Modularized architecture-based resident intelligent operation and maintenance management platform system and method

Abstract

The invention discloses a settled intelligent operation and maintenance management platform system and a settled intelligent operation and maintenance management method based on a modular architecture. The system comprises six core modules, namely a configuration deployment management module, a unified data acquisition and monitoring module, a visual container arrangement management module, a mirror image full life cycle management module, an intelligent analysis and alarm center module and a platform core API gateway module. According to the method, one-key flexible deployment of the operation and maintenance tool stack is realized through configuration deployment; data islands are broken through unified data acquisition; the Kubernetes management is simplified through the visual operation; the security is improved by integrating a mirror image warehouse and security scanning; and intelligent analysis and active alarm are realized by fusing machine learning and a natural language processing technology. According to the method, the problems of complex deployment, data splitting, tedious operation and low intelligent degree of a traditional operation and maintenance scheme are effectively solved, and automation, standardization and intelligence of operation and maintenance management are realized.

Description

A modular architecture-based on-premises intelligent operation and maintenance management platform system and method Technical Field

[0001] This invention belongs to the field of computer technology, specifically referring to an onboard intelligent operation and maintenance management platform system and method based on a modular architecture. Background Technology

[0002] As enterprises deepen their digital transformation, microservices and containerization technologies have become mainstream application deployment methods. To ensure the stability of complex IT environments, enterprises typically need to deploy various independent operation and maintenance tools, such as monitoring, logging, and deployment tools.

[0003] Existing technical solutions have significant drawbacks: First, deployment and configuration are complex and lack flexibility. Different business scenarios require different tool combinations, and existing solutions cannot achieve one-click dynamic deployment of specific operation and maintenance tool stacks. Second, the monitoring system is fragmented, with data generated by various tools being disconnected, making global correlation analysis and fault localization difficult. Third, the management of container clusters such as Kubernetes heavily relies on complex command-line operations, which are difficult to learn, error-prone, and difficult to standardize. Furthermore, traditional operation and maintenance tools have low levels of intelligence, mainly relying on threshold alerts, unable to predict potential risks, and unable to automatically analyze error patterns in application logs, leaving operation and maintenance teams constantly engaged in reactive firefighting. Finally, container image assets lack unified security scanning and lifecycle management, posing a risk of security vulnerability proliferation.

[0004] Therefore, there is an urgent need in this field for a highly integrated platform that can unify operation and maintenance data, automate operation and maintenance operations, and achieve intelligent early warning. Summary of the Invention

[0005] The technical problem to be solved by this invention is to provide an onboard intelligent operation and maintenance management platform system and method based on a modular architecture, so as to realize unified, automated and intelligent operation and maintenance management of heterogeneous IT resources, reduce operation and maintenance complexity, and improve operation and maintenance efficiency and system reliability.

[0006] The present invention is implemented as follows: Firstly, the present invention provides an onboard intelligent operation and maintenance management platform system based on a modular architecture, comprising: a configurable deployment management module, used to receive user selections of predefined functional component packages through a graphical interface, generate a deployment list, and perform one-click deployment of an operation and maintenance tool stack in the target environment based on the list; a unified data collection and monitoring engine, used to non-intrusively collect basic indicators, application performance indicators, and business logs through plug-in collectors, and store them in a unified central database; a visual container orchestration management module, used to provide a web management console for Kubernetes clusters, and perform container workload upgrades, scaling, and log viewing operations through a graphical interface; an image lifecycle management module, integrating a private image repository, used to support image push, security scanning, and version management; an intelligent analysis and alarm center, used to perform multi-dimensional threshold alarms, machine learning-based indicator anomaly detection, and natural language processing-based log pattern recognition based on the data collected by the unified data collection and monitoring engine; and a platform core API gateway, serving as the unified system entry point, responsible for identity authentication, request routing, and providing external interfaces.

