AI 커스텀 규칙 세트 목록 표시
경고Note: This endpoint is in preview and is subject to change.
If you have any feedback, contact Datadog support.
GET
https://api.datadoghq.com/api/v2/static-analysis/ai/rulesetshttps://api.us3.datadoghq.com/api/v2/static-analysis/ai/rulesetshttps://api.us5.datadoghq.com/api/v2/static-analysis/ai/rulesetshttps://api.datadoghq.eu/api/v2/static-analysis/ai/rulesetshttps://api.ap1.datadoghq.com/api/v2/static-analysis/ai/rulesetshttps://api.ap2.datadoghq.com/api/v2/static-analysis/ai/rulesetshttps://api.uk1.datadoghq.com/api/v2/static-analysis/ai/rulesetshttps://api.ddog-gov.com/api/v2/static-analysis/ai/rulesetshttps://api.us2.ddog-gov.com/api/v2/static-analysis/ai/rulesets개요
인증된 조직의 모든 AI 커스텀 규칙 세트를 가져옵니다.
인수
쿼리 문자열
이름
유형
설명
page[offset]integer
The offset for pagination.
0page[limit]integer
The maximum number of rulesets to return.
100응답
Successful response
Response containing a list of AI custom rulesets.
항목
유형
설명
data [required][object]
The list of AI custom rulesets.
attributes [required]object
Response attributes of an AI custom ruleset.
created_at [required]date-time
The creation timestamp.
created_by [required]string
The identifier of the user who created the ruleset.
description [required]string
Base64-encoded full description of the ruleset.
name [required]string
The ruleset name.
rules [required][object]
The rules contained in the ruleset.
created_at [required]date-time
The creation timestamp.
created_by [required]string
The identifier of the user who created the rule.
last_revision [required]object
The most recent revision of the rule.
category [required]enum
Rule category
Allowed enum values:
SECURITY, BEST_PRACTICES, CODE_STYLE, ERROR_PRONE, PERFORMANCEchecksum [required]string
Checksum of the revision content.
content [required]string
Base64-encoded AI model content for this revision.
created_at [required]date-time
The creation timestamp.
created_by [required]string
The identifier of the user who created the revision.
cwe [required]string
The associated CWE identifier.
description [required]string
Base64-encoded full description.
directories [required][string]
Directory patterns this rule applies to.
execution_mode [required]enum
The execution mode for an AI rule revision.
Allowed enum values:
auto, manual, alwaysglobs [required][string]
File glob patterns this rule applies to.
is_default [required]boolean
Whether this is a default Datadog rule.
is_published [required]boolean
Whether this revision is published.
is_testing [required]boolean
Whether this revision is for testing only.
severity [required]enum
Rule severity
Allowed enum values:
ERROR, WARNING, NOTICE, NONEshort_description [required]string
Base64-encoded short description.
version_id [required]int64
The version identifier for this revision.
name [required]string
The rule name.
short_description [required]string
Base64-encoded short description of the ruleset.
id [required]string
The ruleset identifier.
type [required]enum
AI custom ruleset resource type.
Allowed enum values:
ai_ruleset{
"data": [
{
"attributes": {
"created_at": "2024-01-01T00:00:00+00:00",
"created_by": "example-handle",
"description": "Ruleset description",
"name": "my-ai-ruleset",
"rules": [
{
"created_at": "2024-01-01T00:00:00+00:00",
"created_by": "example-handle",
"last_revision": {
"category": "SECURITY",
"checksum": "abc123def456",
"content": "Content",
"created_at": "2024-01-01T00:00:00+00:00",
"created_by": "example-handle",
"cwe": "79",
"description": "Ruleset description",
"directories": [
[]
],
"execution_mode": "auto",
"globs": [
"**/*.py"
],
"is_default": false,
"is_published": false,
"is_testing": false,
"severity": "ERROR",
"short_description": "Ruleset short description",
"version_id": 1
},
"name": "my-ai-rule"
}
],
"short_description": "Ruleset short description"
},
"id": "my-ai-ruleset",
"type": "ai_ruleset"
}
]
}Unauthorized
API error response.
