Recording metrics

This topic explains how to record metrics through the SDK observability plugin.

Overview

The observability plugin provides different functions depending on what kind of data you want to record.

The recorded data is available as an $ld:telemetry:metric event. To learn more, read Metrics autogenerated from observability events.

You can view all metrics sent to LaunchDarkly under Metrics in the LaunchDarkly user interface. To learn more, read Metrics.

Details about each SDK’s configuration are available in the SDK-specific sections below:

• Client-side SDKs
• Server-side SDKs

Client-side SDKs

This feature is available in the observability plugin for the following client-side SDKs:

• iOS
• Android
• JavaScript
• React Native
• React Web
• Vue

iOS

Expand iOS code sample

When you record a metric with the observability plugin, it must include a name and value. Optionally, it can also include attributes and a timestamp. To construct the attributes, use Attributes from the @opentelemetry/api.

Here are the options for recording metrics:

Record point-in-time

        LDObserve.shared.recordMetric(metric: .init(name: "elapsedTimeMs", value: 2200))

To learn more, read Observe.

Android

Expand Android code sample

When you record a metric with the observability plugin, it must include a name and value. Optionally, it can also include attributes and a timestamp. To construct the attributes, use Attributes from the @opentelemetry/api.

Here are the options for recording metrics:

Record point-in-time

        LDObserve.recordMetric(Metric("elapsedTimeMs", 2200))

To learn more, read LDObserve.

Java

Script

Expand JavaScript code sample

Here are the options for recording metrics:

Record point-in-time

      const onClick = () => {
        const start = Date.now();
        doInterestingWork();
        const elapsed = Date.now() - start;
        LDObserve.recordGauge({name: "elapsedTimeMs", value: elapsed});
      };

To learn more, read Observe.

React Native

Expand React Native code sample

When you record a metric with the observability plugin, it must include a name and value. Optionally, it can also include attributes and a timestamp. To construct the attributes, use Attributes from the @opentelemetry/api.

Here are the options for recording metrics:

Record point-in-time

        LDObserve.recordMetric({name: "elapsedTimeMs", value: 2200});

To learn more, read Observe.

React Web

To record metrics with the React Web SDK, follow the example for JavaScript.

Vue

To record metrics with the Vue SDK, follow the example for JavaScript.

Server-side SDKs

This feature is available in the observability plugin for the following server-side SDKs:

• .NET (server-side)
• Go
• Node.js (server-side)
• Python

.NET (server-side)

Expand .NET (server-side) code sample

Here are the options for recording metrics:

Record point-in-time

        Observe.RecordMetric(name, value, attributes);

To learn more, read Observe.

Go

Expand Go code sample

To record a metric, pass the Go context.Context, as well as the name, value, and optional attributes of the metric to the appropriate Record* function. For example, you might want to record the value for a point-in-time measurement, such as the current CPU utilization percentage, or for a counter, such as the number of cache hits. The optional attributes may include any attributes from the OpenTelemetry specification.

Metrics with the same name and attributes are aggregated using the OpenTelemetry SDK. To learn more, read the OTel documentation on the Metrics Data Model.

Here are the options for recording metrics:

Record point-in-time

        ldobserve.RecordMetric(ctx, "example-metric-name", 3.7)

To learn more, read RecordMetric, RecordCount, and RecordHistogram.

Node.js (server-side)

Expand Node.js (server-side) code sample

To record a metric, first create the metric within your application. The Metric interface includes a name, value, and optional tags. For example, you might create a metric for a point-in-time measurement, such as the current CPU utilization percentage, or for a counter, such as the number of cache hits.

Values with the same metric name and attributes are aggregated using the OpenTelemetry SDK. To learn more, read the OTel documentation on the Metrics Data Model.

Create OTel metric

      const metric = {
        name: "exampleMetric",
        value: 42
      }

Here are the options for recording metrics:

Record point-in-time

        LDObserve.recordMetric(metric);

To learn more, read Observe.

Python

Expand Python code sample

To record a metric, pass the name, value, and optional attributes to the appropriate record_* function. For example, you might want to record the value for a point-in-time measurement, such as the current CPU utilization percentage, or for a counter, such as the number of cache hits. The optional attributes may include any attributes from the OpenTelemetry specification.

Metrics with the same name and attributes are aggregated using the OpenTelemetry SDK. To learn more, read the OTel documentation on the Metrics Data Model.

Here are the options for recording metrics:

Record point-in-time

        observe.record_metric("example-metric-name", 3.7)

To learn more, read ldobserve.