[0007] Furthermore, the predefined functional component packages in the configurable deployment management module include basic monitoring, end-to-end monitoring, or security compliance component packages.

[0008] Furthermore, the unified data acquisition and monitoring engine deploys the collector on the Kubernetes cluster nodes using the DaemonSet method.

[0009] Furthermore, the intelligent analysis and alarm center is also used to calculate a comprehensive health score for services or servers.

[0010] Furthermore, the log viewing function of the visual container orchestration management module supports log retrieval and filtering by Pod or container instance, and highlights error and warning messages.

[0011] Secondly, this invention provides an onboard intelligent operation and maintenance management method based on a modular architecture. Based on the onboard intelligent operation and maintenance management platform system based on a modular architecture described in the first aspect, the method includes the following steps: S1: Receiving user graphical selections through a configuration-based deployment management module, generating a deployment list, and executing one-click deployment of the operation and maintenance tool stack; S2: Collecting various operation and maintenance data from managed nodes and storing them in a unified central database through a unified data collection and monitoring engine; S3: Providing a web interface through a visual container orchestration management module to support graphical operation and log viewing of Kubernetes workloads; S4: Performing security scanning and version management on images through an image lifecycle management module; S5: Performing threshold judgment, anomaly detection, and log pattern recognition on the collected data through an intelligent analysis and alarm center, and triggering alarms.

[0012] Furthermore, the one-click deployment of the operation and maintenance tool stack described in step S1 is completed on the target Kubernetes cluster using the Helm tool.

[0013] Furthermore, the log pattern recognition described in step S5 involves using natural language processing technology to perform cluster analysis on application logs to identify error patterns.

[0014] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the modular architecture-based on-premises intelligent operation and maintenance management method as described in the second aspect.

[0015] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of an on-premises intelligent operation and maintenance management method based on a modular architecture as described in the second aspect.

[0016] The advantages of this invention are: 1. High integration and simplification: By integrating the scattered operation and maintenance tools through the configurable deployment management module, one-click deployment can be achieved "out of the box", which greatly reduces the deployment complexity and the threshold for use.

[0017] 2. Unified Operation and Maintenance Data: The unified data acquisition and monitoring engine breaks down data silos, providing a solid data foundation for global situational awareness and root cause analysis.

[0018] 3. Automated and standardized operation and maintenance: The visual container orchestration and management module encapsulates complex Kubernetes command-line operations into simple graphical operations, reducing human error and improving efficiency and standardization.

[0019] 4. Intelligent and proactive operation and maintenance mode: The intelligent analysis and alarm center has realized the transformation from passive alarm to proactive prediction and from manual log investigation to automatic error pattern recognition through machine learning and natural language processing technology, which significantly improves the efficiency of fault handling.

[0020] 5. Enhanced system security and reliability: The image lifecycle management module reduces security risks through integrated security scanning; unified health monitoring and rapid scaling capabilities ensure high availability of services. Attached Figure Description

[0021] The present invention will now be further described with reference to the accompanying drawings and embodiments.

[0022] Figure 1 is a system architecture diagram of the present invention.

[0023] Figure 2 is a business process diagram of the present invention. Detailed Implementation

[0024] Example 1

[0025] Referring to Figure 1, an onboard intelligent operation and maintenance management platform system based on a modular architecture includes: a configuration-based deployment management module, used to receive user selections of predefined functional component packages through a graphical interface, generate a deployment list, and perform one-click deployment of the operation and maintenance tool stack in the target environment based on the list; wherein the predefined functional component packages include basic monitoring, full-link monitoring, or security compliance component packages; a unified data collection and monitoring engine, used to non-intrusively collect basic indicators, application performance indicators, and business logs through plug-in collectors and store them in a unified central database; the unified data collection and monitoring engine deploys collectors on Kubernetes cluster nodes via DaemonSet; and a visual container orchestration management module, used to provide Kubernetes... The Elasticsearch cluster's web management console provides a graphical interface for upgrading, scaling, and viewing logs of container workloads. The log viewing function supports searching and filtering logs by Pod or container instance, and highlights error and warning messages. The image lifecycle management module integrates a private image repository to support image push, security scanning, and version management. The intelligent analysis and alerting center uses data collected by the unified data collection and monitoring engine to perform multi-dimensional threshold alerts, machine learning-based anomaly detection, and natural language processing-based log pattern recognition; it also calculates comprehensive health scores for services or servers. The platform's core API gateway serves as the unified system entry point, responsible for authentication, request routing, and providing external interfaces.

