Create an AI custom rule
https://api.datadoghq.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.us3.datadoghq.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.us5.datadoghq.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.datadoghq.eu/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.ap1.datadoghq.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.ap2.datadoghq.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.uk1.datadoghq.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.ddog-gov.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/ruleshttps://api.us2.ddog-gov.com/api/v2/static-analysis/ai/rulesets/{ruleset_name}/rulesOverview
Create a new AI custom rule within a ruleset.
Arguments
Path Parameters
ruleset_name [required]The ruleset name.
Request
Body Data (required)
dataRequest data for creating an AI custom rule.
attributesAttributes for creating an AI custom rule.
nameThe rule name.
idThe rule identifier, which must match the name.
typeAI custom rule resource type.
ai_rule{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"id": "my-ai-rule",
"type": "ai_rule"
}
}Response
Successfully created
Response containing a single AI custom rule.
data [required]Response data for an AI custom rule.
attributes [required]An AI custom rule embedded within a ruleset response.
created_at [required]The creation timestamp.
created_by [required]The identifier of the user who created the rule.
last_revision [required]The most recent revision of the rule.
category [required]Rule category
SECURITY, BEST_PRACTICES, CODE_STYLE, ERROR_PRONE, PERFORMANCEchecksum [required]Checksum of the revision content.
content [required]Base64-encoded AI model content for this revision.
created_at [required]The creation timestamp.
created_by [required]The identifier of the user who created the revision.
cwe [required]The associated CWE identifier.
description [required]Base64-encoded full description.
directories [required]Directory patterns this rule applies to.
execution_mode [required]The execution mode for an AI rule revision.
auto, manual, alwaysglobs [required]File glob patterns this rule applies to.
is_default [required]Whether this is a default Datadog rule.
is_published [required]Whether this revision is published.
is_testing [required]Whether this revision is for testing only.
severity [required]Rule severity
ERROR, WARNING, NOTICE, NONEshort_description [required]Base64-encoded short description.
version_id [required]The version identifier for this revision.
name [required]The rule name.
id [required]The rule identifier.
type [required]AI custom rule resource type.
ai_rule{
"data": {
"attributes": {
"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"
},
"id": "my-ai-rule",
"type": "ai_rule"
}
}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"
}
]
}Unauthorized
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"
}
]
}Conflict - rule already exists
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"
}
]
}Precondition Failed - validation error or ruleset 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"
]
}Internal Server Error
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"
}
]
}Code Example
# Path parameters
export ruleset_name="my-ai-ruleset"
# 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 POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF# Path parameters
export ruleset_name="my-ai-ruleset"
# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X POST "https://api.${DD_SITE}/api/v2/static-analysis/ai/rulesets/${ruleset_name}/rules" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
"data": {
"attributes": {
"name": "my-ai-rule"
},
"type": "ai_rule"
}
}
EOF// Create an AI custom rule returns "Successfully created" 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.AiCustomRuleRequest{
Data: &datadogV2.AiCustomRuleRequestData{
Attributes: &datadogV2.AiCustomRuleRequestAttributes{
Name: datadog.PtrString("my-ai-rule"),
},
Id: datadog.PtrString("my-ai-rule"),
Type: datadogV2.AICUSTOMRULEDATATYPE_AI_RULE.Ptr(),
},
}
ctx := datadog.NewDefaultContext(context.Background())
ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
configuration := datadog.NewConfiguration()
configuration.SetUnstableOperationEnabled("v2.CreateAiCustomRule", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewStaticAnalysisApi(apiClient)
