Event Suppression in Distributed Processing Systems
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Solution Overview
Problem
In distributed processing systems, the overwhelming number of error and status reports makes it difficult for systems administrators to identify meaningful issues due to the sheer volume of data, leading to irrelevant information.
Innovation Solution
Implementing an event and alert analysis module that assigns events to pools, determines an event suppression duration based on specific attributes, and suppresses events during that duration to filter out unnecessary reports, allowing for more concise alerts to be transmitted to administrators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all events are reported to administrators, then complete information is provided, but the volume of data becomes overwhelming and irrelevant
Solution Approach 1:
The patent extracts and suppresses duplicate or redundant events from the event stream before presenting information to administrators. The event suppression mechanism identifies and removes repetitive events that occur within a suppression duration, keeping only the first occurrence or most significant events. This extraction of unnecessary data reduces administrator workload while preserving meaningful information.
Solution Approach 2:
The patent discards redundant events that occur during the suppression duration after the first event of a particular type is processed. By discarding these duplicate events, the system recovers administrator attention and time, allowing them to focus on unique and meaningful events rather than being overwhelmed by repetitive notifications.
2Ease of operation
If event suppression is applied, then relevant events are highlighted, but some information may be lost
Solution Approach 1:
The patent applies preliminary action by establishing event suppression rules and durations before events occur. The system pre-configures which event types should be suppressed and for how long, allowing rapid filtering of redundant events as they occur. This preliminary setup ensures that only meaningful events are processed while maintaining information completeness for unique events.
Solution Approach 2:
The event suppression mechanism is dynamic, adjusting the suppression duration based on event characteristics and system state. The suppression duration can vary depending on the event type and severity, allowing the system to adaptively balance between filtering redundancy and preserving important information. This dynamic approach prevents permanent loss of potentially relevant events.
Data Source
AI summary
Methods, systems, and computer program products for administering event pools for relevant event analysis are provided. Embodiments include assigning, by an incident analyzer, a plurality of events to an events pool; determining, by the incident analyzer, an event suppression duration; determining, by the incident analyzer in dependence upon event analysis rules, to suppress events having particular attributes indicating the events occurred during the event suppression duration; and suppressing, by the incident analyzer, each event assigned to the events pool having the particular attributes indicating the events occurred during the event suppression duration.