Cloud Network Object Analysis with Visual Mapping and NLP
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing network management solutions fail to provide efficient, agentless, and non-logging management for large, distributed network systems, especially in multi-layered environments, leading to inefficiencies and incomplete analysis of complex network components and connections.
Innovation Solution
A method and system that collects data on network objects across different layers of a cloud environment, constructs a visual representation using natural language processing, and generates textual insights to analyze relationships and identify potential vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of devices, connections, and networks is employed, then thorough and specific analysis of individual network elements is achieved, but prohibitive outlays of time and effort are required
Solution Approach 1:
The patent creates a virtual copy or representation of the network environment that can be analyzed without manually examining each physical component. This virtual model allows comprehensive analysis to be performed on replicated data structures, achieving thoroughness while reducing time investment.
Solution Approach 2:
The system performs preliminary automated analysis of network elements before manual review is needed. By pre-processing and categorizing network data, the system reduces the time required for subsequent analysis while maintaining thoroughness through multiple analysis passes.
2Measurement precision
If specialized analysis solutions for specific device types or protocols are used, then detailed monitoring of those specific elements is improved, but streamlined monitoring of all network components is lost
Solution Approach 1:
The patent implements a universal analysis platform that can handle multiple device types and protocols through a single interface. The system uses abstracted data models that represent different network elements uniformly, allowing one tool to perform specialized analysis across diverse technologies without requiring separate specialized solutions for each device type.
Solution Approach 2:
The system segments the analysis function into independent, interchangeable modules that can be applied to different device types. Each module handles specific protocols or device categories, but they all interface with a common framework, enabling both specialized precision and streamlined operation through modular design.
3Ease of operation
If protocol-agnostic solutions are employed, then overall traffic management is provided, but device-specific insights are lost and connection specification is required
Solution Approach 1:
The patent applies local quality by providing different levels of analysis detail at different locations in the system. The overall protocol-agnostic view provides broad traffic management, while localized analysis modules provide device-specific insights when needed. The system dynamically adjusts the level of detail based on the specific analysis context and user requirements.
Solution Approach 2:
The system dynamically adjusts between protocol-agnostic and device-specific analysis modes based on operational context. The analysis depth and specificity are not fixed but adapt according to the situation, allowing the system to provide overall traffic management when needed while also delivering detailed device insights when required, without requiring manual specification of connections.
4Reliability
If management agents are deployed in large distributed network systems, then monitoring capability is enhanced, but maintenance requirements and system complexity increase
Solution Approach 1:
The patent extracts the monitoring functionality from dedicated management agents and relocates it to a centralized analysis system. Instead of embedding monitoring code in each network device, the system pulls monitoring data through standardized interfaces and performs analysis externally, reducing the complexity and maintenance burden on individual devices while preserving comprehensive monitoring capability.
Solution Approach 2:
The system enables network devices to provide their own monitoring data through lightweight, self-configuring interfaces without requiring dedicated management agents. Devices automatically expose their state and performance information through standard protocols, allowing the centralized system to collect and analyze data without adding complexity to the monitored devices.
Data Source
AI summary
A method and system for providing textual insights on objects deployed in a cloud environment are provided. The method includes collecting object data on objects deployed in the cloud environment, wherein objects are deployed and operable at different layers of the cloud environment; identifying objects deployed in the cloud environment; constructing a visual representation of the cloud environment, including the identified objects and their relationships; and generating textual insights on the identified objects and their relationships using natural language processing.