User Selection Logic for Feature Rollout Stages
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Solution Overview
Problem
Current methods for rolling out new software features do not account for user type and specific user needs, leading to uneven distribution of users across rollout stages and lack of mechanisms for users to opt out of early exposure to potential issues.
Innovation Solution
A system and method that allow users and enterprises to opt into late-stage rollout, ensuring equal distribution of user types and allowing exclusion from early stages based on specific needs, using a rollout plan with multiple stages and user selection logic to manage feature exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users are randomly selected for early rollout stages, then rollout speed is improved, but user distribution fairness deteriorates
Solution Approach 1:
The patent applies local quality by treating different user types differently in the selection process. Instead of uniform random selection, the system identifies specific user categories (e.g., enterprise users, consumers, online users) and applies targeted selection criteria to each group, ensuring fair representation while maintaining rollout efficiency.
2Productivity
If all users are exposed to new features simultaneously, then rollout completeness is improved, but system reliability deteriorates
Solution Approach 1:
The patent implements segmentation by dividing the user population into multiple cohorts that receive the new feature at different times. The system creates distinct rollout stages with controlled user groups, allowing gradual deployment while maintaining system stability through isolated testing cohorts.
Solution Approach 2:
The patent applies preliminary action by implementing a selection process that identifies and prepares specific user groups for early feature exposure before full rollout. The system pre-selects cohorts with appropriate characteristics and obtains necessary approvals before exposing them to new features, ensuring controlled and safe deployment.
3Device complexity
If random user selection is used, then selection simplicity is improved, but user type representation deteriorates
Solution Approach 1:
The patent applies local quality by implementing different selection strategies for different user types. The system identifies specific user categories and applies tailored selection criteria to each group, ensuring proper representation of enterprise users, consumers, and online users while maintaining manageable process complexity.
Data Source
AI summary
A method of and system for selecting users for a rollout process of a feature is carried out by receiving an indication of the rollout process for the feature being rolled out, accessing a rollout plan, the rollout plan including a plurality of stages for the rollout process, and selecting users from a user population for each of the plurality of stages of the rollout process. Selecting the users from a user population includes examining a property to determine if a user in the user population is indicated as opted into being a late-stage receiver, and upon determining that the user is opted into being the late-stage receiver, excluding the user from the user population for one or more early stages of the rollout and including the user into the user population in one or more late stages of the rollout process.