Integrated operation and maintenance method and system in cloud native environment

Abstract

The invention relates to the technical field of automatic operation and maintenance, and particularly provides an integrated operation and maintenance method and system in a cloud native environment, and the method comprises the following steps: S1, a monitoring module carries out the real-time monitoring of each assembly of a cloud native system; s2, when a system has a fault or a performance bottleneck in the intelligent diagnosis module, automatically analyzing monitoring data, and positioning the root of a problem; s3, realizing automation of operation and maintenance work by an automatic operation and maintenance module; and S4, the resource optimization module optimizes the resources of the cloud native system. Compared with the prior art, functions of comprehensive monitoring, intelligent diagnosis, automatic operation and maintenance, resource optimization and the like of the cloud native system can be realized, and the operation and maintenance efficiency and the stability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the field of automated operation and maintenance technology, and specifically provides an integrated operation and maintenance method and system in a cloud-native environment. Background Art

[0002] With the rapid development of cloud computing technology, cloud-native architecture has gradually become the mainstream choice for enterprise IT architecture. Cloud-native architecture is highly scalable, flexible, and fault-tolerant, better adapting to the IT system needs of modern enterprises. However, operations and maintenance in a cloud-native environment also face many challenges:

[0003] Complex system architecture:

[0004] Cloud-native systems are typically composed of multiple containerized applications, microservices, distributed databases, etc. The system architecture is complex, and operations and maintenance personnel need to comprehensively monitor and manage the operating status, performance indicators, log information, etc. of each component, which is a huge workload.

[0005] Dynamic resource allocation:

[0006] In a cloud-native environment, resource allocation and scheduling are dynamic. Operations such as starting, stopping, scaling up, and scaling down containers occur frequently. Operations and maintenance personnel need to track resource changes in real time and reasonably schedule and optimize resources to ensure stable system operation and optimal performance.

[0007] Multi-cloud and hybrid cloud environments:

[0008] Many enterprises adopt multi-cloud or hybrid cloud deployment models. Operations and maintenance personnel need to coordinate and manage between different cloud platforms, which increases the complexity and difficulty of operations and maintenance.

[0009] Continuous Integration and Continuous Deployment (CI / CD):

[0010] In a cloud-native environment, application development, testing, and deployment processes are highly automated, and CI / CD processes run frequently. Operations and maintenance personnel need to ensure that the continuous integration and continuous deployment of code proceed smoothly and promptly identify and resolve potential problems. Summary of the Invention

[0011] In response to the above-mentioned deficiencies in the existing technology, the present invention provides an integrated operation and maintenance method in a cloud-native environment with strong practicality.

[0012] A further technical task of the present invention is to provide an integrated operation and maintenance system in a cloud-native environment that is rationally designed, safe and applicable.

[0013] The technical solution adopted by the present invention to solve its technical problem is:

[0014] The integrated operation and maintenance method in a cloud-native environment has the following steps:

[0015] S1. The monitoring module monitors each component of the cloud native system in real time;

[0016] S2, the intelligent diagnosis module automatically analyzes monitoring data and locates the root cause of the problem when a system failure or performance bottleneck occurs;

[0017] S3, the automated operation and maintenance module realizes the automation of operation and maintenance work;

[0018] S4. The resource optimization module optimizes the resources of the cloud native system.

[0019] Furthermore, in step S1, it includes:

[0020] S1.1. Data collection: By connecting to the API interface of the cloud native platform, the monitoring module regularly collects detailed data on system operation;

[0021] S1.2, data storage, storing the collected data in the monitoring database, and performing historical data query and analysis;

[0022] S1.3, alarm settings, set different monitoring indicators and alarm thresholds according to actual needs;

[0023] S1.4. Alarm notification: When the system operation is abnormal, the monitoring module will promptly send an alarm notification to the operation and maintenance personnel via email, SMS or instant messaging tools so that the operation and maintenance personnel can respond and handle it.

[0024] Furthermore, in step S2, it includes:

[0025] S2.1. Data preprocessing: Clean and preprocess the monitoring data to remove noise data and outliers and extract useful feature information;

[0026] S2.2, Model training, using machine learning algorithms to train and learn historical fault data to establish a fault diagnosis model;

[0027] S2.3. Model evaluation: evaluate the performance and accuracy of the fault diagnosis model through cross-validation to ensure that the model diagnoses the fault type and cause;

[0028] S2.4, Fault diagnosis, when a new fault occurs, the real-time monitoring data is input into the fault diagnosis model for analysis, and the fault diagnosis results are output.

