Cloud Alert Transformation for Consistent, Enriched Monitoring
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Solution Overview
Problem
Cloud computing environments face challenges due to the lack of consistency in alert formats and syntax across different alert generation systems, leading to user confusion, misdiagnosis of issues, and overwhelming repetitive alerts that desensitize users to critical problems.
Innovation Solution
An advanced signal processing module transforms alerts into a consistent format with enriched data, suppressing repetitive alerts and providing detailed information for efficient monitoring and remediation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple different alert generation systems are used to monitor different aspects of cloud computing environment, then monitoring coverage is improved, but alert format consistency deteriorates
Solution Approach 1:
The patent introduces an intermediary component that receives alerts from multiple different alert generation systems and transforms them into a unified format. This intermediary layer maintains compatibility with various source systems while ensuring consistent output format, thereby resolving the contradiction between monitoring coverage and format consistency.
Solution Approach 2:
The patent creates a universal alert processing system that can handle alerts from diverse sources through a single standardized interface. This multi-functional system performs format transformation, enrichment, and routing operations that work across all alert types and sources, achieving both broad monitoring coverage and uniform alert formatting.
2Measurement precision
If alert thresholds are set to be sensitive to detect all issues, then detection precision is improved, but alert repetition increases
Solution Approach 1:
The patent implements preliminary actions by pre-configuring alert suppression rules and grouping logic before alerts are generated. When alerts are received, the system checks against pre-established patterns and suppresses repetitive alerts proactively, preventing alert storms while maintaining sensitive detection through initial configuration rather than reactive filtering.
Solution Approach 2:
The patent employs feedback mechanisms where the system learns from alert patterns and adjusts suppression behavior dynamically. By analyzing the characteristics of generated alerts and their frequency, the system provides feedback to optimize threshold settings and suppression rules, maintaining high detection precision while reducing repetitive alerting through adaptive control.
3Loss of information
If detailed information is included in all alerts, then information completeness is improved, but user cognitive load increases
Solution Approach 1:
The patent applies local quality by providing different levels of information detail in different parts of the alert system. Critical alerts receive comprehensive detailed information while less critical alerts use summarized formats. The system locally adapts the information density based on alert severity, type, and context, ensuring completeness where needed while reducing cognitive load in other areas.
Solution Approach 2:
The patent segments alert information into hierarchical layers: essential summary information presented first, followed by optional detailed sections that can be expanded on demand. This segmentation allows users to quickly grasp critical information without being overwhelmed by complete details, reducing cognitive load while preserving information completeness for those who need it.
Data Source
AI summary
Techniques are provided for managing and transforming alerts generated for cloud computing environments. An alert corresponding to a predefined service name is identified. The alert is transformed with enriched data and into a particular format/syntax such that all generated transformed alerts are consistent in terms of format/syntax. The transformed alert is compared to other existing alerts to determine if the transformed alert is new or repetitive. If the transformed alert is new and does not correspond to a paused event, the transformed alert is published. If the transformed alert is repetitive or corresponds to a paused event, the transformed alert is prevented from being published. The enriched data of the transformed alert can include cloud application specific information and other cloud environment specific information not included in the original alert. The enriched data can be used to more effectively monitor/remediate cloud environment issues.