Host Operational State Classification via Telemetry Clustering
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Solution Overview
Problem
Automating the analysis and identification of operational states of complex information technology equipment and infrastructure is complicated by the vast amount of telemetry data, requiring efficient methods for classification and reactive actions.
Innovation Solution
A method and system for multivariate profile-based host operational state classification, involving the generation of non-geometric shapes from host device telemetry, mapping them onto a feature space, and assigning them to clusters representing target operational states, with reactive actions invoked based on identified states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional telemetry analysis methods are used, then comprehensive data collection is achieved, but analysis complexity and processing time increase significantly
Solution Approach 1:
The patent segments the complex operational state classification problem into distinct phases: telemetry data collection, feature extraction, clustering analysis, and reactive action invocation. By dividing the analysis into manageable components with specialized processing for each stage, the system reduces overall complexity while maintaining comprehensive data analysis capabilities
Solution Approach 2:
The patent introduces intermediate representations including telemetry abstract data types (ADTs), feature vectors, and cluster prototypes as mediators between raw telemetry data and operational state classifications. These intermediaries simplify the transformation process and enable more efficient processing at each stage of the analysis pipeline
2Measurement precision
If comprehensive telemetry data is collected and analyzed, then operational state classification accuracy improves, but processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-defining operational state prototypes and cluster representations before actual telemetry analysis. During runtime, incoming telemetry data is quickly matched against these pre-computed prototypes using efficient distance metrics, significantly reducing processing time while maintaining high classification accuracy
Solution Approach 2:
The patent transforms raw telemetry parameters into standardized feature vectors with consistent scaling and normalization. This parameter transformation enables the use of efficient clustering algorithms and distance-based matching, reducing computational complexity and processing time while preserving the discriminatory power of the original telemetry data
3Ease of operation
If manual operational state analysis is performed, then detailed examination is possible, but automation level remains low
Solution Approach 1:
The patent implements self-service automation where the system automatically collects telemetry data, extracts features, performs clustering analysis, identifies operational states, and invokes reactive actions without human intervention. The automated pipeline processes telemetry streams in real-time, enabling full automation while maintaining the analytical depth previously requiring manual examination
Solution Approach 2:
The patent incorporates feedback mechanisms where cluster prototypes are continuously refined based on incoming telemetry data and identified operational states. This feedback loop enables the system to automatically adapt and improve its classification accuracy over time, enhancing ease of operation while maintaining high levels of automation
Data Source
AI summary
A method and system for multivariate profile-based host operational state classification. Specifically, the disclosed method and system entail the generation of non-geometric shapes derived from operational state inferring features reflective of at least a portion of host device telemetry aggregated for host devices. The non-geometric shapes may subsequently be mapped onto a high-dimensional feature space and, thereafter, assigned into clusters representative of given target operational states that may be exhibited by the host devices. Based on identified operational states, assigned to the non-geometric shapes, reactive actions may be invoked to address or rectify operations and/or configurations on the host devices.