State grid cloud platform health degree analysis and evaluation method and system

Abstract

The invention discloses a state grid cloud platform health degree analysis and evaluation method and system, and the method comprises the steps: collecting cloud platform configuration data and operation indexes, and carrying out the processing and storage of the collected cloud platform data; based on the processed and stored cloud platform data, constructing a state grid cloud platform health degree evaluation model through a state grid cloud health degree algorithm; training and optimizing the state grid cloud platform health degree evaluation model; and inputting cloud platform index data into the optimized state grid cloud platform health degree evaluation model by adopting a big data stream computing technology, and obtaining real-time health degree information of the cloud platform. The health degree analysis is more accurate, more comprehensive and more reasonable, and the service requirements of cloud platform operation and maintenance monitoring are met.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance monitoring technology, and in particular to a method and system for analyzing and evaluating the health of a State Grid cloud platform. Background Art

[0002] The State Grid Corporation of China has built its cloud platform based on Alibaba Cloud and Huawei Cloud, in accordance with the architecture of one cloud and multiple regions. Currently, Alibaba Cloud and Huawei Cloud provide a variety of monitoring tools to monitor their respective cloud platforms. As a result, there are many and scattered cloud platform monitoring tools, and the monitoring indicators are not unified. It is impossible to analyze and evaluate the health of the State Grid cloud platform as a whole. A large number of operation and maintenance personnel are required to monitor the cloud platform, and the monitoring efficiency is low and inaccurate. At present, the monitoring and analysis of the cloud platform mainly have the following difficulties:

[0003] (1) The cloud platform architecture is complex and difficult to monitor: The cloud platform architecture is very complex and can be divided into four major layers: the physical facility layer, the cloud platform base layer, the cloud product layer, and the cloud resource instance layer. The physical facility layer includes the physical servers, network devices, storage devices, and security devices used to deploy the cloud platform; the cloud platform base layer includes distributed file components, resource management and scheduling components, authentication and permission components, and security control components; the cloud product layer includes cloud hosts, cloud databases, cloud networks, and cloud storage products; and the cloud resource instance layer includes instance resources such as cloud host instances, cloud database instances, cloud network instances, and cloud storage instances. The cloud platform contains many components that are interrelated and dependent on each other, making it difficult to monitor the entire cloud platform.

[0004] (2) Cloud platform monitoring indicators are numerous, scattered, and unsystematic: Currently, cloud platform physical facilities, base components, cloud products, and cloud resource instances all have different monitoring indicators. There is a lack of a classification and layered design system for indicators. Monitoring indicators are scattered, overlapping, and lack linkage between them, resulting in scattered monitoring capabilities and low monitoring results.

[0005] (3) The cloud platform health analysis method is simple and lacks an overall analysis model: The current cloud platform health analysis method mainly determines the health of the cloud platform by real-time monitoring of the changes in each independent indicator. It lacks correlation analysis between indicators and an overall cloud platform health analysis model. It is impossible to comprehensively analyze and evaluate the health of the cloud platform, resulting in the cloud platform health analysis being superficial and unable to discover deep-seated problems and the root causes of the problems.

[0006] (4) The cloud platform has a huge number of monitoring indicators and low analysis and calculation efficiency: Since the cloud platform has many monitoring objects and requires real-time monitoring and analysis, the frequency of operation and maintenance data collection is high, the monitoring indicator data is large, and the data volume is huge; in addition, the data analysis process requires frequent reading and writing of data from the disk, and there is a bottleneck in disk IO. This ultimately leads to high pressure on data analysis and calculation, long analysis cycle, and low efficiency, resulting in a serious lag in cloud platform health analysis. Summary of the invention

[0007] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0008] In view of the above existing problems, the present invention is proposed.

[0009] Therefore, the present invention provides a method and system for analyzing and evaluating the health of a State Grid cloud platform to solve the problems of low efficiency and inaccuracy of existing cloud platform monitoring methods.

