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Micro-service reliability prediction method and prediction device, electronic equipment and storage medium

A prediction method and microservice technology, applied in the field of microservices, can solve problems such as the inability to solve the reliability analysis effectively, and the reliability analysis method unable to accurately analyze the reliability of decentralized microservices.

Inactive Publication Date: 2019-12-06
陕西丝路云启智能科技有限公司
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  • Summary
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The reliability analysis methods of traditional microservices are all aimed at multi-instance deployment applications of monolithic architecture or SOA, but using traditional reliability analysis methods cannot accurately analyze the reliability of decentralized microservices. Under the method, it is impossible to solve the reliability and effective analysis of microservice access in the face of large traffic and high concurrent users

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  • Micro-service reliability prediction method and prediction device, electronic equipment and storage medium
  • Micro-service reliability prediction method and prediction device, electronic equipment and storage medium
  • Micro-service reliability prediction method and prediction device, electronic equipment and storage medium

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Embodiment 1

[0048] See figure 1 , figure 1 It is a schematic flowchart of a microservice reliability prediction method provided by an embodiment of the present invention. The present invention provides a microservice reliability prediction method, which may specifically include:

[0049] Step 1. Obtain the first distributed log data in each microservice;

[0050] Step 2. Obtain the fault type sequence and N faults in the prediction stage according to the first distributed log data;

[0051] Step 3, using the one-step transition probability of the Markov chain to process the fault type sequence to obtain the fault type transition matrix;

[0052] Step 4, obtain the fault type transition probability matrix according to the fault type transition matrix;

[0053] Step 5. Obtain the absolute probability vectors of N faults in the prediction stage according to the fault type transition probability matrix of each microservice.

[0054] Nowadays, more and more software systems adopt the micr...

Embodiment 2

[0063] At present, the reliability analysis methods of traditional software systems are all aimed at multi-instance deployment applications of monolithic architecture or SOA. Traditional reliability analysis methods cannot accurately analyze the reliability of decentralized microservices, and traditional reliability analysis methods cannot solve the problem of effective analysis of reliability in the face of large traffic and high concurrent user access to microservices . Secondly, the business of the micro-service system of the Internet of Things is relatively complex, and the traditional reliability analysis method cannot meet the new problems brought about by the expansion of the micro-service business. In addition, the reliability analysis methods in the prior art all require a large amount of service invocation data, that is to say, the reliability of the service is considered from the perspective of the service user. will have a certain impact.

[0064] Based on the ab...

Embodiment 3

[0110] See Figure 4 , Figure 4 It is a structural schematic diagram of a prediction device provided by an embodiment of the present invention.

[0111] The predictive device, including:

[0112] An acquisition module, configured to acquire the first distributed log data in each microservice;

[0113] A processing module, configured to obtain the fault type sequence and N faults in the prediction stage according to the first distributed log data;

[0114] A transition matrix determination module, configured to process the fault type sequence using a one-step transition probability of a Markov chain to obtain a fault type transition matrix;

[0115] A transition probability matrix determination module, configured to obtain the fault type transition probability matrix according to the fault type transition matrix;

[0116] The prediction module is configured to obtain the absolute probability vectors of N faults in the prediction stage according to the fault type transition...

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Abstract

The invention discloses a micro-service reliability prediction method. The method comprises the steps of obtaining first distributed log data in each micro-service, obtaining a fault type sequence andN faults in a prediction stage according to the first distributed log data, processing the fault type sequence by utilizing a one-step transition probability of a Markov chain to obtain a fault typetransition matrix, obtaining the fault type transition probability matrix according to the fault type transition matrix, and obtaining absolute probability vectors of N faults in the prediction stageaccording to the fault type transition probability matrix of each micro-service. According to the invention, the distributed log data of the micro-service system is used as the input, the fault of each micro-service is classified, and the type transition probability matrix of each micro-service is obtained, so that the reliability of each micro-service is obtained, and the reliability of the combined micro-service is predicted and analyzed by using the reliability of each micro-service.

Description

technical field [0001] The invention belongs to the technical field of microservices, and in particular relates to a microservice reliability prediction method, a prediction device, electronic equipment and a storage medium. Background technique [0002] With the development of the Internet, the amount of information interaction between various business systems is increasing. In order to ensure high availability and high performance, microservice clusters based on microservice architecture design have emerged. In this microservice cluster, a client request may call multiple microservices to finally realize the business. [0003] At present, the technical solutions for reliability prediction and analysis of microservices mainly include: 1. Perform group testing on basic services with the same function, calculate the reliability of web services in real time, and use the idea of ​​majority voting to select basic services to participate in execution. This method requires a web ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/18G06F16/2458G06F16/27G06F17/18
CPCG06F17/18G06F16/1815G06F16/2465G06F16/27
Inventor 程末蒲文斌王博梁忠邓万宇孙严
Owner 陕西丝路云启智能科技有限公司
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