System operation detection method and device based on operation and maintenance operation key parameters

Abstract

The invention discloses a system operation detection method and device based on operation and maintenance operation key parameters. The system operation detection method based on the operation and maintenance operation key parameters comprises the steps that an IaaS key parameter set, a PaaS key parameter set and an SaaS key parameter set are obtained, the IaaS key parameter set comprises at least one IaaS key parameter, the PaaS key parameter set comprises at least one PaaS key parameter, and the SaaS key parameter set comprises at least one SaaS key parameter; actual data of IaaS key parameters, actual data of PaaS key parameters and actual data of SaaS key parameters during actual operation are obtained; each IaaS key parameter is endowed with an IaaS key parameter health degree value; each PaaS key parameter is endowed with a PaaS key parameter health degree value; each SaaS key parameter is endowed with an SaaS key parameter health degree value; and obtaining a final health degree score. According to the method, key parameters of three dimensions of IaaS, PaaS and SaaS are comprehensively considered, so that prediction is more accurate.

Description

Technical Field

[0001] This application relates to the field of operation and maintenance technology, and in particular to a system operation detection method and device based on key operation and maintenance parameters. Background Technology

[0002] The main focus of daily work for IT center maintenance personnel in modern enterprises is to ensure the reliability, availability, and high performance of IT systems. Their primary role is to monitor network devices such as routers, switches, and firewalls, as well as security devices and various server systems. They also need to effectively monitor databases and middleware, and conduct effective performance analysis and proactive fault alerts for the entire IT system to meet the requirements of daily maintenance.

[0003] To ensure and improve the service quality of the information center, transform from "passive service" to "proactive service," and shift from "managing IT infrastructure" to "providing IT services to business departments," the information department urgently needs to introduce advanced management systems and concepts to establish a project called "Research and Application of Full-Link Monitoring Technology Based on Integrated Delivery and Operation System" to uniformly monitor and maintain the infrastructure platform, including routers, switches, servers, databases, middleware, and security devices.

[0004] Through the construction of the project "Research and Application of Full-Link Monitoring Technology Based on Integrated Delivery and Operation System", the centralized monitoring, maintenance and management of IT infrastructure will be completed, realizing the evolution from passive firefighting to proactive prevention management, creating a knowable and controllable IT environment, ensuring the reliable, efficient and continuous operation of various business systems, ensuring the stability of IT systems, providing strong support for management and operation, improving maintenance efficiency, enhancing maintenance quality and increasing customer satisfaction.

[0005] By constructing the project "Research and Application of Full-Link Monitoring Technology Based on Integrated Delivery and Operation System", we aim to achieve the goals of "proactive monitoring, centralized management, and timely alarm" for the multi-layered IT architecture, reduce potential risks in operation and maintenance, effectively improve the quality and efficiency of information support services, provide reliable guarantees for the smooth operation of application systems, and reduce business losses.

[0006] However, existing technologies do not provide a comprehensive approach to system maintenance that considers IaaS, PaaS, and SaaS from all three perspectives.

[0007] Therefore, there is a need for a technical solution to address or at least mitigate the aforementioned shortcomings of existing technologies. Summary of the Invention

[0008] The purpose of this invention is to provide a system operation detection method based on key operation and maintenance parameters to at least solve one of the above-mentioned technical problems.

[0009] This invention provides the following solution:

[0010] This application provides a system operation detection method based on key operation and maintenance parameters, the system operation detection method based on key operation and maintenance parameters includes:

[0011] Obtain IaaS key parameter group, PaaS key parameter group, and SaaS key parameter group, wherein the IaaS key parameter group includes at least one IaaS key parameter, the PaaS key parameter group includes at least one PaaS key parameter, and the SaaS key parameter group includes at least one SaaS key parameter;

[0012] Obtain actual data for each key IaaS parameter during actual runtime;

[0013] Obtain actual data for each key PaaS parameter during actual runtime;

[0014] Obtain actual data for each key parameter of each SaaS during actual runtime;

[0015] Assign a health value to each IaaS key parameter based on the actual data of each IaaS key parameter.

[0016] Assign a PaaS health value to each PaaS key parameter based on the actual data of each PaaS key parameter.

[0017] Assign a health value to each SaaS key parameter based on the actual data of each SaaS key parameter;

[0018] The final health score is obtained based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter.

[0019] Optionally, before obtaining the actual data of each IaaS key parameter during actual operation, the system operation detection method based on key operation and maintenance parameters further includes:

[0020] Select multiple IaaS key parameters from the IaaS key parameter group;

[0021] Select multiple PaaS key parameters from the PaaS key parameter group;

[0022] Select multiple SaaS key parameters from the SaaS key parameter group.

[0023] Optionally, the key IaaS parameters include:

[0024] Real-time data for bare metal server CPU utilization, bare metal server memory utilization, bare metal server disk utilization, bare metal server disk I / O read / write rate, bare metal server network I / O read / write rate, host machine CPU utilization, host machine memory utilization, host machine disk utilization, host machine disk I / O read / write rate, host machine network I / O read / write rate, switching device CPU utilization, switching device memory utilization, switching device disk utilization, switching device transmission rate, switching device inbound and outbound traffic, security device CPU utilization, security device memory utilization, security device disk utilization, and real-time data for the number of abnormal behaviors of security devices;

[0025] The key parameters of the PaaS include:

[0026] Real-time data for the following database metrics: current number of SQL statements being executed, number of slow queries, number of table lock waits, current number of connections, number of connections not properly closed, total number of PostgreSQL connections, number of PostgreSQL sessions, number of slow queries, number of PostgreSQL deadlocks, Redis memory usage, number of Redis clients connected, number of Redis slave connections, Redis memory fragmentation rate, number of Redis connection rejections, number of Redis key lookup failures, number of Redis key removals, number of Kafka brokers, cumulative number of Kafka messages, Kafka memory usage, Kafka disk usage, number of Kafka consumers, and number of Kafka queues. Real-time data for Elasticsearch (ES), including: number of ES shards, current ES queries, ES memory usage, ES garbage collection counts, ES CPU utilization, real-time ES node health status, current MongoDB connections, MongoDB CPU utilization, MongoDB memory utilization, MongoDB cluster replica status, MongoDB collective heartbeat data, number of NGINX processes, Nginx active connections, Nginx waiting connections, Starrocks CPU utilization, Starrocks memory utilization, Starrocks disk utilization, Starrocks cluster QPS, operating system CPU utilization, operating system memory utilization, operating system disk utilization, operating system maximum connections, and operating system active processes.

