Cluster intelligent processing method and device based on automatic perception

Abstract

The present invention discloses a cluster intelligent processing method and device based on automatic perception, the method comprising: obtaining the grid business parameters of the target grid, determining the data change information of the target grid within a preset time period according to the grid business parameters; determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions; and performing processing operations matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information. It can be seen that the implementation of the present invention can realize rapid perception and rapid response of clusters based on automatic perception technology to dispatch resources to serve each cluster, which is conducive to improving the intelligence of processing clusters and the accuracy of processing clusters.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a cluster intelligent processing method and device based on automatic perception. Background Art

[0002] With the continuous leap forward of information technology, Internet technology is also developing rapidly, and cluster management is increasingly widely used in the field of information technology. Cluster management is relative to distributed management, which is to deploy a system into multiple copies, each of which is an instance of the system and provides the same services to the outside world. However, the current cluster management can only scale the service cluster according to common hardware indicators such as memory and CPU, and cannot manage newly added clusters when the business is expanded or increased. It can be seen that it is particularly important to provide a new cluster processing method to improve the intelligence and accuracy of cluster processing. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a cluster intelligent processing method and device based on automatic perception, which can realize rapid perception and rapid response of clusters based on automatic perception technology to schedule resources to serve each cluster, which is conducive to improving the intelligence of the processing cluster and the accuracy of the processing cluster.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a cluster intelligent processing method based on automatic perception, the method comprising:

[0005] Acquire power grid service parameters of the target power grid, and determine data change information of the target power grid within a preset time period according to the power grid service parameters;

[0006] Based on the data change information and in combination with preset power grid data conditions, determine the power grid configuration information of the target power grid;

[0007] According to the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

[0008] As an optional implementation manner, in the first aspect of the present invention, before determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data condition, the method further includes:

[0009] Determining a data change trend of the target power grid according to the data change information, wherein the data change trend includes a power grid resource change trend of the target power grid;

[0010] Determining whether the data change trend is used to indicate that the grid resources of the target grid are on a downward trend;

[0011] When it is determined that the data change trend is used to indicate that the grid resources of the target grid are in the downward trend, determining the business service parameters of the target grid according to the data change trend and preset system resources;

[0012] The determining the grid configuration information of the target grid based on the data change information and in combination with preset grid data conditions includes:

[0013] Based on the business service parameters and in combination with preset power grid data conditions, the power grid configuration information of the target power grid is determined.

[0014] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0015] When it is determined that the data change trend is used to indicate that the grid resources of the target grid are on an upward trend, determining a demand service parameter in the target grid that matches the data change trend according to the data change trend and preset system resources;

[0016] Determining whether the required service parameters match the preset system resources;

[0017] When it is determined that the demand service parameter matches the preset system resource, the operation of determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions is triggered.

[0018] As an optional implementation manner, in the first aspect of the present invention, the target power grid includes at least one cluster;

[0019] Before performing a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information, the method further includes:

[0020] Acquiring grid cluster data of each of the clusters in the target grid;

[0021] For each of the clusters, whether the cluster meets a preset processing condition is determined based on the power grid cluster data of the cluster and the power grid configuration information. When it is determined that the cluster meets the preset processing condition, the cluster is determined as a cluster to be processed.

[0022] As an optional implementation manner, in the first aspect of the present invention, performing a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information includes:

[0023] According to the power grid configuration information, a target service interface matching the power grid configuration information is determined, and based on the target service interface and the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

[0024] As an optional implementation manner, in the first aspect of the present invention, before determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data condition, the method further includes:

[0025] Based on the data change information, determining whether there is a faulty service in the target power grid;

[0026] When it is determined that the faulty service exists in the target power grid, analyzing the faulty service to obtain a service fault cause, and determining a service fault type based on the service fault cause;

[0027] The determining the grid configuration information of the target grid based on the data change information and in combination with preset grid data conditions includes:

[0028] Based on the service fault type and in combination with preset power grid data conditions, power grid configuration information of the target power grid is determined.

