과거 작업 나열하기
https://api.datadoghq.com/api/v2/siem-historical-detections/jobshttps://api.us3.datadoghq.com/api/v2/siem-historical-detections/jobshttps://api.us5.datadoghq.com/api/v2/siem-historical-detections/jobshttps://api.datadoghq.eu/api/v2/siem-historical-detections/jobshttps://api.ap1.datadoghq.com/api/v2/siem-historical-detections/jobshttps://api.ap2.datadoghq.com/api/v2/siem-historical-detections/jobshttps://api.uk1.datadoghq.com/api/v2/siem-historical-detections/jobshttps://api.ddog-gov.com/api/v2/siem-historical-detections/jobshttps://api.us2.ddog-gov.com/api/v2/siem-historical-detections/jobs개요
과거 작업을 나열합니다.
인수
쿼리 문자열
page[size]Number of items to return per page. The maximum allowed value is 100.
10page[number]Specific page number to return.
0sortThe order of the jobs in results.
filter[query]Query used to filter items from the fetched list.
응답
OK
List of historical jobs.
dataArray containing the list of historical jobs.
attributesHistorical job attributes.
createdAtTime when the job was created.
createdByHandleThe handle of the user who created the job.
createdByNameThe name of the user who created the job.
createdFromRuleIdID of the rule used to create the job (if it is created from a rule).
jobDefinitionDefinition of a historical job.
calculatedFieldsCalculated fields.
expression [required]Expression.
name [required]Field name.
cases [required]Cases used for generating job results. Up to 10 cases are allowed.
actionsAction to perform for each rule case.
optionsOptions for the rule action
durationDuration of the action in seconds. 0 indicates no expiration.
flaggedIPTypeUsed with the case action of type 'flag_ip'. The value specified in this field is applied as a flag to the IP addresses.
SUSPICIOUS, FLAGGEDuserBehaviorNameUsed with the case action of type 'user_behavior'. The value specified in this field is applied as a risk tag to all users affected by the rule.
typeThe action type.
block_ip, block_user, user_behavior, flag_ipconditionA case contains logical operations (>,>=, &&, ||) to determine if a signal should be generated
based on the event counts in the previously defined queries.
nameName of the case.
notificationsNotification targets.
status [required]Severity of the Security Signal.
info, low, medium, high, criticalfrom [required]Starting time of data analyzed by the job.
groupSignalsByAdditional grouping to perform on top of the existing groups in the query section. Must be a subset of the existing groups.
index [required]Index used to load the data.
message [required]Message for generated results.
name [required]Job name.
optionsJob options.
anomalyDetectionOptionsOptions on anomaly detection method.
bucketDurationDuration in seconds of the time buckets used to aggregate events matched by the rule. Must be greater than or equal to 300.
300, 600, 900, 1800, 3600, 10800detectionToleranceAn optional parameter that sets how permissive anomaly detection is. Higher values require higher deviations before triggering a signal.
1, 2, 3, 4, 5instantaneousBaselineWhen set to true, Datadog uses previous values that fall within the defined learning window to construct the baseline, enabling the system to establish an accurate baseline more rapidly rather than relying solely on gradual learning over time.
learningDurationLearning duration in hours. Anomaly detection waits for at least this amount of historical data before it starts evaluating.
1, 6, 12, 24, 48, 168, 336learningPeriodBaselineAn optional override baseline to apply while the rule is in the learning period. Must be greater than or equal to 0.
detectionMethodThe detection method.
threshold, new_value, anomaly_detection, impossible_travel, hardcoded, third_party, anomaly_threshold, sequence_detectionevaluationWindowA time window is specified to match when at least one of the cases matches true. This is a sliding window and evaluates in real time. For third party detection method, this field is not used.
0, 60, 300, 600, 900, 1800, 3600, 7200, 10800, 21600Show 2 more
43200, 86400impossibleTravelOptionsOptions on impossible travel detection method.
baselineUserLocationsIf true, signals are suppressed for the first 24 hours. In that time, Datadog learns the user's regular access locations. This can be helpful to reduce noise and infer VPN usage or credentialed API access.
baselineUserLocationsDurationThe duration in days during which Datadog learns the user's regular access locations. After this period, signals are generated for accesses from unknown locations.
keepAliveOnce a signal is generated, the signal will remain "open" if a case is matched at least once within this keep alive window. For third party detection method, this field is not used.
0, 60, 300, 600, 900, 1800, 3600, 7200, 10800, 21600Show 2 more
43200, 86400maxSignalDurationA signal will "close" regardless of the query being matched once the time exceeds the maximum duration. This time is calculated from the first seen timestamp.