[0029] Furthermore, in step S3, it includes:

[0030] S3.1. Integration configuration: Integration configuration with Kubernetes, the container orchestration tool for cloud-native platforms, and Jenkins, the CI / CD tool.

[0031] S3.2, Policy setting: Set rules and policies for automated operation and maintenance based on business needs and operation and maintenance strategies;

[0032] S3.3, Task Execution: The automated operation and maintenance module automatically executes application deployment, upgrade, rollback, expansion, and fault recovery based on preset rules and policies;

[0033] S3.4. Log records record the execution process and results of automated operation and maintenance tasks to facilitate auditing and analysis by operation and maintenance personnel.

[0034] Furthermore, in step S4, it includes:

[0035] S4.1. Data analysis: Analyze monitoring data and business load to understand system resource usage and business needs;

[0036] S4.2, Optimization strategy customization, formulate resource optimization strategy based on analysis results;

[0037] S4.3, optimize execution, automatically perform resource optimization operations;

[0038] S4.4. Cost analysis: Conduct resource cost analysis in multi-cloud and hybrid cloud environments.

[0039] An integrated operation and maintenance system in a cloud-native environment, including a monitoring module, an intelligent diagnosis module, an automated operation and maintenance module, and a resource optimization module;

[0040] The monitoring module is used to monitor each component of the cloud native system in real time;

[0041] The intelligent diagnosis module is used to automatically analyze monitoring data and locate the root cause of the problem when a system failure or performance bottleneck occurs;

[0042] The automated operation and maintenance module is used to realize the automation of operation and maintenance work;

[0043] The resource optimization module is used to optimize the resources of the cloud native system.

[0044] Furthermore, the monitoring module regularly collects detailed data on system operation by connecting to the API interface of the cloud native platform;

[0045] Then, data is stored in the monitoring database to query and analyze historical data. After that, different monitoring indicators and alarm thresholds are set according to actual needs.

[0046] Finally, when the system runs abnormally, the monitoring module will promptly send an alarm notification to the operation and maintenance personnel via email, SMS or instant messaging tools so that the operation and maintenance personnel can respond and handle it.

[0047] Furthermore, the intelligent diagnosis module performs data preprocessing, cleans and preprocesses the monitoring data, removes noise data and outliers, and extracts useful feature information;

[0048] Then, model training is carried out, using machine learning algorithms to train and learn historical fault data to establish a fault diagnosis model;

[0049] Model evaluation, which evaluates the performance and accuracy of the fault diagnosis model through cross-validation to ensure that the model diagnoses the fault type and cause;

[0050] Finally, when a new fault occurs, the real-time monitoring data is input into the fault diagnosis model for analysis, and the fault diagnosis results are output.

[0051] Furthermore, the automated operation and maintenance module is used for integrated configuration with Kubernetes, a container orchestration tool of the cloud native platform, and Jenkins, a CI / CD tool;

[0052] Then, according to business needs and operation and maintenance strategies, set up automated operation and maintenance rules and strategies. The automated operation and maintenance module automatically executes application deployment, upgrade, rollback, expansion and fault recovery according to the preset rules and strategies.

[0053] Finally, log records record the execution process and results of automated operation and maintenance tasks, which facilitates auditing and analysis by operation and maintenance personnel.

[0054] Furthermore, in the resource optimization module, data analysis is first performed to analyze monitoring data and business load conditions to understand the system's resource usage and business needs;

[0055] Then, optimization strategy customization, based on the analysis results, formulates resource optimization strategies; optimization execution, automatically performs resource optimization operations;

[0056] Finally, cost analysis is performed to analyze resource costs in multi-cloud and hybrid cloud environments.

[0057] Compared with the existing technologies, the integrated operation and maintenance method and system in the cloud-native environment of the present invention has the following outstanding beneficial effects:

[0058] Through real-time monitoring, intelligent diagnosis, and automated operation and maintenance functions, the present invention allows operation and maintenance personnel to manage and maintain cloud-native systems more efficiently, reduce manual intervention, and lower the operation and maintenance workload.

[0059] Timely discover and resolve system failures, optimize resource allocation, improve system stability and reliability, and ensure business continuity and availability.

[0060] It is applicable to the deployment mode of multiple cloud platforms, and can unify the management and coordination of resources and operation and maintenance work of different cloud platforms, simplifying operation and maintenance management.

