Distributed System Module State Monitoring via Key-Code Data Aggregation
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Solution Overview
Problem
The increasing scale of distributed systems leads to a growing storage cost due to the accumulation of calling data, necessitating an efficient method to reduce storage space and costs while monitoring the running state of each module.
Innovation Solution
A method is introduced where a first calling key-value pair sent by a module in a distributed system is obtained, including a key code value and a keyword value. The key code value uniquely represents a calling associated with the module, and the keyword value represents total calling data. This data is used to determine the current running state of the module based on historical data stored in a preset database, allowing for aggregation and reduced storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calling data is stored in detail to monitor module running state, then monitoring precision is improved, but storage space increases
Solution Approach 1:
The patent extracts only the necessary calling data fields (calling key, module name, calling method, parameters, return value, time cost) from the complete request-response data stream. By selectively capturing only these essential fields rather than storing entire request-response pairs, the system achieves sufficient monitoring precision while significantly reducing storage requirements
Solution Approach 2:
The patent transforms the storage approach by changing from storing complete data structures to storing aggregated statistical parameters. The system accumulates calling frequency, total time cost, and average time cost for each calling relationship, converting detailed temporal data into condensed parameter representations that maintain monitoring effectiveness while reducing storage volume
2Measurement precision
If detailed calling data is accumulated to analyze module performance, then measurement accuracy is improved, but storage cost increases
Solution Approach 1:
The patent merges multiple individual calling records into aggregated statistical data for each calling relationship. Instead of storing and analyzing every single call event separately, the system combines them into summary statistics (calling frequency, total time cost, average time cost), achieving the same analytical capability with significantly reduced data volume and storage cost
Solution Approach 2:
The patent changes the data representation from detailed transactional records to aggregated parameters. By transforming individual calling events into statistical summaries, the system maintains measurement accuracy for performance analysis while reducing the quantity of data that needs to be stored and managed
Data Source
AI summary
A method for monitoring a running state of a distributed system, an electronic device, and a storage medium are provided. The method comprises: acquiring a first calling key-value pair sent by a first component in a distributed system (101); and determining the current running state of the first component according to a first keyword value, and historical calling data corresponding to a first key code value in a preset database (102).