SAST 규칙 세트 가져오기
https://api.datadoghq.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.us3.datadoghq.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.us5.datadoghq.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.datadoghq.eu/api/v2/static-analysis/rulesets/{ruleset_name}https://api.ap1.datadoghq.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.ap2.datadoghq.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.uk1.datadoghq.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.ddog-gov.com/api/v2/static-analysis/rulesets/{ruleset_name}https://api.us2.ddog-gov.com/api/v2/static-analysis/rulesets/{ruleset_name}개요
이름을 사용하여 SAST 규칙 세트를 가져오며 모든 규칙을 포함합니다.
OAuth apps require the code_analysis_read authorization scope to access this endpoint.
인수
경로 파라미터
ruleset_name [required]The name of the ruleset to retrieve.
쿼리 문자열
include_testsWhen true, test cases for each rule are included in the response.
include_testing_rulesWhen true, rules that are in testing mode are included in the response.
응답
OK
The response payload containing a single SAST ruleset and its rules.
data [required]The primary data object representing a SAST ruleset.
attributes [required]The attributes of a SAST ruleset, including its name, description, and rules.
description [required]A detailed description of the ruleset's purpose and the types of issues it targets.
name [required]The unique name of the ruleset.
rules [required]The list of static analysis rules included in this ruleset.
arguments [required]The list of configurable arguments accepted by this rule.
descriptionA human-readable explanation of the argument's purpose and accepted values.
nameThe name of the rule argument.
category [required]The category classifying the type of issue this rule detects (e.g., security, style, performance).
checksum [required]A checksum of the rule definition used to detect changes.
code [required]The rule implementation code used by the static analysis engine.
created_at [required]The date and time when the rule was created.
created_by [required]The identifier of the user or system that created the rule.
cveThe CVE identifier associated with the vulnerability this rule detects, if applicable.
cweThe CWE identifier associated with the weakness category this rule detects, if applicable.
description [required]A detailed explanation of what the rule detects and why it matters.
documentation_urlA URL pointing to additional documentation for this rule.
entity_checkedThe code entity type (e.g., function, class, variable) that this rule inspects.
id [required]The unique identifier of the rule, which is the same as its name.
is_published [required]Indicates whether the rule is publicly published and available to all users.
is_testing [required]Indicates whether the rule is in testing mode and not yet promoted to production.
language [required]The programming language this rule applies to.
last_updated_at [required]The date and time when the rule was last modified.
last_updated_by [required]The identifier of the user or system that last updated the rule.
name [required]The unique name identifying this rule within its ruleset.
regexA regular expression pattern used by the rule for pattern-based detection.
severity [required]The severity level of findings produced by this rule (e.g., ERROR, WARNING, NOTICE).
short_description [required]A brief summary of what the rule detects, suitable for display in listings.
should_use_ai_fix [required]Indicates whether an AI-generated fix suggestion should be offered for findings from this rule.
tests [required]The list of test cases used to validate the rule's behavior.
annotation_countThe expected number of annotations (findings) the rule should produce when run against the test code.
codeThe source code snippet used as input for the rule test.
filenameThe filename associated with the test code snippet.
tree_sitter_queryThe Tree-sitter query expression used by the rule to match code patterns in the AST.
type [required]The rule type indicating the detection mechanism used (e.g., tree_sitter, regex).
short_description [required]A brief summary of the ruleset, suitable for display in listings.
id [required]The unique identifier of the ruleset resource.
type [required]Rulesets resource type.
rulesetsrulesets{
"data": {
"attributes": {
"description": "A collection of Python best practice rules.",
"name": "python-best-practices",
"rules": [
{
"arguments": [
{
"description": "string",
"name": "string"
}
],
"category": "",
"checksum": "",
"code": "",
"created_at": "",
"created_by": "",
"cve": "string",
"cwe": "string",
"description": "",
"documentation_url": "string",
"entity_checked": "string",
"id": "",
"is_published": false,
"is_testing": false,
"language": "",
"last_updated_at": "",
"last_updated_by": "",
"name": "",
"regex": "string",
"severity": "",
"short_description": "",
"should_use_ai_fix": false,
"tests": [
{
"annotation_count": "integer",
"code": "string",
"filename": "string"
}
],
"tree_sitter_query": "string",
"type": ""
}
],
"short_description": "Python best practices ruleset."
