The name or ARN of the project that contains the feature being evaluated.

An array of structures, where each structure assigns a feature variation to one user session.

An array of structures, where each structure displays the results of one feature evaluation assignment to one user session.

The response's http status code.

An optional description of the experiment.

A structure that contains the configuration of which variation to use as the "control" version. tThe "control" version is used for comparison with other variations. This structure also specifies how much experiment traffic is allocated to each variation.

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.

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.

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.

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 Amazon Web Services and are interpreted strictly as strings of characters.

 <p>You can associate as many as 50 tags with an experiment.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

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.

A name for the new experiment.

The name or ARN of the project that you want to create the new experiment in.

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

The response's http status code.

A structure containing the configuration details of the experiment that you created.

The name of the variation to use as the default variation. The default variation is served to users who are not allocated to any ongoing launches or experiments of this feature.

This variation must also be listed in the variations structure.

If you omit defaultVariation, the first variation listed in the variations structure is used as the default variation.

An optional description of the feature.

Specify users that should always be served a specific variation of a feature. Each user is specified by a key-value pair . For each key, specify a user by entering their user ID, account ID, or some other identifier. For the value, specify the name of the variation that they are to be served.

Specify ALL_RULES to activate the traffic allocation specified by any ongoing launches or experiments. Specify DEFAULT_VARIATION to serve the default variation to all users instead.

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

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 Amazon Web Services and are interpreted strictly as strings of characters.

 <p>You can associate as many as 50 tags with a feature.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

The name for the new feature.

The name or ARN of the project that is to contain the new feature.

An array of structures that contain the configuration of the feature's different variations.

A structure that contains information about the new feature.

The response's http status code.

An optional description for the launch.

An array of structures that define the metrics that will be used to monitor the launch performance.

When Evidently assigns a particular user session to a launch, 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 launch name as the randomizationSalt.

An array of structures that define the traffic allocation percentages among the feature variations during each step of the launch.

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

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 Amazon Web Services and are interpreted strictly as strings of characters.

 <p>You can associate as many as 50 tags with a launch.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

An array of structures that contains the feature and variations that are to be used for the launch.

The name for the new launch.

The name or ARN of the project that you want to create the launch in.

The response's http status code.

A structure that contains the configuration of the launch that was created.

Use this parameter if the project will use /client-side evaluation powered by AppConfig/. Client-side evaluation allows your application to assign variations to user sessions locally instead of by calling the EvaluateFeature operation. This mitigates the latency and availability risks that come with an API call. For more information, see Client-side evaluation - powered by AppConfig.

This parameter is a structure that contains information about the AppConfig application and environment that will be used as for client-side evaluation.

To create a project that uses client-side evaluation, you must have the evidently:ExportProjectAsConfiguration permission.

A structure that contains information about where Evidently is to store evaluation events for longer term storage, if you choose to do so. If you choose not to store these events, Evidently deletes them after using them to produce metrics and other experiment results that you can view.

An optional description of the project.

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

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 Amazon Web Services and are interpreted strictly as strings of characters.

 <p>You can associate as many as 50 tags with a project.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

The name for the project.

The response's http status code.

A structure that contains information about the created project.

An optional description for this segment.

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

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 Amazon Web Services and are interpreted strictly as strings of characters.

 <p>You can associate as many as 50 tags with a segment.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

A name for the segment.

The pattern to use for the segment. For more information about pattern syntax, see Segment rule pattern syntax.

The response's http status code.

A structure that contains the complete information about the segment that was just created.

The name of the experiment to delete.

The name or ARN of the project that contains the experiment to delete.

The response's http status code.

The name of the feature to delete.

The name or ARN of the project that contains the feature to delete.

The response's http status code.

The name of the launch to delete.

The name or ARN of the project that contains the launch to delete.

The response's http status code.

The name or ARN of the project to delete.

The response's http status code.

Specifies the segment to delete.

The response's http status code.

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>

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

The name of the feature being evaluated.

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

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

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.

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

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

The response's http status code.

The name of the experiment that you want to see the details of.

The name or ARN of the project that contains the experiment.

A structure containing the configuration details of the experiment.

The response's http status code.