[0029] As an optional implementation manner, in the first aspect of the present invention, the determining whether the required service parameter matches the preset system resource includes:

[0030] Determine the service demand resources corresponding to the demand service parameters;

[0031] Determining whether the service demand resources are less than or equal to the preset system resources;

[0032] When it is determined that the service demand resource is less than or equal to the preset system resource, determining that the demand service parameter matches the system resource;

[0033] When it is determined that the service demand resources are greater than the preset system resources, it is determined that the demand service parameters do not match the system resources.

[0034] The second aspect of the present invention discloses a cluster intelligent processing device based on automatic perception, the device comprising:

[0035] An acquisition module, used to acquire power grid service parameters of a target power grid;

[0036] A determination module, used to determine data change information of the target power grid within a preset time period according to the power grid service parameters;

[0037] The determination module is further used to determine the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions;

[0038] A processing module is used to perform a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information.

[0039] As an optional implementation, in the second aspect of the present invention, the determination module is further used to determine the data change trend of the target power grid according to the data change information before determining the power grid configuration information of the target power grid based on the data change information and in combination with the preset power grid data condition, wherein the data change trend includes the power grid resource change trend of the target power grid;

[0040] The device also includes:

[0041] A judgment module, used for judging whether the data change trend is used to indicate that the grid resources of the target grid are on a downward trend;

[0042] The determination module is further configured to determine the business service parameters of the target power grid according to the data change trend and preset system resources when the determination module determines that the data change trend is used to indicate that the power grid resources of the target power grid are in the downward trend;

[0043] The specific manner in which the determination module determines the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions includes:

[0044] Based on the business service parameters and in combination with preset power grid data conditions, the power grid configuration information of the target power grid is determined.

[0045] As an optional implementation, in the second aspect of the present invention, the determination module is further used to determine, when the judgment module determines that the data change trend is used to indicate that the grid resources of the target grid are on an upward trend, a demand service parameter in the target grid that matches the data change trend according to the data change trend and preset system resources;

[0046] The judgment module is also used to judge whether the demand service parameters match the preset system resources; when it is judged that the demand service parameters match the preset system resources, the determination module is triggered to execute the operation of determining the grid configuration information of the target grid based on the data change information and combined with the preset grid data conditions.

[0047] As an optional implementation, in the second aspect of the present invention, the target power grid includes at least one cluster;

[0048] The acquisition module is further configured to acquire grid cluster data of each of the clusters in the target grid before the processing module performs a processing operation matching the grid configuration information on the to-be-processed clusters in the target grid according to the grid configuration information;

[0049] The judgment module is further used to judge, for each of the clusters, whether the cluster meets a preset processing condition according to the power grid cluster data of the cluster and the power grid configuration information;

[0050] The determination module is further configured to determine the cluster as a to-be-processed cluster when the determination module determines that the cluster satisfies the preset processing condition.

[0051] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the processing module performs a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information includes:

[0052] According to the power grid configuration information, a target service interface matching the power grid configuration information is determined, and based on the target service interface and the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

[0053] As an optional implementation, in the second aspect of the present invention, the judgment module is further configured to judge whether there is a faulty service in the target power grid based on the data change information before the determination module determines the power grid configuration information of the target power grid based on the data change information and in combination with the preset power grid data condition;

[0054] The device also includes:

[0055] An analysis module, configured to analyze the faulty service to obtain a cause of the service failure when the judgment module judges that the faulty service exists in the target power grid;

[0056] The determination module is further used to determine the service failure type based on the service failure cause;

[0057] The specific manner in which the determination module determines the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions includes:

[0058] Based on the service fault type and in combination with preset power grid data conditions, power grid configuration information of the target power grid is determined.