[0026] In a practical implementation, the system of this invention allows users to access the platform's core API gateway via a browser and, after authentication, enter the web management interface. The configurable deployment management module displays built-in functional component packages (such as basic monitoring and end-to-end monitoring) to the user, who can then generate a customized deployment list by selecting appropriate options. This module calls backend services through the API gateway and utilizes automation tools such as Helm to perform one-click deployment on the target Kubernetes cluster or server.

[0027] The unified data acquisition and monitoring engine continuously collects basic metrics such as CPU, memory, and disk I / O through collectors deployed on various nodes in a DaemonSet manner, and collects application performance monitoring data and business logs in a non-intrusive way. All data is aggregated into a time-series database and a log database, forming a unified data foundation.

[0028] Operations personnel can perform rolling upgrades and one-click horizontal scaling (HPA) of Kubernetes workloads through the visual container orchestration and management module on the web interface, without having to remember or type complex kubectl commands. The module also provides integrated real-time log viewing capabilities, supporting retrieval by Pod and container instance, and highlighting error messages.

[0029] After developers push newly built images to the private repository integrated with the image lifecycle management module via the CI / CD pipeline, the module will automatically trigger a security scan, detect known vulnerabilities, and manage image versions according to preset policies.

[0030] The intelligent analysis and alarm center reads monitoring and log data from the central database. On one hand, it allows users to configure flexible, multi-dimensional threshold alarm rules; on the other hand, it uses machine learning models to analyze historical indicator data to detect abnormal fluctuations. Simultaneously, it uses natural language processing technology to perform cluster analysis on application logs, automatically identifying high-frequency or severe error patterns. When an anomaly is detected or a critical error pattern is identified, alarms are triggered via email, SMS, etc. Example 2

[0031] Please refer to Figure 2, which describes an onboard intelligent operation and maintenance management platform system based on a modular architecture, as described in Embodiment 1 above. This embodiment provides an onboard intelligent operation and maintenance management method based on a modular architecture, which includes the following steps: S1: The configuration deployment management module receives user graphical selections, generates a deployment list, and executes one-click operation and maintenance tool stack deployment. The one-click operation and maintenance tool stack deployment is completed on the target Kubernetes cluster using the Helm tool; S2: The unified data collection and monitoring engine collects various operation and maintenance data from the managed nodes and stores them in a unified central database; S3: The visual container orchestration management module provides a web interface to support graphical operation and log viewing of Kubernetes workloads; S4: The image lifecycle management module performs security scanning and version management on images; S5: The intelligent analysis and alarm center performs threshold judgment, anomaly detection, and log pattern recognition on the collected data and triggers alarms. Log pattern recognition uses natural language processing technology to cluster application logs to identify error patterns. Embodiment 3

[0032] This embodiment provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, can implement any of the embodiments in Embodiment 2.

[0033] Since the computer-readable storage medium described in this embodiment is the same computer-readable storage medium used in implementing the method in Embodiment 2 of this application, those skilled in the art can understand the specific implementation methods and various variations of the computer-readable storage medium in this embodiment based on the method described in Embodiment 2 of this application. Therefore, how this computer-readable storage medium implements the method in the embodiments of this application will not be described in detail here. Any computer-readable storage medium used by those skilled in the art in implementing the method in the embodiments of this application falls within the scope of protection intended for this application. Embodiment 4

[0034] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it can implement any of the embodiments in Embodiment 2.