[0027] The key parameters of the SaaS include:

[0028] Detect application liveness, port connectivity, Docker liveness, monitor interface status, and use Skywalking for APM monitoring.

[0029] Optionally, the system operation detection method based on key operation and maintenance parameters includes:

[0030] Obtain the IaaS key parameter type for each IaaS key parameter, wherein the IaaS key parameter type includes a first IaaS class and a second IaaS class;

[0031] When the IaaS key parameter type is the second IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0032] Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one IaaS key parameter range value, and an IaaS key parameter health value; wherein, one IaaS key parameter range value corresponds to one IaaS key parameter health value.

[0033] For each IaaS key parameter that has obtained actual data and belongs to the second IaaS category, perform the following operations:

[0034] Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database;

[0035] The health value of the IaaS key parameter corresponding to the range of the actual data is used as the health value of the IaaS key parameter.

[0036] When the IaaS key parameter type is the first IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0037] The following formula is used to obtain the health value of each IaaS key parameter belonging to the first IaaS category:

[0038] Actual data for 1-IaaS key parameters.

[0039] Optionally, the system operation detection method based on key operation and maintenance parameters includes:

[0040] The system operation detection method based on key operation and maintenance parameters includes:

[0041] Obtain the PaaS key parameter type for each PaaS key parameter, wherein the PaaS key parameter type includes a first PaaS type and a second PaaS type;

[0042] When the PaaS key parameter type is the second PaaS type, assigning a PaaS key parameter health value to each PaaS key parameter based on the actual data of each PaaS key parameter includes:

[0043] Obtain the PaaS key parameter database, which includes multiple PaaS key parameter sub-databases. Each PaaS key parameter sub-database includes a PaaS key parameter name, at least one PaaS key parameter range value, and a PaaS key parameter health value; wherein, one PaaS key parameter range value corresponds to one PaaS key parameter health value.

[0044] For each PaaS key parameter that has obtained actual data and belongs to the second PaaS category, perform the following operations:

[0045] Retrieve the PaaS key parameter sub-database containing the PaaS key parameter name that is identical to the PaaS key parameter name in the PaaS key parameter database;

[0046] The PaaS key parameter health value corresponding to the PaaS key parameter range value where the actual data is located is obtained as the PaaS key parameter health value of that PaaS key parameter.

[0047] When the PaaS key parameter type is the first PaaS type, assigning a PaaS key parameter health value to each PaaS key parameter based on the actual data of each PaaS key parameter includes:

[0048] The following formulas are used to obtain the health value of each PaaS key parameter belonging to the first PaaS category:

[0049] Actual data for key parameters of 1-PaaS.

[0050] Optionally, the system operation detection method based on key operation and maintenance parameters includes:

[0051] The system operation detection method based on key operation and maintenance parameters includes:

[0052] The process of assigning a health value to each IaaS key parameter based on its actual data includes:

[0053] Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one PaaS key parameter range value, and an IaaS key parameter health value. Among them, one IaaS key parameter range value corresponds to one IaaS key parameter health value.

[0054] For each key IaaS parameter for which actual data has been obtained, perform the following operations:

[0055] Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database;

[0056] The health value of the IaaS key parameter corresponding to the range of the actual data is obtained as the health value of the IaaS key parameter.

[0057] Optionally, obtaining the final health score based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter includes:

[0058] Clustering of each IaaS key parameter yields multiple sets of IaaS key parameter groups;

[0059] Cluster the key parameters of each PaaS to obtain multiple sets of key parameters of PaaS;

[0060] Cluster the key parameters of each SaaS to obtain multiple sets of key SaaS parameters;

[0061] Based on the obtained health value of each IaaS key parameter, obtain the health value of each group of IaaS key parameter groups.

[0062] Based on the obtained health value of each PaaS key parameter, obtain the health value of each PaaS key parameter group.

[0063] Based on the obtained health value of each SaaS key parameter, obtain the health value of each group of SaaS key parameter groups;

[0064] The final health score is obtained based on the health scores of the IaaS key parameter groups, the PaaS key parameter groups, and the SaaS key parameter groups for each group of IaaS key parameters.

[0065] Optionally, the system operation detection method based on key operation and maintenance parameters further includes:

[0066] Determine whether the final health score exceeds a preset threshold; if so, then...

[0067] Generate an alarm signal.

[0068] This application also provides a system operation detection device based on key operation and maintenance parameters, the system operation detection device based on key operation and maintenance parameters includes:

[0069] The acquisition module is used to acquire IaaS key parameter groups, PaaS key parameter groups, and SaaS key parameter groups. The IaaS key parameter group includes at least one IaaS key parameter, the PaaS key parameter group includes at least one PaaS key parameter, and the SaaS key parameter group includes at least one SaaS key parameter.

[0070] The IaaS key parameter data acquisition module is used to acquire the actual data of each IaaS key parameter during actual operation.