[0059] As an optional implementation manner, in the second aspect of the present invention, the specific manner in which the judgment module judges whether the required service parameters match the preset system resources includes:

[0060] Determine the service demand resources corresponding to the demand service parameters;

[0061] Determining whether the service demand resources are less than or equal to the preset system resources;

[0062] When it is determined that the service demand resource is less than or equal to the preset system resource, determining that the demand service parameter matches the system resource;

[0063] When it is determined that the service demand resources are greater than the preset system resources, it is determined that the demand service parameters do not match the system resources.

[0064] The third aspect of the present invention discloses another cluster intelligent processing device based on automatic perception, the device comprising:

[0065] A memory storing executable program code;

[0066] a processor coupled to the memory;

[0067] The processor calls the executable program code stored in the memory to execute the automatic perception-based cluster intelligent processing method disclosed in the first aspect of the present invention.

[0068] The fourth aspect of the present invention discloses a computer storable medium, wherein the computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the automatic perception-based cluster intelligent processing method disclosed in the first aspect of the present invention.

[0069] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0070] In the embodiment of the present invention, the grid service parameters of the target grid are obtained, and the data change information of the target grid within a preset time period is determined according to the grid service parameters; the grid configuration information of the target grid is determined based on the data change information and in combination with the preset grid data conditions; and the processing operation matching the grid configuration information is performed on the to-be-processed cluster in the target grid according to the grid configuration information. It can be seen that the implementation of the present invention can realize the rapid perception and rapid response of the cluster based on the automatic perception technology to dispatch resources to serve each cluster, which is conducive to improving the intelligence of the processing cluster and the accuracy of the processing cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of 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 work.

[0072] Figure 1 It is a flow chart of a cluster intelligent processing method based on automatic perception disclosed in an embodiment of the present invention;

[0073] Figure 2 It is a flow chart of another cluster intelligent processing method based on automatic perception disclosed in an embodiment of the present invention;

[0074] Figure 3 It is a structural schematic diagram of a cluster intelligent processing device based on automatic perception disclosed in an embodiment of the present invention;

[0075] Figure 4 It is a structural schematic diagram of another cluster intelligent processing device based on automatic perception disclosed in an embodiment of the present invention;

[0076] Figure 5 It is a structural diagram of another automatic perception-based cluster intelligent processing device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0077] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0079] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0080] The present invention discloses a cluster intelligent processing method and device based on automatic perception, which can realize rapid perception and rapid response of clusters based on automatic perception technology to dispatch resources to serve each cluster, which is beneficial to improving the intelligence of processing clusters and the accuracy of processing clusters. The following are detailed descriptions.

[0081] Embodiment 1

[0082] See also Figure 1 , Figure 1 : is a flow chart of a cluster intelligent processing method based on automatic perception disclosed in an embodiment of the present invention. Figure 1 The described automatic sensing based cluster intelligent processing method can be applied to an automatic sensing based cluster intelligent processing device, and can also be applied to a cloud server or a local server based on automatic sensing cluster intelligent processing, which is not limited in the embodiments of the present invention. Figure 1 As shown, the cluster intelligent processing method based on automatic perception may include the following operations:

[0083] 101. Obtain power grid business parameters of a target power grid, and determine data change information of the target power grid within a preset time period according to the power grid business parameters.

[0084] In an embodiment of the present invention, optionally, the grid business parameters of the target grid may be acquired in real time, may be acquired periodically according to a preset time period, or may be acquired when an instruction to perform a processing operation on a cluster in the target grid is received, and the embodiment of the present invention is not limited thereto.

[0085] In an embodiment of the present invention, optionally, the grid service parameters of the target grid include grid resource change parameters of the target grid. Further optionally, the grid resources of the target grid include one or more of substation resources, line resources, transformer resources, and collection device channel resources. Further, the grid resource change parameters include one or more of substation resource quantity change parameters, line resource quantity change parameters, transformer resource quantity change parameters, and collection device channel resource quantity change parameters.

[0086] In the embodiment of the present invention, optionally, the preset time period may be 1 minute, 2 hours, or 48 hours, which is not specifically limited in the embodiment of the present invention.