[0035] Since the electronic device described in this embodiment is the device used to implement the method in Embodiment 2 of this application, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in Embodiment 2 of this application. Therefore, how the electronic device implements the method in the embodiment of this application will not be described in detail here. Any device used by those skilled in the art to implement the method in the embodiment of this application falls within the scope of protection of this application.

[0036] The above embodiments and figures are not intended to limit the product form and style of the present invention. Any appropriate changes or modifications made by those skilled in the art should be considered as not departing from the patent scope of the present invention.

Claims

1. A modular architecture-based on-premises intelligent operation and maintenance management platform system, characterized in that: include: The configurable deployment management module is used to receive the user's selection of predefined functional component packages through a graphical interface, generate a deployment list, and perform one-click deployment of the operation and maintenance tool stack in the target environment based on the list. A unified data acquisition and monitoring engine is used to non-intrusively collect basic metrics, application performance metrics, and business logs through plug-in collectors and store them in a unified central database. The visual container orchestration and management module provides a web management console for Kubernetes clusters, enabling users to upgrade, scale, and view logs of container workloads through a graphical interface. The image lifecycle management module integrates a private image repository to support image push, security scanning, and version management. The intelligent analysis and alarm center performs multi-dimensional threshold alarms, machine learning-based anomaly detection, and natural language processing-based log pattern recognition based on data collected by the unified data collection and monitoring engine. The platform's core API gateway serves as the unified entry point for the system, responsible for identity authentication, request routing, and providing external interfaces.

2. The modular architecture-based resident intelligent operation and maintenance management platform system according to claim 1, characterized in that: The predefined functional component packages in the configurable deployment management module include basic monitoring, end-to-end monitoring, or security compliance component packages.

3. The modular architecture-based on-premises intelligent operation and maintenance management platform system according to claim 1, characterized in that: The unified data acquisition and monitoring engine deploys the collector on Kubernetes cluster nodes using the DaemonSet method.

4. The modular architecture-based resident intelligent operation and maintenance management platform system according to claim 1, characterized in that: The intelligent analysis and alerting center is also used to calculate a comprehensive health score for services or servers.

5. The modular architecture-based resident intelligent operation and maintenance management platform system according to claim 1, characterized in that: The log viewing function of the visual container orchestration and management module supports log retrieval and filtering by Pod or container instance, and highlights error and warning messages.

6. A modular architecture-based on-premises intelligent operation and maintenance management method, characterized in that: Based on any one of claims 1 to 5, an onboard intelligent operation and maintenance management platform system with a modular architecture is provided, the method comprising the following steps: S1: receiving user graphical selections through a configurational deployment management module, generating a deployment list, and executing one-click deployment of the operation and maintenance tool stack; S2: collecting various operation and maintenance data from managed nodes and storing them in a unified central database through a unified data collection and monitoring engine; S3: providing a web interface through a visual container orchestration management module to support graphical operation and log viewing of Kubernetes workloads; S4: performing security scanning and version management on images through an image lifecycle management module; S5: performing threshold judgment, anomaly detection, and log pattern recognition on the collected data through an intelligent analysis and alarm center, and triggering alarms.

7. The on-site intelligent operation and maintenance management method based on a modular architecture as described in claim 6, characterized in that: The one-click deployment of the operation and maintenance tool stack described in step S1 is completed on the target Kubernetes cluster using the Helm tool.

8. The on-site intelligent operation and maintenance management method based on a modular architecture according to claim 6, characterized in that: The log pattern recognition described in step S5 is to use natural language processing technology to cluster application logs to identify error patterns.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the steps of the modular architecture-based on-premises intelligent operation and maintenance management method as described in any one of claims 6 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of an on-premises intelligent operation and maintenance management method based on a modular architecture as described in any one of claims 6 to 8.

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