Package-level declarations
Types
You can use Amazon CloudWatch Evidently to safely validate new features by serving them to a specified percentage of your users while you roll out the feature. You can monitor the performance of the new feature to help you decide when to ramp up traffic to your users. This helps you reduce risk and identify unintended consequences before you fully launch the feature.
Functions
This operation assigns feature variation to user sessions. For each user session, you pass in an entityID that represents the user. Evidently then checks the evaluation rules and assigns the variation.
Creates an Evidently experiment. Before you create an experiment, you must create the feature to use for the experiment.
Creates an Evidently feature that you want to launch or test. You can define up to five variations of a feature, and use these variations in your launches and experiments. A feature must be created in a project. For information about creating a project, see CreateProject.
Creates a launch of a given feature. Before you create a launch, you must create the feature to use for the launch.
Creates a project, which is the logical object in Evidently that can contain features, launches, and experiments. Use projects to group similar features together.
Use this operation to define a segment of your audience. 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.
Deletes an Evidently experiment. The feature used for the experiment is not deleted.
Deletes an Evidently feature.
Deletes an Evidently launch. The feature used for the launch is not deleted.
Deletes an Evidently project. Before you can delete a project, you must delete all the features that the project contains. To delete a feature, use DeleteFeature.
Deletes a segment. You can't delete a segment that is being used in a launch or experiment, even if that launch or experiment is not currently running.
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.
Returns the details about one experiment. You must already know the experiment name. To retrieve a list of experiments in your account, use ListExperiments.
Retrieves the results of a running or completed experiment. No results are available until there have been 100 events for each variation and at least 10 minutes have passed since the start of the experiment. To increase the statistical power, Evidently performs an additional offline p-value analysis at the end of the experiment. Offline p-value analysis can detect statistical significance in some cases where the anytime p-values used during the experiment do not find statistical significance.
Returns the details about one feature. You must already know the feature name. To retrieve a list of features in your account, use ListFeatures.
Returns the details about one launch. You must already know the launch name. To retrieve a list of launches in your account, use ListLaunches.
Returns the details about one launch. You must already know the project name. To retrieve a list of projects in your account, use ListProjects.
Returns information about the specified segment. Specify the segment you want to view by specifying its ARN.
Returns configuration details about all the experiments in the specified project.
Returns configuration details about all the features in the specified project.
Returns configuration details about all the launches in the specified project.
Returns configuration details about all the projects in the current Region in your account.
Use this operation to find which experiments or launches are using a specified segment.
Returns a list of audience segments that you have created in your account in this Region.
Displays the tags associated with an Evidently resource.
Sends performance events to Evidently. These events can be used to evaluate a launch or an experiment.
Starts an existing experiment. To create an experiment, use CreateExperiment.
Starts an existing launch. To create a launch, use CreateLaunch.
Stops an experiment that is currently running. If you stop an experiment, you can't resume it or restart it.
Stops a launch that is currently running. After you stop a launch, you will not be able to resume it or restart it. Also, it will not be evaluated as a rule for traffic allocation, and the traffic that was allocated to the launch will instead be available to the feature's experiment, if there is one. Otherwise, all traffic will be served the default variation after the launch is stopped.
Assigns one or more tags (key-value pairs) to the specified CloudWatch Evidently resource. Projects, features, launches, and experiments can be tagged.
Use this operation to test a rules pattern that you plan to use to create an audience segment. For more information about segments, see CreateSegment.
Removes one or more tags from the specified resource.
Updates an Evidently experiment.
Updates an existing feature.
Updates a launch of a given feature.
Updates the description of an existing project.
Updates the data storage options for this project. If you store evaluation events, you an keep them and analyze them on your own. If you choose not to store evaluation events, Evidently deletes them after using them to produce metrics and other experiment results that you can view.
Create a copy of the client with one or more configuration values overridden. This method allows the caller to perform scoped config overrides for one or more client operations.