--- title: 참조 표 업데이트 description: "ID를 사용하여 Reference Table을 업데이트합니다. 테이블의 데이터, 설명 및 태그를 업데이트할 수 있습니다. 참고: 테이블 생성 후에는 소스 유형을 변경할 수 없습니다. 데이터 업데이트의 경우: source:LOCAL_FILE 유형의 기존 테이블은 먼저 POST…" breadcrumbs: 문서 > API > 참조 표 업데이트 --- > For the complete documentation index, see [llms.txt](https://dnd37xeb23o8n.cloudfront.net/stefon.simmons/docs-astro-web-10435/llms.txt). # 참조 표 업데이트 ## v2 (latest) | Datadog site | API endpoint | | ----------------- | ----------------------------------------------------------------------- | | app.datadoghq.com | PATCH https://api.datadoghq.com/api/v2/reference-tables/tables/{id} | | us3.datadoghq.com | PATCH https://api.us3.datadoghq.com/api/v2/reference-tables/tables/{id} | | us5.datadoghq.com | PATCH https://api.us5.datadoghq.com/api/v2/reference-tables/tables/{id} | | app.datadoghq.eu | PATCH https://api.datadoghq.eu/api/v2/reference-tables/tables/{id} | | ap1.datadoghq.com | PATCH https://api.ap1.datadoghq.com/api/v2/reference-tables/tables/{id} | | ap2.datadoghq.com | PATCH https://api.ap2.datadoghq.com/api/v2/reference-tables/tables/{id} | | uk1.datadoghq.com | PATCH https://api.uk1.datadoghq.com/api/v2/reference-tables/tables/{id} | | app.ddog-gov.com | PATCH https://api.ddog-gov.com/api/v2/reference-tables/tables/{id} | | us2.ddog-gov.com | PATCH https://api.us2.ddog-gov.com/api/v2/reference-tables/tables/{id} | ### Overview ID를 사용하여 Reference Table을 업데이트합니다. 테이블의 데이터, 설명 및 태그를 업데이트할 수 있습니다. 참고: 테이블 생성 후에는 소스 유형을 변경할 수 없습니다. 데이터 업데이트의 경우: `source:LOCAL_FILE` 유형의 기존 테이블은 먼저 POST api/v2/reference-tables/uploads를 호출하여 업로드 ID를 얻은 다음 제공된 각 URL에 CSV 데이터 청크를 PUT하고, 마지막으로 file_metadata의 upload_id를 사용하여 이 PATCH 엔드포인트를 호출합니다. `source:` 유형이 `S3`, `GCS` 또는 `AZURE`인 기존 테이블의 경우, 동일한 유형의 클라우드 스토리지에 있는 CSV 파일을 가리키는 업데이트된 access_details를 file_metadata에 제공합니다. ### Arguments #### Path Parameters | Field | Type | Description | | --------------- | ------ | -------------------------------------------------- | | id [*required*] | string | Unique identifier of the reference table to update | ### Request #### Body Data (required) {% tabs %} {% tab label="Model" %} | Parent field | Field | Type | Description | | -------------- | -------------------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | | data | object | 기존 Reference Table을 업데이트하기 위한 요청 본문입니다. | | data | attributes | object | Attributes that define the updates to the reference table's configuration and properties. | | attributes | description | string | Optional text describing the purpose or contents of this reference table. | | attributes | file_metadata | | Metadata specifying where and how to access the reference table's data file. | | file_metadata | Object 1 | object | Cloud storage file metadata for patch requests. Allows partial updates of access_details and sync_enabled. | | Object 1 | access_details | object | Cloud storage access configuration for the reference table data file. | | access_details | aws_detail | object | Amazon Web Services S3 storage access configuration. | | aws_detail | aws_account_id | string | AWS account ID where the S3 bucket is located. | | aws_detail | aws_bucket_name | string | S3 bucket containing the CSV file. | | aws_detail | file_path | string | The relative file path from the S3 bucket root to the CSV file. | | access_details | azure_detail | object | Azure Blob Storage access configuration. | | azure_detail | azure_client_id | string | Azure service principal (application) client ID with permissions to read from the container. | | azure_detail | azure_container_name | string | Azure Blob Storage container containing the CSV file. | | azure_detail | azure_storage_account_name | string | Azure storage account where the container is located. | | azure_detail | azure_tenant_id | string | Azure Active Directory tenant ID. | | azure_detail | file_path | string | The relative file path from the Azure container root to the CSV file. | | access_details | gcp_detail | object | Google Cloud Platform storage access configuration. | | gcp_detail | file_path | string | The relative file path from the GCS bucket root to the CSV file. | | gcp_detail | gcp_bucket_name | string | GCP bucket containing the CSV file. | | gcp_detail | gcp_project_id | string | GCP project ID where the bucket is located. | | gcp_detail | gcp_service_account_email | string | Service account email with read permissions for the GCS bucket. | | Object 1 | sync_enabled | boolean | Whether this table is synced automatically. | | file_metadata | Object 2 | object | Local file metadata for patch requests using upload ID. | | Object 2 | upload_id [*required*] | string | The upload ID. | | attributes | schema | object | Schema defining the updates to the structure and columns of the reference table. Schema fields cannot be deleted or renamed. | | schema | fields [*required*] | [object] | The schema fields. Maximum of 200 columns. | | fields | name [*required*] | string | The field name. | | fields | type [*required*] | enum | The field type for reference table schema fields. Allowed enum values: `STRING`, `INT32`. | | schema | primary_keys [*required*] | [string] | List of field names that serve as primary keys for the table. Only one primary key is supported, and it is used as an ID to retrieve rows. Primary keys cannot be changed after table creation. | | attributes | tags | [string] | Tags for organizing and filtering reference tables. | | data | type [*required*] | enum | Reference table resource type. Allowed enum values: `reference_table`. Default: `reference_table`. | {% /tab %} {% tab label="Example" %} ```json { "data": { "attributes": { "description": "example description", "file_metadata": { "access_details": { "aws_detail": { "aws_account_id": "123456789000", "aws_bucket_name": "example-data-bucket", "file_path": "reference-tables/users.csv" }, "azure_detail": { "azure_client_id": "aaaaaaaa-1111-2222-3333-bbbbbbbbbbbb", "azure_container_name": "reference-data", "azure_storage_account_name": "examplestorageaccount", "azure_tenant_id": "cccccccc-4444-5555-6666-dddddddddddd", "file_path": "tables/users.csv" }, "gcp_detail": { "file_path": "data/reference_tables/users.csv", "gcp_bucket_name": "example-data-bucket", "gcp_project_id": "example-gcp-project-12345", "gcp_service_account_email": "example-service@example-gcp-project-12345.iam.gserviceaccount.com" } }, "sync_enabled": false }, "schema": { "fields": [ { "name": "field_1", "type": "STRING" } ], "primary_keys": [ "field_1" ] }, "tags": [ "tag_1", "tag_2" ] }, "type": "reference_table" } } ``` {% /tab %} {% /tabs %} ### Response {% tabs %} {% tab label="200" %} OK {% /tab %} {% tab label="400" %} Bad Request {% tabs %} {% tab label="Model" %} API error response. | Field | Type | Description | | ------------------- | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="403" %} Forbidden {% tabs %} {% tab label="Model" %} API error response. | Field | Type | Description | | ------------------- | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="429" %} Too many requests {% tabs %} {% tab label="Model" %} API error response. | Field | Type | Description | | ------------------- | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% /tabs %} ### Code Example {% tabs %} {% tab label="Curl" %} ```bash # Path parameters export id="CHANGE_ME" # Set your Datadog site and credentials export DD_SITE="datadoghq.com" # Or us3.datadoghq.com, us5.datadoghq.com, datadoghq.eu, ap1.datadoghq.com, ap2.datadoghq.com, uk1.datadoghq.com, ddog-gov.com, us2.ddog-gov.com # Use a Personal Access Token or Service Access Token export DD_BEARER_TOKEN="" curl -X PATCH "https://api.${DD_SITE}/api/v2/reference-tables/tables/${id}" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer ${DD_BEARER_TOKEN}" \ -d @- << EOF { "data": { "attributes": { "description": "this is a cloud table generated via a cloud bucket sync", "file_metadata": { "access_details": { "aws_detail": { "aws_account_id": "test-account-id", "aws_bucket_name": "test-bucket", "file_path": "test_rt.csv" } }, "sync_enabled": true }, "schema": { "fields": [ { "name": "id", "type": "INT32" }, { "name": "name", "type": "STRING" } ], "primary_keys": [ "id" ] }, "tags": [ "test_tag" ] }, "type": "reference_table" } } EOF ``` {% /tab %} {% tab label="Go" %} ```go // Update reference table returns "OK" response package main import ( "context" "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.PatchTableRequest{ Data: &datadogV2.PatchTableRequestData{ Attributes: &datadogV2.PatchTableRequestDataAttributes{ Description: datadog.PtrString("this is a cloud table generated via a cloud bucket sync"), FileMetadata: &datadogV2.PatchTableRequestDataAttributesFileMetadata{ PatchTableRequestDataAttributesFileMetadataCloudStorage: &datadogV2.PatchTableRequestDataAttributesFileMetadataCloudStorage{ AccessDetails: &datadogV2.