[0010] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0011] In a first aspect, the present invention provides a method for analyzing and evaluating the health of a State Grid cloud platform, comprising:

[0012] The collection and preprocessing module is used to collect cloud platform configuration data and operation indicators, and process and store the collected cloud platform data;

[0013] A construction module is used to construct a State Grid cloud platform health evaluation model based on the processed and stored cloud platform data through the State Grid cloud health algorithm;

[0014] The training and optimization module is used to train and optimize the health evaluation model of the State Grid cloud platform;

[0015] The computing module is used to use big data streaming computing technology to input cloud platform indicator data into the optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

[0016] As a preferred solution of the method for analyzing and evaluating the health of the State Grid cloud platform described in the present invention, wherein:

[0017] The collecting of cloud platform configuration data and operation indicators includes the following steps:

[0018] Configure the collection task, including the task name, collection cycle, and collection indicators;

[0019] Connect to the cloud platform, call the cloud platform interface, and obtain cloud platform indicators;

[0020] Save the indicators and store the cloud platform configuration data in the State Grid Cloud CMDB library. The operation indicators will be managed through subsequent indicator standardization and stored in the time series library and historical library.

[0021] As a preferred solution of the method for analyzing and evaluating the health of the State Grid cloud platform described in the present invention, wherein:

[0022] The processing of the collected cloud platform data includes the following steps:

[0023] Unify the names of monitoring indicators of the cloud platform;

[0024] Unified management of cloud platform monitoring indicator units;

[0025] Formulate standard classifications for cloud platform indicators and label indicator data with classifications;

[0026] Unify the semantics of the definitions, scopes and prerequisites of each monitoring indicator of the cloud platform.

[0027] As a preferred solution of the method for analyzing and evaluating the health of the State Grid cloud platform described in the present invention, wherein:

[0028] The storing of the collected cloud platform data comprises the following steps:

[0029] The standardized cloud platform monitoring indicators are stored in a history library and a time series library.

[0030] The historical database uses a data warehouse to store massive data, and the time series database uses InfluxDB for storage;

[0031] Build a cloud platform CMDB library to store the basic configuration data of the cloud platform and the relationship data between the components within the cloud platform;

[0032] The CMDB library is stored in a relational database.

[0033] As a preferred solution of the method for analyzing and evaluating the health of the State Grid cloud platform described in the present invention, wherein:

[0034] The construction of the State Grid cloud platform health evaluation model by using the State Grid cloud health algorithm includes the following steps:

[0035] According to the architecture of the State Grid cloud platform, the model evaluation rules are set, and a deduction system is adopted. The initial score is 100 points. Points are deducted based on the alarm level of different components of the cloud platform, component importance, and component unavailability and vulnerability level security to obtain the final score;

[0036] The alarm level deducts 2 points, 1 point, and 0 points respectively for fault, serious, and general alarms;

[0037] The importance of the component will be deducted by 3 points, 2 points, and 1 point respectively according to the importance, general, and unimportant;

[0038] If the component is unavailable, 100 points, 50 points, and 20 points will be deducted based on importance, general, and unimportance, respectively;

[0039] The vulnerability level will be deducted 2 points, 1 point, and 0 points respectively according to high risk, medium risk, and low risk;

[0040] The scoring weights include 50% for availability, 50% for key points, and 10% for security.

[0041] The availability score is deducted based on the level of component unavailability;

[0042] The key point scoring comprehensively considers the alarm level and component importance, calculates the total deduction value of the associated object, and then calculates the final deduction value based on the total score ratio and weight;

[0043] The security score is deducted based on the vulnerability level, and the total deduction limit is the maximum security deduction weight multiplied by 100 points.

[0044] As a preferred solution of the method for analyzing and evaluating the health of the State Grid cloud platform described in the present invention, wherein:

[0045] The training of the State Grid cloud platform health evaluation model includes inputting the cloud platform monitoring historical data and score information into the State Grid cloud platform health evaluation model, analyzing and calculating, and obtaining the cloud platform health data.

[0046] As a preferred solution of the method for analyzing and evaluating the health of the State Grid cloud platform described in the present invention, wherein:

[0047] The optimization of the State Grid cloud platform health evaluation model includes evaluating the cloud platform health data, evaluating whether the model parameters are appropriate, whether the parameter weights are appropriate, outputting model optimization suggestions, and iterating the next round of model training based on the optimization suggestions until the accuracy of the model training results meets the standards, and releasing the optimized cloud platform health evaluation model.

