[ aws . evidently ]

evaluate-feature

Description

This operation assigns a feature variation to one given user session. You pass in an entityID that represents the user. Evidently then checks the evaluation rules and assigns the variation.

The first rules that are evaluated are the override rules. If the user’s entityID matches an override rule, the user is served the variation specified by that rule.

<p>If there is a current launch with this feature that uses segment overrides, and if the user session's <code>evaluationContext</code> matches a segment rule defined in a segment override, the configuration in the segment overrides is used. For more information about segments, see <a href="https://docs.aws.amazon.com/cloudwatchevidently/latest/APIReference/API_CreateSegment.html">CreateSegment</a> and <a href="https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Evidently-segments.html">Use segments to focus your audience</a>.</p> <p>If there is a launch with no segment overrides, the user might be assigned to a variation in the launch. The chance of this depends on the percentage of users that are allocated to that launch. If the user is enrolled in the launch, the variation they are served depends on the allocation of the various feature variations used for the launch.</p> <p>If the user is not assigned to a launch, and there is an ongoing experiment for this feature, the user might be assigned to a variation in the experiment. The chance of this depends on the percentage of users that are allocated to that experiment.</p> <p>If the experiment uses a segment, then only user sessions with <code>evaluationContext</code> values that match the segment rule are used in the experiment.</p> <p>If the user is enrolled in the experiment, the variation they are served depends on the allocation of the various feature variations used for the experiment. </p> <p>If the user is not assigned to a launch or experiment, they are served the default variation.</p>

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  evaluate-feature
--entity-id <value>
[--evaluation-context <value>]
--feature <value>
--project <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options

--entity-id (string)

An internal ID that represents a unique user of the application. This entityID is checked against any override rules assigned for this feature.

--evaluation-context (string)

A JSON object of attributes that you can optionally pass in as part of the evaluation event sent to Evidently from the user session. Evidently can use this value to match user sessions with defined audience segments. For more information, see Use segments to focus your audience .

<p>If you include this parameter, the value must be a JSON object. A JSON array is not supported.</p>

--feature (string)

The name of the feature being evaluated.

--project (string)

The name or ARN of the project that contains this feature.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

See ‘aws help’ for descriptions of global parameters.

Output

details -> (string)

If this user was assigned to a launch or experiment, this field lists the launch or experiment name.

reason -> (string)

Specifies the reason that the user session was assigned this variation. Possible values include DEFAULT , meaning the user was served the default variation; LAUNCH_RULE_MATCH , if the user session was enrolled in a launch; EXPERIMENT_RULE_MATCH , if the user session was enrolled in an experiment; or ENTITY_OVERRIDES_MATCH , if the user’s entityId matches an override rule.

value -> (structure)

The value assigned to this variation to differentiate it from the other variations of this feature.

boolValue -> (boolean)

If this feature uses the Boolean variation type, this field contains the Boolean value of this variation.

doubleValue -> (double)

If this feature uses the double integer variation type, this field contains the double integer value of this variation.

longValue -> (long)

If this feature uses the long variation type, this field contains the long value of this variation.

stringValue -> (string)

If this feature uses the string variation type, this field contains the string value of this variation.

variation -> (string)

The name of the variation that was served to the user session.