},
"id": "python-best-practices",
"type": "rulesets"
}
}Bad Request
API error response.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"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.
errors [required]A list of errors.
detailA human-readable explanation specific to this occurrence of the error.
metaNon-standard meta-information about the error
sourceReferences to the source of the error.
headerA string indicating the name of a single request header which caused the error.
parameterA string indicating which URI query parameter caused the error.
pointerA JSON pointer to the value in the request document that caused the error.
statusStatus code of the response.
titleShort human-readable summary of the error.
{
"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.
errors [required]A list of errors.
{
"errors": [
"Bad Request"
]
}코드 예시
# Path parameters
export ruleset_name="python-best-practices"
# 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.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export ruleset_name="python-best-practices"
# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/rulesets/${ruleset_name}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"// Get a SAST ruleset 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.GetStaticAnalysisRuleset", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewSecurityMonitoringApi(apiClient)
resp, r, err := api.GetStaticAnalysisRuleset(ctx, "python-best-practices", *datadogV2.NewGetStaticAnalysisRulesetOptionalParameters())
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `SecurityMonitoringApi.GetStaticAnalysisRuleset`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `SecurityMonitoringApi.GetStaticAnalysisRuleset`:\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"// Get a SAST ruleset returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.SecurityMonitoringApi;
import com.datadog.api.client.v2.model.SastRulesetResponse;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
defaultClient.setUnstableOperationEnabled("v2.getStaticAnalysisRuleset", true);
SecurityMonitoringApi apiInstance = new SecurityMonitoringApi(defaultClient);
try {
SastRulesetResponse result = apiInstance.getStaticAnalysisRuleset("python-best-practices");
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling SecurityMonitoringApi#getStaticAnalysisRuleset");
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""""
Get a SAST ruleset returns "OK" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.security_monitoring_api import SecurityMonitoringApi
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["get_static_analysis_ruleset"] = True
with ApiClient(configuration) as api_client:
api_instance = SecurityMonitoringApi(api_client)
response = api_instance.get_static_analysis_ruleset(
ruleset_name="python-best-practices",
)
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"# Get a SAST ruleset returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.get_static_analysis_ruleset".to_sym] = true
end
api_instance = DatadogAPIClient::V2::SecurityMonitoringAPI.new
p api_instance.get_static_analysis_ruleset("python-best-practices")
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"// Get a SAST ruleset returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_security_monitoring::GetStaticAnalysisRulesetOptionalParams;
use datadog_api_client::datadogV2::api_security_monitoring::SecurityMonitoringAPI;
#[tokio::main]
async fn main() {
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.get_static_analysis_ruleset", true);
let api = SecurityMonitoringAPI::with_config(configuration);
let resp = api
.get_static_analysis_ruleset(
"python-best-practices".to_string(),
GetStaticAnalysisRulesetOptionalParams::default(),
)
.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="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us3.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us5.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="datadoghq.eu" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ap1.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ap2.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="uk1.datadoghq.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="ddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo runDD_SITE="us2.ddog-gov.com" DD_API_KEY="<DD_API_KEY>" DD_APP_KEY="<DD_APP_KEY>" cargo run/**
* Get a SAST ruleset 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.getStaticAnalysisRuleset"] = true;
const apiInstance = new v2.SecurityMonitoringApi(configuration);
const params: v2.SecurityMonitoringApiGetStaticAnalysisRulesetRequest = {
rulesetName: "python-best-practices",
};
apiInstance
.getStaticAnalysisRuleset(params)
.then((data: v2.SastRulesetResponse) => {
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"