Ler dados de métricas alinhados por média

Demonstra como ler dados de série temporal alinhados por média.

Páginas de documentação que incluem esta amostra de código

Para visualizar o exemplo de código usado em contexto, consulte a seguinte documentação:

Exemplo de código

C#

public static object ReadTimeSeriesAggregate(string projectId,
    string metricType = "compute.googleapis.com/instance/cpu/utilization")
{
    // Create client.
    MetricServiceClient metricServiceClient = MetricServiceClient.Create();
    // Initialize request argument(s).
    string filter = $"metric.type=\"{metricType}\"";
    ListTimeSeriesRequest request = new ListTimeSeriesRequest
    {
        ProjectName = new ProjectName(projectId),
        Filter = filter,
        Interval = new TimeInterval(),
    };
    // Create timestamp for current time formatted in seconds.
    long timeStamp = (long)(DateTime.UtcNow - s_unixEpoch).TotalSeconds;
    Timestamp startTimeStamp = new Timestamp();
    // Set startTime to limit results to the last 20 minutes.
    startTimeStamp.Seconds = timeStamp - (60 * 20);
    Timestamp endTimeStamp = new Timestamp();
    // Set endTime to current time.
    endTimeStamp.Seconds = timeStamp;
    TimeInterval interval = new TimeInterval();
    interval.StartTime = startTimeStamp;
    interval.EndTime = endTimeStamp;
    request.Interval = interval;
    // Aggregate results per matching instance
    Aggregation aggregation = new Aggregation();
    Duration alignmentPeriod = new Duration();
    alignmentPeriod.Seconds = 600;
    aggregation.AlignmentPeriod = alignmentPeriod;
    aggregation.PerSeriesAligner = Aggregation.Types.Aligner.AlignMean;
    // Add the aggregation to the request.
    request.Aggregation = aggregation;
    // Make the request.
    PagedEnumerable<ListTimeSeriesResponse, TimeSeries> response =
        metricServiceClient.ListTimeSeries(request);
    // Iterate over all response items, lazily performing RPCs as required.
    Console.WriteLine($"{projectId} CPU utilization:");
    foreach (var item in response)
    {
        var points = item.Points;
        var labels = item.Metric.Labels;
        Console.WriteLine($"{labels.Values.FirstOrDefault()}");
        if (points.Count > 0)
        {
            Console.WriteLine($"  Now: {points[0].Value.DoubleValue}");
        }
        if (points.Count > 1)
        {
            Console.WriteLine($"  10 min ago: {points[1].Value.DoubleValue}");
        }
    }
    return 0;
}

Go

import (
	"context"
	"fmt"
	"io"
	"time"

	monitoring "cloud.google.com/go/monitoring/apiv3"
	"github.com/golang/protobuf/ptypes/duration"
	"github.com/golang/protobuf/ptypes/timestamp"
	"google.golang.org/api/iterator"
	monitoringpb "google.golang.org/genproto/googleapis/monitoring/v3"
)

// readTimeSeriesAlign reads the last 20 minutes of the given metric and aligns
// everything on 10 minute intervals.
func readTimeSeriesAlign(w io.Writer, projectID string) error {
	ctx := context.Background()
	client, err := monitoring.NewMetricClient(ctx)
	if err != nil {
		return fmt.Errorf("NewMetricClient: %v", err)
	}
	defer client.Close()
	startTime := time.Now().UTC().Add(time.Minute * -20)
	endTime := time.Now().UTC()
	req := &monitoringpb.ListTimeSeriesRequest{
		Name:   "projects/" + projectID,
		Filter: `metric.type="compute.googleapis.com/instance/cpu/utilization"`,
		Interval: &monitoringpb.TimeInterval{
			StartTime: &timestamp.Timestamp{
				Seconds: startTime.Unix(),
			},
			EndTime: &timestamp.Timestamp{
				Seconds: endTime.Unix(),
			},
		},
		Aggregation: &monitoringpb.Aggregation{
			PerSeriesAligner: monitoringpb.Aggregation_ALIGN_MEAN,
			AlignmentPeriod: &duration.Duration{
				Seconds: 600,
			},
		},
	}
	it := client.ListTimeSeries(ctx, req)
	for {
		resp, err := it.Next()
		if err == iterator.Done {
			break
		}
		if err != nil {
			return fmt.Errorf("could not read time series value: %v", err)
		}
		fmt.Fprintln(w, resp.GetMetric().GetLabels()["instance_name"])
		fmt.Fprintf(w, "\tNow: %.4f\n", resp.GetPoints()[0].GetValue().GetDoubleValue())
		if len(resp.GetPoints()) > 1 {
			fmt.Fprintf(w, "\t10 minutes ago: %.4f\n", resp.GetPoints()[1].GetValue().GetDoubleValue())
		}
	}
	fmt.Fprintln(w, "Done")
	return nil
}

