CfnExperimentProps
- class aws_cdk.aws_evidently.CfnExperimentProps(*, metric_goals, name, online_ab_config, project, treatments, description=None, randomization_salt=None, remove_segment=None, running_status=None, sampling_rate=None, segment=None, tags=None)
Bases:
object
Properties for defining a
CfnExperiment
.- Parameters:
metric_goals (
Union
[IResolvable
,Sequence
[Union
[MetricGoalObjectProperty
,Dict
[str
,Any
],IResolvable
]]]) – 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 (
str
) – A name for the new experiment.online_ab_config (
Union
[IResolvable
,OnlineAbConfigObjectProperty
,Dict
[str
,Any
]]) – 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 (
str
) – The name or the ARN of the project where this experiment is to be created.treatments (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,TreatmentObjectProperty
,Dict
[str
,Any
]]]]) – An array of structures that describe the configuration of each feature variation used in the experiment.description (
Optional
[str
]) – An optional description of the experiment.randomization_salt (
Optional
[str
]) – 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 andrandomizationSalt
. If you omitrandomizationSalt
, Evidently uses the experiment name as therandomizationSalt
.remove_segment (
Union
[bool
,IResolvable
,None
]) – Set this totrue
to remove the segment that is associated with this experiment. You can’t use this parameter if the experiment is currently running.running_status (
Union
[IResolvable
,RunningStatusObjectProperty
,Dict
[str
,Any
],None
]) – A structure that you can use to start and stop the experiment.sampling_rate (
Union
[int
,float
,None
]) – 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 (
Optional
[str
]) – 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 (
Optional
[Sequence
[Union
[CfnTag
,Dict
[str
,Any
]]]]) – 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 .
- Link:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-evidently-experiment.html
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_evidently as evidently cfn_experiment_props = evidently.CfnExperimentProps( metric_goals=[evidently.CfnExperiment.MetricGoalObjectProperty( desired_change="desiredChange", entity_id_key="entityIdKey", metric_name="metricName", value_key="valueKey", # the properties below are optional event_pattern="eventPattern", unit_label="unitLabel" )], name="name", online_ab_config=evidently.CfnExperiment.OnlineAbConfigObjectProperty( control_treatment_name="controlTreatmentName", treatment_weights=[evidently.CfnExperiment.TreatmentToWeightProperty( split_weight=123, treatment="treatment" )] ), project="project", treatments=[evidently.CfnExperiment.TreatmentObjectProperty( feature="feature", treatment_name="treatmentName", variation="variation", # the properties below are optional description="description" )], # the properties below are optional description="description", randomization_salt="randomizationSalt", remove_segment=False, running_status=evidently.CfnExperiment.RunningStatusObjectProperty( status="status", # the properties below are optional analysis_complete_time="analysisCompleteTime", desired_state="desiredState", reason="reason" ), sampling_rate=123, segment="segment", tags=[CfnTag( key="key", value="value" )] )
Attributes
- description
An optional description of the experiment.
- metric_goals
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
A name for the new experiment.
- online_ab_config
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
The name or the ARN of the project where this experiment is to be created.
- randomization_salt
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 omitrandomizationSalt
, Evidently uses the experiment name as therandomizationSalt
.
- remove_segment
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.
- running_status
A structure that you can use to start and stop the experiment.
- sampling_rate
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
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
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 .
- treatments
An array of structures that describe the configuration of each feature variation used in the experiment.