Alarm Deployment for Long-Tail Indicators via Aggregation
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Solution Overview
Problem
Conventional monitoring platforms face challenges in accurately and comprehensively identifying crucial risk points due to excessive resource consumption and noise from large-scale indicator sets, particularly with long-tail indicators that generate low-frequency traffic, making it difficult to monitor and alarm effectively.
Innovation Solution
The method involves distinguishing between non-long-tail and long-tail indicators, scheduling tasks with different time intervals for each, using a shorter interval for non-long-tail indicators and a longer interval for long-tail indicators to perform aggregation processing and alarm calculations, thereby optimizing resource use and reducing monitoring costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional monitoring platforms use the same data collection and alarm notification process for all indicators, then the monitoring process is simple and unified, but storage and calculation resources consumed are huge and alarm noise is loud
Solution Approach 1:
The patent segments indicators into long-tail indicators and non-long-tail indicators based on traffic characteristics. Different monitoring strategies are applied to each segment: aggregation processing with longer time intervals for long-tail indicators, and direct monitoring with shorter time intervals for non-long-tail indicators. This segmentation resolves the contradiction by avoiding uniform processing of all indicators, thereby reducing overall resource consumption while maintaining monitoring effectiveness.
2Adaptability or versatility
If conventional monitoring platforms use the same process for all indicators, then the alarm notification is comprehensive, but alarm noise is loud and it is difficult to accurately hit crucial risk points
Solution Approach 1:
The patent applies local quality by customizing monitoring and alarm strategies according to the specific characteristics of different indicator groups. Long-tail indicators receive aggregation processing with longer time intervals, while non-long-tail indicators receive direct monitoring with shorter time intervals. This localized differentiation reduces alarm noise for less critical indicators while maintaining high detection accuracy for crucial risk points, thereby improving overall measurement precision.
3Use of energy by moving object
If longer time interval is used for aggregation processing of long-tail indicators, then resource consumption is reduced, but monitoring responsiveness may be delayed
Solution Approach 1:
The patent implements dynamics by adapting time intervals based on indicator characteristics. Long-tail indicators use longer time intervals for aggregation processing to reduce resource consumption, while non-long-tail indicators use shorter time intervals to maintain responsiveness. The system dynamically adjusts monitoring strategies based on traffic patterns and indicator importance, resolving the contradiction between resource consumption and monitoring responsiveness through flexible, context-aware time interval selection.
Data Source
AI summary
Embodiments of this specification disclose large-scale alarm deployment computer-implemented methods, systems, apparatuses, devices, and computer-readable media. In an example, whether an indicator in a large-scale indicator set is a non-long-tail indicator or a long-tail indicator is determined. For the non-long-tail indicator, a first task is scheduled for traffic data of the non-long-tail indicator by using a first time interval, and alarm calculation is performed by executing the first task. For the long-tail indicator, aggregation processing is performed on traffic data of the long-tail indicator, a second task is scheduled for correspondingly obtained aggregated data by using a second time interval longer than the first time interval, and alarm calculation is performed by executing the second task.