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.
You can also conduct A/B experiments to make feature design decisions based on evidence and data. An experiment can test as many as five variations at once. Evidently collects experiment data and analyzes it using statistical methods. It also provides clear recommendations about which variations perform better. You can test both user-facing features and backend features.
Some APIs require complex or nested arguments. These exist in
The other modules within this crate are not required for normal usage.
Client and fluent builders for calling the service.
Configuration for the service.
Errors that can occur when calling the service.
Input structures for operations.
Generated accessors for nested fields
Base Middleware Stack
Data structures used by operation inputs/outputs.
All operations that this crate can perform.
Output structures for operations.
Paginators for the service
Re-exported types from supporting crates.
App name that can be configured with an AWS SDK client to become part of the user agent string.
Client for Amazon CloudWatch Evidently
AWS SDK Credentials
The region to send requests to.
Retry configuration for requests.
All possible error types for this service.
Crate version number.