Monitoring Client Libraries

This page shows how to get started with the Cloud Client Libraries for the Cloud Monitoring API. Read more about the client libraries for Cloud APIs, including the older Google APIs Client Libraries, in Client Libraries Explained.

The samples on this page use custom, or user-defined, metrics to illustrate the use of the client libraries. The system-defined metrics described in the Metrics list are collected for you. You don't need to write any code to collect them, although the agent metrics do require the installation of the Cloud Monitoring agent. For more information on agent metrics, see the Agent metrics list.

For information about the previous Monitoring API client libraries, see Monitoring API Client Libraries.

Installing the client library


For more information, see Setting Up a C# Development Environment.

In Visual Studio 2013/2015, open the Package Manager Console and run this command:

Install-Package Google.Cloud.Monitoring.V3 -Pre


For more information, see Setting Up a Go Development Environment.

go get -u


For more information, see Setting Up a Java Development Environment.

Si usas Maven con una BOM, agrega lo siguiente al archivo pom.xml:



Si usas Maven sin una BOM, agrega esto a las dependencias:


Si usas Gradle, agrega lo siguiente a las dependencias:

compile ''

Si usas sbt, agrega lo siguiente a las dependencias:

libraryDependencies += "" % "google-cloud-monitoring" % "2.0.4"

Si usas IntelliJ o Eclipse, puedes agregar bibliotecas cliente a tu proyecto mediante los siguientes complementos de IDE:

Los complementos brindan funcionalidades adicionales, como administración de claves para las cuentas de servicio. Consulta la documentación de cada complemento para obtener más detalles.


For more information, see Setting Up a Node.js Development Environment.

npm install --save @google-cloud/monitoring


For more information, see Using PHP on Google Cloud.

composer require google/cloud-monitoring


For more information, see Setting Up a Python Development Environment.

pip install --upgrade google-cloud-monitoring


For more information, see Setting Up a Ruby Development Environment.

gem install google-cloud-monitoring

Setting up authentication

To run the client library, you must first set up authentication by creating a service account and setting an environment variable. Complete the following steps to set up authentication. For other ways to authenticate, see the GCP authentication documentation.

Cloud Console

  1. En Cloud Console, ve a la página Crear una clave de cuenta de servicio.

    Ir a la página Crear clave de la cuenta de servicio
  2. En la lista Cuenta de servicio, selecciona Cuenta de servicio nueva.
  3. Ingresa un nombre en el campo Nombre de cuenta de servicio.
  4. En la lista Función, selecciona Proyecto > Propietario.

  5. Haz clic en Crear. Se descargará un archivo JSON que contiene tus claves a tu computadora.

Línea de comandos

Puedes ejecutar los siguientes comandos mediante el SDK de Cloud en tu máquina local o en Cloud Shell.

  1. Crea la cuenta de servicio. Reemplaza NAME por un nombre para la cuenta de servicio.

    gcloud iam service-accounts create NAME
  2. Otorga permisos a la cuenta de servicio. Reemplaza PROJECT_ID por el ID del proyecto.

    gcloud projects add-iam-policy-binding PROJECT_ID --member="" --role="roles/owner"
  3. Genera el archivo de claves. Reemplaza FILE_NAME por un nombre para el archivo de claves.

    gcloud iam service-accounts keys create FILE_NAME.json

Configura la variable de entorno GOOGLE_APPLICATION_CREDENTIALS para proporcionar credenciales de autenticación al código de la aplicación. Reemplaza [PATH] por la ruta de acceso del archivo JSON que contiene la clave de tu cuenta de servicio. Esta variable solo se aplica a la sesión actual de shell. Por lo tanto, si abres una sesión nueva, deberás volver a configurar la variable.

Linux o macOS


Por ejemplo:

export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/my-key.json"


Con PowerShell:


Por ejemplo:


Con el símbolo del sistema:


Using the client library

The following example shows how to use the client library.


