Controller Proxy Selection via Health and Policy Scoring
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Solution Overview
Problem
In computer cluster environments, existing methods lack an efficient and intelligent mechanism for selecting a controller proxy that balances system health and policy compliance, often leading to suboptimal management and resource utilization.
Innovation Solution
A method and system that automatically trigger alerts for changing the controller proxy based on monitoring the cluster environment and policy rules, determining candidate proxies by broadcasting alerts, assessing system health using prediction models, and selecting the best proxy based on health status and policy compliance scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional methods are used for selecting controller proxy in computer cluster environments, then the selection process is simple, but the system health optimization and policy compliance are insufficient
Solution Approach 1:
The system performs preliminary assessments of candidate proxies by evaluating system health status predictions and policy compliance scores before making the final selection. This advance evaluation ensures that the selected controller proxy optimizes system health while meeting policy requirements, resolving the contradiction between reliability improvement and complexity increase by structuring the complexity as a systematic multi-criteria evaluation process
Solution Approach 2:
The invention introduces multiple evaluation parameters (system health status, policy compliance score) to transform the simple selection process into a multi-dimensional assessment. By changing from a single-criterion to multi-criterion selection based on predicted system health and policy compliance, the system achieves better reliability while managing complexity through structured parameter evaluation
2Extent of automation
If automated monitoring and selection mechanisms are implemented, then the intelligence and optimization of controller proxy selection improve, but the system complexity increases
Solution Approach 1:
The system enables automated self-selection of controller proxies by having candidate proxies evaluate themselves against system health predictions and policy compliance criteria. The automated monitoring mechanism triggers selections based on predefined conditions, reducing the need for manual intervention while maintaining manageable complexity through rule-based automation
Solution Approach 2:
The invention implements feedback loops where system health status and policy compliance scores are continuously evaluated and fed back into the selection process. This automated feedback mechanism enables intelligent, adaptive selection of controller proxies while managing complexity through structured feedback evaluation cycles
Data Source
AI summary
An automatic triggering alert for changing a controller proxy in a computer cluster environment can be received, based on monitoring the computer cluster environment and policy rules associated with the computer cluster environment. The triggering alert can be broadcast to a plurality of agents in the computer cluster environment. Candidate proxies among the plurality of agents can be determined. For each of the candidate proxies, a system health status based on a prediction model's forecast and a policy compliance score based on the policy rules can be determined. Based on the system health status and the policy compliance score associated with each of the candidate proxies, a new controller proxy among the candidate proxies can be selected for the computer cluster environment. The new controller proxy can be notified to perform management of the computer cluster environment.