Get experiment
https://api.datadoghq.com/api/v2/experiments/{experiment_id}https://api.us3.datadoghq.com/api/v2/experiments/{experiment_id}https://api.us5.datadoghq.com/api/v2/experiments/{experiment_id}https://api.datadoghq.eu/api/v2/experiments/{experiment_id}https://api.ap1.datadoghq.com/api/v2/experiments/{experiment_id}https://api.ap2.datadoghq.com/api/v2/experiments/{experiment_id}https://api.uk1.datadoghq.com/api/v2/experiments/{experiment_id}https://api.ddog-gov.com/api/v2/experiments/{experiment_id}https://api.us2.ddog-gov.com/api/v2/experiments/{experiment_id}Présentation
Get a complete experiment by ID. The response includes structured metadata, related links, and, when a complete setup exists, decision metrics, variants, warehouse_exposure_configuration, datadog_flag_configuration, STATIC or STEPS traffic exposure, and assignment and event dates. STEPS describes the configured plan rather than wall-clock history; Datadog step durations exclude pauses. The list endpoint omits these setup details.
OAuth apps require the product_analytics_experiments_read authorization scope to access this endpoint.
Arguments
Paramètres du chemin
experiment_id [required]The UUID of the experiment.
Réponse
OK
Response containing an experiment and its configuration.
data [required]Experiment resource with its identifier and configuration.
attributesDetails of the experiment.
assignments_end_dateEnd of the time window for experiment assignments.
assignments_start_dateStart of the time window for experiment assignments.
concluded_atTime when the experiment was concluded.
conclusionOutcome and supporting text recorded when the experiment is concluded.
decision_reasonReason for the recorded decision.
outcomeRecorded experiment outcome.
POSITIVE, NEGATIVE, NEUTRAL, INCONCLUSIVE, MISCONFIGURED, UNKNOWNsummarySummary of the experiment conclusion.
created_atTime when this resource was created.
datadog_flag_configurationFeature flag, environment, and targeting configuration for the experiment.
allocation_keyKey of the feature flag allocation linked to the experiment.
entry_point [required]Datadog measure and filters used to select analyzed subjects.
filters [required]Complete Datadog OR-of-ANDs entry-point filter expression.
measure_id [required]Datadog measure UUID.
environment_idID of the feature flag environment used by the experiment.
feature_flag_idID of the feature flag linked to the experiment.
targeting_rulesRules that select subjects for the experiment.
conditions [required]Conditions that must all match for this rule. Each condition must use exactly one shape: saved_filter_id alone or operator plus attribute plus value.
Object 1A condition that uses a saved filter. Inline fields must be omitted or null.
saved_filter_id [required]Saved-filter UUID.
Object 2An inline condition. The saved_filter_id field must be omitted or null.
attribute [required]Attribute to evaluate.
operator [required]Required with attribute and value for an inline condition; omit when saved_filter_id is set.
LT, LTE, GT, GTE, MATCHES, NOT_MATCHES, ONE_OF, NOT_ONE_OF, IS_NULL, EQUALSShow 6 more
SEMVER_EQ, SEMVER_NEQ, SEMVER_LT, SEMVER_LTE, SEMVER_GT, SEMVER_GTEvalue [required]Values used by the operator. Every operator requires at least one value.
decision_metricsMetrics used to decide the experiment outcome.
is_primary [required]Whether this is the experiment primary metric.
metric_id [required]Decision metric UUID.
decision_variant_keyKey of the variant selected in the experiment decision.
events_end_dateEnd of the time window for metric events.
events_start_dateStart of the time window for metric events.
experiment_typeKind of experiment. STANDARD is an ordinary experiment. Other values, such as CANARY and HOLDOUT, identify experiments owned by another workflow. New kinds may be added; treat unknown values as non-standard.
hypothesisExpected effect that the experiment is intended to test.
migration_metadataMetadata retained for resources imported from another system.
nameDisplay name of the experiment.
pipeline_table_suffixSuffix used to identify the experiment's pipeline output table.
protocol_idID of the protocol associated with the experiment.
related_linksLinks to supporting material for the experiment.
idLink ID. Omit it when adding a link.
titleOptional display title.
url [required]Absolute URL.
results_last_updatedTime of the most recent update to the experiment's results.
split_by_propertiesProperties used to split the experiment results into groups.
column_name [required]Exposure field or Warehouse column used for the analysis dimension.
column_type [required]Type of the Datadog exposure field or Warehouse column.
varchar, int, double, boolean, varchar_array, int_array, double_array, raw, STRING, INTEGERShow 4 more
FLOAT, BOOLEAN, DATE, TIMESTAMPid [required]Read-only property ID. Omit it from POST and PATCH; writes identify properties by column_name.
name [required]Display name for the analysis dimension.
statusCurrent stage in the experiment lifecycle.