Java

MetricServiceClient metricServiceClient = MetricServiceClient.create();
String projectId = System.getProperty("projectId");
ProjectName name = ProjectName.of(projectId);

// Restrict time to last 20 minutes
long startMillis = System.currentTimeMillis() - ((60 * 20) * 1000);
TimeInterval interval =
    TimeInterval.newBuilder()
        .setStartTime(Timestamps.fromMillis(startMillis))
        .setEndTime(Timestamps.fromMillis(System.currentTimeMillis()))
        .build();

Aggregation aggregation =
    Aggregation.newBuilder()
        .setAlignmentPeriod(Duration.newBuilder().setSeconds(600).build())
        .setPerSeriesAligner(Aggregation.Aligner.ALIGN_MEAN)
        .build();

ListTimeSeriesRequest.Builder requestBuilder =
    ListTimeSeriesRequest.newBuilder()
        .setName(name.toString())
        .setFilter("metric.type=\"compute.googleapis.com/instance/cpu/utilization\"")
        .setInterval(interval)
        .setAggregation(aggregation);

ListTimeSeriesRequest request = requestBuilder.build();

ListTimeSeriesPagedResponse response = metricServiceClient.listTimeSeries(request);

System.out.println("Got timeseries: ");
for (TimeSeries ts : response.iterateAll()) {
  System.out.println(ts);
}

Node.js

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

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

async function readTimeSeriesAggregate() {
  /**
   * TODO(developer): Uncomment and edit the following lines of code.
   */
  // const projectId = 'YOUR_PROJECT_ID';

  const request = {
    name: client.projectPath(projectId),
    filter: 'metric.type="compute.googleapis.com/instance/cpu/utilization"',
    interval: {
      startTime: {
        // Limit results to the last 20 minutes
        seconds: Date.now() / 1000 - 60 * 20,
      },
      endTime: {
        seconds: Date.now() / 1000,
      },
    },
    // Aggregate results per matching instance
    aggregation: {
      alignmentPeriod: {
        seconds: 600,
      },
      perSeriesAligner: 'ALIGN_MEAN',
    },
  };

  // Writes time series data
  const [timeSeries] = await client.listTimeSeries(request);
  console.log('CPU utilization:');
  timeSeries.forEach(data => {
    console.log(data.metric.labels.instance_name);
    console.log(`  Now: ${data.points[0].value.doubleValue}`);
    if (data.points.length > 1) {
      console.log(`  10 min ago: ${data.points[1].value.doubleValue}`);
    }
    console.log('=====');
  });
}
readTimeSeriesAggregate();

PHP

use Google\Cloud\Monitoring\V3\MetricServiceClient;
use Google\Cloud\Monitoring\V3\Aggregation_Aligner;
use Google\Cloud\Monitoring\V3\Aggregation;
use Google\Cloud\Monitoring\V3\TimeInterval;
use Google\Cloud\Monitoring\V3\ListTimeSeriesRequest_TimeSeriesView;
use Google\Protobuf\Duration;
use Google\Protobuf\Timestamp;

