Telemetry Heatmap Matching for Consolidated Infrastructure Alerts
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Solution Overview
Problem
Infrastructure and application monitoring tools generate multiple alerts for the same incident or root cause, leading to inefficiencies as each alert requires individual investigation by system engineers.
Innovation Solution
A computing platform trains an image comparison model using historical telemetry state images to identify matches, consolidating system alerts into a single alert when images match, and sending a unified alert to user devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If monitoring tools generate alerts for each incident, then system reliability is improved, but the quantity of alerts increases leading to engineering inefficiency
Solution Approach 1:
The patent merges multiple alerts into a single consolidated alert by comparing telemetry state images. When images from different alerts match above a threshold, the alerts are combined into one unified alert with aggregated details, reducing the total quantity of alerts while preserving system reliability through comprehensive monitoring coverage.
2Measurement precision
If multiple alerts are generated for the same incident, then measurement precision is improved, but loss of time increases due to repeated investigations
Solution Approach 1:
The patent creates a visual representation (telemetry state image) as a copy of the system state for each alert. These images serve as comparable representations that enable automatic identification of duplicate incidents, allowing engineers to focus only on unique issues and reducing repeated investigation time while maintaining detection precision through the image comparison process.
3Productivity
If alert consolidation is implemented, then productivity is improved, but device complexity increases due to image comparison processing
Solution Approach 1:
The patent replaces manual alert review processes with automated image comparison using machine learning models. The system automatically generates telemetry state images, compares them using trained models, and consolidates alerts without human intervention in the comparison process, improving productivity while managing complexity through automation rather than manual procedures.
Data Source
AI summary
A computing platform may train, using historical telemetry state images, an image comparison model to identify matches between telemetry state images. The computing platform may generate a plurality of system alerts corresponding to a period of time. The computing platform may access telemetry data corresponding to the period of time. The computing platform may generate, based on the telemetry data and for a time corresponding to each of the plurality of system alerts, a telemetry state image. The computing platform may input, into the image comparison model, the telemetry state images to identify whether or not any of the plurality of telemetry state images match. Based on detecting a match, the computing platform may consolidate system alerts corresponding to the matching telemetry state images, which may produce a single system alert and may send, to a user device, the single system alert.