DRAFT, SCHEDULED, IN_PROGRESS, READY_FOR_DECISION, DECISION_MADE, CANCELLED, UNKNOWNstructured_metadataValues of structured metadata fields attached to the experiment.
enum_valuesSelected values for an enumerated metadata field.
field_display_nameDisplay name of the metadata field.
field_key [required]Key that identifies the metadata field.
field_typeType of value stored in the structured metadata field.
FREETEXT, ENUMfreetext_valueText value for a free-text metadata field.
subject_type_idID of the subject type used by this configuration.
summarySummary text recorded for the experiment.
tagsTags attached to the experiment.
teamsTeams associated with the experiment.
traffic_exposureTraffic exposure fraction or schedule configured for the experiment.
fractionSTATIC exposure fraction. Draft experiments can change this value. After start only warehouse experiments without a Datadog flag can change a STATIC fraction through the public API.
mode [required]Whether exposure uses a fixed fraction or a sequence of steps.
STATIC, STEPSstepsConfigured exposure plan rather than wall-clock history. At least two steps must have strictly increasing fractions and no gaps. Warehouse steps start at assignments_start_date and can use different durations. New Datadog plans have at most five steps and a first fraction above zero. Their nonfinal durations must be equal and exclude time paused. Datadog steps start with the experiment. Running warehouse experiments can replace step fractions, durations, and the exposure mode. After start, Datadog exposure plans cannot change through the public API. The final duration is null and its fraction holds until assignment ends.
duration_ms [required]Positive step duration in milliseconds. Datadog durations exclude pauses. Send null for the final step.
fraction [required]Fraction of traffic exposed during this step.
updated_atTime when this resource was last updated.
variantsVariants configured for the experiment.
feature_flag_variant_idBacking feature flag variant ID. Present for Datadog feature flag experiments and omitted for Warehouse experiments.
is_active [required]Whether this variant participates in the experiment.
is_control [required]Whether this is the single control variant.
key [required]Value recorded in exposure data for this variant.
nameDisplay name of the experiment variant.
weight [required]Traffic allocation percentage.
warehouse_exposure_configurationWarehouse exposure model and settings used to identify experiment assignments.
entry_point [required]Optional Warehouse measure that scopes analyzed subjects.
filters [required]Complete ordered Warehouse entry-point filter set.
operation [required]Comparison applied by the warehouse entry-point filter.
IS, IS_NOTproperty_id [required]Warehouse property UUID.
values [required]Ordered values used by the filter.
measure_id [required]Warehouse measure UUID.
experiment_key [required]Warehouse experiment key. Reads can return null for incomplete configuration; configuration writes require a value.
exposure_sql_model_id [required]ID of the exposure SQL model that provides assignment data.
id [required]Identifier of the experiment.
type [required]Experiments resource type.
experimentsexperiments{
"data": {
"attributes": {
"assignments_end_date": "2026-08-15T00:00:00Z",
"assignments_start_date": "2026-08-01T00:00:00Z",
"concluded_at": "2026-08-05T09:30:00Z",
"conclusion": {
"decision_reason": "The primary metric improved without material regressions",
"outcome": "POSITIVE",
"summary": "The treatment improved conversion"
},
"created_at": "2026-08-01T12:00:00Z",
"datadog_flag_configuration": null,
"decision_metrics": [
{
"is_primary": true,
"metric_id": "b1a2c3d4-0000-0000-0000-000000000000"
}
],
"decision_variant_key": "treatment",
"events_end_date": "2026-08-22T00:00:00Z",
"events_start_date": "2026-08-01T00:00:00Z",
"experiment_type": "STANDARD",
"hypothesis": "A clearer checkout button increases purchase conversion",
"name": "Checkout button test",
"pipeline_table_suffix": "a1b2c3d4",
"protocol_id": "e4d5f6a7-0000-0000-0000-000000000000",
"related_links": [
{
"id": "d1d2d3d4-0000-0000-0000-000000000000",
"title": "Experiment design",
"url": "https://docs.example.com/checkout-experiment"
}
],
"results_last_updated": "2026-08-05T09:25:00Z",
"split_by_properties": [],
"status": "DECISION_MADE",
"structured_metadata": [
{
"enum_values": [
"beta"
],
"field_display_name": "Launch stage",
"field_key": "launch_stage",
"field_type": "ENUM"
},
{
"field_display_name": "Notes",
"field_key": "notes",
"field_type": "FREETEXT",
"freetext_value": "Checkout redesign"
}
],
"subject_type_id": "c2b3d4e5-0000-0000-0000-000000000000",
"summary": "The treatment improved conversion",
"tags": [
"growth"
],
"teams": [
"growth"
],
"traffic_exposure": {
"fraction": 1,
"mode": "STATIC"
},
"updated_at": "2026-08-05T09:30:00Z",
"variants": [
{
"is_active": true,
"is_control": true,
"key": "control",
"name": "Control",
"weight": 50
},
{
"is_active": true,
"is_control": false,
"key": "treatment",
"name": "Treatment",
"weight": 50
}
],
"warehouse_exposure_configuration": {
"entry_point": null,
"experiment_key": "checkout_button_test",
"exposure_sql_model_id": "f5e6a7b8-0000-0000-0000-000000000000"
}
},
"id": "550e8400-e29b-41d4-a716-446655440000",
"type": "experiments"
}
}Malformed experiment ID (not a valid UUID).