[0048] In a second aspect, the present invention provides a state grid cloud platform health analysis and evaluation system, comprising:

[0049] The data collection module is used to collect cloud platform configuration data and operation indicators, and process and store the collected cloud platform data;

[0050] The data management module is used to build a State Grid cloud platform health evaluation model based on the processed and stored cloud platform data through the State Grid cloud health algorithm;

[0051] Business analysis module, used to train and optimize the health evaluation model of the State Grid cloud platform;

[0052] The application display module is used to adopt big data streaming computing technology to input cloud platform indicator data into the optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

[0053] In a third aspect, the present invention provides a computing device, comprising:

[0054] Memory, used to store programs;

[0055] A processor is used to execute the computer executable instructions, which, when executed by the processor, implement the steps of the State Grid cloud platform health analysis and evaluation method.

[0056] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising: when the program is executed by a processor, the steps of implementing the State Grid cloud platform health analysis and evaluation method are implemented.

[0057] Beneficial effects of the present invention: Based on various operation and maintenance monitoring data generated by the operation of the cloud platform, including operation log data, cloud platform physical equipment monitoring index data, cloud platform base component monitoring index data, cloud product monitoring index data, and cloud resource instance monitoring index data, the present invention analyzes the health of the cloud platform operation in real time, timely grasps the changes in health, and ensures the stable and efficient operation of the cloud platform. Compared with the existing analysis methods, the health analysis of the present invention is more accurate, more comprehensive, and more reasonable, and meets the business requirements of cloud platform operation and maintenance monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0059] Figure 1 A basic flow chart of a method for analyzing and evaluating the health of a State Grid cloud platform provided by an embodiment of the present invention;

[0060] Figure 2 A schematic diagram of a state grid cloud platform health analysis process of a state grid cloud platform health analysis and evaluation method provided by an embodiment of the present invention;

[0061] Figure 3 An existing State Grid cloud platform architecture diagram of a State Grid cloud platform health analysis and evaluation method provided by an embodiment of the present invention;

[0062] Figure 4 An architecture diagram of a State Grid cloud platform health analysis system providing a State Grid cloud platform health analysis and evaluation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0065] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0066] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0067] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0068] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0069] Example 1

[0070] Reference Figure 1-2 , is an embodiment of the present invention, and provides a method for analyzing and evaluating the health of a State Grid cloud platform, such as Figure 1 As shown, the following steps are included:

[0071] S1: Collect cloud platform configuration data and operation indicators, and process and store the collected cloud platform data;

[0072] In an embodiment of the present application, collecting cloud platform configuration management data includes collecting basic configuration data of physical devices, cloud platform base components, cloud product components and cloud resource instances of the cloud platform according to the architecture of the State Grid cloud platform, collecting attribute information such as physical server code, physical server name, physical server MAC address, base component code, base component name, cloud product code, cloud product name, cloud resource instance ID and cloud resource instance name; at the same time, collecting the association between server and base component, the association between server and cloud product, the association between cloud product and base component, the association between cloud product and resource instance, etc.; based on the basic configuration data, building the State Grid cloud platform CMDB library.

[0073] In the embodiment of the present application, collecting cloud platform operation indicators includes collecting the operation status and operation performance indicator data of the cloud platform's physical devices, cloud platform base components, cloud product components and cloud resource instances, collecting physical server status, base component status, cloud product status and cloud resource instance status information; at the same time, collecting physical server CPU usage, physical server memory usage, physical server network IO, physical server network delay, physical server network packet loss rate, physical server disk IO, NTP offset, DNS resolution error rate, database CPU usage, database memory usage, database disk usage, number of database slow SQL, product component page connectivity, product component page delay, base component security vulnerabilities, base component defects, cloud product security vulnerabilities, cloud product defects, cloud resource instance CPU usage, cloud resource instance memory usage and cloud resource instance disk usage and other indicators. Based on the collected cloud platform operation indicators, a full historical indicator library and real-time time series library are constructed to provide basic data for subsequent cloud platform health evaluation model training and provide real-time data for cloud platform health analysis.

[0074] In an embodiment of the present application, the collected cloud platform data is processed and stored, including the following steps:

[0075] Unified definition and planning of cloud platform monitoring indicators, formulation of indicator specifications, indicator data governance specifications, design of monitoring indicator models, and construction of a complete monitoring indicator system.

