Compatibility Analysis Engine for Server Consolidation
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Solution Overview
Problem
Large organizations face challenges in managing distributed computing systems due to underutilization and redundancy of servers, leading to increased costs and maintenance burdens, as well as difficulties in achieving system consolidation due to their heterogeneous nature.
Innovation Solution
A method and computer program for determining compatibility between multiple computer systems by generating configuration and workload compatibility scores, using an analysis engine to evaluate configuration and workload data, and a client for displaying compatibility scores in a graphical interface, facilitating server consolidation and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed systems are used to handle large amounts of data, then processing capacity and efficiency are improved, but system complexity and difficulty of management increase
Solution Approach 1:
The patent introduces a compatibility analysis system as an intermediary tool that automatically evaluates and scores potential target systems for consolidation. This mediator analyzes configuration data, workload characteristics, and hardware specifications to generate compatibility scores, thereby simplifying the complex decision-making process in distributed system management without reducing the actual processing capacity.
2Productivity
If server hardware is added to increase processing capacity, then productivity is improved, but cost and maintenance burden increase
Solution Approach 1:
The patent applies preliminary action by performing compatibility analysis before consolidation decisions are made. The system pre-evaluates potential target systems by analyzing their configuration data, workload capacity, and hardware specifications, generating compatibility scores that predict successful consolidation outcomes. This preliminary assessment prevents unnecessary hardware additions by identifying existing systems that can absorb additional workloads.
Solution Approach 2:
The patent changes parameters by transforming qualitative assessments of system compatibility into quantitative compatibility scores. By analyzing multiple parameters (configuration match, workload capacity, hardware specifications) and synthesizing them into numerical scores, the system enables objective comparison and decision-making, thereby optimizing hardware utilization without simply adding more servers.
3Reliability
If multiple servers are maintained to ensure system availability, then reliability is improved, but operational cost and maintenance effort increase
Solution Approach 1:
The compatibility analysis system serves as an intermediary that objectively evaluates whether consolidating servers will maintain or improve system availability. By analyzing workload patterns, capacity headroom, and configuration compatibility, the tool provides data-driven recommendations that balance reliability requirements with maintenance simplification, eliminating the need for manual assessment of multiple redundant servers.
4Productivity
If heterogeneous systems are consolidated to reduce costs, then resource utilization is improved, but compatibility assessment difficulty increases
Solution Approach 1:
The patent directly addresses heterogeneous system consolidation by transforming the difficulty of compatibility assessment into a structured parameter-based evaluation. The system collects configuration data, workload metrics, and hardware specifications, then converts these diverse parameters into standardized compatibility scores. This approach enables objective comparison across different server platforms, operating systems, and configurations, making heterogeneous consolidation feasible and measurable.
Data Source
AI summary
Systems and method for performing a consolidation analysis and visually representing the analysis are provided. The analysis is conducted by performing an audit, performing system compatibility and workload compatibility analyses using the audit data and rule sets. The results of the individual analyses are combined to create an overall compatibility co-habitation analysis and visual consolidation roadmap including scorecard information. The system and workload analyses may be performed to contribute to the overall co-habitation analyses, but also performed on their own.