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"
}
]
}Missing or invalid authentication (dd-api-key + dd-application-key headers, or a valid user session).
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"
}
]
}Authenticated caller lacks the product_analytics_experiments_read permission, or lacks feature-flag and environment read permissions for a Datadog-backed configuration.
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"
}
]
}No experiment with this ID exists for the organization.
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"
}
]
}The stored assignment configuration cannot be represented losslessly by this API (unsupported_configuration).
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"
]
}Exemple de code
# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# 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.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="us3.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="us5.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="datadoghq.eu"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="ap1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="ap2.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="uk1.datadoghq.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"# Path parameters
export experiment_id="550e8400-e29b-41d4-a716-446655440000"
# Set your Datadog site and credentials
export DD_SITE="us2.ddog-gov.com"
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"
curl -X GET "https://api.${DD_SITE}/api/v2/experiments/${experiment_id}" \
-H "Accept: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}"// Get experiment 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"
"github.com/google/uuid"
)
func main() {
// there is a valid "experiment" in the system
ExperimentDataID := uuid.MustParse(os.Getenv("EXPERIMENT_DATA_ID"))
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.NewExperimentsApi(apiClient)
resp, r, err := api.GetExperiment(ctx, ExperimentDataID)
if err != nil {
fmt.Fprintf(os.Stderr, "Error when calling `ExperimentsApi.GetExperiment`: %v\n", err)
fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
}
responseContent, _ := json.MarshalIndent(resp, "", " ")
fmt.Fprintf(os.Stdout, "Response from `ExperimentsApi.GetExperiment`:\n%s\n", responseContent)
}
Instructions
First install the library and its dependencies and then save the example to main.go and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"// Get experiment returns "OK" response
import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ExperimentsApi;
import com.datadog.api.client.v2.model.ExperimentsExperimentV2DTO;
import java.util.UUID;
public class Example {
public static void main(String[] args) {
ApiClient defaultClient = ApiClient.getDefaultApiClient();
defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
ExperimentsApi apiInstance = new ExperimentsApi(defaultClient);
// there is a valid "experiment" in the system
UUID EXPERIMENT_DATA_ID = null;
try {
EXPERIMENT_DATA_ID = UUID.fromString(System.getenv("EXPERIMENT_DATA_ID"));
} catch (IllegalArgumentException e) {
System.err.println("Error parsing UUID: " + e.getMessage());
}
try {
ExperimentsExperimentV2DTO result = apiInstance.getExperiment(EXPERIMENT_DATA_ID);
System.out.println(result);
} catch (ApiException e) {
System.err.println("Exception when calling ExperimentsApi#getExperiment");
System.err.println("Status code: " + e.getCode());
System.err.println("Reason: " + e.getResponseBody());
System.err.println("Response headers: " + e.getResponseHeaders());
e.printStackTrace();
}
}
}
Instructions
First install the library and its dependencies and then save the example to Example.java and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java""""
Get experiment returns "OK" response
"""
from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.experiments_api import ExperimentsApi
# there is a valid "experiment" in the system
EXPERIMENT_DATA_ID = environ["EXPERIMENT_DATA_ID"]
configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
with ApiClient(configuration) as api_client:
api_instance = ExperimentsApi(api_client)
response = api_instance.get_experiment(
experiment_id=EXPERIMENT_DATA_ID,
)
print(response)
Instructions
First install the library and its dependencies and then save the example to example.py and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"# Get experiment returns "OK" response
require "datadog_api_client"
DatadogAPIClient.configure do |config|
config.access_token = ENV["DD_BEARER_TOKEN"]
end
api_instance = DatadogAPIClient::V2::ExperimentsAPI.new
# there is a valid "experiment" in the system
EXPERIMENT_DATA_ID = ENV["EXPERIMENT_DATA_ID"]
p api_instance.get_experiment(EXPERIMENT_DATA_ID)
Instructions
First install the library and its dependencies and then save the example to example.rb and run following commands:
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us3.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us5.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="datadoghq.eu" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ap1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ap2.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="uk1.datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"DD_SITE="us2.ddog-gov.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"// Get experiment returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_experiments::ExperimentsAPI;
#[tokio::main]
async fn main() {
// there is a valid "experiment" in the system
let experiment_data_id =
uuid::Uuid::parse_str(&std::env::var("EXPERIMENT_DATA_ID").unwrap()).expect("Invalid UUID");
let configuration = datadog::Configuration::new();
let api = ExperimentsAPI::with_config(configuration);
let resp = api.get_experiment(experiment_data_id.clone()).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