[0076] ①Indicator definition

[0077] A unified definition of cloud platform monitoring indicators is made, and a metadata database of monitoring indicators is constructed. The metadata information of indicators includes: indicator ID, indicator English name, indicator Chinese name, monitoring object, indicator classification, indicator grading, indicator description, collection method, collection evaluation rate, indicator calculation method, indicator function, etc.

[0078] ②Indicator data governance specifications

[0079] According to the cloud platform monitoring business needs and operation and maintenance data specification requirements, cloud platform monitoring indicator governance specifications are formulated. The specifications include: indicator data type, indicator value length, indicator value range, indicator enumeration value type, whether the indicator value can be empty and other rules and requirements.

[0080] ③Indicator classification and grading

[0081] The cloud platform monitoring indicators are uniformly classified and graded according to their meaning and function, including: business category, performance indicator category, alarm category, etc.; the indicators are graded according to the associated derivative relationship of the indicators, including: primary indicators, secondary indicators and tertiary indicators.

[0082] ④Indicator model

[0083] Analyze the cloud platform monitoring indicators, design the indicator dimension model and indicator entity model; the indicator dimensions include: indicator time, unit, cloud platform, indicator object, indicator type, indicator level, etc.; the indicator entity model contains specific indicator value information; build the monitoring cloud platform monitoring indicator cube based on the indicator dimension model and indicator entity model to achieve aggregation and drill-down of indicator data in different dimensions, and slice and combine the operation and maintenance data according to multiple dimensions to show the relationship between different dimensions.

[0084] S2: Based on the processed and stored cloud platform data, the State Grid cloud platform health evaluation model is constructed through the State Grid cloud health algorithm;

[0085] In the embodiment of the present application, according to the architecture of the State Grid cloud platform, the golden indicators of various monitoring objects of the cloud platform are selected, the golden indicator weighting rules are designed, the cloud platform health scoring rules are designed, and the State Grid cloud platform health evaluation model is constructed. The model adopts a deduction system with a full score of 100 points. The specific parameters of the model are shown in Table 1.

[0086] Table 1 Parameters of the State Grid Cloud Platform Health Evaluation Model

[0087]

[0088]

[0089] In the embodiment of the present application, the State Grid cloud health algorithm includes the following steps:

[0090] The specific calculation rules for the health model score are as follows:

[0091] ① Calculation method of cloud platform availability score:

[0092] Availability deduction points = ∑(J1)+∑(J2)+∑(J3)

[0093] Among them, ∑(J1) represents the sum of the number of unavailable objects of all important levels multiplied by the important level score J1; ∑(J2) represents the sum of the number of unavailable objects of all general levels multiplied by the general level score J2; ∑(J3) represents the sum of the number of unavailable objects of all unimportant levels multiplied by the unimportant level score J3;

[0094] If the cumulative availability deduction score is > 100, then X1 = 100*K1;

[0095] Otherwise, X1 = "Availability deduction points accumulated" * K1;

[0096] Among them, X1 represents the cumulative deduction of availability, and K1 represents the maximum deduction weight of availability.

[0097] ② Calculation method of key point scores of cloud platform:

[0098] 1.

[0099] 2. Cumulative deduction value of associated objects = ∑(On*Amax)+∑(On*R1)+∑(On*R2)

[0100] +∑(On*R3);

[0101] 3. Total score of associated objects = ∑(O*A1+O*R);

[0102] Among them, X2 represents the key point deduction value, K2 represents the maximum deduction weight of the key point, ∑(On*Amax) represents the number of objects with alarms multiplied by the maximum score of the alarm level of the object, and only one highest level alarm is taken when there are multiple alarms; A1 represents a fault alarm, A2 represents a serious alarm, and A3 represents a general alarm; ∑(On*R1) represents the number of important level objects with alarms multiplied by the important level score R1; ∑(On*R2) represents the number of general alarm objects multiplied by the general level score R2; ∑(On*R3) represents the number of unimportant alarm objects multiplied by the unimportant level score R3; ∑(O*A1+O*R) represents the number of all associated objects × the fault alarm score A1 + the number of all associated objects × the corresponding object important level score R;

[0103] ③ Cloud platform security score calculation method:

[0104] Safety deduction points = ∑(L1)+∑(L2)+∑(L3)

[0105] If "Safety deduction points accumulated" > (K3*100), X3 = K3*100;

[0106] Otherwise X3 = "accumulated safety deduction points".

