Crear una métrica basada en tramos

// Create a span-based metric returns "OK" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.SpansMetricCreateRequest{
		Data: datadogV2.SpansMetricCreateData{
			Attributes: datadogV2.SpansMetricCreateAttributes{
				Compute: datadogV2.SpansMetricCompute{
					AggregationType:    datadogV2.SPANSMETRICCOMPUTEAGGREGATIONTYPE_DISTRIBUTION,
					IncludePercentiles: datadog.PtrBool(false),
					Path:               datadog.PtrString("@duration"),
				},
				Filter: &datadogV2.SpansMetricFilter{
					Query: datadog.PtrString("@http.status_code:200 service:my-service"),
				},
				GroupBy: []datadogV2.SpansMetricGroupBy{
					{
						Path:    "resource_name",
						TagName: datadog.PtrString("resource_name"),
					},
				},
			},
			Id:   "ExampleSpansMetric",
			Type: datadogV2.SPANSMETRICTYPE_SPANS_METRICS,
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewSpansMetricsApi(apiClient)
	resp, r, err := api.CreateSpansMetric(ctx, body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `SpansMetricsApi.CreateSpansMetric`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `SpansMetricsApi.CreateSpansMetric`:\n%s\n", responseContent)
}

// Create a span-based metric returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.SpansMetricsApi;
import com.datadog.api.client.v2.model.SpansMetricCompute;
import com.datadog.api.client.v2.model.SpansMetricComputeAggregationType;
import com.datadog.api.client.v2.model.SpansMetricCreateAttributes;
import com.datadog.api.client.v2.model.SpansMetricCreateData;
import com.datadog.api.client.v2.model.SpansMetricCreateRequest;
import com.datadog.api.client.v2.model.SpansMetricFilter;
import com.datadog.api.client.v2.model.SpansMetricGroupBy;
import com.datadog.api.client.v2.model.SpansMetricResponse;
import com.datadog.api.client.v2.model.SpansMetricType;
import java.util.Collections;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
    SpansMetricsApi apiInstance = new SpansMetricsApi(defaultClient);

    SpansMetricCreateRequest body =
        new SpansMetricCreateRequest()
            .data(
                new SpansMetricCreateData()
                    .attributes(
                        new SpansMetricCreateAttributes()
                            .compute(
                                new SpansMetricCompute()
                                    .aggregationType(SpansMetricComputeAggregationType.DISTRIBUTION)
                                    .includePercentiles(false)
                                    .path("@duration"))
                            .filter(
                                new SpansMetricFilter()
                                    .query("@http.status_code:200 service:my-service"))
                            .groupBy(
                                Collections.singletonList(
                                    new SpansMetricGroupBy()
                                        .path("resource_name")
                                        .tagName("resource_name"))))
                    .id("ExampleSpansMetric")
                    .type(SpansMetricType.SPANS_METRICS));

    try {
      SpansMetricResponse result = apiInstance.createSpansMetric(body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling SpansMetricsApi#createSpansMetric");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

"""
Create a span-based metric returns "OK" response
"""

from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.spans_metrics_api import SpansMetricsApi
from datadog_api_client.v2.model.spans_metric_compute import SpansMetricCompute
from datadog_api_client.v2.model.spans_metric_compute_aggregation_type import SpansMetricComputeAggregationType
from datadog_api_client.v2.model.spans_metric_create_attributes import SpansMetricCreateAttributes
from datadog_api_client.v2.model.spans_metric_create_data import SpansMetricCreateData
from datadog_api_client.v2.model.spans_metric_create_request import SpansMetricCreateRequest
from datadog_api_client.v2.model.spans_metric_filter import SpansMetricFilter
from datadog_api_client.v2.model.spans_metric_group_by import SpansMetricGroupBy
from datadog_api_client.v2.model.spans_metric_type import SpansMetricType

body = SpansMetricCreateRequest(
    data=SpansMetricCreateData(
        attributes=SpansMetricCreateAttributes(
            compute=SpansMetricCompute(
                aggregation_type=SpansMetricComputeAggregationType.DISTRIBUTION,
                include_percentiles=False,
                path="@duration",
            ),
            filter=SpansMetricFilter(
                query="@http.status_code:200 service:my-service",
            ),
            group_by=[
                SpansMetricGroupBy(
                    path="resource_name",
                    tag_name="resource_name",
                ),
            ],
        ),
        id="ExampleSpansMetric",
        type=SpansMetricType.SPANS_METRICS,
    ),
)

configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
with ApiClient(configuration) as api_client:
    api_instance = SpansMetricsApi(api_client)
    response = api_instance.create_spans_metric(body=body)

    print(response)