[0071] The PaaS key parameter data acquisition module is used to acquire the actual data of each PaaS key parameter during actual operation.

[0072] A SaaS key parameter data acquisition module is used to acquire the actual data of each SaaS key parameter during actual operation.

[0073] The IaaS key parameter health value assignment module is used to assign an IaaS key parameter health value to each IaaS key parameter according to the actual data of each IaaS key parameter.

[0074] The PaaS key parameter health value assignment module is used to assign a PaaS key parameter health value to each PaaS key parameter according to the actual data of each PaaS key parameter.

[0075] The SaaS key parameter health value assignment module is used to assign a SaaS key parameter health value to each SaaS key parameter based on the actual data of each SaaS key parameter.

[0076] The final health score acquisition module is used to acquire the final health score based on the health score values ​​of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter.

[0077] The system operation detection method based on key operation and maintenance parameters of this application comprehensively judges the running system based on key operation parameters of IaaS, PaaS, and SaaS to predict whether the system may have problems. Compared with the existing technology, this application comprehensively considers the key parameters of IaaS, PaaS, and SaaS, thus making the prediction more accurate. Attached Figure Description

[0078] Figure 1 This is a flowchart illustrating a system operation detection method based on key operation and maintenance parameters according to an embodiment of this application.

[0079] Figure 2 It is used to implement Figure 1 The diagram shows an electronic device for a system operation detection method based on key operation and maintenance parameters. Detailed Implementation

[0080] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] Figure 1 This is a flowchart illustrating a system operation detection method based on key operation and maintenance parameters according to an embodiment of this application.

[0082] like Figure 1 The system operation detection methods based on key operation and maintenance parameters shown include:

[0083] Step 1: Obtain the IaaS key parameter group, PaaS key parameter group, and SaaS key parameter group. The IaaS key parameter group includes at least one IaaS key parameter, the PaaS key parameter group includes at least one PaaS key parameter, and the SaaS key parameter group includes at least one SaaS key parameter.

[0084] Step 2: Obtain the actual data for each key IaaS parameter during actual runtime;

[0085] Step 3: Obtain the actual data for each key PaaS parameter during actual runtime;

[0086] Step 4: Obtain actual data for each key SaaS parameter during actual runtime;

[0087] Step 5: Assign a health value to each IaaS key parameter based on the actual data of each IaaS key parameter;

[0088] Step 6: Assign a PaaS health value to each PaaS key parameter based on the actual data of each PaaS key parameter;

[0089] Step 7: Assign a health value to each SaaS key parameter based on the actual data of each SaaS key parameter;

[0090] Step 8: Obtain the final health score based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter.

[0091] The system operation detection method based on key operation and maintenance parameters of this application comprehensively judges the running system based on key operation parameters of IaaS, PaaS, and SaaS to predict whether the system may have problems. Compared with the existing technology, this application comprehensively considers the key parameters of IaaS, PaaS, and SaaS, thus making the prediction more accurate.

[0092] In this embodiment, before obtaining the actual data of each IaaS key parameter during actual operation, the system operation detection method based on operation and maintenance key parameters further includes:

[0093] Select multiple IaaS key parameters from the IaaS key parameter group;

[0094] Select multiple PaaS key parameters from the PaaS key parameter group;

[0095] Select multiple SaaS key parameters from the SaaS key parameter group.

[0096] In this embodiment, the key IaaS parameters include:

[0097] Real-time data for bare metal server CPU utilization, bare metal server memory utilization, bare metal server disk utilization, bare metal server disk I / O read / write rate, bare metal server network I / O read / write rate, host machine CPU utilization, host machine memory utilization, host machine disk utilization, host machine disk I / O read / write rate, host machine network I / O read / write rate, switching device CPU utilization, switching device memory utilization, switching device disk utilization, switching device transmission rate, switching device inbound and outbound traffic, security device CPU utilization, security device memory utilization, security device disk utilization, and real-time data for the number of abnormal behaviors of security devices;

[0098] The key parameters of the PaaS include:

[0099] Real-time data for the following database metrics: current number of SQL statements being executed, number of slow queries, number of table lock waits, current number of connections, number of connections not properly closed, total number of PostgreSQL connections, number of PostgreSQL sessions, number of slow queries, number of PostgreSQL deadlocks, Redis memory usage, number of Redis clients connected, number of Redis slave connections, Redis memory fragmentation rate, number of Redis connection rejections, number of Redis key lookup failures, number of Redis key removals, number of Kafka brokers, cumulative number of Kafka messages, Kafka memory usage, Kafka disk usage, number of Kafka consumers, and number of Kafka queues. Real-time data for Elasticsearch (ES), including: number of ES shards, current ES queries, ES memory usage, ES garbage collection counts, ES CPU utilization, real-time ES node health status, current MongoDB connections, MongoDB CPU utilization, MongoDB memory utilization, MongoDB cluster replica status, MongoDB collective heartbeat data, number of NGINX processes, Nginx active connections, Nginx waiting connections, Starrocks CPU utilization, Starrocks memory utilization, Starrocks disk utilization, Starrocks cluster QPS, operating system CPU utilization, operating system memory utilization, operating system disk utilization, operating system maximum connections, and operating system active processes.

[0100] The key parameters of the SaaS include:

[0101] Detect application liveness, port connectivity, Docker liveness, monitor interface status, and use Skywalking for APM monitoring.

[0102] In this embodiment, the system operation detection method based on key operation and maintenance parameters includes:

[0103] Obtain the IaaS key parameter type for each IaaS key parameter, wherein the IaaS key parameter type includes a first IaaS class and a second IaaS class;

[0104] When the IaaS key parameter type is the second IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0105] Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one IaaS key parameter range value, and an IaaS key parameter health value; wherein, one IaaS key parameter range value corresponds to one IaaS key parameter health value.