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails{ AwsDetail: &datadogV2.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail{ AwsAccountId: datadog.PtrString("test-account-id"), AwsBucketName: datadog.PtrString("test-bucket"), FilePath: datadog.PtrString("test_rt.csv"), }, }, SyncEnabled: datadog.PtrBool(true), }}, Schema: &datadogV2.PatchTableRequestDataAttributesSchema{ Fields: []datadogV2.PatchTableRequestDataAttributesSchemaFieldsItems{ { Name: "id", Type: datadogV2.REFERENCETABLESCHEMAFIELDTYPE_INT32, }, { Name: "name", Type: datadogV2.REFERENCETABLESCHEMAFIELDTYPE_STRING, }, }, PrimaryKeys: []string{ "id", }, }, Tags: []string{ "test_tag", }, }, Type: datadogV2.PATCHTABLEREQUESTDATATYPE_REFERENCE_TABLE, }, } 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.NewReferenceTablesApi(apiClient) r, err := api.UpdateReferenceTable(ctx, "id", body) if err != nil { fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.UpdateReferenceTable`: %v\n", err) fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r) } } ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=go) and then save the example to `main.go` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" go run "main.go" ``` {% /tab %} {% tab label="Java" %} ```java // Update reference table returns "OK" response import com.datadog.api.client.ApiClient; import com.datadog.api.client.ApiException; import com.datadog.api.client.v2.api.ReferenceTablesApi; import com.datadog.api.client.v2.model.PatchTableRequest; import com.datadog.api.client.v2.model.PatchTableRequestData; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributes; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadata; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadataCloudStorage; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesSchema; import com.datadog.api.client.v2.model.PatchTableRequestDataAttributesSchemaFieldsItems; import com.datadog.api.client.v2.model.PatchTableRequestDataType; import com.datadog.api.client.v2.model.ReferenceTableSchemaFieldType; import java.util.Arrays; import java.util.Collections; public class Example { public static void main(String[] args) { ApiClient defaultClient = ApiClient.getDefaultApiClient(); defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN")); ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient); PatchTableRequest body = new PatchTableRequest() .data( new PatchTableRequestData() .attributes( new PatchTableRequestDataAttributes() .description("this is a cloud table generated via a cloud bucket sync") .fileMetadata( new PatchTableRequestDataAttributesFileMetadata( new PatchTableRequestDataAttributesFileMetadataCloudStorage() .accessDetails( new PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails() .awsDetail( new PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail() .awsAccountId("test-account-id") .awsBucketName("test-bucket") .filePath("test_rt.csv"))) .syncEnabled(true))) .schema( new PatchTableRequestDataAttributesSchema() .fields( Arrays.asList( new PatchTableRequestDataAttributesSchemaFieldsItems() .name("id") .type(ReferenceTableSchemaFieldType.INT32), new PatchTableRequestDataAttributesSchemaFieldsItems() .name("name") .type(ReferenceTableSchemaFieldType.STRING))) .primaryKeys(Collections.singletonList("id"))) .tags(Collections.singletonList("test_tag"))) .type(PatchTableRequestDataType.REFERENCE_TABLE)); try { apiInstance.updateReferenceTable("id", body); } catch (ApiException e) { System.err.println("Exception when calling ReferenceTablesApi#updateReferenceTable"); 