[0061] Through resource optimization and automated operation and maintenance, resource utilization can be improved, resource waste can be reduced, and the enterprise's operation and maintenance costs can be lowered. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0063] Attachment Figure 1 It is a flowchart of an integrated operation and maintenance method in a cloud-native environment. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the solutions of the present invention, the present invention will be further described in detail below in conjunction with specific embodiments. Obviously, the embodiments described are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0065] A best embodiment is given below:

[0066] like Figure 1 As shown, an integrated operation and maintenance method in a cloud-native environment in this embodiment has the following steps:

[0067] S1. The monitoring module monitors each component of the cloud native system in real time;

[0068] include:

[0069] S1.1. Data collection: By connecting to the API interface of the cloud native platform, the monitoring module regularly collects detailed data on system operation;

[0070] S1.2, data storage, storing the collected data in the monitoring database, and performing historical data query and analysis;

[0071] S1.3, alarm settings, set different monitoring indicators and alarm thresholds according to actual needs;

[0072] S1.4. Alarm notification: When the system operation is abnormal, the monitoring module will promptly send an alarm notification to the operation and maintenance personnel via email, SMS or instant messaging tools so that the operation and maintenance personnel can respond and handle it.

[0073] S2, the intelligent diagnosis module automatically analyzes monitoring data and locates the root cause of the problem when a system failure or performance bottleneck occurs;

[0074] include:

[0075] S2.1. Data preprocessing: Clean and preprocess the monitoring data to remove noise data and outliers and extract useful feature information;

[0076] S2.2, Model training, using machine learning algorithms to train and learn historical fault data to establish a fault diagnosis model;

[0077] S2.3. Model evaluation: evaluate the performance and accuracy of the fault diagnosis model through cross-validation to ensure that the model diagnoses the fault type and cause;

[0078] S2.4, Fault diagnosis, when a new fault occurs, the real-time monitoring data is input into the fault diagnosis model for analysis, and the fault diagnosis results are output.

[0079] S3, the automated operation and maintenance module realizes the automation of operation and maintenance work;

[0080] include:

[0081] S3.1. Integration configuration: Integration configuration with Kubernetes, the container orchestration tool for cloud-native platforms, and Jenkins, the CI / CD tool.

[0082] S3.2, Policy setting: Set rules and policies for automated operation and maintenance based on business needs and operation and maintenance strategies;

[0083] S3.3, Task Execution: The automated operation and maintenance module automatically executes application deployment, upgrade, rollback, expansion, and fault recovery based on preset rules and policies;

[0084] S3.4. Log records record the execution process and results of automated operation and maintenance tasks to facilitate auditing and analysis by operation and maintenance personnel.

[0085] S4, the resource optimization module optimizes the resources of the cloud native system;

[0086] include:

[0087] S4.1. Data analysis: Analyze monitoring data and business load to understand system resource usage and business needs;

[0088] S4.2, Optimization strategy customization, formulate resource optimization strategy based on analysis results;

[0089] S4.3, optimize execution, automatically perform resource optimization operations;

[0090] S4.4. Cost analysis: Conduct resource cost analysis in multi-cloud and hybrid cloud environments.

[0091] Based on the above method, the integrated operation and maintenance system in the cloud native environment in this embodiment includes a monitoring module, an intelligent diagnosis module, an automated operation and maintenance module, and a resource optimization module;

[0092] Among them, the monitoring module is used to monitor each component of the cloud native system in real time;

[0093] This includes information such as the operating status of containers, microservice performance metrics, and distributed database query response times. The monitoring module connects to the cloud-native platform's API to obtain detailed system operation data and stores it in the monitoring database. The monitoring module also supports customizable monitoring metrics and alert rules. Operations and maintenance personnel can set different monitoring metrics and alert thresholds based on actual needs. When system operation anomalies occur, the monitoring module can promptly issue alert notifications.

[0094] The monitoring module connects to the cloud-native platform's API interface to periodically collect detailed data on system operation;

[0095] Then, data is stored in the monitoring database to query and analyze historical data. After that, different monitoring indicators and alarm thresholds are set according to actual needs.

[0096] Finally, when the system runs abnormally, the monitoring module will promptly send an alarm notification to the operation and maintenance personnel via email, SMS or instant messaging tools so that the operation and maintenance personnel can respond and handle it.

