Network Alert System Using Natural Language Parsing
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Solution Overview
Problem
Conventional computing environments face difficulties in creating customized alerts and monitoring network performance due to limitations in programming languages and the number of concurrently running network monitoring processes, which are inadequate for growing data networks.
Innovation Solution
A system and method for generating alerts in a computing environment that allows users to define alert conditions and actions, with a processor configured to monitor network data according to a predetermined schedule and generate alerts upon detecting specific conditions, using a processor-readable medium with instructions for implementing this method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users create custom alerts using conventional methods, then alert customization is possible, but the process is complex and limited by predetermined formats and programming language restrictions
Solution Approach 1:
The system changes the parameter of alert definition from requiring programming knowledge and predetermined formats to using natural language input. Users can define alert conditions by simply typing what they want to monitor, and the system automatically parses and configures the alert parameters, eliminating the need for JSON formatting or DSL knowledge.
Solution Approach 2:
The system introduces an intermediary natural language processing layer between the user and the alert configuration system. This intermediary automatically translates user-friendly natural language inputs into the internal alert configuration format, shielding users from the complexity of traditional alert creation methods while maintaining full customization capability.
2Reliability
If the system limits the number of concurrently running network monitoring processes, then system stability is maintained, but the ability to support growing data networks and monitor multiple alert conditions is inadequate
Solution Approach 1:
The system merges multiple alert condition evaluations into a single unified monitoring process. Instead of running separate monitoring processes for each alert condition, the system consolidates them into one process that can evaluate multiple conditions simultaneously, thereby increasing monitoring capacity without proportionally increasing process count and maintaining system stability.
Solution Approach 2:
The monitoring process is designed to be universal and multi-functional, capable of handling various types of alert conditions within a single process. This allows the system to support growing data networks and multiple alert conditions without requiring dedicated processes for each condition, thus improving productivity while maintaining reliability.
3Ease of manufacture
If the system uses predetermined alert formats and limited programming languages, then implementation is simpler, but the ability to detect complex conditions and perform sophisticated actions is restricted
Solution Approach 1:
The system enables self-service where the natural language input itself carries the complexity information. Users describe complex conditions in natural language, and the system automatically parses and configures the appropriate detection logic, eliminating the need for predetermined format constraints while maintaining ease of use. The system serves itself by automatically generating the configuration from user-friendly input.
Data Source
AI summary
Provided are systems and methods for generating alerts in a computing environment. An example method may commence with receiving parameters associated with an alert. The parameters may include at least an alert condition and an action to be performed based on the alert condition. The method may further include monitoring at least a portion of a network data according to a predetermined schedule based on the parameters. The method may further include generating the alert upon detection of the alert condition.