[0106] For each IaaS key parameter that has obtained actual data and belongs to the second IaaS category, perform the following operations:

[0107] Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database;

[0108] The health value of the IaaS key parameter corresponding to the range of the actual data is used as the health value of the IaaS key parameter.

[0109] When the IaaS key parameter type is the first IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0110] The following formula is used to obtain the health value of each IaaS key parameter belonging to the first IaaS category:

[0111] Actual data for 1-IaaS key parameters.

[0112] In this embodiment, the system operation detection method based on key operation and maintenance parameters includes:

[0113] The system operation detection method based on key operation and maintenance parameters includes:

[0114] Obtain the PaaS key parameter type for each PaaS key parameter, wherein the PaaS key parameter type includes a first PaaS type and a second PaaS type;

[0115] When the PaaS key parameter type is the second PaaS type, assigning a PaaS key parameter health value to each PaaS key parameter based on the actual data of each PaaS key parameter includes:

[0116] Obtain the PaaS key parameter database, which includes multiple PaaS key parameter sub-databases. Each PaaS key parameter sub-database includes a PaaS key parameter name, at least one PaaS key parameter range value, and a PaaS key parameter health value; wherein, one PaaS key parameter range value corresponds to one PaaS key parameter health value.

[0117] For each PaaS key parameter that has obtained actual data and belongs to the second PaaS category, perform the following operations:

[0118] Retrieve the PaaS key parameter sub-database containing the PaaS key parameter name that is identical to the PaaS key parameter name in the PaaS key parameter database;

[0119] The PaaS key parameter health value corresponding to the PaaS key parameter range value where the actual data is located is obtained as the PaaS key parameter health value of that PaaS key parameter.

[0120] When the PaaS key parameter type is the first PaaS type, assigning a PaaS key parameter health value to each PaaS key parameter based on the actual data of each PaaS key parameter includes:

[0121] The following formulas are used to obtain the health value of each PaaS key parameter belonging to the first PaaS category:

[0122] Actual data for key parameters of 1-PaaS.

[0123] In this embodiment, the system operation detection method based on key operation and maintenance parameters includes:

[0124] The system operation detection method based on key operation and maintenance parameters includes:

[0125] The process of assigning a health value to each IaaS key parameter based on its actual data includes:

[0126] Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one PaaS key parameter range value, and an IaaS key parameter health value. Among them, one IaaS key parameter range value corresponds to one IaaS key parameter health value.

[0127] For each key IaaS parameter for which actual data has been obtained, perform the following operations:

[0128] Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database;

[0129] The health value of the IaaS key parameter corresponding to the range of the actual data is obtained as the health value of the IaaS key parameter.

[0130] In this embodiment, obtaining the final health score based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter includes:

[0131] Clustering of each IaaS key parameter yields multiple sets of IaaS key parameter groups;

[0132] Cluster the key parameters of each PaaS to obtain multiple sets of key parameters of PaaS;

[0133] Clustering of each IaaS key parameter yields multiple sets of IaaS key parameter groups;

[0134] Based on the obtained health value of each IaaS key parameter, obtain the health value of each group of IaaS key parameter groups.

[0135] Based on the obtained health value of each PaaS key parameter, obtain the health value of each PaaS key parameter group.

[0136] Based on the obtained health value of each IaaS key parameter, obtain the health value of each group of IaaS key parameter groups.

[0137] The final health score is obtained based on the health scores of the IaaS key parameter groups, the PaaS key parameter groups, and the IaaS key parameter groups for each group of IaaS key parameter groups.

[0138] In this embodiment, the system operation detection method based on key operation and maintenance parameters further includes:

[0139] Determine whether the final health score exceeds a preset threshold; if so, then...

[0140] Generate an alarm signal.

[0141] The following examples further illustrate this application in detail. It is understood that these examples do not constitute any limitation on this application.

[0142] In this embodiment, the key parameters of IaaS, PaaS, and SaaS of this application are specifically shown in Table 1 below:

[0143]

[0144]

[0145]

[0146] In this embodiment, the types of key IaaS parameters include a first IaaS class and a second IaaS class;

[0147] When the IaaS key parameter type is the second IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0148] Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one IaaS key parameter range value, and an IaaS key parameter health value; wherein, one IaaS key parameter range value corresponds to one IaaS key parameter health value.

[0149] For each IaaS key parameter that has obtained actual data and belongs to the second IaaS category, perform the following operations:

[0150] Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database;

[0151] The health value of the IaaS key parameter corresponding to the range of the actual data is used as the health value of the IaaS key parameter.

[0152] When the IaaS key parameter type is the first IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0153] The following formula is used to obtain the health value of each IaaS key parameter belonging to the first IaaS category:

[0154] Actual data for 1-IaaS key parameters.

[0155] In this embodiment, the parameters of the first IaaS class are as follows:

[0156] Bare metal server CPU utilization, bare metal server memory utilization, bare metal server disk utilization, host machine CPU utilization, host machine memory utilization, host machine disk utilization, switch device CPU utilization, switch device memory utilization, switch device disk utilization, security device CPU utilization, security device memory utilization, security device disk utilization.

[0157] In this embodiment, the other key IaaS parameters are second IaaS class parameters.

[0158] The IaaS key parameter database includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one IaaS key parameter range value, and an IaaS key parameter health value.

[0159] For example, an IaaS key parameter sub-library (hereinafter referred to as Sub-library A) includes the following:

[0160] Key IaaS parameters: Bare metal server network I / O read / write speed;

[0161] Key IaaS parameter ranges: 1-30; 31-50; 51-100.

[0162] Key IaaS health values: 1, 0.6, -3.

