Model Lab 실행 패싯 값 목록 표시 - Model Lab API

경고Note: This endpoint is in preview and is subject to change. If you have any feedback, contact Datadog support.

GEThttps://api.datadoghq.com/api/v2/model-lab-api/facet-valueshttps://api.us3.datadoghq.com/api/v2/model-lab-api/facet-valueshttps://api.us5.datadoghq.com/api/v2/model-lab-api/facet-valueshttps://api.datadoghq.eu/api/v2/model-lab-api/facet-valueshttps://api.ap1.datadoghq.com/api/v2/model-lab-api/facet-valueshttps://api.ap2.datadoghq.com/api/v2/model-lab-api/facet-valueshttps://api.uk1.datadoghq.com/api/v2/model-lab-api/facet-valueshttps://api.ddog-gov.com/api/v2/model-lab-api/facet-valueshttps://api.us2.ddog-gov.com/api/v2/model-lab-api/facet-values

개요

특정 실행 패싯 키에 사용 가능한 패싯 값을 나열합니다.

인수

쿼리 문자열

이름

유형

설명

filter[project_id] [required]

integer

Filter by project ID.

facet_type [required]

enum

Facet type. Valid values: parameter, attribute, tag, metric.

Allowed enum values: parameter, attribute, tag, metric

facet_name [required]

string

Facet name.

응답

Response containing available values for a facet key.

항목

유형

설명

data [required]

object

A facet values JSON:API resource object.

{
  "data": {
    "attributes": {
      "facet_name": "model",
      "facet_type": "tag",
      "metric_stat_ranges": [
        {
          "max": 1,
          "min": 0,
          "stat": "mean"
        }
      ],
      "numeric_range": {
        "max": 1,
        "min": 0
      },
      "values": [
        "gpt4"
      ]
    },
    "id": "1",
    "type": "facet_values"
  }
}

Bad Request

API error response.

항목

유형

설명

errors [required]

[object]

A list of errors.

{
  "errors": [
    {
      "detail": "Missing required attribute in body",
      "meta": {},
      "source": {
        "header": "Authorization",
        "parameter": "limit",
        "pointer": "/data/attributes/title"
      },
      "status": "400",
      "title": "Bad Request"
    }
  ]
}

Not Found

API error response.

항목

유형

설명

errors [required]

[object]

A list of errors.

{
  "errors": [
    {
      "detail": "Missing required attribute in body",
      "meta": {},
      "source": {
        "header": "Authorization",
        "parameter": "limit",
        "pointer": "/data/attributes/title"
      },
      "status": "400",
      "title": "Bad Request"
    }
  ]
}

Too many requests

API error response.

항목

유형

설명

errors [required]

[string]

A list of errors.

{
  "errors": [
    "Bad Request"
  ]
}

Internal Server Error

API error response.

항목

유형

설명

errors [required]

[object]

A list of errors.

{
  "errors": [
    {
      "detail": "Missing required attribute in body",
      "meta": {},
      "source": {
        "header": "Authorization",
        "parameter": "limit",
        "pointer": "/data/attributes/title"
      },
      "status": "400",
      "title": "Bad Request"
    }
  ]
}

코드 예시

Model Lab 실행 패싯 값 목록 표시

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

# Required query arguments
export filter_project_id="101"
export facet_type="tag"
export facet_name="algorithm"

# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X GET "https://api.${DD_SITE}/api/v2/model-lab-api/facet-values?filter%5Bproject_id%5D=${filter_project_id}&facet_type=${facet_type}&facet_name=${facet_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"

Model Lab 실행 패싯 값 목록 표시

// List Model Lab run facet values 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() {
	ctx := datadog.NewDefaultContext(context.Background())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	configuration := datadog.NewConfiguration()
	configuration.SetUnstableOperationEnabled("v2.ListModelLabRunFacetValues", true)
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewModelLabAPIApi(apiClient)
	resp, r, err := api.ListModelLabRunFacetValues(ctx, 2387, datadogV2.MODELLABFACETTYPE_TAG, "model")

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

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

Instructions

First install the library and its dependencies and then save the example to main.go and run following commands:

DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"

Model Lab 실행 패싯 값 목록 표시

// List Model Lab run facet values returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ModelLabApiApi;
import com.datadog.api.client.v2.model.ModelLabFacetType;
import com.datadog.api.client.v2.model.ModelLabFacetValuesResponse;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
    defaultClient.setUnstableOperationEnabled("v2.listModelLabRunFacetValues", true);
    ModelLabApiApi apiInstance = new ModelLabApiApi(defaultClient);

    try {
      ModelLabFacetValuesResponse result =
          apiInstance.listModelLabRunFacetValues(2387L, ModelLabFacetType.TAG, "model");
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling ModelLabApiApi#listModelLabRunFacetValues");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

Instructions

First install the library and its dependencies and then save the example to Example.java and run following commands:

DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"

Model Lab 실행 패싯 값 목록 표시

"""
List Model Lab run facet values returns "OK" response
"""

from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.model_lab_api_api import ModelLabAPIApi
from datadog_api_client.v2.model.model_lab_facet_type import ModelLabFacetType

configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["list_model_lab_run_facet_values"] = True
with ApiClient(configuration) as api_client:
    api_instance = ModelLabAPIApi(api_client)
    response = api_instance.list_model_lab_run_facet_values(
        filter_project_id=2387,
        facet_type=ModelLabFacetType.TAG,
        facet_name="model",
    )

    print(response)

Instructions

First install the library and its dependencies and then save the example to example.py and run following commands:

DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"

Model Lab 실행 패싯 값 목록 표시

# List Model Lab run facet values returns "OK" response

require "datadog_api_client"
DatadogAPIClient.configure do |config|
  config.access_token = ENV["DD_BEARER_TOKEN"]
  config.unstable_operations["v2.list_model_lab_run_facet_values".to_sym] = true
end
api_instance = DatadogAPIClient::V2::ModelLabAPIAPI.new
p api_instance.list_model_lab_run_facet_values(2387, ModelLabFacetType::TAG, "model")

Instructions

First install the library and its dependencies and then save the example to example.rb and run following commands:

DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"

Model Lab 실행 패싯 값 목록 표시

// List Model Lab run facet values returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_model_lab_api::ModelLabAPIAPI;
use datadog_api_client::datadogV2::model::ModelLabFacetType;

#[tokio::main]
async fn main() {
    let mut configuration = datadog::Configuration::new();
    configuration.set_unstable_operation_enabled("v2.list_model_lab_run_facet_values", true);
    let api = ModelLabAPIAPI::with_config(configuration);
    let resp = api
        .list_model_lab_run_facet_values(2387, ModelLabFacetType::TAG, "model".to_string())
        .await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

Instructions

First install the library and its dependencies and then save the example to src/main.rs and run following commands:

DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="us3.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="us5.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="datadoghq.eu" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="ap1.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="ap2.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="uk1.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="ddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

DD_SITE="us2.ddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run

Model Lab 실행 패싯 값 목록 표시

/**
 * List Model Lab run facet values 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,
    },
  },
});
configuration.unstableOperations["v2.listModelLabRunFacetValues"] = true;
const apiInstance = new v2.ModelLabAPIApi(configuration);

const params: v2.ModelLabAPIApiListModelLabRunFacetValuesRequest = {
  filterProjectId: 2387,
  facetType: "tag",
  facetName: "model",
};

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

Instructions

First install the library and its dependencies and then save the example to example.ts and run following commands:

DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"

DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"