Phased Enterprise Configuration Rollouts With Adaptive Throttling
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Solution Overview
Problem
IT administrators face inefficiencies and costs due to unnoticed failures or regressions in implementing configuration changes across enterprise systems, lacking effective methods to manage these changes while minimizing downtime and maximizing user experience.
Innovation Solution
Client devices are divided into groups for phased implementation, with real-time monitoring and scoring to determine if the next phase should be throttled based on user experience metrics, allowing for automatic correction of issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If configuration changes are implemented all at once across the enterprise, then implementation speed is improved, but failure detection is delayed and user experience deteriorates
Solution Approach 1:
The patent segments the enterprise client devices into multiple groups (e.g., first group, second group, third group) and implements configuration changes in phases across these groups rather than all at once. This allows monitoring of each phase's impact on user experience while maintaining overall implementation progress, thus resolving the contradiction between implementation speed and failure detection capability.
2Loss of time
If configuration changes are implemented all at once, then implementation time is reduced, but user experience monitoring becomes ineffective
Solution Approach 1:
The patent implements a feedback mechanism where user experience information is collected from client devices after each phase of configuration change implementation. This feedback is used to determine whether to proceed to the next phase or throttle implementation. This resolves the contradiction by enabling continuous user experience monitoring throughout the implementation process while maintaining reduced overall implementation time through phased deployment.
3Productivity
If configuration changes are implemented without throttling, then implementation completeness is improved, but cost increases due to productivity loss
Solution Approach 1:
The patent implements dynamic throttling of configuration change deployment based on real-time user experience feedback. When negative feedback is detected, the system automatically throttles or pauses implementation in affected groups while continuing implementation in other groups. This dynamic adjustment maintains implementation completeness while minimizing productivity loss by preventing widespread deployment of problematic changes.
4Productivity
If configuration changes are implemented without A/B testing, then implementation speed is improved, but effectiveness determination becomes impossible
Solution Approach 1:
The patent segments the enterprise into multiple client device groups and implements configuration changes in phases across these segments. Each phase serves as an A/B test where the first group experiences the change before the second group, allowing effectiveness determination through comparison. This segmented approach maintains implementation speed while enabling precise effectiveness measurement through controlled phased rollouts.
Data Source
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AI summary
Techniques are described herein that are capable of selectively throttling an implementation of configuration changes in an enterprise. For instance, incremental phases of the implementation on respective subsets of clients are selectively throttled during respective periods of time by performing operations for each subset during a respective phase that precedes a respective next phase of the implementation. The operations include gathering information regarding the phase from the clients in the subset; generating a score that indicates an extent to which metrics associated with the implementation are satisfied during the phase based at least in part on the information; comparing the score to a reference score for the subset to determine whether the score is within a tolerance associated with the reference score; and selectively throttling the next phase of the implementation based at least in part on whether the score is within the tolerance.