0, 60, 300, 600, 900, 1800, 3600, 7200, 10800, 21600Show 2 more
43200, 86400newValueOptionsOptions on new value detection method.
forgetAfterThe duration in days after which a learned value is forgotten.
instantaneousBaselineWhen set to true, Datadog uses previous values that fall within the defined learning window to construct the baseline, enabling the system to establish an accurate baseline more rapidly rather than relying solely on gradual learning over time.
learningDurationThe duration in days during which values are learned, and after which signals will be generated for values that weren't learned. If set to 0, a signal will be generated for all new values after the first value is learned.
0learningMethodThe learning method used to determine when signals should be generated for values that weren't learned.
durationduration, thresholdlearningThresholdA number of occurrences after which signals will be generated for values that weren't learned.
00, 1sequenceDetectionOptionsOptions on sequence detection method.
stepTransitionsTransitions defining the allowed order of steps and their evaluation windows.
childName of the child step.
evaluationWindowA time window is specified to match when at least one of the cases matches true. This is a sliding window and evaluates in real time. For third party detection method, this field is not used.
0, 60, 300, 600, 900, 1800, 3600, 7200, 10800, 21600Show 2 more
43200, 86400parentName of the parent step.
stepsSteps that define the conditions to be matched in sequence.
conditionCondition referencing rule queries (e.g., a > 0).
evaluationWindowA time window is specified to match when at least one of the cases matches true. This is a sliding window and evaluates in real time. For third party detection method, this field is not used.
0, 60, 300, 600, 900, 1800, 3600, 7200, 10800, 21600Show 2 more
43200, 86400nameUnique name identifying the step.
thirdPartyRuleOptionsOptions on third party detection method.
defaultNotificationsNotification targets for the logs that do not correspond to any of the cases.
defaultStatusSeverity of the Security Signal.
info, low, medium, high, criticalrootQueriesQueries to be combined with third party case queries. Each of them can have different group by fields, to aggregate differently based on the type of alert.
groupByFieldsFields to group by.
queryQuery to run on logs.
signalTitleTemplateA template for the signal title; if omitted, the title is generated based on the case name.
queries [required]Queries for selecting logs analyzed by the job. Up to 10 queries are allowed.
additionalFiltersAdditional filters appended to the query at evaluation time.
aggregationThe aggregation type.
count, cardinality, sum, max, new_value, geo_data, event_count, nonecorrelatedByFieldsFields used to correlate results across queries in sequence detection rules.
correlatedQueryIndexZero-based index of the query to correlate with in sequence detection rules. Up to 10 queries are supported, so valid values are 0 to 9.
customQueryExtensionCustom query extension used to refine the base query.
dataSourceSource of events, either logs, audit trail, security signals, or Datadog events. app_sec_spans is deprecated in favor of spans.
logslogs, audit, app_sec_spans, spans, security_runtime, network, events, security_signalsdatasetIdsIDs of reference datasets used by this query.
distinctFieldsField for which the cardinality is measured. Sent as an array.
groupByFieldsFields to group by.
hasOptionalGroupByFieldsWhen false, events without a group-by value are ignored by the query. When true, events with missing group-by fields are processed with N/A, replacing the missing values.
falseindexIndex used to load the data for this query.
indexesIndexes used to load the data for this query. Mutually exclusive with index.
metricsGroup of target fields to aggregate over when using the sum, max, geo data, or new value aggregations. The sum, max, and geo data aggregations only accept one value in this list, whereas the new value aggregation accepts up to five values.
nameName of the query.
queryQuery to run on logs.
queryLanguageLanguage used to parse the query string.
referenceTablesReference tables used in the queries.
checkPresenceWhether to include or exclude the matched values.
columnNameThe name of the column in the reference table.
logFieldPathThe field in the log to match against the reference table.
ruleQueryNameThe name of the query to apply the reference table to.
tableNameThe name of the reference table.
tagsTags for generated signals.
thirdPartyCasesCases for generating results from third-party detection method. Only available for third-party detection method. Up to 10 cases are allowed.
nameName of the case.
notificationsNotification targets for each case.
queryA query to map a third party event to this case.
status [required]Severity of the Security Signal.
info, low, medium, high, criticalto [required]Ending time of data analyzed by the job.
typeJob type.
jobNameJob name.
jobStatusJob status.
modifiedAtLast modification time of the job.
progressRateJob execution progress as a value between 0 and 1. Available for ongoing jobs.
signalOutputWhether the job outputs signals.
idID of the job.
typeType of payload.
historicalDetectionsJobmetaMetadata about the list of jobs.
totalCountNumber of jobs in the list.
