Monitoring Client Libraries

This page shows how to get started with the Cloud Client Libraries for the Stackdriver 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 Stackdriver agents. 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


go get -u


For more information, see Setting Up a Java Development Environment. 如果您是使用 Maven,請在 pom.xml 檔案中新增以下指令:
如果您是使用 Gradle,請在相依元件中新增以下指令:
compile ''
如果您是使用 SBT,請在相依元件中新增以下指令:
libraryDependencies += "" % "google-cloud-monitoring" % "1.75.0"

如果您使用 IntelliJ 或 Eclipse,可以使用以下 IDE 外掛程式將用戶端程式庫加入專案中:



For more information, see Setting Up a Node.js Development Environment.
npm install --save @google-cloud/monitoring


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.

GCP 主控台

  1. 在 GCP 主控台中,前往「Create service account key」(建立服務帳戶金鑰) 頁面。

    前往「Create Service Account Key」(建立服務帳戶金鑰) 頁面
  2. 從 [Service account] (服務帳戶) 清單中選取 [New service account] (新增服務帳戶)
  3. 在 [Service account name] (服務帳戶名稱) 欄位中輸入一個名稱。
  4. 從 [Role] (角色) 清單中,選取 [Project] (專案) > [Owner] (擁有者)

    附註:「Role」(角色) 欄位會授權服務帳戶存取資源。以後您可以使用 GCP 主控台查看及變更這個欄位。如果您要開發正式版應用程式,請指定比 [Project] (專案) > [Owner] (擁有者) 更精細的權限。詳情請參閱為服務帳戶授予角色一文。
  5. 點選 [建立]。一個包含您金鑰的 JSON 檔案會下載到電腦中。


您可以使用本機電腦上的 Cloud SDK,或在 Cloud Shell 內執行下列指令。

  1. 建立服務帳戶。將 [NAME] 換成服務帳戶的名稱。

    gcloud iam service-accounts create [NAME]
  2. 向服務帳戶授予權限。用您的專案 ID 取代 [PROJECT_ID]

    gcloud projects add-iam-policy-binding [PROJECT_ID] --member "serviceAccount:[NAME]@[PROJECT_ID]" --role "roles/owner"
    附註:「Role」(角色) 欄位會授權服務帳戶存取資源。您稍後可以使用 GCP 主控台查看及變更這個欄位。如果您要開發正式版應用程式,請指定比 [Project] (專案) > [Owner] (擁有者) 更精細的權限。詳情請參閱為服務帳戶授予角色一文。
  3. 產生金鑰檔案。用金鑰檔案的名稱取代 [FILE_NAME]

    gcloud iam service-accounts keys create [FILE_NAME].json --iam-account [NAME]@[PROJECT_ID]

設定環境變數 GOOGLE_APPLICATION_CREDENTIALS 來為應用程式程式碼提供驗證憑證。 將 [PATH] 改成包含您的服務帳戶金鑰的 JSON 檔案路徑,並將 [FILE_NAME] 改成檔案名稱。 此變數僅適用於您目前的殼層工作階段,所以如果您開啟新的工作階段,請再次設定變數。

Linux 或 macOS



export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/[FILE_NAME].json"


使用 PowerShell:






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;

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

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

            // Prepare monitored resource.
            MonitoredResource resource = new MonitoredResource();
            resource.Type = "global";
            resource.Labels.Add("project_id", projectId);

            // Create a new time series using inputs.
            TimeSeries timeSeriesData = new TimeSeries();
            timeSeriesData.Metric = metric;
            timeSeriesData.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 = TimeInterval.newBuilder()
    TypedValue value = TypedValue.newBuilder()
    Point point = Point.newBuilder()

    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 = Metric.newBuilder()

    // Prepares the monitored resource descriptor
    Map<String, String> resourceLabels = new HashMap<String, String>();
    resourceLabels.put("project_id", projectId);
    MonitoredResource resource = MonitoredResource.newBuilder()

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

    CreateTimeSeriesRequest request = CreateTimeSeriesRequest.newBuilder()

    // 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 = client.project_path(project)

series = monitoring_v3.types.TimeSeries()
series.metric.type = ''
series.resource.type = 'gce_instance'
series.resource.labels['instance_id'] = '1234567890123456789'
series.resource.labels['zone'] = 'us-central1-f'
point = series.points.add()
point.value.double_value = 3.14
now = time.time()
point.interval.end_time.seconds = int(now)
point.interval.end_time.nanos = int(
    (now - point.interval.end_time.seconds) * 10**9)
client.create_time_series(project_name, [series])
print('Successfully wrote time series.')


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

# Instantiates a client
metric_service_client =
project_path = Google::Cloud::Monitoring::V3::MetricServiceClient.project_path project_id

series =
series.metric = type: ""

resource = type: "gce_instance"
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.usec
point.interval = end_time: end_time
series.points << point

metric_service_client.create_time_series project_path, [series]

puts "Successfully wrote time series."

Additional resources



Stackdriver Monitoring