[0097] The intelligent diagnosis module is used to automatically analyze monitoring data and locate the root cause of the problem when a system failure or performance bottleneck occurs;

[0098] This module uses machine learning algorithms and big data analysis techniques to train and learn from historical fault data to build a fault diagnosis model. When a new fault occurs, the intelligent diagnosis module inputs real-time monitoring data into the fault diagnosis model for analysis and outputs fault diagnosis results, including the fault type, possible cause, and recommended solutions, providing decision support for operations and maintenance personnel.

[0099] The intelligent diagnosis module performs data preprocessing, cleans and preprocesses the monitoring data, removes noise data and outliers, and extracts useful feature information;

[0100] Then, model training is carried out, using machine learning algorithms to train and learn historical fault data to establish a fault diagnosis model;

[0101] Model evaluation, which evaluates the performance and accuracy of the fault diagnosis model through cross-validation to ensure that the model diagnoses the fault type and cause;

[0102] Finally, when a new fault occurs, the real-time monitoring data is input into the fault diagnosis model for analysis, and the fault diagnosis results are output.

[0103] The automated operation and maintenance module is used to automate operation and maintenance work;

[0104] This includes features such as automated deployment, automated capacity expansion, and automated fault recovery. The automated operations module integrates with Kubernetes, the cloud-native platform's container orchestration tool, and Jenkins, the CI / CD tool. It automates application deployment, upgrades, and rollbacks based on operational policies and rules. When system resources are insufficient, the automated operations module automatically increases the number of containers or adjusts resource allocation to meet business needs based on pre-set capacity expansion policies. In the event of a system failure, the automated operations module automatically performs fault recovery operations, such as restarting containers and migrating services, to quickly restore the system to normal operation.

[0105] The automated operation and maintenance module is used for integrated configuration with Kubernetes, the container orchestration tool for cloud-native platforms, and Jenkins, the CI / CD tool.

[0106] Then, according to business needs and operation and maintenance strategies, set up automated operation and maintenance rules and strategies. The automated operation and maintenance module automatically executes application deployment, upgrade, rollback, expansion and fault recovery according to the preset rules and strategies.

[0107] Finally, log records record the execution process and results of automated operation and maintenance tasks, making it easier for operation and maintenance personnel to conduct audits and analysis.

[0108] The resource optimization module is used to optimize the resources of the cloud native system;

[0109] This module includes resource utilization optimization and cost optimization. By analyzing monitoring data and business load, the resource optimization module intelligently adjusts resource allocation strategies, improving resource utilization and avoiding resource waste. This module also supports resource cost analysis and optimization in multi-cloud and hybrid cloud environments, helping enterprises reduce operational costs while ensuring system performance.

[0110] First, perform data analysis to analyze monitoring data and business load to understand the system's resource usage and business needs;

[0111] Then, optimization strategy customization, based on the analysis results, formulates resource optimization strategies; optimization execution, automatically performs resource optimization operations;

[0112] Finally, cost analysis is performed to analyze resource costs in multi-cloud and hybrid cloud environments.

[0113] The above-mentioned specific implementation methods are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above-mentioned specific implementation methods. Any technical solutions that conform to the above-mentioned specific implementation methods of the present invention and any appropriate changes or substitutions made thereto by ordinary technicians in the relevant technical field shall fall within the patent protection scope of the present invention.

[0114] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An integrated operation and maintenance method in a cloud-native environment, characterized by: The steps are as follows: S1. The monitoring module monitors each component of the cloud native system in real time; S2, the intelligent diagnosis module automatically analyzes monitoring data and locates the root cause of the problem when a system failure or performance bottleneck occurs; S3, the automated operation and maintenance module realizes the automation of operation and maintenance work; S4. The resource optimization module optimizes the resources of the cloud native system.

2. The integrated operation and maintenance method in a cloud native environment according to claim 1, characterized in that: In step S1, it includes: S1.

1. Data collection: By connecting to the API interface of the cloud native platform, the monitoring module regularly collects detailed data on system operation; S1.2, data storage, storing the collected data in the monitoring database, and performing historical data query and analysis; S1.3, alarm settings, set different monitoring indicators and alarm thresholds according to actual needs; S1.

4. Alarm notification: When the system operation is abnormal, the monitoring module will promptly send an alarm notification to the operation and maintenance personnel via email, SMS or instant messaging tools so that the operation and maintenance personnel can respond and handle it.

