Graph-Based Infrastructure Model for Virtualization Complexity
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Solution Overview
Problem
The management of virtualized computer infrastructures is complicated by the rapid growth of cloud and virtualization technologies, leading to complexities in delivering guaranteed service levels, performance, and security due to dynamic environments and increased object relationships, making it difficult for administrators to understand workload behavior and its effects on infrastructure.
Innovation Solution
A method and apparatus using graph theory and clustering analysis to model hierarchies, relationships, and groups of objects within a computer infrastructure, allowing administrators to ask questions about the environment, perform root cause analysis, and manage resources effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtualization and cloud infrastructure resources are deployed to increase flexibility and scalability, then adaptability and productivity are improved, but device complexity and difficulty of detecting and measuring increase
Solution Approach 1:
The patent segments the complex virtualized infrastructure into distinct layers (physical infrastructure layer, virtualization layer, and workload layer) and models relationships within each layer separately using graph theory. This segmentation allows administrators to manage complexity by focusing on individual layers while understanding their interconnections, resolving the contradiction between maintaining flexibility and reducing management complexity.
Solution Approach 2:
The patent introduces an intermediary analysis system that uses graph theory models and statistical classification to mediate between the complex virtualized infrastructure and human administrators. This intermediary automatically correlates events, identifies relationships, and provides insights, reducing the complexity burden on administrators while preserving the full capabilities of the virtualized environment.
2Adaptability or versatility
If the number of objects and their relationships increase in dynamic environments, then adaptability is improved, but difficulty of detecting and measuring and loss of information increase
Solution Approach 1:
The patent performs preliminary actions by proactively modeling the infrastructure topology and relationships before events occur. The graph theory framework pre-establishes the structure of objects and their relationships, enabling the system to quickly detect and measure changes when events happen, rather than attempting to understand complex relationships in real-time during incidents.
Solution Approach 2:
The patent implements feedback mechanisms through statistical classification that continuously analyzes events and provides insights about workload behavior and infrastructure relationships. This feedback loop helps administrators understand the dynamic environment by translating complex object interactions into meaningful patterns and correlations, reducing the difficulty of detection and measurement.
3Ease of operation
If conventional flat structure systems are used for simplicity, then ease of operation is improved, but adaptability and measurement precision deteriorate
Solution Approach 1:
The patent transitions from a conventional flat structure to a multi-dimensional graph-based model that adds layers of abstraction and relationship depth. Instead of simple flat listings, the system creates dimensional representations of infrastructure objects with multiple attributes and relationship types, enabling precise measurement and understanding of complex relationships while maintaining operational simplicity through automated analysis tools.
Data Source
AI summary
Embodiments of the innovation relate to a method and apparatus for utilizing graph theory and clustering analysis to build relationships among applications and corresponding and/or dependent virtualization, cloud and datacenter infrastructure components and to derive the definition of application boundaries and corresponding infrastructure components. This allows a system administrator to manage and address complex issues within a computer infrastructure, such as availability, service level deliverable/guarantees, performance, and resource optimization.