[0163] In this embodiment, a range of IaaS key parameters corresponds to an IaaS key parameter health value. For example, 1-30 corresponds to an IaaS key parameter health value of 1, 31-50 corresponds to an IaaS key parameter health value of 0.6, and 51-100 corresponds to an IaaS key parameter health value of -3.

[0164] In this embodiment, the IaaS key parameter sub-database containing the IaaS key parameter name that is the same as the IaaS key parameter name is obtained from the IaaS key parameter database.

[0165] For example, a comparison reveals that the bare metal server's network I / O read / write speed has the same name as the key IaaS parameter in sub-library A.

[0166] Retrieve the sub-database of IaaS key parameters containing the same IaaS key parameter name as the given IaaS key parameter in the IaaS key parameter database; that is, retrieve sub-database A.

[0167] The health value of the IaaS key parameter corresponding to the range of the actual data is obtained as the health value of the IaaS key parameter.

[0168] Assuming the actual data is 35, then by comparison it is found to be within the range of 31-50, so the score corresponding to 31-50 is 0.6.

[0169] When the IaaS key parameter type is the first IaaS category, the step of assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes:

[0170] The following formula is used to obtain the health value of each IaaS key parameter belonging to the first IaaS category:

[0171] Actual data for 1-IaaS key parameters.

[0172] For example, if the CPU utilization of a bare metal server is 0.8, then 1 - 0.8 = 0.2, so the health value of the IaaS key parameter of the bare metal server's CPU utilization is 0.2.

[0173] The calculation methods for the health values ​​of PaaS key parameters and IaaS key parameters are the same as those for IaaS key parameters, and will not be repeated here.

[0174] In this embodiment, after obtaining the health values ​​of all IaaS key parameters, PaaS key parameters, and SaaS key parameters, the final health score is obtained based on the health value of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter, including:

[0175] Clustering of each IaaS key parameter yields multiple IaaS key parameter groups, as shown in Table 1 above. Table 1 shows that server CPU utilization, memory utilization, disk utilization, etc., all belong to bare metal servers, thus bare metal servers constitute one group of IaaS key parameter groups.

[0176] In this embodiment, the health value of each IaaS key parameter group is obtained based on the obtained health value of each IaaS key parameter.

[0177] For example, the health value of the IaaS key parameter group for bare metal servers can be obtained using the following formula:

[0178] ((1-Server CPU utilization)+(1-Server memory utilization)+(1-Server disk utilization)+(1-Server memory utilization)+(Server network I / O read / write rate: 0.6 (obtained by comparison with IaaS key parameter sub-library)) / 5.

[0179] Similarly, obtain the corresponding health value for each IaaS key parameter group, PaaS key parameter group, and IaaS key parameter group.

[0180] After obtaining the corresponding health values ​​for each IaaS key parameter group and PaaS key parameter group, the final health score is obtained using the following formula:

[0181] ((Sum of health values ​​of each IaaS key parameter group divided by the number of groups) + (Sum of health values ​​of each PaaS key parameter group divided by the number of groups) + (Sum of health values ​​of each SaaS key parameter group divided by the number of groups)) / 3.

[0182] The detailed expressions are shown below using the key parameters listed in Table 1:

[0183] The sum of the health values ​​of each group of IaaS key parameters, divided by the number of groups, is as follows (for ease of explanation, F1 will be used below):

[0184] (((1-Bare Metal Server CPU Utilization)+(1-Bare Metal Server Memory Utilization)+(1-Bare Metal Server Disk Utilization)+(1-Bare Metal Server Memory Utilization)+(Bare Metal Server Network I / O Read / Write Rate: Obtained through IaaS Key Parameter Sub-library)) / 5+((1-Host CPU Utilization)+(1-Host Memory Utilization)+(1-Host Disk Utilization)+(1-Host Memory Utilization)+((Host Network I / O Read / Write Rate: Obtained through IaaS Key Parameter Sub-library)) / 5+((1-Host CPU Utilization)+(1-Host Memory ...(Host Network I / O Read / Write Rate: Obtained through IaaS Key Parameter Sub-library)) / 5+((1-Host CPU Utilization)+(1-Host Memory Utilization)+((Host Network I / O Read / Write Rate: Obtained through IaaS Key Parameter Sub-library)) / 5+((1-Host CPU Utilization)+(1-Host Memory Utilization)+(1-Host Disk Utilization)+((Host Network I / O Read / Write Rate: Obtained through IaaS Key Parameter Sub-library)) / 5+((1-Host CPU Utilization)+(1-Host Memory Utilization)+((Host Network I / O Read / Write Rate: Obtained through IaaS Key Parameter Sub-library) / 5+((1-Host CPU Utilization)+(1-Host (Reference from the database) / 5+((1-Switching device CPU utilization)+(1-Switching device memory utilization)+(1-Switching device disk utilization)+(Switching device transfer rate: obtained through reference from the IaaS key parameter sub-database)+(Real-time data of switching device inbound and outbound traffic: obtained through reference from the IaaS key parameter sub-database)) / 5+((1-Security device CPU utilization)+(1-Security device memory utilization)+(1-Security device disk utilization)+(Real-time data of the number of abnormal behaviors: obtained through reference from the IaaS key parameter sub-database)) / 4) / 4;

[0185] The sum of the health values ​​of each PaaS key parameter group divided by the number of groups is as follows (for ease of explanation, F2 will be used below):