resp, r, err := api.CreateAiCustomRule(ctx, "my-ai-ruleset", body)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `StaticAnalysisApi.CreateAiCustomRule`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `StaticAnalysisApi.CreateAiCustomRule`:\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"// Create an AI custom rule returns "Successfully created" 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.AiCustomRuleDataType;
import com.datadog.api.client.v2.model.AiCustomRuleRequest;
import com.datadog.api.client.v2.model.AiCustomRuleRequestAttributes;
import com.datadog.api.client.v2.model.AiCustomRuleRequestData;
import com.datadog.api.client.v2.model.AiCustomRuleResponse;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
defaultClient.setUnstableOperationEnabled("v2.createAiCustomRule", true);
StaticAnalysisApi apiInstance = new StaticAnalysisApi(defaultClient);
AiCustomRuleRequest body =
new AiCustomRuleRequest()
.data(
new AiCustomRuleRequestData()
.attributes(new AiCustomRuleRequestAttributes().name("my-ai-rule"))
.id("my-ai-rule")
.type(AiCustomRuleDataType.AI_RULE));
try {
AiCustomRuleResponse result = apiInstance.createAiCustomRule("my-ai-ruleset", body);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling StaticAnalysisApi#createAiCustomRule");
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""""
Create an AI custom rule returns "Successfully created" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.static_analysis_api import StaticAnalysisApi
from datadog_api_client.v2.model.ai_custom_rule_data_type import AiCustomRuleDataType
from datadog_api_client.v2.model.ai_custom_rule_request import AiCustomRuleRequest
from datadog_api_client.v2.model.ai_custom_rule_request_attributes import AiCustomRuleRequestAttributes
from datadog_api_client.v2.model.ai_custom_rule_request_data import AiCustomRuleRequestData
body = AiCustomRuleRequest(
data=AiCustomRuleRequestData(
attributes=AiCustomRuleRequestAttributes(
name="my-ai-rule",
),
id="my-ai-rule",
type=AiCustomRuleDataType.AI_RULE,
),
)
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
configuration.unstable_operations["create_ai_custom_rule"] = True
with ApiClient(configuration) as api_client:
api_instance = StaticAnalysisApi(api_client)
response = api_instance.create_ai_custom_rule(ruleset_name="my-ai-ruleset", body=body)
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"# Create an AI custom rule returns "Successfully created" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.create_ai_custom_rule".to_sym] = true
end
api_instance = DatadogAPIClient::V2::StaticAnalysisAPI.new
body = DatadogAPIClient::V2::AiCustomRuleRequest.new({
data: DatadogAPIClient::V2::AiCustomRuleRequestData.new({
attributes: DatadogAPIClient::V2::AiCustomRuleRequestAttributes.new({
name: "my-ai-rule",
}),
id: "my-ai-rule",
type: DatadogAPIClient::V2::AiCustomRuleDataType::AI_RULE,
}),
})
p api_instance.create_ai_custom_rule("my-ai-ruleset", body)
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"// Create an AI custom rule returns "Successfully created" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_static_analysis::StaticAnalysisAPI;
use datadog_api_client::datadogV2::model::AiCustomRuleDataType;
use datadog_api_client::datadogV2::model::AiCustomRuleRequest;
use datadog_api_client::datadogV2::model::AiCustomRuleRequestAttributes;
use datadog_api_client::datadogV2::model::AiCustomRuleRequestData;
#[tokio::main]
async fn main() {
let body = AiCustomRuleRequest::new().data(
AiCustomRuleRequestData::new()
.attributes(AiCustomRuleRequestAttributes::new().name("my-ai-rule".to_string()))
.id("my-ai-rule".to_string())
.type_(AiCustomRuleDataType::AI_RULE),
);
let mut configuration = datadog::Configuration::new();
configuration.set_unstable_operation_enabled("v2.create_ai_custom_rule", true);
let api = StaticAnalysisAPI::with_config(configuration);
let resp = api
.create_ai_custom_rule("my-ai-ruleset".to_string(), body)
.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 run/**
* Create an AI custom rule returns "Successfully created" 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.createAiCustomRule"] = true;
const apiInstance = new v2.StaticAnalysisApi(configuration);
const params: v2.StaticAnalysisApiCreateAiCustomRuleRequest = {
body: {
data: {
attributes: {
name: "my-ai-rule",
},
id: "my-ai-rule",
type: "ai_rule",
},
},
rulesetName: "my-ai-ruleset",
};
apiInstance
.createAiCustomRule(params)
.then((data: v2.AiCustomRuleResponse) => {
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"