Aggregated Computing Infrastructure Analyzer for Operational Risk
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Solution Overview
Problem
Complex computing infrastructures face challenges in identifying and addressing operational risks due to the complexity of interactions among multiple hardware and software systems, generating large amounts of operational status data that is difficult to analyze effectively.
Innovation Solution
The development of techniques for receiving, authenticating, parsing, and storing operational status data (telemetry data) from aggregated computing infrastructures, creating and retrieving operational risk rules, and evaluating these rules to determine operational risk items and values, enabling the generation of operational risk reports that include risk issue descriptions, prioritizations, severity calculations, and remedial recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple interactive hardware and software systems are integrated into an aggregated computing infrastructure, then the computing infrastructure can provide comprehensive capabilities (storage, networking, software support, data storage), but the complexity of interactions and effects among these systems increases, making operational risk analysis difficult
Solution Approach 1:
The patent segments the complex operational status data into structured formats with defined schemas for different system types (hardware, software, networking). Each system component is analyzed independently according to its specific data structure, then results are aggregated to provide comprehensive risk analysis without being overwhelmed by the overall complexity of interactions.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives operational status data from multiple diverse systems, standardizes the data into common formats, and applies uniform risk analysis rules. This intermediary layer acts as a buffer that manages the complexity of interactions while preserving the comprehensive capabilities of the integrated infrastructure.
2Loss of information
If operational status data is collected from multiple systems within an aggregated computing infrastructure, then more complete operational information is obtained, but the large amounts of data generated make effective analysis difficult
Solution Approach 1:
The patent extracts only the relevant operational status data items needed for risk analysis based on predefined risk rules. Instead of analyzing all collected data, the system identifies and extracts specific data elements that are pertinent to operational risk assessment, reducing the volume of data requiring detailed analysis while maintaining information completeness for risk evaluation.
Solution Approach 2:
The patent transforms operational status data into standardized parameters and metrics that can be uniformly analyzed across different system types. By changing the representation of data from diverse system-specific formats to common operational parameters, the system maintains complete operational information while simplifying the analysis process through parameter standardization.
3Measurement precision
If detailed operational status data is collected and analyzed from all systems, then operational risks can be more accurately identified, but the time and resources required for analysis increase
Solution Approach 1:
The patent performs preliminary structuring and validation of operational status data as it is collected, organizing data into standardized formats and identifying potential risk indicators in advance. This preliminary action reduces the processing burden during detailed analysis, maintaining high accuracy in risk identification while improving overall analysis efficiency by preparing data beforehand.
Solution Approach 2:
The patent implements feedback mechanisms where risk analysis results are used to refine data collection priorities and analysis focus areas. Based on identified risks and patterns, the system adjusts which operational status data items require detailed analysis, maintaining high measurement precision for critical risks while reducing analysis effort for low-risk areas, thereby improving overall productivity.
Data Source
AI summary
Embodiments of the invention provide techniques for receiving, authenticating, parsing, and storing operational status data (or telemetry data) from one or more hardware and software systems within an aggregated computing infrastructure. Operational status data may be transmitted over secure transmission channels and stored within secure data stores at a computing infrastructure analyzer. Additionally, some embodiments describe techniques for creating, storing, and retrieving operational risk rules that may apply to one or more computing infrastructures. Based on the operational risk rules, one or more determinations may be performed to identify data items for extraction from the received telemetry data of an aggregated computing infrastructure. Using the extracted telemetry data items, one or more operational risk rules may be evaluated with respect to the aggregated computing infrastructure. Based on the evaluation of operational risk rules, one or more operational risk items and/or operational risk values may be determined for the aggregated computing infrastructure.