[0107] Among them, X3 represents the security deduction value, K3 represents the maximum security deduction weight, ∑(L1) represents the number of high-risk vulnerabilities × the high-risk score L1; ∑(L2) represents the number of medium-risk vulnerabilities × the medium-risk score L2; ∑(L3) represents the number of general vulnerabilities × the general score L3.

[0108] S3: Train and optimize the health evaluation model of the State Grid cloud platform;

[0109] In an embodiment of the present application, according to the State Grid cloud platform health evaluation model, based on the collected cloud platform historical data, the cloud platform health evaluation model is trained, and the parameters of the health model are continuously optimized to make the model increasingly stable and reliable.

[0110] S4: Using big data streaming computing technology, the cloud platform indicator data is input into the optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

[0111] In the embodiment of the present application, distributed streaming computing technology is used to input cloud platform indicator data into the health model, and the health of the cloud platform is analyzed and calculated in real time to improve the efficiency of indicator analysis and calculation.

[0112] In the embodiments of the present application, Figure 2As shown in the figure, cloud resource instances, cloud product components, cloud platform base components and physical devices of the cloud platform are collected; cloud platform configuration data is stored in the State Grid Cloud CMDB library, and the operation indicators are standardized and managed through subsequent indicators, and stored in the time series library and the historical library. Standardization of cloud platform operation data includes unified naming, unified units, unified classification and unified semantics; extract historical data from the historical library and combine it with data annotation, input the health evaluation model of the State Grid cloud platform, analyze and calculate, obtain cloud platform health data, evaluate the model training results, evaluate the accuracy of the results, evaluate whether the model parameters are appropriate according to the results, whether the parameter weights are appropriate, and output suggestions for model optimization. According to the optimization suggestions, the next round of model training is iterated until the accuracy of the model training results reaches more than 90%, and finally the trained model is released. Data annotation includes annotation of cloud platform monitoring indicators, annotation of indicator data classification, importance, components and security, etc. Using big data streaming computing technology, access to cloud platform real-time monitoring indicator data, and according to the cloud platform health evaluation model released by training, real-time calculation and analysis are performed to obtain real-time health information of the cloud platform. The whole network health aggregation is based on the cloud platform health information calculated in real time, and aggregates the health of a single region, cloud product health, service cluster health and physical server health; the overall health of the cloud platform network is obtained. The health of a single region is obtained by aggregating the health of each region (Region) in the cloud platform to locate the problem area. The health of cloud products reflects the overall health of cloud products by aggregating the health of service clusters, helping operation and maintenance personnel to pay attention to products that may have problems. The health of service clusters is aggregated from the health of physical servers, reflecting the operating status of service clusters and providing a basis for operation and maintenance decisions. The health of physical servers is the smallest granularity of health analysis and reflects the health of a single physical server.

[0113] This embodiment also provides a State Grid cloud platform health analysis and evaluation system, including:

[0114] The data collection module is used to collect cloud platform configuration data and operation indicators, and process and store the collected cloud platform data;

[0115] The data management module is used to build a State Grid cloud platform health evaluation model based on the processed and stored cloud platform data through the State Grid cloud health algorithm;

[0116] Business analysis module, used to train and optimize the health evaluation model of the State Grid cloud platform;

[0117] The application display module is used to adopt big data streaming computing technology to input cloud platform indicator data into the optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

[0118] Furthermore, it also includes:

[0119] Memory, used to store programs;

[0120] A processor is used to load the program to execute the State Grid cloud platform health analysis and evaluation method.

[0121] This embodiment also provides a computer-readable storage medium storing a program, which, when executed by a processor, implements the method for analyzing and evaluating the health of the State Grid cloud platform.