[0186] (((Current number of SQL statements executed in the database: <Normal value: obtained by comparing with the PaaS key parameter sub-database)+(Number of slow queries in the database: obtained by comparing with the PaaS key parameter sub-database)+(Number of table lock waits in the database: obtained by comparing with the PaaS key parameter sub-database)+(Current number of database connections: obtained by comparing with the PaaS key parameter sub-database)+(Real-time data on the number of database connections not closed properly: obtained by comparing with the PaaS key parameter sub-database)) / 5+((Total number of PostgreSQL connections: obtained by comparing with the PaaS key parameter sub-database)+(PostgreSQL Session count: obtained by comparing with PaaS key parameter sub-database) + (Postgresql slow query count: obtained by comparing with PaaS key parameter sub-database) + (Real-time data on PostgreSQL deadlock count: obtained by comparing with PaaS key parameter sub-database)) / 4 + ((Redis used memory rate: obtained by comparing with PaaS key parameter sub-database) + (Redis connected client count: obtained by comparing with PaaS key parameter sub-database) + (Redis slave connection count: obtained by comparing with PaaS key parameter sub-database) + (Redis memory fragmentation rate: obtained by comparing with PaaS key parameter sub-database) + (Redis connection refused count: obtained by comparing with PaaS key parameter sub-database) + (Redis key lookup failure count: obtained by comparing with PaaS key parameter sub-database) + (Real-time data on Redis key removal count: obtained by comparing with PaaS key parameter sub-database)) / 7 + ((Kafka) Number of brokers: obtained by referring to the PaaS key parameter sub-database) + (1 - Kafka memory usage) + (1 - Kafka disk usage) + (Number of Kafka consumers: obtained by referring to the PaaS key parameter sub-database) + (Real-time data on the number of Kafka queues: obtained by referring to the PaaS key parameter sub-database)) / 6 + ((Number of Elasticsearch shards: obtained by referring to the PaaS key parameter sub-database) + (Current number of Elasticsearch queries: obtained by referring to the PaaS key parameter sub-database) + (Elasticsearch memory usage: obtained by referring to the PaaS key parameter sub-database) + (Elasticsearch garbage collection count: obtained by referring to the PaaS key parameter sub-database) + (Real-time data on Elasticsearch node health status: obtained by referring to the PaaS key parameter sub-database) + (1 - escup usage)) / 6 + ((Current number of MongoDB connections: <normal value: obtained by referring to the PaaS key parameter sub-database) + (1 - MongoDB connections)(cup utilization) + (1 - MongoDB memory utilization) + (MongoDB cluster replica status: obtained through PaaS key parameter sub-database) + (Real-time data of MongoDB collective heartbeat: obtained through PaaS key parameter sub-database)) / 5 + ((Number of NGINX processes: obtained through PaaS key parameter sub-database) + (Number of active NGINX connections: obtained through PaaS key parameter sub-database) + (Real-time data of NGINX waiting connections: obtained through PaaS key parameter sub-database)) / 3 + ((1 - Starrocks CPU utilization) + (1 - Starrocks memory utilization) + (1 - Starrocks disk utilization) + (Real-time data of Starrocks cluster QPS: obtained by comparison through PaaS key parameter sub-library)) / 4 + ((1 - Operating system CPU utilization) + (1 - Operating system memory utilization) + (1 - Operating system disk utilization) + (Maximum number of connections of operating system: obtained by comparison through PaaS key parameter sub-library) + (Number of active processes of operating system: obtained by comparison through PaaS key parameter sub-library)) / 5) / 9;

[0187] The sum of the health values ​​of each SaaS key parameter group divided by the number of groups is as follows (for ease of explanation, F3 will be used below):

[0188] ((Detecting application liveness: <Normal value: obtained by comparison with SaaS key parameter sub-database)+(Detecting port connectivity: obtained by comparison with SaaS key parameter sub-database)+(Detecting Docker liveness: obtained by comparison with SaaS key parameter sub-database)+(Monitoring interface status: obtained by comparison with SaaS key parameter sub-database)+(Using Skywalking to monitor APM running number: obtained by comparison with SaaS key parameter sub-database)) / 5.

[0189] In this embodiment, the final health score is:

[0190] (F1+F2+F3) / 3.

[0191] This application also provides a system operation detection device based on key operation and maintenance parameters. The device includes an acquisition module, an IaaS key parameter data acquisition module, a PaaS key parameter data acquisition module, a SaaS key parameter data acquisition module, an IaaS key parameter health value assignment module, a PaaS key parameter health value assignment module, a SaaS key parameter health value assignment module, and a final health score acquisition module.

[0192] The acquisition module is used to acquire IaaS key parameter groups, PaaS key parameter groups, and SaaS key parameter groups. The IaaS key parameter group includes at least one IaaS key parameter, the PaaS key parameter group includes at least one PaaS key parameter, and the SaaS key parameter group includes at least one SaaS key parameter.

[0193] The IaaS key parameter data acquisition module is used to acquire the actual data of each IaaS key parameter during actual runtime.

[0194] The PaaS key parameter data acquisition module is used to acquire the actual data of each PaaS key parameter during actual runtime.

[0195] The SaaS key parameter data acquisition module is used to acquire the actual data of each SaaS key parameter during actual operation.

[0196] The IaaS key parameter health value assignment module is used to assign a health value to each IaaS key parameter based on the actual data of each IaaS key parameter.

[0197] The PaaS key parameter health value assignment module is used to assign a PaaS key parameter health value to each PaaS key parameter according to the actual data of each PaaS key parameter.

[0198] The SaaS key parameter health value assignment module is used to assign a SaaS key parameter health value to each SaaS key parameter based on the actual data of each SaaS key parameter.

[0199] The final health score acquisition module is used to obtain the final health score based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter.

[0200] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and will not be repeated here.

[0201] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, it implements the above-mentioned system operation detection method based on key operation and maintenance parameters.

[0202] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the above-described system operation detection method based on key operation and maintenance parameters.

[0203] Figure 2This is an exemplary structural diagram of an electronic device capable of implementing a system operation detection method based on key operation and maintenance parameters provided in one embodiment of this application.