The statistic used to calculate experiment results. Currently the only valid value is mean, which uses the mean of the collected values as the statistic.

The date and time that the experiment ended, if it is completed. This must be no longer than 30 days after the experiment start time.

In seconds, the amount of time to aggregate results together.

The names of the report types that you want to see. Currently, BayesianInference is the only valid value.

The statistics that you want to see in the returned results.

• PValue specifies to use p-values for the results. A p-value is used in hypothesis testing to measure how often you are willing to make a mistake in rejecting the null hypothesis. A general practice is to reject the null hypothesis and declare that the results are statistically significant when the p-value is less than 0.05.
• ConfidenceInterval specifies a confidence interval for the results. The confidence interval represents the range of values for the chosen metric that is likely to contain the true difference between the baseStat of a variation and the baseline. Evidently returns the 95% confidence interval.
• TreatmentEffect is the difference in the statistic specified by the baseStat parameter between each variation and the default variation.
• BaseStat returns the statistical values collected for the metric for each variation. The statistic uses the same statistic specified in the baseStat parameter. Therefore, if baseStat is mean, this returns the mean of the values collected for each variation.

The date and time that the experiment started.

The name of the experiment to retrieve the results of.

The names of the experiment metrics that you want to see the results of.

The name or ARN of the project that contains the experiment that you want to see the results of.

The names of the experiment treatments that you want to see the results for.

If the experiment doesn't yet have enough events to provide valid results, this field is returned with the message Not enough events to generate results. If there are enough events to provide valid results, this field is not returned.

An array of structures that include the reports that you requested.

An array of structures that include experiment results including metric names and values.

The timestamps of each result returned.

The response's http status code.

The name of the feature that you want to retrieve information for.

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

The response's http status code.

A structure containing the configuration details of the feature.

The name of the launch that you want to see the details of.

The name or ARN of the project that contains the launch.

A structure containing the configuration details of the launch.

The response's http status code.

The name or ARN of the project that you want to see the details of.

The response's http status code.

A structure containing the configuration details of the project.

The ARN of the segment to return information for.

The response's http status code.

A structure that contains the complete information about the segment.

The maximum number of results to include in the response.

The token to use when requesting the next set of results. You received this token from a previous ListExperiments operation.

Use this optional parameter to limit the returned results to only the experiments with the status that you specify here.

The name or ARN of the project to return the experiment list from.

An array of structures that contain the configuration details of the experiments in the specified project.

The token to use in a subsequent ListExperiments operation to return the next set of results.

The response's http status code.

The maximum number of results to include in the response.

The token to use when requesting the next set of results. You received this token from a previous ListFeatures operation.

The name or ARN of the project to return the feature list from.

An array of structures that contain the configuration details of the features in the specified project.

The token to use in a subsequent ListFeatures operation to return the next set of results.

The response's http status code.

The maximum number of results to include in the response.

The token to use when requesting the next set of results. You received this token from a previous ListLaunches operation.

Use this optional parameter to limit the returned results to only the launches with the status that you specify here.

The name or ARN of the project to return the launch list from.

An array of structures that contain the configuration details of the launches in the specified project.

The token to use in a subsequent ListLaunches operation to return the next set of results.

The response's http status code.

The maximum number of results to include in the response.

The token to use when requesting the next set of results. You received this token from a previous ListProjects operation.

The token to use in a subsequent ListProjects operation to return the next set of results.

An array of structures that contain the configuration details of the projects in the Region.

The response's http status code.

The maximum number of results to include in the response. If you omit this, the default of 50 is used.

The token to use when requesting the next set of results. You received this token from a previous ListSegmentReferences operation.

The ARN of the segment that you want to view information for.

Specifies whether to return information about launches or experiments that use this segment.

The token to use in a subsequent ListSegmentReferences operation to return the next set of results.

An array of structures, where each structure contains information about one experiment or launch that uses this segment.

The response's http status code.

The maximum number of results to include in the response. If you omit this, the default of 50 is used.

The token to use when requesting the next set of results. You received this token from a previous ListSegments operation.

The token to use in a subsequent ListSegments operation to return the next set of results.

An array of structures that contain information about the segments in this Region.

The response's http status code.