3. The integrated operation and maintenance method in a cloud native environment according to claim 2, characterized in that: In step S2, it includes: S2.

1. Data preprocessing: Clean and preprocess the monitoring data to remove noise data and outliers and extract useful feature information; S2.2, Model training, using machine learning algorithms to train and learn historical fault data to establish a fault diagnosis model; S2.

3. Model evaluation: evaluate the performance and accuracy of the fault diagnosis model through cross-validation to ensure that the model diagnoses the fault type and cause; S2.4, Fault diagnosis, when a new fault occurs, the real-time monitoring data is input into the fault diagnosis model for analysis, and the fault diagnosis results are output.

4. The integrated operation and maintenance method in a cloud native environment according to claim 3 is characterized in that: In step S3, it includes: S3.

1. Integration configuration: Integration configuration with Kubernetes, the container orchestration tool for cloud-native platforms, and Jenkins, the CI / CD tool. S3.2, Policy setting: Set rules and policies for automated operation and maintenance based on business needs and operation and maintenance strategies; S3.3, Task Execution: The automated operation and maintenance module automatically executes application deployment, upgrade, rollback, expansion, and fault recovery based on preset rules and policies; S3.

4. Log records record the execution process and results of automated operation and maintenance tasks to facilitate auditing and analysis by operation and maintenance personnel.

5. The integrated operation and maintenance method in a cloud native environment according to claim 4 is characterized in that: In step S4, it includes: S4.

1. Data analysis: Analyze monitoring data and business load to understand system resource usage and business needs; S4.2, Optimization strategy customization, formulate resource optimization strategy based on analysis results; S4.3, optimize execution, automatically perform resource optimization operations; S4.

4. Cost analysis: Conduct resource cost analysis in multi-cloud and hybrid cloud environments.

6. The integrated operation and maintenance system in the cloud native environment is characterized by: Including monitoring module, intelligent diagnosis module, automated operation and maintenance module and resource optimization module; The monitoring module is used to monitor each component of the cloud native system in real time; The intelligent diagnosis module is used to automatically analyze monitoring data and locate the root cause of the problem when a system failure or performance bottleneck occurs; The automated operation and maintenance module is used to realize the automation of operation and maintenance work; The resource optimization module is used to optimize the resources of the cloud native system.

7. The integrated operation and maintenance system in a cloud-native environment according to claim 6, characterized in that: The monitoring module collects detailed data of system operation regularly by connecting to the API interface of the cloud native platform; Then, data is stored in the monitoring database to query and analyze historical data. After that, different monitoring indicators and alarm thresholds are set according to actual needs. Finally, when the system runs abnormally, the monitoring module will promptly send an alarm notification to the operation and maintenance personnel via email, SMS or instant messaging tools so that the operation and maintenance personnel can respond and handle it.

8. The integrated operation and maintenance system in a cloud-native environment according to claim 7, characterized in that: The intelligent diagnosis module performs data preprocessing, cleans and preprocesses the monitoring data, removes noise data and outliers, and extracts useful feature information; Then, model training is carried out, using machine learning algorithms to train and learn historical fault data to establish a fault diagnosis model; Model evaluation, which evaluates the performance and accuracy of the fault diagnosis model through cross-validation to ensure that the model diagnoses the fault type and cause; Finally, when a new fault occurs, the real-time monitoring data is input into the fault diagnosis model for analysis, and the fault diagnosis results are output.

9. The integrated operation and maintenance system in a cloud-native environment according to claim 8, characterized in that: The automated operation and maintenance module is used for integrated configuration with Kubernetes, a container orchestration tool for the cloud native platform, and Jenkins, a CI / CD tool. Then, set up automated operation and maintenance rules and policies based on business needs and operation and maintenance strategies; The automated operation and maintenance module automatically executes application deployment, upgrade, rollback, expansion, and fault recovery based on preset rules and policies; Finally, log records record the execution process and results of automated operation and maintenance tasks, making it easier for operation and maintenance personnel to conduct audits and analysis.

10. The integrated operation and maintenance system in a cloud-native environment according to claim 9, characterized in that: In the resource optimization module, data analysis is first performed to analyze monitoring data and business load to understand the system's resource usage and business needs; Then, optimization strategy customization, based on the analysis results, formulates resource optimization strategies; optimization execution, automatically performs resource optimization operations; Finally, cost analysis is performed to analyze resource costs in multi-cloud and hybrid cloud environments.

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