[0087] 102. Based on the data change information and in combination with preset power grid data conditions, determine the power grid configuration information of the target power grid.

[0088] In the embodiment of the present invention, optionally, the preset power grid data condition includes K8S elastic expansion and contraction. K8S is kubernetes, which is an abbreviation formed by replacing the eight characters "ubernete" in the middle of the name with 8. It is an open source containerized application for managing multiple hosts in the cloud platform. The goal of Kubernetes is to make the deployment of containerized applications simple and efficient. Kubernetes provides a mechanism for application deployment, planning, updating, and maintenance. The K8S method is implemented by deploying containers. Each container is isolated from each other, each container has its own file system, and the processes between containers will not affect each other, and computing resources can be distinguished. Compared with virtual machines, containers can be deployed quickly. Since containers are decoupled from underlying facilities and machine file systems, they can be migrated between different clouds and different versions of operating systems. Containers occupy less resources and are deployed quickly. Each application can be packaged into a container image. The one-to-one relationship between each application and the container also makes the container have greater advantages. Using containers can create container images for applications in the build or release stage, because each application does not need to be combined with the rest of the application stack, nor does it rely on the production environment infrastructure, which enables a consistent environment to be provided from R&D to testing and production. Similarly, containers are lighter and more "transparent" than virtual machines, which makes them easier to monitor and manage; elastic scaling: In distributed application management, elastic scaling is a very important operation and maintenance capability. Elastic scaling can sense the status of each instance in the application and dynamically expand or shrink the application based on the instance status, thereby improving the availability of the application while ensuring service quality.

[0089] In the embodiment of the present invention, optionally, the grid configuration information of the target grid includes one or more of the type of instances of the target grid, the number of instances, the source of status data of the instances, and application configuration information of the instances.

[0090] 103. According to the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

[0091] In the embodiment of the present invention, optionally, the number of the to-be-processed clusters in the target power grid may be one or more, which is not specifically limited in the embodiment of the present invention.

[0092] In the embodiment of the present invention, optionally, when there are multiple clusters to be processed, performing a processing operation matching the grid configuration information on the clusters to be processed in the target grid according to the grid configuration information includes:

[0093] For each to-be-processed cluster in the target power grid, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster according to the power grid configuration information.

[0094] It can be seen that the implementation Figure 1 The described cluster intelligent processing method based on automatic perception can obtain the power grid business parameters of the target power grid, determine the data change information of the target power grid within a preset time period according to the power grid business parameters, determine the power grid configuration information of the target power grid based on the data change information and in combination with the preset power grid data conditions, and perform processing operations matching the power grid configuration information on the cluster to be processed in the target power grid according to the power grid configuration information. It can realize rapid perception and rapid response of the cluster based on automatic perception technology to dispatch resources to serve each cluster, which is conducive to improving the intelligence of the processing cluster and improving the accuracy of the processing cluster.

[0095] Embodiment 2

[0096] See also Figure 2 , Figure 2 is a flow chart of another cluster intelligent processing method based on automatic perception disclosed in an embodiment of the present invention. Figure 2 The described automatic sensing based cluster intelligent processing method can be applied to an automatic sensing based cluster intelligent processing device, and can also be applied to a cloud server or a local server for automatic sensing based cluster intelligent processing, which is not limited in the embodiments of the present invention. Figure 2 As shown, the cluster intelligent processing method based on automatic perception may include the following operations:

[0097] 201. Obtain power grid business parameters of a target power grid, and determine data change information of the target power grid within a preset time period according to the power grid business parameters.

[0098] 202. Determine the data change trend of the target power grid according to the data change information.

[0099] In the embodiment of the present invention, the data change trend includes a grid resource change trend of the target grid.

[0100] In an embodiment of the present invention, optionally, the data change information includes grid resource change parameters of the target grid, including one or more of substation resource quantity change parameters, line resource quantity change parameters, transformer resource quantity change parameters, and collection device channel quantity change parameters.

