Data processing method, device and equipment

Abstract

The embodiment of the invention provides a data processing method, device and equipment, and the method comprises the steps: obtaining the basic data information and service call link routing data ofa to-be-processed application, and enabling the to-be-processed application to comprise one or more application containers; establishing a simulation model according to the basic data information, wherein the simulation model comprises a plurality of node models corresponding to the application containers; and processing the to-be-processed application according to the simulation model and the service call link routing data. The simulation model is established through the basic data information; the application is processed by utilizing the simulation model and the service call link routing data, large-scale simulation disaster tolerance exercise is carried out on the application under the condition of consuming extremely few resources, the effectiveness is high, the cost of the simulationexercise is low, the simulation disaster tolerance exercise can be carried out at a higher frequency, the stability of online services is ensured, and thus the accuracy and reliability of processingthe application by the simulation model are improved.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a data processing method, device and equipment. Background technique [0002] At present, to solve the availability verification of large-scale distributed application clusters in failure scenarios, disaster recovery drills are usually carried out according to expected plans, and the scope of drills, drill time, recovery plans, etc. are determined in advance, and online drills are performed within expectations. However, although the above-mentioned disaster recovery drill is expected and planned, because of the uncertainty of the performance of online applications in failure scenarios, it usually has an inevitable impact on the business, which is likely to cause business damage; in addition, during the drill During the implementation process, the developers of key applications need to be on duty on site, and the labor cost is high. In addition, it is impossible to pe...

AI Technical Summary

Problems solved by technology

However, although the above-mentioned disaster recovery drill is expected and planned, because of the uncertainty of the performance of online applications in failure scenarios, it usually has an inevitable impact on the business, which is likely to cause business damage; in addition, during the drill During the implementation process, the developers of key applications need to be on duty on site, and the labor cost is high. In addition, it is impossible to perform frequent fault drills on the real line, so it is difficult to accurately evaluate the disaster recovery capability of the online cluster. Thus reducing the real-time and accuracy of usability verification

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