Abstract System Model for Cloud Infrastructure Incident Detection
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Solution Overview
Problem
Existing methods for monitoring and managing IT system infrastructure rely heavily on manual analysis of system logs, which is time-consuming and inefficient, especially in distributed cloud environments where rapid incident detection is critical.
Innovation Solution
A system and method for modeling deployed system infrastructure in a cloud computing environment, involving the generation of an abstract system model with selectors indicating associated infrastructure elements, building an inventory of these elements, and creating a bound system model to output data on infrastructure status or incidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of system logs is used, then detailed diagnostic information can be obtained, but the time required for incident detection and troubleshooting increases
Solution Approach 1:
The patent segments the monolithic log analysis process into multiple specialized components: log collection agents distributed across infrastructure elements, a centralized log management platform, pattern matching engines, correlation analysis modules, and alerting systems. Each component handles specific aspects of log processing, enabling parallel operation and reducing overall analysis time while maintaining comprehensive diagnostic capability
Solution Approach 2:
The patent introduces an intermediary log management platform that sits between the infrastructure elements and analysts. This platform automatically collects, normalizes, stores, and pre-processes logs from multiple sources, applying pattern matching and correlation rules to identify issues before they reach analysts. The intermediary handles routine analysis tasks, freeing analysts to focus on complex diagnostic problems
2Productivity
If automated log analysis tools are used, then incident detection speed improves, but the ability to handle complex troubleshooting scenarios decreases
Solution Approach 1:
The patent implements local quality by providing different analysis capabilities at different levels: automated pattern matching and alerting for routine issues, semi-automated correlation analysis for moderate complexity problems, and manual expert analysis for complex scenarios. Each level is optimized for its specific purpose, with the system automatically routing log analysis tasks to the appropriate level based on complexity and severity
Solution Approach 2:
The patent creates a dynamic analysis system that adapts its approach based on the situation. The log management platform continuously learns from historical data, adjusting pattern matching sensitivity, correlation rules, and alert thresholds. Analysts can dynamically configure analysis parameters and switch between automated and manual modes as troubleshooting evolves, allowing the system to flexibly respond to varying incident complexities
3Loss of information
If comprehensive monitoring of all infrastructure components is implemented, then system visibility improves, but the complexity of managing and analyzing data increases
Solution Approach 1:
The patent extracts and separates different aspects of monitoring data into distinct functional modules: log collection, normalization, storage, pattern matching, correlation analysis, and alerting. Each module handles a specific aspect of data processing, reducing the complexity of managing comprehensive monitoring by breaking it into manageable, independently configurable components
Solution Approach 2:
The patent implements universality through a standardized log management platform that handles multiple types of infrastructure components (servers, databases, network devices, cloud services) using common protocols and data formats. The platform provides unified collection, storage, and analysis capabilities that work across diverse technologies, reducing complexity by applying the same framework to varied monitoring needs
Data Source
AI summary
An abstract system model comprising one or more model elements corresponding to one or more infrastructure elements of a deployed system infrastructure is generated. Each model element specifies one or more selectors, and for each model element, each selector includes an indication of at least one infrastructure element that is associated with the model element. An inventory of the one or more infrastructure elements is built. For at least one model element, at least one infrastructure element of the inventory associated with the at least one model element is identified as indicated by the respective one or more selectors of the at least one model element. A bound system model comprising one or more associations between the model elements of the abstract system model and the inventory of the infrastructure elements is generated.