Configuration Partitioning via Policy Manager Blocks
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Solution Overview
Problem
Current configuration partitioning technologies face challenges in optimizing and balancing the distribution of applications among physical servers in data centers, particularly as the scale increases, leading to inefficiencies in management and resource allocation.
Innovation Solution
A system and method for configuration partitioning that includes policy managers, application groups, and blocks, where application groups and blocks are prioritized and assigned to policy managers, with the ability to break blocks into application groups if initial assignment is not possible, ensuring efficient resource allocation based on priority.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of physical servers or applications is increased to improve data center scalability, then the scale and capacity of the data center is improved, but the complexity of managing and distributing configurations among servers increases significantly
Solution Approach 1:
The patent segments configuration management by introducing a hierarchical structure with configuration servers grouped into blocks, which are then assigned to policy managers. This segmentation allows the system to handle large-scale data centers by dividing the monolithic configuration management problem into smaller, manageable units (blocks of configuration servers), thereby improving scalability without proportionally increasing management complexity.
2Productivity
If configuration partitioning is optimized to improve resource allocation efficiency, then productivity is improved, but the difficulty of detecting and measuring optimal partitioning configurations increases
Solution Approach 1:
The patent applies parameter changes by introducing priority levels as a key parameter for configuration server blocks. Policy managers use these priority parameters to make automated decisions about which blocks to process first, transforming the optimization problem from a complex combinatorial search into a more manageable parameter-based allocation process. This allows the system to improve resource allocation efficiency while reducing the difficulty of determining optimal configurations through the use of priority parameters.
Data Source
AI summary
Techniques for optimizing configuration partitioning are disclosed. In one particular exemplary embodiment, the techniques may be realized as a system for configuration partitioning comprising a module for providing one or more policy managers, a module for providing one or more applications, the one or more applications assigned to one or more application groups, a module for associating related application groups with one or more blocks, and a module for assigning each of the one or more blocks to one of the one or more policy managers, wherein if one or more of the one or more blocks cannot be assigned to a policy manager, breaking the one or more blocks into the one or more application groups and assigning the one or more application groups to one of the one or more policy managers.