See for instructions on using Visual Studio to build and run this sample C# code.

using System;
using System.Collections.Generic;
using Google.Cloud.Monitoring.V3;
using Google.Protobuf.WellKnownTypes;
using Google.Api;
using Google.Api.Gax.ResourceNames;

namespace GoogleCloudSamples
    public class QuickStart
        public static void Main(string[] args)
            // Your Google Cloud Platform project ID.
            string projectId = "YOUR-PROJECT-ID";

            // Create client.
            MetricServiceClient metricServiceClient = MetricServiceClient.Create();

            // Initialize request argument(s).
            ProjectName name = new ProjectName(projectId);

            // Prepare a data point.
            TypedValue salesTotal = new TypedValue
                DoubleValue = 123.45
            Point dataPoint = new Point
                Value = salesTotal
            // Sets data point's interval end time to current time.
            DateTime UnixEpoch = new DateTime(1970, 1, 1, 0, 0, 0, DateTimeKind.Utc);
            Timestamp timeStamp = new Timestamp
                Seconds = (long)(DateTime.UtcNow - UnixEpoch).TotalSeconds
            TimeInterval interval = new TimeInterval
                EndTime = timeStamp
            dataPoint.Interval = interval;

            // Prepare custom metric.
            Metric metric = new Metric
                Type = ""
            metric.Labels.Add("store_id", "Pittsburgh");

            // Prepare monitored resource.
            MonitoredResource resource = new MonitoredResource
                Type = "gce_instance"
            resource.Labels.Add("project_id", projectId);
            resource.Labels.Add("instance_id", "1234567890123456789");
            resource.Labels.Add("zone", "us-central1-f");

            // Create a new time series using inputs.
            TimeSeries timeSeriesData = new TimeSeries
                Metric = metric,
                Resource = resource

            // Add newly created time series to list of time series to be written.
            IEnumerable<TimeSeries> timeSeries = new List<TimeSeries> { timeSeriesData };
            // Write time series data.
            metricServiceClient.CreateTimeSeries(name, timeSeries);
            Console.WriteLine("Done writing time series data.");


// Sample monitoring-quickstart writes a data point to Stackdriver Monitoring.
package main

import (

	monitoring ""
	googlepb ""
	metricpb ""
	monitoredrespb ""
	monitoringpb ""

func main() {
	ctx := context.Background()

	// Creates a client.
	client, err := monitoring.NewMetricClient(ctx)
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)

	// Sets your Google Cloud Platform project ID.
	projectID := "YOUR_PROJECT_ID"

	// Prepares an individual data point
	dataPoint := &monitoringpb.Point{
		Interval: &monitoringpb.TimeInterval{
			EndTime: &googlepb.Timestamp{
				Seconds: time.Now().Unix(),
		Value: &monitoringpb.TypedValue{
			Value: &monitoringpb.TypedValue_DoubleValue{
				DoubleValue: 123.45,

	// Writes time series data.
	if err := client.CreateTimeSeries(ctx, &monitoringpb.CreateTimeSeriesRequest{
		Name: monitoring.MetricProjectPath(projectID),
		TimeSeries: []*monitoringpb.TimeSeries{
				Metric: &metricpb.Metric{
					Type: "",
					Labels: map[string]string{
						"store_id": "Pittsburg",
				Resource: &monitoredrespb.MonitoredResource{
					Type: "global",
					Labels: map[string]string{
						"project_id": projectID,
				Points: []*monitoringpb.Point{
	}); err != nil {
		log.Fatalf("Failed to write time series data: %v", err)

	// Closes the client and flushes the data to Stackdriver.
	if err := client.Close(); err != nil {
		log.Fatalf("Failed to close client: %v", err)

	fmt.Printf("Done writing time series data.\n")


import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

// Imports the Google Cloud client library

public class QuickstartSample {

  public static void main(String... args) throws Exception {
    // Your Google Cloud Platform project ID
    String projectId = System.getProperty("projectId");

    if (projectId == null) {
      System.err.println("Usage: QuickstartSample -DprojectId=YOUR_PROJECT_ID");

    // Instantiates a client
    MetricServiceClient metricServiceClient = MetricServiceClient.create();

    // Prepares an individual data point
    TimeInterval interval =
    TypedValue value = TypedValue.newBuilder().setDoubleValue(3.14).build();
    Point point = Point.newBuilder().setInterval(interval).setValue(value).build();

    List<Point> pointList = new ArrayList<>();

    ProjectName name = ProjectName.of(projectId);

    // Prepares the metric descriptor
    Map<String, String> metricLabels = new HashMap<String, String>();
    metricLabels.put("store_id", "Pittsburg");
    Metric metric =

    // Prepares the monitored resource descriptor
    Map<String, String> resourceLabels = new HashMap<String, String>();
    resourceLabels.put("instance_id", "1234567890123456789");
    resourceLabels.put("zone", "us-central1-f");
    MonitoredResource resource =