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](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=java) and then save the example to `Example.java` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" java "Example.java" ``` {% /tab %} {% tab label="Python" %} ```python """ Update reference table returns "OK" response """ from os import environ from datadog_api_client import ApiClient, Configuration from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi from datadog_api_client.v2.model.patch_table_request import PatchTableRequest from datadog_api_client.v2.model.patch_table_request_data import PatchTableRequestData from datadog_api_client.v2.model.patch_table_request_data_attributes import PatchTableRequestDataAttributes from datadog_api_client.v2.model.patch_table_request_data_attributes_file_metadata_cloud_storage import ( PatchTableRequestDataAttributesFileMetadataCloudStorage, ) from datadog_api_client.v2.model.patch_table_request_data_attributes_file_metadata_one_of_access_details import ( PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails, ) from datadog_api_client.v2.model.patch_table_request_data_attributes_file_metadata_one_of_access_details_aws_detail import ( PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail, ) from datadog_api_client.v2.model.patch_table_request_data_attributes_schema import PatchTableRequestDataAttributesSchema from datadog_api_client.v2.model.patch_table_request_data_attributes_schema_fields_items import ( PatchTableRequestDataAttributesSchemaFieldsItems, ) from datadog_api_client.v2.model.patch_table_request_data_type import PatchTableRequestDataType from datadog_api_client.v2.model.reference_table_schema_field_type import ReferenceTableSchemaFieldType body = PatchTableRequest( data=PatchTableRequestData( attributes=PatchTableRequestDataAttributes( description="this is a cloud table generated via a cloud bucket sync", file_metadata=PatchTableRequestDataAttributesFileMetadataCloudStorage( access_details=PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails( aws_detail=PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail( aws_account_id="test-account-id", aws_bucket_name="test-bucket", file_path="test_rt.csv", ), ), sync_enabled=True, ), schema=PatchTableRequestDataAttributesSchema( fields=[ PatchTableRequestDataAttributesSchemaFieldsItems( name="id", type=ReferenceTableSchemaFieldType.INT32, ), PatchTableRequestDataAttributesSchemaFieldsItems( name="name", type=ReferenceTableSchemaFieldType.STRING, ), ], primary_keys=[ "id", ], ), tags=[ "test_tag", ], ), type=PatchTableRequestDataType.REFERENCE_TABLE, ), ) configuration = Configuration() configuration.access_token = environ["DD_BEARER_TOKEN"] with ApiClient(configuration) as api_client: api_instance = ReferenceTablesApi(api_client) api_instance.update_reference_table(id="id", body=body) ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=python) and then save the example to `example.py` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" python3 "example.py" ``` {% /tab %} {% tab label="Ruby" %} ```ruby # Update reference table returns "OK" response require "datadog_api_client" DatadogAPIClient.configure do |config| config.access_token = ENV["DD_BEARER_TOKEN"] end api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new body = DatadogAPIClient::V2::PatchTableRequest.new({ data: DatadogAPIClient::V2::PatchTableRequestData.new({ attributes: DatadogAPIClient::V2::PatchTableRequestDataAttributes.new({ description: "this is a cloud table generated via a cloud bucket sync", file_metadata: DatadogAPIClient::V2::PatchTableRequestDataAttributesFileMetadataCloudStorage.new({ access_details: DatadogAPIClient::V2::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails.new({ aws_detail: DatadogAPIClient::V2::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail.new({ aws_account_id: "test-account-id", aws_bucket_name: "test-bucket", file_path: "test_rt.csv", }), }), sync_enabled: true, }), schema: DatadogAPIClient::V2::PatchTableRequestDataAttributesSchema.new({ fields: [ DatadogAPIClient::V2::PatchTableRequestDataAttributesSchemaFieldsItems.new({ name: "id", type: DatadogAPIClient::V2::ReferenceTableSchemaFieldType::INT32, }), DatadogAPIClient::V2::PatchTableRequestDataAttributesSchemaFieldsItems.new({ name: "name", type: DatadogAPIClient::V2::ReferenceTableSchemaFieldType::STRING, }), ], primary_keys: [ "id", ], }), tags: [ "test_tag", ], }), type: DatadogAPIClient::V2::PatchTableRequestDataType::REFERENCE_TABLE, }), }) p api_instance.update_reference_table("id", body) ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=ruby) and then save the example to `example.rb` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" rb "example.rb" ``` {% /tab %} {% tab label="Rust" %} ```rust // Update reference table returns "OK" response use datadog_api_client::datadog; use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI; use datadog_api_client::datadogV2::model::PatchTableRequest; use datadog_api_client::datadogV2::model::PatchTableRequestData; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributes; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadata; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadataCloudStorage; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesSchema; use datadog_api_client::datadogV2::model::PatchTableRequestDataAttributesSchemaFieldsItems; use datadog_api_client::datadogV2::model::PatchTableRequestDataType; use datadog_api_client::datadogV2::model::ReferenceTableSchemaFieldType; #[tokio::main] async fn main() { let body = PatchTableRequest ::new().data( PatchTableRequestData::new( PatchTableRequestDataType::REFERENCE_TABLE, ).attributes( PatchTableRequestDataAttributes::new() .description("this is a cloud table generated via a cloud bucket sync".to_string()) .file_metadata( PatchTableRequestDataAttributesFileMetadata ::PatchTableRequestDataAttributesFileMetadataCloudStorage( Box::new( PatchTableRequestDataAttributesFileMetadataCloudStorage::new() .access_details( PatchTableRequestDataAttributesFileMetadataOneOfAccessDetails ::new().aws_detail( PatchTableRequestDataAttributesFileMetadataOneOfAccessDetailsAwsDetail ::new() .aws_account_id("test-account-id".to_string()) .aws_bucket_name("test-bucket".to_string()) .file_path("test_rt.csv".to_string()), ), ) .sync_enabled(true), ), ), ) .schema( PatchTableRequestDataAttributesSchema::new( vec![ PatchTableRequestDataAttributesSchemaFieldsItems::new( "id".to_string(), ReferenceTableSchemaFieldType::INT32, ), PatchTableRequestDataAttributesSchemaFieldsItems::new( "name".to_string(), ReferenceTableSchemaFieldType::STRING, ) ], vec!["id".to_string()], ), ) .tags(vec!["test_tag".to_string()]), ), ); let configuration = datadog::Configuration::new(); let api = ReferenceTablesAPI::with_config(configuration); let resp = api.update_reference_table("id".to_string(), body).await; if let Ok(value) = resp { println!("{:#?}", value); } else { println!("{:#?}", resp.unwrap_err()); } } ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=rust) and then save the example to `src/main.rs` and run following commands: ```bash DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" cargo run ``` {% /tab %} {% tab label="TypeScript" %} ```typescript /** * Update reference table 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.ReferenceTablesApi(configuration); const params: v2.ReferenceTablesApiUpdateReferenceTableRequest = { body: { data: { attributes: { description: "this is a cloud table generated via a cloud bucket sync", fileMetadata: { accessDetails: { awsDetail: { awsAccountId: "test-account-id", awsBucketName: "test-bucket", filePath: "test_rt.csv", }, }, syncEnabled: true, }, schema: { fields: [ { name: "id", type: "INT32", }, { name: "name", type: "STRING", }, ], primaryKeys: ["id"], }, tags: ["test_tag"], }, type: "reference_table", }, }, id: "id", }; apiInstance .updateReferenceTable(params) .then((data: any) => { console.log( "API called successfully. Returned data: " + JSON.stringify(data) ); }) .catch((error: any) => console.error(error)); ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=typescript) and then save the example to `example.ts` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" tsc "example.ts" ``` {% /tab %} {% /tabs %}