Dynamic Software Version Allocation via Real-Time Performance Analysis
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Solution Overview
Problem
Conventional A/B testing methods are limited in their ability to dynamically adjust user allocations and resource distribution based on real-time performance and user interaction analysis, leading to suboptimal software version deployment and potential user dissatisfaction.
Innovation Solution
A system that uses an allocation module to gradually shift user allocations between software versions based on performance and user interaction data, dynamically reallocating resources to optimize system performance and user experience, while maintaining consistent user experiences through adaptive allocation rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional A/B testing methods are used with fixed allocation, then implementation simplicity is maintained, but adaptability to real-time performance and user interaction is reduced
Solution Approach 1:
The patent implements dynamic allocation rules that automatically adjust user distribution between software versions based on real-time performance metrics and user interaction data. The system transitions from static fixed allocation to dynamic adaptive allocation, where allocation percentages are continuously optimized based on observed outcomes, thereby resolving the contradiction between adaptability and system complexity.
Solution Approach 2:
The system incorporates feedback loops that collect performance data and user interaction metrics, analyze results, and use this information to adjust allocation rules. This feedback mechanism enables the system to adapt to real-time conditions while maintaining manageable complexity through automated decision-making algorithms that process feedback data systematically.
2Productivity
If user allocations are dynamically adjusted based on real-time analysis, then software deployment efficiency is improved, but system complexity increases
Solution Approach 1:
The system implements self-service capabilities where the allocation module automatically adjusts user distributions based on pre-defined performance criteria and collected data, without requiring manual intervention. This automation improves deployment efficiency while containing complexity through rule-based decision-making that operates autonomously once configured.
Solution Approach 2:
The patent utilizes parameter changes in allocation percentages based on observed performance metrics and user interaction outcomes. By dynamically adjusting these parameters according to measured results, the system optimizes deployment efficiency while managing complexity through systematic parameter optimization rather than complex control structures.
3Reliability
If resources are reallocated to optimize performance, then system performance is improved, but resource allocation complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-defining allocation rules and performance criteria before dynamic allocation begins. This preparation work establishes the framework for automated resource reallocation, improving system performance while containing complexity through advance planning and rule configuration rather than complex real-time decision-making.
Data Source
AI summary
This disclosure is directed in part to testing of different versions of software or software components (software versions) and analyzing results of use (e.g., user interaction) of the different software versions. The techniques described herein provide software testing that varies the allocation to enable a ramp up of allocations to/from another software version. The allocation module may use allocation rules to assign requests to each software version based on various factors such as load balancing, user attributes, past user assignment, and/or other rules or logic. An analysis of the different software versions may include an analysis of system performance resulting from operation of each software version. An analysis may determine attributes of each user and then allocate the user to a software version based on at least some of the determined attributes.