[0101] In the embodiment of the present invention, optionally, the data change trend may include one or more forms of expression such as a line graph, a curve graph, text, etc., which is not specifically limited in the embodiment of the present invention.

[0102] 203. Determine whether the data change trend is used to indicate that the grid resources of the target grid are on a downward trend.

[0103] In the embodiment of the present invention, optionally, when it is determined that the data change trend is used to indicate that the grid resources of the target grid are on a downward trend, it is determined that the usage amount of the grid resources of the target grid is decreasing.

[0104] 204. When it is determined that the data change trend is used to indicate that the grid resources of the target grid are on a downward trend, a business service parameter of the target grid is determined according to the data change trend and preset system resources.

[0105] In the embodiment of the present invention, optionally, the preset system resources are the maximum resource values ​​that can be used by the system.

[0106] In the embodiment of the present invention, optionally, the business service parameters of the target power grid include one or more of substation resource service parameters, line resource service parameters, transformer resource service parameters, and collection device channel resource service parameters.

[0107] 205. Based on the business service parameters and in combination with preset power grid data conditions, determine the power grid configuration information of the target power grid.

[0108] In the embodiment of the present invention, optionally, the preset power grid data condition includes a maximum data volume condition of the target power grid.

[0109] 206. According to the power grid configuration information, execute a processing operation matching the power grid configuration information on the to-be-processed cluster in the target power grid.

[0110] In the embodiment of the present invention, for the detailed description of step 201 and step 206, please refer to the other descriptions of step 101 and step 103 in the first embodiment, and the embodiment of the present invention will not be repeated.

[0111] It can be seen that the implementation Figure 2The described cluster intelligent processing method based on automatic perception can determine the data change trend of the target power grid according to the data change information, and judge whether the data change trend is used to indicate that the power grid resources of the target power grid are on a downward trend. If so, the business service parameters of the target power grid are determined according to the data change trend and the preset system resources, and the power grid configuration information of the target power grid is determined based on the business service parameters and the preset power grid data conditions. The power grid trend can be determined according to the data change trend of the target power grid and then the power grid configuration information of the target power grid can be determined. When the power grid resources of the target power grid are reduced, the number of business services can be reduced accordingly, which is conducive to saving system resources, improving the efficiency of system operation, and saving the system's operating memory and system storage space. It can improve the accuracy and reliability of determining the trend of the power grid resources of the target power grid, thereby improving the accuracy and intelligence of determining the business service parameters of the target power grid, and then helping to improve the accuracy and reliability of determining the power grid configuration information of the target power grid, and helping to improve the accuracy and reliability of subsequent processing operations on the cluster to be processed in the target power grid, and helping to improve the intelligence and efficiency of processing operations on the cluster to be processed in the target power grid.

[0112] In an optional embodiment, the method further comprises:

[0113] When it is determined that the data change trend is used to indicate that the grid resources of the target grid are on an upward trend, a demand service parameter matching the data change trend in the target grid is determined according to the data change trend and preset system resources;

[0114] Determine whether the required service parameters match the preset system resources;

[0115] When it is determined that the demand service parameters match the preset system resources, an operation of determining the grid configuration information of the target grid based on the data change information and the preset grid data conditions is triggered.

[0116] In this optional embodiment, optionally, when it is determined that the data change trend is used to indicate that the grid resources of the target grid are on an upward trend, it is determined that the usage amount of the grid resources of the target grid is increasing.

[0117] In this optional embodiment, optionally, when it is determined that the required server parameters do not match the preset system resources, the process can be terminated.

[0118] In this optional embodiment, optionally, for example, when the number of plants in the target power grid increases by 1, the data change trend is determined to indicate that the power grid resources of the target power grid are on an upward trend, and the demand service parameters in the target power grid that match the data change trend are determined to increase the data acquisition channels corresponding to the target power grid by 100, and it is determined whether the data acquisition channels corresponding to the target power grid match the preset system resources. If they match, the data processing service of 1 site and the data acquisition service of 100 data acquisition channels are dynamically added, which can improve the stability of system operation and ensure the stability of data processing.