항목
유형
설명
errors [required][object]
A list of errors.
detailstring
A human-readable explanation specific to this occurrence of the error.
metaobject
Non-standard meta-information about the error
sourceobject
References to the source of the error.
headerstring
A string indicating the name of a single request header which caused the error.
parameterstring
A string indicating which URI query parameter caused the error.
pointerstring
A JSON pointer to the value in the request document that caused the error.
statusstring
Status code of the response.
titlestring
Short 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.
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.
detailstring
A human-readable explanation specific to this occurrence of the error.
metaobject
Non-standard meta-information about the error
sourceobject
References to the source of the error.
headerstring
A string indicating the name of a single request header which caused the error.
parameterstring
A string indicating which URI query parameter caused the error.
pointerstring
A JSON pointer to the value in the request document that caused the error.
statusstring
Status code of the response.
titlestring
Short 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"
}
]
}코드 예시
AI 커스텀 규칙 세트 목록 표시
# 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/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"AI 커스텀 규칙 세트 목록 표시
// List AI custom rulesets returns "Successful response" 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.ListAiCustomRulesets", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewStaticAnalysisApi(apiClient)
resp, r, err := api.ListAiCustomRulesets(ctx, *datadogV2.NewListAiCustomRulesetsOptionalParameters())
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `StaticAnalysisApi.ListAiCustomRulesets`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `StaticAnalysisApi.ListAiCustomRulesets`:\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"AI 커스텀 규칙 세트 목록 표시
// List AI custom rulesets returns "Successful response" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.StaticAnalysisApi;
import com.datadog.api.client.v2.model.AiCustomRulesetsResponse;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
defaultClient.setUnstableOperationEnabled("v2.listAiCustomRulesets", true);
StaticAnalysisApi apiInstance = new StaticAnalysisApi(defaultClient);
try {
AiCustomRulesetsResponse result = apiInstance.listAiCustomRulesets();
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling StaticAnalysisApi#listAiCustomRulesets");
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"AI 커스텀 규칙 세트 목록 표시
"""
List AI custom rulesets returns "Successful response" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.static_analysis_api import StaticAnalysisApi
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["list_ai_custom_rulesets"] = True
with ApiClient(configuration) as api_client:
api_instance = StaticAnalysisApi(api_client)
response = api_instance.list_ai_custom_rulesets()
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"AI 커스텀 규칙 세트 목록 표시
# List AI custom rulesets returns "Successful response" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.list_ai_custom_rulesets".to_sym] = true
end
api_instance = DatadogAPIClient::V2::StaticAnalysisAPI.new
p api_instance.list_ai_custom_rulesets()
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"AI 커스텀 규칙 세트 목록 표시
// List AI custom rulesets returns "Successful response" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_static_analysis::ListAiCustomRulesetsOptionalParams;
use datadog_api_client::datadogV2::api_static_analysis::StaticAnalysisAPI;
#[tokio::main]
async fn main() {
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.list_ai_custom_rulesets", true);
let api = StaticAnalysisAPI::with_config(configuration);
let resp = api
.list_ai_custom_rulesets(ListAiCustomRulesetsOptionalParams::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="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="us3.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="us5.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="datadoghq.eu" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="ap1.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="ap2.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="uk1.datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="ddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runDD_SITE="us2.ddog-gov.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo runAI 커스텀 규칙 세트 목록 표시
/**
* List AI custom rulesets returns "Successful response" 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.listAiCustomRulesets"] = true;
const apiInstance = new v2.StaticAnalysisApi(configuration);
apiInstance
.listAiCustomRulesets()
.then((data: v2.AiCustomRulesetsResponse) => {
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"