The ARN of the resource that you want to see the tags of.

The list of tag keys and values associated with the resource you specified.

The response's http status code.

An array of event structures that contain the performance data that is being sent to Evidently.

The name or ARN of the project to write the events to.

A structure that contains Evidently's response to the sent events, including an event ID and error codes, if any.

The number of events in the operation that could not be used by Evidently.

The response's http status code.

The date and time to end the experiment. This must be no more than 30 days after the experiment starts.

The name of the experiment to start.

The name or ARN of the project that contains the experiment to start.

A timestamp that indicates when the experiment started.

The response's http status code.

The name of the launch to start.

The name or ARN of the project that contains the launch to start.

The response's http status code.

A structure that contains information about the launch that was started.

Specify whether the experiment is to be considered COMPLETED or CANCELLED after it stops.

A string that describes why you are stopping the experiment.

The name of the experiment to stop.

The name or ARN of the project that contains the experiment to stop.

The date and time that the experiment stopped.

The response's http status code.

Specify whether to consider the launch as COMPLETED or CANCELLED after it stops.

A string that describes why you are stopping the launch.

The name of the launch to stop.

The name or ARN of the project that contains the launch that you want to stop.

The date and time that the launch stopped.

The response's http status code.

The ARN of the CloudWatch Evidently resource that you're adding tags to.

The list of key-value pairs to associate with the resource.

The response's http status code.

The pattern to test.

A sample evaluationContext JSON block to test against the specified pattern.

The response's http status code.

Returns true if the pattern matches the payload.

The ARN of the CloudWatch Evidently resource that you're removing tags from.

The list of tag keys to remove from the resource.

The response's http status code.

An optional description of the experiment.

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.

A structure that contains the configuration of which variation o 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.

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.

Removes a segment from being used in an experiment. You can't use this parameter if the experiment is currently running.

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 20,000 to allocate 20% of the available audience.

Adds an audience segment to an experiment. When a segment is used in an experiment, only user sessions that match the segment pattern are used in the experiment. You can't use this parameter if the experiment is currently running.

An array of structures that define the variations being tested in the experiment.

The name of the experiment to update.

The name or ARN of the project that contains the experiment that you want to update.

The response's http status code.

A structure containing the configuration details of the experiment that was updated.

To update variation configurations for this feature, or add new ones, specify this structure. In this array, include any variations that you want to add or update. If the array includes a variation name that already exists for this feature, it is updated. If it includes a new variation name, it is added as a new variation.

The name of the variation to use as the default variation. The default variation is served to users who are not allocated to any ongoing launches or experiments of this feature.

An optional description of the feature.

Specified users that should always be served a specific variation of a feature. Each user is specified by a key-value pair . For each key, specify a user by entering their user ID, account ID, or some other identifier. For the value, specify the name of the variation that they are to be served.

Specify ALL_RULES to activate the traffic allocation specified by any ongoing launches or experiments. Specify DEFAULT_VARIATION to serve the default variation to all users instead.

Removes a variation from the feature. If the variation you specify doesn't exist, then this makes no change and does not report an error.

This operation fails if you try to remove a variation that is part of an ongoing launch or experiment.

The name of the feature to be updated.

The name or ARN of the project that contains the feature to be updated.

The response's http status code.

A structure that contains information about the updated feature.

An optional description for the launch.

An array of structures that contains the feature and variations that are to be used for the launch.

An array of structures that define the metrics that will be used to monitor the launch performance.

When Evidently assigns a particular user session to a launch, 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 launch name as the randomizationSalt.

An array of structures that define the traffic allocation percentages among the feature variations during each step of the launch.

The name of the launch that is to be updated.

The name or ARN of the project that contains the launch that you want to update.

The response's http status code.

A structure that contains the new configuration of the launch that was updated.

Use this parameter if the project will use client-side evaluation powered by AppConfig. Client-side evaluation allows your application to assign variations to user sessions locally instead of by calling the EvaluateFeature operation. This mitigates the latency and availability risks that come with an API call. allows you to

This parameter is a structure that contains information about the AppConfig application that will be used for client-side evaluation.

An optional description of the project.

The name or ARN of the project to update.

The response's http status code.