[0204] like Figure 2 As shown, the electronic device includes an input device 501, an input interface 502, a central processing unit 503, a memory 504, an output interface 505, and an output device 506. The input interface 502, central processing unit 503, memory 504, and output interface 505 are interconnected via a bus 507. The input device 501 and output device 506 are connected to the bus 507 via the input interface 502 and output interface 505, respectively, and thus connected to other components of the electronic device. Specifically, the input device 504 receives input information from the outside and transmits it to the central processing unit 503 via the input interface 502. The central processing unit 503 processes the input information based on computer-executable instructions stored in the memory 504 to generate output information, temporarily or permanently storing the output information in the memory 504, and then transmitting the output information to the output device 506 via the output interface 505. The output device 506 outputs the output information to the outside of the electronic device for user use.

[0205] In other words, Figure 2 The illustrated electronic device may also be implemented as including: a memory storing computer-executable instructions; and one or more processors, which can be coupled when executing the computer-executable instructions. Figure 1 The method described is a system operation detection method based on key operation and maintenance parameters.

[0206] In one embodiment, Figure 2 The electronic device shown can be implemented as including: a memory 504 configured to store executable program code; and one or more processors 503 configured to run the executable program code stored in the memory 504 to execute the system operation detection method based on key operation and maintenance parameters in the above embodiments.

[0207] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0208] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0209] Computer-readable media include both permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, DVD or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0210] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0211] Furthermore, it is clear that the word "comprising" does not exclude other units or steps. Multiple units, modules, or devices recited in the apparatus claims may also be implemented by a single unit or overall apparatus via software or hardware.

[0212] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutively marked blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or the overall flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0213] In this embodiment, the processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0214] Memory can be used to store computer programs and / or modules. The processor implements various functions of the device / terminal equipment by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area can store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). In addition, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0215] In this embodiment, if the modules / units integrated into the device / terminal equipment are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of this application. Therefore, the scope of protection of this application should be determined by the scope defined in the claims of this application.

[0216] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0217] Furthermore, it is clear that the word "comprising" does not exclude other units or steps. Multiple units, modules, or devices recited in the apparatus claims may also be implemented by a single unit or overall apparatus via software or hardware.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A system operation detection method based on key operation and maintenance parameters, characterized in that, The system operation detection method based on key operation and maintenance parameters includes: Obtain IaaS key parameter group, PaaS key parameter group, and SaaS key parameter group, wherein the IaaS key parameter group includes at least one IaaS key parameter, the PaaS key parameter group includes at least one PaaS key parameter, and the SaaS key parameter group includes at least one SaaS key parameter; Obtain actual data for each key IaaS parameter during actual runtime; Obtain actual data for each key PaaS parameter during actual runtime; Obtain actual data for each key parameter of each SaaS during actual runtime; Assign a health value to each IaaS key parameter based on the actual data of each IaaS key parameter. Assign a PaaS health value to each PaaS key parameter based on the actual data of each PaaS key parameter. Assign a health value to each SaaS key parameter based on the actual data of each SaaS key parameter; The final health score is obtained based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter.

2. The system operation detection method based on key operation and maintenance parameters as described in claim 1, characterized in that, Before obtaining the actual data of each key IaaS parameter during actual operation, the system operation detection method based on key operation and maintenance parameters further includes: Select multiple IaaS key parameters from the IaaS key parameter group; Select multiple PaaS key parameters from the PaaS key parameter group; Select multiple SaaS key parameters from the SaaS key parameter group.

3. The system operation detection method based on key operation and maintenance parameters as described in claim 2, characterized in that, The key parameters of IaaS include: Real-time data for bare metal server CPU utilization, bare metal server memory utilization, bare metal server disk utilization, bare metal server disk I / O read / write rate, bare metal server network I / O read / write rate, host machine CPU utilization, host machine memory utilization, host machine disk utilization, host machine disk I / O read / write rate, host machine network I / O read / write rate, switching device CPU utilization, switching device memory utilization, switching device disk utilization, switching device transmission rate, switching device inbound and outbound traffic, security device CPU utilization, security device memory utilization, security device disk utilization, and real-time data for the number of abnormal behaviors of security devices; The key parameters of the PaaS include: Real-time data for the following database metrics: current number of SQL statements being executed, number of slow queries, number of table lock waits, current number of connections, number of connections not properly closed, total number of PostgreSQL connections, number of PostgreSQL sessions, number of slow queries, number of PostgreSQL deadlocks, Redis memory usage, number of Redis clients connected, number of Redis slave connections, Redis memory fragmentation rate, number of Redis connection rejections, number of Redis key lookup failures, number of Redis key removals, number of Kafka brokers, cumulative number of Kafka messages, Kafka memory usage, Kafka disk usage, number of Kafka consumers, and number of Kafka queues. Real-time data for Elasticsearch (ES), including: number of ES shards, current ES queries, ES memory usage, ES garbage collection counts, ES CPU utilization, real-time ES node health status, current MongoDB connections, MongoDB CPU utilization, MongoDB memory utilization, MongoDB cluster replica status, MongoDB collective heartbeat data, number of NGINX processes, Nginx active connections, Nginx waiting connections, Starrocks CPU utilization, Starrocks memory utilization, Starrocks disk utilization, Starrocks cluster QPS, operating system CPU utilization, operating system memory utilization, operating system disk utilization, operating system maximum connections, and operating system active processes. The key parameters of the SaaS include: Detect application liveness, port connectivity, Docker liveness, monitor interface status, and use Skywalking for APM monitoring.

