider = std::shared_ptr<opentelemetry::metrics::MeterProvider>(new opentelemetry::sdk::metrics::MeterProvider());
auto p = std::static_pointer_cast<opentelemetry::sdk::metrics::MeterProvider>(provider);
p->AddMetricReader(std::move(reader));
Create a counter
Create a Counter instrument from the Meter, and record the measurement. Every Meter pointer returned by the MeterProvider points to the same Meter. This means that the Meter can combine metrics captured from different functions without having to constantly pass the Meter around the library.
auto meter = provider->GetMeter(name, "1.2.0");
auto double_counter = meter->CreateDoubleCounter(counter_name);
// Create a label set which annotates metric values
std::map<std::string, std::string> labels = {{"key", "value"}};
auto labelkv = common::KeyValueIterableView<decltype(labels)>{labels};
double_counter->Add(val, labelkv);
Create a histogram
Create a histogram instrument from the meter, and record the measurement.
auto meter = provider->GetMeter(name, "1.2.0");
auto histogram_counter = meter->CreateDoubleHistogram("histogram_name");
histogram_counter->Record(val, labelkv);
Create an observable counter
Create an observable counter instrument from the meter, and add a callback. The callback is used to record the measurement during metrics collection. Ensure to keep the Instrument object active for the lifetime of collection.
auto meter = provider->GetMeter(name, "1.2.0");
auto counter = meter->CreateDoubleObservableCounter(counter_name);
counter->AddCallback(MeasurementFetcher::Fetcher, nullptr);
Create views
Map the counter instrument to sum aggregation
Create a view to map the Counter Instrument to Sum Aggregation. Add this view to provider. View creation is optional unless you want to add custom aggregation config, and attribute processor. Metrics SDK creates a missing view with default mapping between Instrument and Aggregation.
std::unique_ptr<opentelemetry::sdk::metrics::InstrumentSelector> instrument_selector{
new opentelemetry::sdk::metrics::InstrumentSelector(opentelemetry::sdk::metrics::InstrumentType::kCounter, "counter_name")};
std::unique_ptr<opentelemetry::sdk::metrics::MeterSelector> meter_selector{
new opentelemetry::sdk::metrics::MeterSelector(name, version, schema)};
std::unique_ptr<opentelemetry::sdk::metrics::View> sum_view{
new opentelemetry::sdk::metrics::View{name, "description", opentelemetry::sdk::metrics::AggregationType::kSum}};
p->AddView(std::move(instrument_selector), std::move(meter_selector), std::move(sum_view));
Map the histogram instrument to histogram aggregation
std::unique_ptr<opentelemetry::sdk::metrics::InstrumentSelector> histogram_instrument_selector{
new opentelemetry::sdk::metrics::InstrumentSelector(opentelemetry::sdk::metrics::InstrumentType::kHistogram, "histogram_name")};
std::unique_ptr<opentelemetry::sdk::metrics::MeterSelector> histogram_meter_selector{
new opentelemetry::sdk::metrics::MeterSelector(name, version, schema)};
std::unique_ptr<opentelemetry::sdk::metrics::View> histogram_view{
new opentelemetry::sdk::metrics::View{name, "description", opentelemetry::sdk::metrics::AggregationType::kHistogram}};
p->AddView(std::move(histogram_instrument_selector), std::move(histogram_meter_selector),
std::move(histogram_view));
Map the observable counter instrument to sum aggregation
std::unique_ptr<opentelemetry::sdk::metrics::InstrumentSelector> observable_instrument_selector{
new opentelemetry::sdk::metrics::InstrumentSelector(opentelemetry::sdk::metrics::InstrumentType::kObservableCounter,
"observable_counter_name")};
std::unique_ptr<opentelemetry::sdk::metrics::MeterSelector> observable_meter_selector{
new opentelemetry::sdk::metrics::MeterSelector(name, version, schema)};
std::unique_ptr<opentelemetry::sdk::metrics::View> observable_sum_view{
new opentelemetry::sdk::metrics::View{name, "description", opentelemetry::sdk::metrics::AggregationType::kSum}};
p->AddView(std::move(observable_instrument_selector), std::move(observable_meter_selector),
std::move(observable_sum_view));
Further reading
Logs
The documentation for the logs API & SDK is missing, you can help make it available by editing this page.
Next steps
You’ll also want to configure an appropriate exporter to export your telemetry data to one or more telemetry backends.
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