# Create a span-based metric returns "OK" response

require "datadog_api_client"
DatadogAPIClient.configure do |config|
  config.access_token = ENV["DD_BEARER_TOKEN"]
end
api_instance = DatadogAPIClient::V2::SpansMetricsAPI.new

body = DatadogAPIClient::V2::SpansMetricCreateRequest.new({
  data: DatadogAPIClient::V2::SpansMetricCreateData.new({
    attributes: DatadogAPIClient::V2::SpansMetricCreateAttributes.new({
      compute: DatadogAPIClient::V2::SpansMetricCompute.new({
        aggregation_type: DatadogAPIClient::V2::SpansMetricComputeAggregationType::DISTRIBUTION,
        include_percentiles: false,
        path: "@duration",
      }),
      filter: DatadogAPIClient::V2::SpansMetricFilter.new({
        query: "@http.status_code:200 service:my-service",
      }),
      group_by: [
        DatadogAPIClient::V2::SpansMetricGroupBy.new({
          path: "resource_name",
          tag_name: "resource_name",
        }),
      ],
    }),
    id: "ExampleSpansMetric",
    type: DatadogAPIClient::V2::SpansMetricType::SPANS_METRICS,
  }),
})
p api_instance.create_spans_metric(body)

// Create a span-based metric returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_spans_metrics::SpansMetricsAPI;
use datadog_api_client::datadogV2::model::SpansMetricCompute;
use datadog_api_client::datadogV2::model::SpansMetricComputeAggregationType;
use datadog_api_client::datadogV2::model::SpansMetricCreateAttributes;
use datadog_api_client::datadogV2::model::SpansMetricCreateData;
use datadog_api_client::datadogV2::model::SpansMetricCreateRequest;
use datadog_api_client::datadogV2::model::SpansMetricFilter;
use datadog_api_client::datadogV2::model::SpansMetricGroupBy;
use datadog_api_client::datadogV2::model::SpansMetricType;

#[tokio::main]
async fn main() {
    let body = SpansMetricCreateRequest::new(SpansMetricCreateData::new(
        SpansMetricCreateAttributes::new(
            SpansMetricCompute::new(SpansMetricComputeAggregationType::DISTRIBUTION)
                .include_percentiles(false)
                .path("@duration".to_string()),
        )
        .filter(
            SpansMetricFilter::new().query("@http.status_code:200 service:my-service".to_string()),
        )
        .group_by(vec![SpansMetricGroupBy::new("resource_name".to_string())
            .tag_name("resource_name".to_string())]),
        "ExampleSpansMetric".to_string(),
        SpansMetricType::SPANS_METRICS,
    ));
    let configuration = datadog::Configuration::new();
    let api = SpansMetricsAPI::with_config(configuration);
    let resp = api.create_spans_metric(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

/**
 * Create a span-based metric returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration({
  authMethods: {
    AuthZ: {
      accessToken: process.env.DD_BEARER_TOKEN as string,
    },
  },
});
const apiInstance = new v2.SpansMetricsApi(configuration);

const params: v2.SpansMetricsApiCreateSpansMetricRequest = {
  body: {
    data: {
      attributes: {
        compute: {
          aggregationType: "distribution",
          includePercentiles: false,
          path: "@duration",
        },
        filter: {
          query: "@http.status_code:200 service:my-service",
        },
        groupBy: [
          {
            path: "resource_name",
            tagName: "resource_name",
          },
        ],
      },
      id: "ExampleSpansMetric",
      type: "spans_metrics",
    },
  },
};

apiInstance
  .createSpansMetric(params)
  .then((data: v2.SpansMetricResponse) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));