4. The system operation detection method based on key operation and maintenance parameters as described in claim 3, characterized in that, The system operation detection method based on key operation and maintenance parameters includes: Obtain the IaaS key parameter type for each IaaS key parameter, wherein the IaaS key parameter type includes a first IaaS class and a second IaaS class; When the IaaS key parameter type is the second IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes: Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one IaaS key parameter range value, and an IaaS key parameter health value; wherein, one IaaS key parameter range value corresponds to one IaaS key parameter health value. For each IaaS key parameter that has obtained actual data and belongs to the second IaaS category, perform the following operations: Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database; The health value of the IaaS key parameter corresponding to the range of the actual data is used as the health value of the IaaS key parameter. When the IaaS key parameter type is the first IaaS type, assigning an IaaS key parameter health value to each IaaS key parameter based on the actual data of each IaaS key parameter includes: The following formula is used to obtain the health value of each IaaS key parameter belonging to the first IaaS category: Actual data for 1-IaaS key parameters.

5. The system operation detection method based on key operation and maintenance parameters as described in claim 4, characterized in that, The system operation detection method based on key operation and maintenance parameters includes: The system operation detection method based on key operation and maintenance parameters includes: Obtain the PaaS key parameter type for each PaaS key parameter, wherein the PaaS key parameter type includes a first PaaS type and a second PaaS type; When the PaaS key parameter type is the second PaaS type, assigning a PaaS key parameter health value to each PaaS key parameter based on the actual data of each PaaS key parameter includes: Obtain the PaaS key parameter database, which includes multiple PaaS key parameter sub-databases. Each PaaS key parameter sub-database includes a PaaS key parameter name, at least one PaaS key parameter range value, and a PaaS key parameter health value; wherein, one PaaS key parameter range value corresponds to one PaaS key parameter health value. For each PaaS key parameter that has obtained actual data and belongs to the second PaaS category, perform the following operations: Retrieve the PaaS key parameter sub-database containing the PaaS key parameter name that is identical to the PaaS key parameter name in the PaaS key parameter database; The PaaS key parameter health value corresponding to the PaaS key parameter range value where the actual data is located is obtained as the PaaS key parameter health value of that PaaS key parameter. When the PaaS key parameter type is the first PaaS type, assigning a PaaS key parameter health value to each PaaS key parameter based on the actual data of each PaaS key parameter includes: The following formulas are used to obtain the health value of each PaaS key parameter belonging to the first PaaS category: Actual data for key parameters of 1-PaaS.

6. The system operation detection method based on key operation and maintenance parameters as described in claim 5, characterized in that, The system operation detection method based on key operation and maintenance parameters includes: The system operation detection method based on key operation and maintenance parameters includes: The process of assigning a health value to each IaaS key parameter based on its actual data includes: Obtain the IaaS key parameter database, which includes multiple IaaS key parameter sub-databases. Each IaaS key parameter sub-database includes an IaaS key parameter name, at least one PaaS key parameter range value, and an IaaS key parameter health value. Among them, one IaaS key parameter range value corresponds to one IaaS key parameter health value. For each key IaaS parameter for which actual data has been obtained, perform the following operations: Retrieve the IaaS key parameter sub-database containing the IaaS key parameter name that has the same name as the given IaaS key parameter in the IaaS key parameter database; The health value of the IaaS key parameter corresponding to the range of the actual data is obtained as the health value of the IaaS key parameter.

7. The system operation detection method based on key operation and maintenance parameters as described in claim 6, characterized in that, The process of obtaining the final health score based on the health scores of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter includes: Clustering of each IaaS key parameter yields multiple sets of IaaS key parameter groups; Cluster the key parameters of each PaaS to obtain multiple sets of key parameters of PaaS; Cluster the key parameters of each SaaS to obtain multiple sets of key SaaS parameters; Based on the obtained health value of each IaaS key parameter, obtain the health value of each group of IaaS key parameter groups. Based on the obtained health value of each PaaS key parameter, obtain the health value of each PaaS key parameter group. Based on the obtained health value of each SaaS key parameter, obtain the health value of each group of SaaS key parameter groups; The final health score is obtained based on the health scores of the IaaS key parameter groups, the PaaS key parameter groups, and the SaaS key parameter groups for each group of IaaS key parameters.

8. The system operation detection method based on key operation and maintenance parameters as described in any one of claims 1 to 7, characterized in that, The system operation detection method based on key operation and maintenance parameters further includes: Determine whether the final health score exceeds a preset threshold; if so, then... Generate an alarm signal.

9. A system operation detection device based on key operation and maintenance parameters, characterized in that, The system operation detection device based on key operation and maintenance parameters includes: The acquisition module is used to acquire IaaS key parameter groups, PaaS key parameter groups, and SaaS key parameter groups. The IaaS key parameter group includes at least one IaaS key parameter, the PaaS key parameter group includes at least one PaaS key parameter, and the SaaS key parameter group includes at least one SaaS key parameter. The IaaS key parameter data acquisition module is used to acquire the actual data of each IaaS key parameter during actual operation. The PaaS key parameter data acquisition module is used to acquire the actual data of each PaaS key parameter during actual operation. A SaaS key parameter data acquisition module is used to acquire the actual data of each SaaS key parameter during actual operation. The IaaS key parameter health value assignment module is used to assign an IaaS key parameter health value to each IaaS key parameter according to the actual data of each IaaS key parameter. The PaaS key parameter health value assignment module is used to assign a PaaS key parameter health value to each PaaS key parameter according to the actual data of each PaaS key parameter. The SaaS key parameter health value assignment module is used to assign a SaaS key parameter health value to each SaaS key parameter based on the actual data of each SaaS key parameter. The final health score acquisition module is used to acquire the final health score based on the health score values ​​of each IaaS key parameter, each PaaS key parameter, and each SaaS key parameter.

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