interface CfnExperimentProps

Language	Type name
.NET	`Amazon.CDK.AWS.Evidently.CfnExperimentProps`
Go	`github.com/aws/aws-cdk-go/awscdk/v2/awsevidently#CfnExperimentProps`
Java	`software.amazon.awscdk.services.evidently.CfnExperimentProps`
Python	`aws_cdk.aws_evidently.CfnExperimentProps`
TypeScript	`aws-cdk-lib` » `aws_evidently` » `CfnExperimentProps`

Properties for defining a CfnExperiment.

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_evidently as evidently } from 'aws-cdk-lib';
const cfnExperimentProps: evidently.CfnExperimentProps = {
  metricGoals: [{
    desiredChange: 'desiredChange',
    entityIdKey: 'entityIdKey',
    metricName: 'metricName',
    valueKey: 'valueKey',

    // the properties below are optional
    eventPattern: 'eventPattern',
    unitLabel: 'unitLabel',
  }],
  name: 'name',
  onlineAbConfig: {
    controlTreatmentName: 'controlTreatmentName',
    treatmentWeights: [{
      splitWeight: 123,
      treatment: 'treatment',
    }],
  },
  project: 'project',
  treatments: [{
    feature: 'feature',
    treatmentName: 'treatmentName',
    variation: 'variation',

    // the properties below are optional
    description: 'description',
  }],

  // the properties below are optional
  description: 'description',
  randomizationSalt: 'randomizationSalt',
  removeSegment: false,
  runningStatus: {
    status: 'status',

    // the properties below are optional
    analysisCompleteTime: 'analysisCompleteTime',
    desiredState: 'desiredState',
    reason: 'reason',
  },
  samplingRate: 123,
  segment: 'segment',
  tags: [{
    key: 'key',
    value: 'value',
  }],
};

Properties

Name	Type	Description
metricGoals	`IResolvable` `\|` `IResolvable` `\|` `MetricGoalObjectProperty[]`	An array of structures that defines the metrics used for the experiment, and whether a higher or lower value for each metric is the goal.
name	`string`	A name for the new experiment.
onlineAbConfig	`IResolvable` `\|` `OnlineAbConfigObjectProperty`	A structure that contains the configuration of which variation to use as the "control" version.
project	`string`	The name or the ARN of the project where this experiment is to be created.
treatments	`IResolvable` `\|` `IResolvable` `\|` `TreatmentObjectProperty[]`	An array of structures that describe the configuration of each feature variation used in the experiment.
description?	`string`	An optional description of the experiment.
randomizationSalt?	`string`	When Evidently assigns a particular user session to an experiment, it must use a randomization ID to determine which variation the user session is served.
removeSegment?	`boolean \|` `IResolvable`	Set this to `true` to remove the segment that is associated with this experiment.
runningStatus?	`IResolvable` `\|` `RunningStatusObjectProperty`	A structure that you can use to start and stop the experiment.
samplingRate?	`number`	The portion of the available audience that you want to allocate to this experiment, in thousandths of a percent.
segment?	`string`	Specifies an audience segment to use in the experiment.
tags?	`CfnTag[]`	Assigns one or more tags (key-value pairs) to the experiment.

metricGoals

Type: IResolvable | IResolvable | MetricGoalObjectProperty[]

An array of structures that defines the metrics used for the experiment, and whether a higher or lower value for each metric is the goal.

You can use up to three metrics in an experiment.

name

Type: string

A name for the new experiment.

onlineAbConfig

Type: IResolvable | OnlineAbConfigObjectProperty

A structure that contains the configuration of which variation to use as the "control" version.

The "control" version is used for comparison with other variations. This structure also specifies how much experiment traffic is allocated to each variation.

project

Type: string

The name or the ARN of the project where this experiment is to be created.

treatments

Type: IResolvable | IResolvable | TreatmentObjectProperty[]

An array of structures that describe the configuration of each feature variation used in the experiment.

description?

Type: string (optional)

An optional description of the experiment.

randomizationSalt?

Type: string (optional)

When Evidently assigns a particular user session to an experiment, it must use a randomization ID to determine which variation the user session is served.

This randomization ID is a combination of the entity ID and randomizationSalt . If you omit randomizationSalt , Evidently uses the experiment name as the randomizationSalt .

removeSegment?

Type: boolean | IResolvable (optional)

Set this to true to remove the segment that is associated with this experiment.

You can't use this parameter if the experiment is currently running.

runningStatus?

Type: IResolvable | RunningStatusObjectProperty (optional)

A structure that you can use to start and stop the experiment.

samplingRate?

Type: number (optional)

The portion of the available audience that you want to allocate to this experiment, in thousandths of a percent.

The available audience is the total audience minus the audience that you have allocated to overrides or current launches of this feature.

This is represented in thousandths of a percent. For example, specify 10,000 to allocate 10% of the available audience.

segment?

Type: string (optional)

Specifies an audience segment to use in the experiment.

When a segment is used in an experiment, only user sessions that match the segment pattern are used in the experiment.

For more information, see Segment rule pattern syntax .

tags?

Type: CfnTag[] (optional)

Assigns one or more tags (key-value pairs) to the experiment.

Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values.

Tags don't have any semantic meaning to AWS and are interpreted strictly as strings of characters.

You can associate as many as 50 tags with an experiment.

For more information, see Tagging AWS resources .