What is @opentelemetry/sdk-metrics-base?
@opentelemetry/sdk-metrics-base is a package that provides the core functionalities for collecting and reporting metrics in applications using OpenTelemetry. It allows developers to create and manage various types of metrics, such as counters, gauges, and histograms, and export them to different backends for monitoring and analysis.
What are @opentelemetry/sdk-metrics-base's main functionalities?
Creating a Meter
This code demonstrates how to create a MeterProvider and obtain a Meter instance. A Meter is used to create and manage metrics.
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const meterProvider = new MeterProvider();
const meter = meterProvider.getMeter('example-meter');
Creating a Counter
This code shows how to create a Counter metric and increment its value. Counters are used to count occurrences of events.
const counter = meter.createCounter('example_counter', {
description: 'An example counter'
});
counter.add(10);
Creating a Histogram
This code demonstrates how to create a Histogram metric and record a value. Histograms are used to measure the distribution of values.
const histogram = meter.createHistogram('example_histogram', {
description: 'An example histogram'
});
histogram.record(100);
Creating an UpDownCounter
This code shows how to create an UpDownCounter metric and adjust its value up or down. UpDownCounters are used to track values that can increase or decrease.
const upDownCounter = meter.createUpDownCounter('example_updowncounter', {
description: 'An example updown counter'
});
upDownCounter.add(5);
upDownCounter.add(-3);
Exporting Metrics
This code demonstrates how to export metrics using a ConsoleMetricExporter. Metrics can be exported to various backends for monitoring and analysis.
const { ConsoleMetricExporter, PeriodicExportingMetricReader } = require('@opentelemetry/sdk-metrics-base');
const exporter = new ConsoleMetricExporter();
meterProvider.addMetricReader(new PeriodicExportingMetricReader({ exporter }));
Other packages similar to @opentelemetry/sdk-metrics-base
prom-client
prom-client is a Prometheus client for Node.js that allows you to create and manage metrics, such as counters, gauges, histograms, and summaries. It is similar to @opentelemetry/sdk-metrics-base in that it provides a way to collect and export metrics, but it is specifically designed for use with Prometheus.
statsd
statsd is a simple, lightweight daemon that listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite). It is similar to @opentelemetry/sdk-metrics-base in that it collects and reports metrics, but it is more focused on network-based metric collection.
newrelic
newrelic is a Node.js agent for New Relic, which provides performance monitoring and management for applications. It is similar to @opentelemetry/sdk-metrics-base in that it collects and reports metrics, but it is specifically designed to work with the New Relic platform.
OpenTelemetry Metrics SDK
OpenTelemetry metrics allow a user to collect data and export it to a metrics backend like Prometheus.
Installation
npm install --save @opentelemetry/sdk-metrics-base
Usage
Counter
Choose this kind of metric when the value is a quantity, the sum is of primary interest, and the event count and value distribution are not of primary interest. It is restricted to non-negative increments.
Example uses for Counter:
- count the number of bytes received
- count the number of requests completed
- count the number of accounts created
- count the number of checkpoints run
- count the number of 5xx errors.
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const meter = new MeterProvider().getMeter('your-meter-name');
const counter = meter.createCounter('metric_name', {
description: 'Example of a counter'
});
const labels = { pid: process.pid };
const boundCounter = counter.bind(labels);
boundCounter.add(10);
UpDownCounter
UpDownCounter
is similar to Counter
except that it supports negative increments. It is generally useful for capturing changes in an amount of resources used, or any quantity that rises and falls during a request.
Example uses for UpDownCounter:
- count the number of active requests
- count memory in use by instrumenting new and delete
- count queue size by instrumenting enqueue and dequeue
- count semaphore up and down operations
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const meter = new MeterProvider().getMeter('your-meter-name');
const counter = meter.createUpDownCounter('metric_name', {
description: 'Example of a UpDownCounter'
});
const labels = { pid: process.pid };
const boundCounter = counter.bind(labels);
boundCounter.add(Math.random() > 0.5 ? 1 : -1);
Value Observer
Choose this kind of metric when only last value is important without worry about aggregation.