A structure containing information about the updated project.

A structure containing the CloudWatch Logs log group where you want to store evaluation events.

A structure containing the S3 bucket name and bucket prefix where you want to store evaluation events.

The name or ARN of the project that you want to modify the data storage options for.

The response's http status code.

A structure containing details about the project that you updated.

The name of the log group where the project stores evaluation events.

The name of the log group where the project stores evaluation events.

A JSON block of attributes that you can optionally pass in. This JSON block is included in the evaluation events sent to Evidently from the user session.

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

The name of the feature being evaluated.

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

The name or ARN of the project that contains the feature being evaluated.

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; or EXPERIMENT_RULE_MATCH, if the user session was enrolled in an experiment.

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

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

An internal ID that represents a unique user session of the application.

The name of the feature being evaluated.

The name of the experiment or launch.

This value is aws.evidently.splits if this is an evaluation rule for a launch, and it is aws.evidently.onlineab if this is an evaluation rule for an experiment.

The event data.

The timestamp of the event.

aws.evidently.evaluation specifies an evaluation event, which determines which feature variation that a user sees. aws.evidently.custom specifies a custom event, which generates metrics from user actions such as clicks and checkouts.

A description of the experiment.

A structure that contains the date and time that the experiment started and ended.

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.

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.

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

This value is used when Evidently assigns a particular user session to the experiment. It helps create a randomization ID to determine which variation the user session is served. This randomization ID is a combination of the entity ID and randomizationSalt.

In thousandths of a percent, the amount of the available audience that is allocated to this experiment. 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, so a value of 10,000 is 10% of the available audience.

A structure that contains the time and date that Evidently completed the analysis of the experiment.

The audience segment being used for the experiment, if a segment is being used.

If the experiment was stopped, this is the string that was entered by the person who stopped the experiment, to explain why it was stopped.

The list of tag keys and values associated with this experiment.

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

The ARN of the experiment.

The date and time that the experiment is first created.

The date and time that the experiment was most recently updated.

The name of the experiment.

The current state of the experiment.

The type of this experiment. Currently, this value must be aws.experiment.onlineab.

The date and time that the experiment ended.

The date and time that the experiment started.

The content of the report.

The name of the metric that is analyzed in this experiment report.

The type of analysis used for this report.

The name of the variation that this report pertains to.

The name of the metric.

The experiment statistic that these results pertain to.

The treatment, or variation, that returned the values in this structure.

The values for the metricName that were recorded in the experiment.

The time and date that Evidently completed the analysis of the experiment.

The name of the variation that is used as the default variation. The default variation is served to users who are not allocated to any ongoing launches or experiments of this feature.

This variation must also be listed in the variations structure.

If you omit defaultVariation, the first variation listed in the variations structure is used as the default variation.

The description of the feature.

A set of key-value pairs that specify users who should always be served a specific variation of a feature. Each key specifies a user using their user ID, account ID, or some other identifier. The value specifies the name of the variation that the user is to be served.

For the override to be successful, the value of the key must match the entityId used in the EvaluateFeature operation.

An array of structures that define the evaluation rules for the feature.

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

The list of tag keys and values associated with this feature.

The ARN of the feature.

The date and time that the feature is created.

If this value is ALL_RULES, the traffic allocation specified by any ongoing launches or experiments is being used. If this is DEFAULT_VARIATION, the default variation is being served to all users.

The date and time that the feature was most recently updated.

The name of the feature.

The current state of the feature.

Defines the type of value used to define the different feature variations. For more information, see Variation types

An array of structures that contain the configuration of the feature's different variations.

The name of the variation that is used as the default variation. The default variation is served to users who are not allocated to any ongoing launches or experiments of this feature.

An array of structures that define

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

The list of tag keys and values associated with this feature.

The ARN of the feature.

The date and time that the feature is created.

If this value is ALL_RULES, the traffic allocation specified by any ongoing launches or experiments is being used. If this is DEFAULT_VARIATION, the default variation is being served to all users.

The date and time that the feature was most recently updated.

The name of the feature.

The current state of the feature.

The description of the launch.

A structure that contains information about the start and end times of the launch.

An array of structures that define the feature variations that are being used in the launch.

