Service application development and service operation and maintenance management system based on machine learning

Abstract

The invention discloses a business application development and business operation and maintenance management system based on machine learning. The system comprises a demand management platform, a machine learning platform, a cloud management platform, a DevOps deliverable tool chain platform, and a monitoring and automatic acquisition and automatic engine platform. Through the DevOps tool chain, automatic deployment of the service application and an automatic acquisition technology of cloud resources and the service application are realized, operation and operation and maintenance data aggregation are realized, various service scenes are simulated by using a machine learning algorithm, automatic healing and stable operation of the service application in various scenes are realized, and the operation efficiency of the service application is improved. Business application development is achieved through the machine learning technology, the cloud technology and a DevOps tool chain are fully used for achieving automatic resource and business application delivery capacity, a machine learning algorithm is explored to simulate various business scenes, and self-healing stable operation of the business operation environment can be achieved.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a machine learning-based business application development and business operation and maintenance management system. Background technique [0002] Both domestically and internationally, the current external environment is that university professional laboratories are actively expanding outwards, using machine learning as a means to actively search for experimental environments, obtain real training cases, and then achieve closer to real effects through continuous training in the laboratory to meet the needs of the real environment. But judging from this trend, it is true that machine learning is a technical force that technology-related institutions and enterprises at all levels are striving to develop, and has great potential to change the future industrial structure. Therefore, technical schools, scientific research institutions, and professional enterprises at home and abroad a...

AI Technical Summary

Problems solved by technology

[0012] High business coupling: business systems are highly coupled, business logic is complex, business delivery is difficult, and maintenance costs are high

[0013] 3. The version is messy:

[0014] Multi-vendor: The system is built by multiple vendors, the code standards are not uniform, and the PaaS platform is not uniform

[0015] Multiple versions of open source software: The baseline of open source software versions of the developer's software platform is inconsistent, security vulnerabilities, configuration optimization, and low product performance controllability

[0016] Inconsistent maintenance: multiple developers lead to large differences in system standards, different maintenance standards, and maintenance cannot be unified and centralized

[0017] 4. Inefficient operation and maintenance:

[0024] Insufficient visualization ability: Under the huge and complex architecture, more powerful visualization ability is needed to show the system architecture and health

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