Standalone Decision Service for A/B Testing Integration
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Solution Overview
Problem
Current A/B testing systems require complex integration of SDKs into applications, which can be cumbersome and limit flexibility, especially when users want to implement feature flagging and testing as a standalone service for better control and scalability.
Innovation Solution
A customizable decision service is introduced as a standalone, open-source microservice with a REST API, providing simplified endpoints for A/B testing functionality, allowing users to manage feature flags and experiments independently of application development, and offering improved scalability and standardization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If SDKs are integrated into applications for A/B testing, then A/B testing functionality is provided, but integration complexity increases and flexibility decreases
Solution Approach 1:
The patent extracts A/B testing functionality from application-specific SDKs and consolidates it into a standalone decision service. This allows the core testing functionality to be separated from individual applications, reducing integration complexity while maintaining flexibility through centralized management and standardized interfaces.
Solution Approach 2:
The decision service provides universal A/B testing capabilities that can be accessed by multiple applications through a common interface. This multi-functional approach eliminates the need for separate SDK integrations in each application, thereby reducing overall integration complexity while enhancing flexibility across the system.
2Productivity
If SDKs are integrated into each application, then A/B testing is enabled, but scalability and standardization are limited
Solution Approach 1:
The system segments A/B testing functionality into a separate, independent decision service that operates autonomously from individual applications. This segmentation enables scalable deployment where the core service can handle multiple applications without requiring proportional increases in integration complexity, thereby improving scalability while maintaining standardization.
Solution Approach 2:
The decision service acts as an intermediary between applications and A/B testing infrastructure. This mediator layer provides standardized interfaces and centralized control, enabling consistent testing practices across multiple applications while simplifying individual application integrations and improving overall scalability.
Data Source
AI summary
A method of executing an A/B testing service comprises deploying an instance of the A/B testing service between a client device and an A/B testing server and receiving by the A/B testing service from the A/B testing server a software development kit (SDK) key for a client device, the SDK key indicating an A/B testing environment to be associated with the instance. The method further comprises, in response to receiving the SDK key: storing data associated with the A/B testing environment in memory of the client device; providing a HyperText Transfer Protocol (HTTP) application programming interface (API) associated with the instance of the A/B testing service to one or more applications associated with the A/B testing environment; and executing, by a processing device, commands between the client device and the one or more applications on behalf of the A/B testing environment.