The callback can be sync or async.
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const meter = new MeterProvider().getMeter('your-meter-name');
meter.createValueObserver('your_metric_name', {
description: 'Example of an async observer with callback',
}, async (observerResult) => {
const value = await getAsyncValue();
observerResult.observe(value, { label: '1' });
});
function getAsyncValue() {
return new Promise((resolve) => {
setTimeout(()=> {
resolve(Math.random());
}, 100);
});
}
meter.createValueObserver('your_metric_name', {
description: 'Example of a sync observer with callback',
}, (observerResult) => {
observerResult.observe(getRandomValue(), { label: '1' });
observerResult.observe(getRandomValue(), { label: '2' });
});
function getRandomValue() {
return Math.random();
}
UpDownSumObserver
Choose this kind of metric when sum is important and you want to capture any value that starts at zero and rises or falls throughout the process lifetime.
The callback can be sync or async.
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const meter = new MeterProvider().getMeter('your-meter-name');
meter.createUpDownSumObserver('your_metric_name', {
description: 'Example of an async observer with callback',
}, async (observerResult) => {
const value = await getAsyncValue();
observerResult.observe(value, { label: '1' });
});
function getAsyncValue() {
return new Promise((resolve) => {
setTimeout(()=> {
resolve(Math.random());
}, 100);
});
}
meter.createUpDownSumObserver('your_metric_name', {
description: 'Example of a sync observer with callback',
}, (observerResult) => {
observerResult.observe(getRandomValue(), { label: '1' });
});
function getRandomValue() {
return Math.random();
}
Sum Observer
Choose this kind of metric when collecting a sum that never decreases.
The callback can be sync or async.
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const meter = new MeterProvider().getMeter('your-meter-name');
meter.createSumObserver('example_metric', {
description: 'Example of an async sum observer with callback',
}, async (observerResult) => {
const value = await getAsyncValue();
observerResult.observe(value, { label: '1' });
});
function getAsyncValue() {
return new Promise((resolve) => {
setTimeout(() => {
resolve(Math.random());
}, 100)
});
}
meter.createSumObserver('example_metric', {
description: 'Example of a sync sum observer with callback',
}, (observerResult) => {
const value = getRandomValue();
observerResult.observe(value, { label: '1' });
});
function getRandomValue() {
return Math.random();
}
Batch Observer
Choose this kind of metric when you need to update multiple observers with the results of a single async calculation.
const { MeterProvider } = require('@opentelemetry/sdk-metrics-base');
const { PrometheusExporter } = require('@opentelemetry/exporter-prometheus');
const exporter = new PrometheusExporter(
{
startServer: true,
},
() => {
console.log('prometheus scrape endpoint: http://localhost:9464/metrics');
},
);
const meter = new MeterProvider({
exporter,
interval: 3000,
}).getMeter('example-observer');
const cpuUsageMetric = meter.createValueObserver('cpu_usage_per_app', {
description: 'CPU',
});
const MemUsageMetric = meter.createValueObserver('mem_usage_per_app', {
description: 'Memory',
});
meter.createBatchObserver((observerBatchResult) => {
getSomeAsyncMetrics().then(metrics => {
observerBatchResult.observe({ app: 'myApp' }, [
cpuUsageMetric.observation(metrics.value1),
MemUsageMetric.observation(metrics.value2)
]);
});
});
function getSomeAsyncMetrics() {
return new Promise((resolve, reject) => {
setTimeout(() => {
resolve({
value1: Math.random(),
value2: Math.random(),
});
}, 100)
});
}
See examples/prometheus for a short example.
Value Recorder
ValueRecorder
is a non-additive synchronous instrument useful for recording any non-additive number, positive or negative.
Values captured by ValueRecorder.record(value)
are treated as individual events belonging to a distribution that is being summarized.
ValueRecorder
should be chosen either when capturing measurements that do not contribute meaningfully to a sum, or when capturing numbers that are additive in nature, but where the distribution of individual increments is considered interesting.
Useful links
License
Apache 2.0 - See LICENSE for more information.