A distributed micro-service architecture data center intelligent sensing control system and method

Abstract

The invention relates to a distributed micro-service architecture data center intelligent sensing control system and method. According to the system and the method, a traditional monitoring Web application architecture is improved, a vertical monitoring architecture is changed into a system architecture combining a distributed architecture and a micro-service, the system architecture is independently deployed on professional equipment, a cluster monitoring function is independent from a cluster, and meanwhile, the complexity is simplified by changing offline confirmation and data synchronization operation, functions are converted into online visual processing, and the operation and maintenance difficulty is reduced. Functionally, software and hardware states of a vehicle depot cluster canbe monitored, an opposite-end control center cluster can also be monitored, a fault can be rapidly reported to an uploading platform once the fault occurs, and after the fault is recovered, an operator of the double centers checks the fault, and when it is confirmed that data synchronization operation can be carried out under the current condition, data synchronization operation is triggered manually, so that data consistency among clusters is ensured.

Description

[0001] The present invention relates to an intelligent perception control system and method, belonging to the technical field of big data processing, in particular to an intelligent perception control system and method for a distributed micro-service architecture data center. Background technique [0002] The monitoring of equipment and service status in the subway industry is related to the safety and stability of the entire subway operation, and has high requirements for high reliability, high availability and security of data. [0003] At present, there are the following problems in equipment and service status monitoring: [0004] (1) Deploying monitoring services on a single server is prone to equipment single point failure problems. [0005] (2) The monitoring service is deployed on multiple nodes and multiple servers, which greatly increases the cost and wastes resources. [0006] (3) The monitoring service is deployed in the business cluster, and the server resources ...

AI Technical Summary

Problems solved by technology

[0004] (1) A single server deploys monitoring services, which is prone to equipment single point failure problems

[0005] (2) Multi-node and multiple servers deploy monitoring services, which greatly increases the cost and wastes resources

[0006] (3) The monitoring service is deployed in the business cluster, and the server resources are easily occupied by the main business, which leads to the performance degradation of the monitoring system, and problems such as freezing or even crashing

[0007] (4) The types of failures of equipment and services require human judgment, and are not intelligently combined with operation and maintenance strategies, making operation and maintenance difficult and costly

Such an architecture cannot meet the particularity of high reliability and high availability in the rail transit industry

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