    // Prepares the time series request
    TimeSeries timeSeries =
    List<TimeSeries> timeSeriesList = new ArrayList<>();

    CreateTimeSeriesRequest request =

    // Writes time series data

    System.out.printf("Done writing time series data.%n");



// Imports the Google Cloud client library
const monitoring = require('@google-cloud/monitoring');

async function quickstart() {
  // Your Google Cloud Platform project ID
  const projectId = process.env.GCLOUD_PROJECT || 'YOUR_PROJECT_ID';

  // Creates a client
  const client = new monitoring.MetricServiceClient();

  // Prepares an individual data point
  const dataPoint = {
    interval: {
      endTime: {
        seconds: / 1000,
    value: {
      // The amount of sales
      doubleValue: 123.45,

  // Prepares the time series request
  const request = {
    name: client.projectPath(projectId),
    timeSeries: [
        // Ties the data point to a custom metric
        metric: {
          type: '',
          labels: {
            store_id: 'Pittsburgh',
        resource: {
          type: 'global',
          labels: {
            project_id: projectId,
        points: [dataPoint],

  // Writes time series data
  const [result] = await client.createTimeSeries(request);
  console.log('Done writing time series data.', result);


# Includes the autoloader for libraries installed with composer
require_once __DIR__ . '/vendor/autoload.php';

# Imports the Google Cloud client library
use Google\Api\Metric;
use Google\Api\MonitoredResource;
use Google\Cloud\Monitoring\V3\MetricServiceClient;
use Google\Cloud\Monitoring\V3\Point;
use Google\Cloud\Monitoring\V3\TimeInterval;
use Google\Cloud\Monitoring\V3\TimeSeries;
use Google\Cloud\Monitoring\V3\TypedValue;
use Google\Protobuf\Timestamp;

// These variables are set by the App Engine environment. To test locally,
// ensure these are set or manually change their values.
$projectId = getenv('GCLOUD_PROJECT') ?: 'YOUR_PROJECT_ID';
$instanceId = '1234567890123456789';
$zone = 'us-central1-f';

try {
    $client = new MetricServiceClient();
    $formattedProjectName = $client->projectName($projectId);
    $labels = [
        'instance_id' => $instanceId,
        'zone' => $zone,

    $m = new Metric();

    $r = new MonitoredResource();

    $value = new TypedValue();

    $timestamp = new Timestamp();

    $interval = new TimeInterval();

    $point = new Point();
    $points = [$point];

    $timeSeries = new TimeSeries();

    $client->createTimeSeries($formattedProjectName, [$timeSeries]);
    print('Successfully submitted a time series' . PHP_EOL);
} finally {


from import monitoring_v3

import time

client = monitoring_v3.MetricServiceClient()
# project = 'my-project'  # TODO: Update to your project ID.
project_name = f"projects/{project}"

series = monitoring_v3.TimeSeries()
series.metric.type = ""
series.resource.type = "gce_instance"
series.resource.labels["instance_id"] = "1234567890123456789"
series.resource.labels["zone"] = "us-central1-f"
now = time.time()
seconds = int(now)
nanos = int((now - seconds) * 10 ** 9)
interval = monitoring_v3.TimeInterval(
    {"end_time": {"seconds": seconds, "nanos": nanos}}
point = monitoring_v3.Point({"interval": interval, "value": {"double_value": 3.14}})
series.points = [point]
client.create_time_series(request={"name": project_name, "time_series": [series]})
print("Successfully wrote time series.")


# Your Google Cloud Platform project ID
# project_id = "YOUR_PROJECT_ID"

# Example metric label
# metric_label = "my-value"

# Instantiates a client
metric_service_client = Google::Cloud::Monitoring.metric_service
project_path = metric_service_client.project_path project: project_id

series =
series.metric = type:   "",
                                        labels: { "my_key" => metric_label }

resource = type: "gce_instance"
resource.labels["project_id"] = project_id
resource.labels["instance_id"] = "1234567890123456789"
resource.labels["zone"] = "us-central1-f"
series.resource = resource

point =
point.value = double_value: 3.14
now =
end_time = seconds: now.to_i, nanos: now.nsec
point.interval = end_time: end_time
series.points << point

metric_service_client.create_time_series name: project_path, time_series: [series]

puts "Successfully wrote time series."

Additional resources