An array of structures that define the metrics that are being used to monitor the launch performance.

The name or ARN of the project that contains the launch.

This value is used when Evidently assigns a particular user session to the launch, to help create a randomization ID to determine which variation the user session is served. This randomization ID is a combination of the entity ID and randomizationSalt.

An array of structures that define the traffic allocation percentages among the feature variations during each step of the launch.

If the launch was stopped, this is the string that was entered by the person who stopped the launch, to explain why it was stopped.

The list of tag keys and values associated with this launch.

The ARN of the launch.

The date and time that the launch is created.

The date and time that the launch was most recently updated.

The name of the launch.

The current state of the launch.

The type of launch.

The date and time that the launch ended.

The date and time that the launch started.

A description of the launch group.

The feature variation for this launch group. This is a key-value pair.

The name of the launch group.

A description of the launch group.

The feature that this launch is using.

A name for this launch group.

The feature variation to use for this launch group.

The entity, such as a user or session, that does an action that causes a metric value to be recorded.

The EventBridge event pattern that defines how the metric is recorded.

For more information about EventBridge event patterns, see Amazon EventBridge event patterns.

The name of the metric.

The label for the units that the metric is measuring.

The value that is tracked to produce the metric.

The EventBridge event pattern that defines how the metric is recorded.

For more information about EventBridge event patterns, see Amazon EventBridge event patterns.

A label for the units that the metric is measuring.

The entity, such as a user or session, that does an action that causes a metric value to be recorded. An example is userDetails.userID.

A name for the metric.

The value that is tracked to produce the metric.

INCREASE means that a variation with a higher number for this metric is performing better.

DECREASE means that a variation with a lower number for this metric is performing better.

A structure that contains details about the metric.

INCREASE means that a variation with a higher number for this metric is performing better.

DECREASE means that a variation with a lower number for this metric is performing better.

A structure that contains details about the metric.

A structure that defines the metric.

A structure that defines the metric.

The name of the variation that is to be the default variation that the other variations are compared to.

A set of key-value pairs. The keys are variation names, and the values are the portion of experiment traffic to be assigned to that variation. Specify the traffic portion in thousandths of a percent, so 20,000 for a variation would allocate 20% of the experiment traffic to that variation.

The name of the variation that is the default variation that the other variations are compared to.

A set of key-value pairs. The keys are variation names, and the values are the portion of experiment traffic to be assigned to that variation. The traffic portion is specified in thousandths of a percent, so 20,000 for a variation would allocate 20% of the experiment traffic to that variation.

The number of ongoing experiments currently in the project.

The number of ongoing launches currently in the project.

This structure defines the configuration of how your application integrates with AppConfig to run client-side evaluation.

A structure that contains information about where Evidently is to store evaluation events for longer term storage.

The user-entered description of the project.

The number of experiments currently in the project. This includes all experiments that have been created and not deleted, whether they are ongoing or not.

The number of features currently in the project.

The number of launches currently in the project. This includes all launches that have been created and not deleted, whether they are ongoing or not.

The list of tag keys and values associated with this project.

The name or ARN of the project.

The date and time that the project is created.

The date and time that the project was most recently updated.

The name of the project.

The current state of the project.

The ID of the AppConfig application to use for client-side evaluation.

The ID of the AppConfig profile to use for client-side evaluation.

The ID of the AppConfig environment to use for client-side evaluation. This must be an environment that is within the application that you specify for applicationId.

The ID of the AppConfig application to use for client-side evaluation.

The ID of the AppConfig environment to use for client-side evaluation. This must be an environment that is within the application that you specify for applicationId.

If the project stores evaluation events in CloudWatch Logs, this structure stores the log group name.

If the project stores evaluation events in an Amazon S3 bucket, this structure stores the bucket name and bucket prefix.

If the project stores evaluation events in CloudWatch Logs, this structure stores the log group name.

If the project stores evaluation events in an Amazon S3 bucket, this structure stores the bucket name and bucket prefix.

The number of experiments currently in the project.

The number of ongoing launches currently in the project.

The description of the project.

The number of experiments currently in the project.

The number of features currently in the project.

The number of launches currently in the project, including launches that are ongoing, completed, and not started yet.