{
"data": [
{
"attributes": {
"createdAt": "string",
"createdByHandle": "string",
"createdByName": "string",
"createdFromRuleId": "string",
"jobDefinition": {
"calculatedFields": [
{
"expression": "@request_end_timestamp - @request_start_timestamp",
"name": "response_time"
}
],
"cases": [
{
"actions": [
{
"options": {
"duration": 0,
"flaggedIPType": "FLAGGED",
"userBehaviorName": "string"
},
"type": "string"
}
],
"condition": "string",
"name": "string",
"notifications": [],
"status": "critical"
}
],
"from": 1729843470000,
"groupSignalsBy": [
"service"
],
"index": "cloud_siem",
"message": "A large number of failed login attempts.",
"name": "Excessive number of failed attempts.",
"options": {
"anomalyDetectionOptions": {
"bucketDuration": 300,
"detectionTolerance": 5,
"instantaneousBaseline": false,
"learningDuration": "integer",
"learningPeriodBaseline": "integer"
},
"detectionMethod": "string",
"evaluationWindow": "integer",
"impossibleTravelOptions": {
"baselineUserLocations": true,
"baselineUserLocationsDuration": "integer"
},
"keepAlive": "integer",
"maxSignalDuration": "integer",
"newValueOptions": {
"forgetAfter": "integer",
"instantaneousBaseline": false,
"learningDuration": "integer",
"learningMethod": "string",
"learningThreshold": "integer"
},
"sequenceDetectionOptions": {
"stepTransitions": [
{
"child": "string",
"evaluationWindow": "integer",
"parent": "string"
}
],
"steps": [
{
"condition": "string",
"evaluationWindow": "integer",
"name": "string"
}
]
},
"thirdPartyRuleOptions": {
"defaultNotifications": [],
"defaultStatus": "critical",
"rootQueries": [
{
"groupByFields": [],
"query": "source:cloudtrail"
}
],
"signalTitleTemplate": "string"
}
},
"queries": [
{
"additionalFilters": "string",
"aggregation": "string",
"correlatedByFields": [],
"correlatedQueryIndex": "integer",
"customQueryExtension": "string",
"dataSource": "logs",
"datasetIds": [],
"distinctFields": [],
"groupByFields": [],
"hasOptionalGroupByFields": false,
"index": "string",
"indexes": [],
"metrics": [],
"name": "string",
"query": "a > 3",
"queryLanguage": "string"
}
],
"referenceTables": [
{
"checkPresence": false,
"columnName": "string",
"logFieldPath": "string",
"ruleQueryName": "string",
"tableName": "string"
}
],
"tags": [],
"thirdPartyCases": [
{
"name": "string",
"notifications": [],
"query": "string",
"status": "critical"
}
],
"to": 1729847070000,
"type": "string"
},
"jobName": "string",
"jobStatus": "string",
"modifiedAt": "string",
"progressRate": "number",
"signalOutput": false
},
"id": "string",
"type": "string"
}
],
"meta": {
"totalCount": "integer"
}
}Bad Request
API error response.
errors [required]A list of errors.
{
"errors": [
"Bad Request"
]
}Not Authorized
API error response.
errors [required]A list of errors.
{
"errors": [
"Bad Request"
]
}Too many requests
API error response.
errors [required]A list of errors.
{
"errors": [
"Bad Request"
]
}코드 예시
# 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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-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/siem-historical-detections/jobs" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"// List historical jobs 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.ListHistoricalJobs", true)
apiClient := datadog.NewAPIClient(configuration)
api := datadogV2.NewSecurityMonitoringApi(apiClient)
resp, r, err := api.ListHistoricalJobs(ctx, *datadogV2.NewListHistoricalJobsOptionalParameters())
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `SecurityMonitoringApi.ListHistoricalJobs`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `SecurityMonitoringApi.ListHistoricalJobs`:\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"// List historical jobs 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.ListHistoricalJobsResponse;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
defaultClient.setUnstableOperationEnabled("v2.listHistoricalJobs", true);
SecurityMonitoringApi apiInstance = new SecurityMonitoringApi(defaultClient);
try {
ListHistoricalJobsResponse result = apiInstance.listHistoricalJobs();
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling SecurityMonitoringApi#listHistoricalJobs");
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""""
List historical jobs 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["list_historical_jobs"] = True
with ApiClient(configuration) as api_client:
api_instance = SecurityMonitoringApi(api_client)
response = api_instance.list_historical_jobs()
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"# List historical jobs returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
config.unstable_operations["v2.list_historical_jobs".to_sym] = true
end
api_instance = DatadogAPIClient::V2::SecurityMonitoringAPI.new
p api_instance.list_historical_jobs()
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"// List historical jobs returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_security_monitoring::ListHistoricalJobsOptionalParams;
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.list_historical_jobs", true);
let api = SecurityMonitoringAPI::with_config(configuration);
let resp = api
.list_historical_jobs(ListHistoricalJobsOptionalParams::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/**
* List historical jobs 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.listHistoricalJobs"] = true;
const apiInstance = new v2.SecurityMonitoringApi(configuration);
apiInstance
.listHistoricalJobs()
.then((data: v2.ListHistoricalJobsResponse) => {
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"