AIOps intelligent operation and maintenance system based on artificial intelligence technology

Abstract

The invention provides an AIOps intelligent operation and maintenance system based on an artificial intelligence technology. The AIOps intelligent operation and maintenance system comprises an AIOps intelligent operation and maintenance center system, a data middle station system, an AI middle station system, a technology middle station system, a service middle station system and a service application system. The intelligent operation and maintenance center system additionally comprises a system health degree scoring module, a root cause analysis module, a fault prediction module, a capacity evaluation module and an intelligent alarm convergence and noise reduction module. Monitoring operation and maintenance of'one center and four middle stations' and five-layer architecture are switched on, log, monitoring, performance and other data related to operation and maintenance are collected in various forms, operation and maintenance interfaces of a front stage, a middle stage and a back stage are switched on, and centralized management of operation and maintenance of a unified portal is achieved; tenant mode docking capability with group unified AI is reasonably constructed, an AI model and algorithm are reasonably introduced, computing resources are combined with local operation and maintenance data, an AIOps scene model and a centralized AI platform are carried out to complete training framework and standard compatibility, and sharing and multiplexing of model services are achieved.

Description

technical field [0001] The present invention relates to the technical field of operation and maintenance management, in particular to an AIOps intelligent operation and maintenance system based on artificial intelligence technology. Background technique [0002] AIOps (Artificial Intelligence for IT Operations), that is, intelligent operation and maintenance, combines the capabilities of artificial intelligence with operation and maintenance, and improves the efficiency of operation and maintenance through machine learning. [0003] In the traditional automated operation and maintenance system, the labor cost and efficiency problems of repetitive operation and maintenance work have been effectively resolved. However, in the process of troubleshooting, change management, capacity management, and service resources in complex scenarios, people still need to control the decision-making process, which hinders the further improvement of operation and maintenance efficiency. The i...

AI Technical Summary

Problems solved by technology

[0005] The current operation and maintenance system mainly has the following problems: 1. Fault location needs to be optimized: after cloud computing and PAAS containerization are launched, the operation and maintenance environment becomes more and more complex, and it becomes more and more difficult to locate faults. , Locating faults consumes a lot of time, and even exceeds the time spent on troubleshooting; 2. Intelligent O&M needs to be optimized: Intelligent O&M is not applied enough in actual O&M, and most O&M scenarios are still solved manually and by experience. Promote effective landing plans for each operation and maintenance scenario; 3: The operation and maintenance scenario needs to be adapted: the on-site operation and maintenance scenario is complex, and the data sources are diverse. The current AI model is poorly adaptable to the on-site operation and maintenance scenario. Poor situation; 4: Unable to conduct cross-domain centralized analysis and operation and maintenance: unable to analyze cross-domain, cross-platform, cross-application business and call chain; unable to realize health monitoring of cross-domain, cross-platform, cross-application asset resources; monitoring Scattered tools, scattered operation and maintenance tools, scattered monitoring indicators, monitoring data has not fully exploited its value, and monitoring and operation and maintenance operations are not linked; no PASS dual-state operation and maintenance: currently it is still intelligent operation and maintenance of traditional applications, and it is connecting with PASS operation and maintenance management , monitoring and operation and maintenance collaborative operation; cross-domain, cross-platform monitoring, health detection, and alarm aggregation cannot be realized

Intelligent operation and maintenance capabilities such as data collection, data analysis, and AI operation and maintenance scenarios without AIOps to drive precise and refined operation and maintenance of various domains and platforms

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