The list of tag keys and values associated with this project.

The name or ARN of the project.

The date and time that the project is created.

The date and time that the project was most recently updated.

The name of the project.

The current state of the project.

If the PutProjectEvents operation has an error, the error code is returned here.

If the PutProjectEvents operation has an error, the error message is returned here.

A unique ID assigned to this PutProjectEvents operation.

The ARN of the experiment or launch.

The day and time that this experiment or launch ended.

The day and time that this experiment or launch was most recently updated.

The day and time that this experiment or launch started.

The status of the experiment or launch.

The name of the experiment or launch.

Specifies whether the resource that this structure contains information about is an experiment or a launch.

The name of the bucket in which Evidently stores evaluation events.

The bucket prefix in which Evidently stores evaluation events.

The name of the bucket in which Evidently stores evaluation events.

The bucket prefix in which Evidently stores evaluation events.

The traffic allocation percentages among the feature variations during one step of a launch. This is a set of key-value pairs. The keys are variation names. The values represent the percentage of traffic to allocate to that variation during this step.

The values is expressed in thousandths of a percent, so assigning a weight of 50000 assigns 50% of traffic to that variation.

If the sum of the weights for all the variations in a segment override does not add up to 100,000, then the remaining traffic that matches this segment is not assigned by this segment override, and instead moves on to the next segment override or the default traffic split.

Use this parameter to specify different traffic splits for one or more audience segments. A segment is a portion of your audience that share one or more characteristics. Examples could be Chrome browser users, users in Europe, or Firefox browser users in Europe who also fit other criteria that your application collects, such as age.

This parameter is an array of up to six segment override objects. Each of these objects specifies a segment that you have already created, and defines the traffic split for that segment.

The date and time that this step of the launch starts.

Use this parameter to specify different traffic splits for one or more audience segments. A segment is a portion of your audience that share one or more characteristics. Examples could be Chrome browser users, users in Europe, or Firefox browser users in Europe who also fit other criteria that your application collects, such as age.

This parameter is an array of up to six segment override objects. Each of these objects specifies a segment that you have already created, and defines the traffic split for that segment.

The traffic allocation percentages among the feature variations during one step of a launch. This is a set of key-value pairs. The keys are variation names. The values represent the percentage of traffic to allocate to that variation during this step.

 <p>The values is expressed in thousandths of a percent, so assigning a weight of 50000 assigns 50% of traffic to that variation.</p> <p>If the sum of the weights for all the variations in a segment override does not add up to 100,000, then the remaining traffic that matches this segment is not assigned by this segment override, and instead moves on to the next segment override or the default traffic split.</p>

The date and time that this step of the launch starts.

An array of structures that define the traffic allocation percentages among the feature variations during each step of the launch. This also defines the start time of each step.

An array of structures that define the traffic allocation percentages among the feature variations during each step of the launch. This also defines the start time of each step.

The customer-created description for this segment.

The number of experiments that this segment is used in. This count includes all current experiments, not just those that are currently running.

The number of launches that this segment is used in. This count includes all current launches, not just those that are currently running.

The list of tag keys and values associated with this launch.

The ARN of the segment.

The date and time that this segment was created.

The date and time that this segment was most recently updated.

The name of the segment.

The pattern that defines the attributes to use to evalute whether a user session will be in the segment. For more information about the pattern syntax, see Segment rule pattern syntax.

A number indicating the order to use to evaluate segment overrides, if there are more than one. Segment overrides with lower numbers are evaluated first.

The ARN of the segment to use.

The traffic allocation percentages among the feature variations to assign to this segment. This is a set of key-value pairs. The keys are variation names. The values represent the amount of traffic to allocate to that variation for this segment. This is expressed in thousandths of a percent, so a weight of 50000 represents 50% of traffic.

The description of the treatment.

The feature variation used for this treatment. This is a key-value pair. The key is the feature name, and the value is the variation name.

The name of this treatment.

A description for this treatment.

The feature that this experiment is testing.

A name for this treatment.

The name of the variation to use as this treatment in the experiment.

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

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

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

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

The name of the variation.

The value assigned to this variation.

The name of the variation.

The value assigned to this variation.