/**
 * Example:
 * ```
 * read_timeseries_align($projectId);
 * ```
 *
 * @param string $projectId Your project ID
 */
function read_timeseries_align($projectId, $minutesAgo = 20)
{
    $metrics = new MetricServiceClient([
        'projectId' => $projectId,
    ]);

    $projectName = $metrics->projectName($projectId);
    $filter = 'metric.type="compute.googleapis.com/instance/cpu/utilization"';

    $startTime = new Timestamp();
    $startTime->setSeconds(time() - (60 * $minutesAgo));
    $endTime = new Timestamp();
    $endTime->setSeconds(time());

    $interval = new TimeInterval();
    $interval->setStartTime($startTime);
    $interval->setEndTime($endTime);

    $alignmentPeriod = new Duration();
    $alignmentPeriod->setSeconds(600);
    $aggregation = new Aggregation();
    $aggregation->setAlignmentPeriod($alignmentPeriod);
    $aggregation->setPerSeriesAligner(Aggregation_Aligner::ALIGN_MEAN);

    $view = ListTimeSeriesRequest_TimeSeriesView::FULL;

    $result = $metrics->listTimeSeries(
        $projectName,
        $filter,
        $interval,
        $view,
        ['aggregation' => $aggregation]);

    printf('CPU utilization:' . PHP_EOL);
    foreach ($result->iterateAllElements() as $timeSeries) {
        printf($timeSeries->getMetric()->getLabels()['instance_name'] . PHP_EOL);
        printf('  Now: ');
        printf($timeSeries->getPoints()[0]->getValue()->getDoubleValue() . PHP_EOL);
        if (count($timeSeries->getPoints()) > 1) {
            printf('  10 minutes ago: ');
            printf($timeSeries->getPoints()[1]->getValue()->getDoubleValue() . PHP_EOL);
        }
    }
}

Python

from google.cloud import monitoring_v3

client = monitoring_v3.MetricServiceClient()
project_name = f"projects/{project_id}"

now = time.time()
seconds = int(now)
nanos = int((now - seconds) * 10 ** 9)
interval = monitoring_v3.TimeInterval(
    {
        "end_time": {"seconds": seconds, "nanos": nanos},
        "start_time": {"seconds": (seconds - 3600), "nanos": nanos},
    }
)
aggregation = monitoring_v3.Aggregation(
    {
        "alignment_period": {"seconds": 1200},  # 20 minutes
        "per_series_aligner": monitoring_v3.Aggregation.Aligner.ALIGN_MEAN,
    }
)

results = client.list_time_series(
    request={
        "name": project_name,
        "filter": 'metric.type = "compute.googleapis.com/instance/cpu/utilization"',
        "interval": interval,
        "view": monitoring_v3.ListTimeSeriesRequest.TimeSeriesView.FULL,
        "aggregation": aggregation,
    }
)
for result in results:
    print(result)

Ruby

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

client = Google::Cloud::Monitoring.metric_service
project_name = client.project_path project: project_id

interval = Google::Cloud::Monitoring::V3::TimeInterval.new
now = Time.now
interval.end_time = Google::Protobuf::Timestamp.new seconds: now.to_i,
                                                    nanos:   now.nsec
interval.start_time = Google::Protobuf::Timestamp.new seconds: now.to_i - 1200,
                                                      nanos:   now.nsec
filter = 'metric.type = "compute.googleapis.com/instance/cpu/utilization"'
view = Google::Cloud::Monitoring::V3::ListTimeSeriesRequest::TimeSeriesView::FULL
aggregation = Google::Cloud::Monitoring::V3::Aggregation.new(
  alignment_period:   { seconds: 1200 },
  per_series_aligner: Google::Cloud::Monitoring::V3::Aggregation::Aligner::ALIGN_MEAN
)

results = client.list_time_series name:        project_name,
                                  filter:      filter,
                                  interval:    interval,
                                  view:        view,
                                  aggregation: aggregation
results.each do |result|
  p result
end

A seguir

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