[0122] The storage medium proposed in this embodiment and the State Grid cloud platform health analysis and evaluation method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0123] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0124] Example 2

[0125] Reference Figure 3-4 , which is an embodiment of the present invention, provides a 6P pulse excitation rectifier system, including a data acquisition module, a data management module, a business analysis module and an application display module;

[0126] In the embodiment of the present application, the data collection module includes collecting cloud platform configuration data and operating indicators, and processing and storing the collected cloud platform data;

[0127] In the embodiment of the present application, the data management module includes building a State Grid cloud platform health evaluation model through a State Grid cloud health algorithm based on the processed and stored cloud platform data;

[0128] In the embodiment of the present application, the business analysis module includes training and optimizing the health evaluation model of the State Grid cloud platform;

[0129] In an embodiment of the present application, the application display module includes using big data streaming computing technology to input cloud platform indicator data into an optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

[0130] like Figure 3 The figure shows the existing State Grid cloud platform architecture diagram, which shows the architectural hierarchy and components of the State Grid cloud platform. From top to bottom, there are cloud resource instances, cloud platform product components, cloud platform base components and cloud platform physical facilities; cloud resource instances are the top-level application layer, which include various cloud service instances, such as cloud host instances, cloud database instances, private network instances, cloud firewall instances, cloud container instances, etc. Cloud platform product components include databases, middleware, big data, etc. Among them, databases are further divided into relational databases and NoSQL databases; middleware includes cloud messaging, cloud service bus, etc.; big data covers data warehouses, real-time computing, data buses, machine learning and other fields. In addition, there are four major categories of product components: computing, storage, network and security. The cloud platform base components include distributed files, resource management and scheduling, authentication and permission control, security management and control and other functional modules. The cloud platform physical facilities include physical servers, network equipment, security equipment and storage equipment.

[0131] like Figure 4 As shown in the figure, it is the architecture diagram of the health analysis system of the State Grid cloud platform of the present invention, which includes three levels: application display, business analysis and data collection; application display includes monitoring and displaying the health of cloud resources, cloud products, cloud platform base components, cloud platform physical equipment and the overall health of the cloud platform; business analysis mainly involves the analysis of the health of the cloud platform, including the management, calculation, abnormal alarm and abnormal analysis of the health analysis model. At the same time, it also includes data annotation, model training, model publishing and model evaluation and optimization. In addition, there are indicator models, health analysis models, algorithm libraries and other contents. Data management is mainly responsible for cloud platform CMDB, cloud platform indicator management and data governance management. Among them, the cloud platform CMDB contains indicator metadata, historical indicator library and real-time indicator library. Data collection includes data such as account information, performance indicators, alarms and vulnerabilities of cloud platform components collected during the data collection stage.

[0132] from Figure 3 and Figure 4 The comparison shows that Figure 4 The implementation process of the cloud platform health analysis and evaluation model is described in more detail, starting from data collection, through business analysis and data management, and finally forming an application display. This design is conducive to improving the monitorability and maintainability of the cloud platform, allowing operation and maintenance personnel to better understand and grasp the status of the cloud platform, discover problems in a timely manner and respond.

[0133] from Figure 4 It can be seen that the present invention covers the health monitoring of all aspects of the cloud platform, from resource instances to product components, base components, physical facilities and even overall health, achieving all-round monitoring. It provides functions such as health analysis model management, calculation, abnormal alarm and abnormal analysis, which facilitates in-depth understanding of the operation status of the cloud platform; through data annotation, model training, publishing and optimization, data is used to improve the accuracy and practicality of the model, and the CMDB, indicator management and data governance of the cloud platform are carefully divided, which improves the organization and management efficiency of data. Through the real-time indicator library and alarm system, the latest status of the cloud platform can be quickly obtained and responded to in time, which helps to improve the reliability and stability of the cloud platform, reduce the risk of failure, and ensure service quality.

[0134] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for analyzing and evaluating the health of a State Grid cloud platform, characterized in that: include: Collect cloud platform configuration data and operating indicators, and process and store the collected cloud platform data; Based on the processed and stored cloud platform data, the State Grid cloud platform health evaluation model is constructed through the State Grid cloud health algorithm; Train and optimize the health evaluation model of the State Grid cloud platform; Using big data streaming computing technology, the cloud platform indicator data is input into the optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

2. The method for analyzing and evaluating the health of the State Grid cloud platform according to claim 1, characterized in that: The collecting of cloud platform configuration data and operation indicators includes the following steps: Configure the collection task, including the task name, collection cycle, and collection indicators; Connect to the cloud platform, call the cloud platform interface, and obtain cloud platform indicators; Save the indicators and store the cloud platform configuration data in the State Grid Cloud CMDB library. The operation indicators will be managed through subsequent indicator standardization and stored in the time series library and historical library.

3. The method for analyzing and evaluating the health of the State Grid cloud platform according to claim 1 or 2, characterized in that: The processing of the collected cloud platform data includes the following steps: Unify the names of monitoring indicators of the cloud platform; Unified management of cloud platform monitoring indicator units; Formulate standard classifications for cloud platform indicators and label indicator data with classifications; Unify the semantics of the definitions, scopes and prerequisites of each monitoring indicator of the cloud platform.

4. The method for analyzing and evaluating the health of the State Grid cloud platform according to claim 3, characterized in that: The storing of the collected cloud platform data comprises the following steps: The standardized cloud platform monitoring indicators are stored in a history library and a time series library. The historical database uses a data warehouse to store massive data, and the time series database uses InfluxDB for storage; Build a cloud platform CMDB library to store the basic configuration data of the cloud platform and the relationship data between the components within the cloud platform; The CMDB library is stored in a relational database.

5. The method for analyzing and evaluating the health of the State Grid cloud platform according to claim 4, characterized in that: The construction of the State Grid cloud platform health evaluation model by using the State Grid cloud health algorithm includes the following steps: According to the architecture of the State Grid cloud platform, the model evaluation rules are set, and a deduction system is adopted. The initial score is 100 points. Points are deducted based on the alarm level of different components of the cloud platform, component importance, and component unavailability and vulnerability level security to obtain the final score; The alarm level deducts 2 points, 1 point, and 0 points respectively for fault, serious, and general alarms; The importance of the component will be deducted by 3 points, 2 points, and 1 point respectively according to the importance, general, and unimportant; If the component is unavailable, 100 points, 50 points, and 20 points will be deducted based on importance, general, and unimportance, respectively; The vulnerability level will be deducted 2 points, 1 point, and 0 points respectively according to high risk, medium risk, and low risk; The scoring weights include 50% for availability, 50% for key points, and 10% for security. The availability score is deducted based on the level of component unavailability; The key point scoring comprehensively considers the alarm level and component importance, calculates the total deduction value of the associated object, and then calculates the final deduction value based on the total score ratio and weight; The security score is deducted based on the vulnerability level, and the total deduction limit is the maximum security deduction weight multiplied by 100 points.

6. The method for analyzing and evaluating the health of the State Grid cloud platform according to claim 5, characterized in that: The training of the State Grid cloud platform health evaluation model includes inputting the cloud platform monitoring historical data and score information into the State Grid cloud platform health evaluation model, analyzing and calculating, and obtaining the cloud platform health data.

7. The method for analyzing and evaluating the health of the State Grid cloud platform according to claim 6, characterized in that: The optimization of the State Grid cloud platform health evaluation model includes evaluating the cloud platform health data, evaluating whether the model parameters are appropriate, whether the parameter weights are appropriate, outputting model optimization suggestions, and iterating the next round of model training based on the optimization suggestions until the accuracy of the model training results meets the standards, and releasing the optimized cloud platform health evaluation model.

8. A system based on the method for analyzing and evaluating the health of the State Grid cloud platform according to claim 1, characterized in that: The data collection module is used to collect cloud platform configuration data and operation indicators, and process and store the collected cloud platform data; The data management module is used to build a State Grid cloud platform health evaluation model based on the processed and stored cloud platform data through the State Grid cloud health algorithm; Business analysis module, used to train and optimize the health evaluation model of the State Grid cloud platform; The application display module is used to adopt big data streaming computing technology to input cloud platform indicator data into the optimized State Grid cloud platform health evaluation model to obtain real-time health information of the cloud platform.

9. An electronic device, characterized in that: include: Memory, used to store programs; A processor, used to load the program to execute the steps of the State Grid cloud platform health analysis and evaluation method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a program, characterized in that: When the program is executed by the processor, the steps of the State Grid cloud platform health analysis and evaluation method as described in any one of claims 1-7 are implemented.

Images