[0119] It can be seen that the implementation of this optional embodiment can determine the demand service parameters in the target power grid that match the data change trend when it is judged that the data change trend is used to indicate that the power grid resources of the target power grid are on an upward trend. It can also determine whether the demand service parameters match the preset system resources. If so, it triggers the execution of an operation to determine the power grid configuration information of the target power grid based on the data change information combined with the preset power grid data conditions. This can improve the stability of system operation, ensure the stability of data processing, and improve the accuracy and intelligence of determining the business service parameters of the target power grid, thereby facilitating the improvement of the accuracy and reliability of determining the power grid configuration information of the target power grid, as well as facilitating the improvement of the accuracy and reliability of subsequent processing operations on the cluster to be processed in the target power grid, and facilitating the improvement of the intelligence and efficiency of processing operations on the cluster to be processed in the target power grid.

[0120] In another optional embodiment, the target power grid includes at least one cluster;

[0121] Before executing a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information, the method further includes:

[0122] Obtaining grid cluster data for each cluster in the target grid;

[0123] For each cluster, whether the cluster meets the preset processing conditions is determined based on the power grid cluster data and power grid configuration information of the cluster. When it is determined that the cluster meets the preset processing conditions, the cluster is determined as a cluster to be processed.

[0124] In this optional embodiment, the number of clusters included in the target power grid may be one or more, which is not limited in the embodiment of the present invention. Further, when the number of clusters included in the target power grid is one, the cluster is determined as the cluster to be processed in the target power grid.

[0125] In this optional embodiment, optionally, the power grid cluster data of each cluster in the target power grid includes one or more of cluster service category data of the cluster, data on the number of nodes included in the cluster, node type data of the nodes included in the cluster, server category data of the cluster, and server usage status data of the cluster.

[0126] In this optional embodiment, optionally, when it is determined that all clusters do not meet the preset processing conditions, the process can be terminated.

[0127] It can be seen that implementing this optional embodiment can obtain the power grid cluster data of each cluster in the target power grid. For each cluster, it is determined whether the cluster meets the preset processing conditions based on the power grid cluster data and power grid configuration information of the cluster. If so, the cluster is determined as a cluster to be processed. It can be determined whether the preset processing conditions are met based on the power grid cluster data and power grid configuration information of each cluster, which can improve the intelligence of determining the cluster to be processed, and can improve the accuracy and reliability of determining the cluster to be processed, which is conducive to improving the accuracy and reliability of executing corresponding processing operations on the cluster to be processed, and is conducive to improving the intelligence and efficiency of executing processing operations on the cluster to be processed in the target power grid.

[0128] In yet another optional embodiment, according to the power grid configuration information, performing a processing operation matching the power grid configuration information on the to-be-processed cluster in the target power grid includes:

[0129] According to the power grid configuration information, a target service interface matching the power grid configuration information is determined, and based on the target service interface and the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

[0130] In this optional embodiment, the target service interface is optionally a K8S api interface. It should be noted that api is an application programming interface, which is a set of predefined interfaces (such as functions, HTTP interfaces), or refers to the agreement for connecting different components of a software system. It is used to provide a set of routines that applications and developers can access based on certain software or hardware without having to access the source code or understand the details of the internal working mechanism.

[0131] It can be seen that the implementation of this optional embodiment can determine the target service interface that matches the power grid configuration information according to the power grid configuration information, and based on the target service interface and the power grid configuration information, perform processing operations that match the power grid configuration information on the cluster to be processed in the target power grid; can perform processing operations on the cluster to be processed in the target power grid based on the target service interface, can improve the efficiency of performing processing operations on the cluster to be processed, and can improve the intelligence of performing processing operations on the cluster to be processed, which is conducive to improving the timeliness of performing processing operations on the cluster to be processed.

[0132] In yet another optional embodiment, before determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data condition, the method further includes:

[0133] Based on the data change information, determine whether there is a faulty service in the target power grid;

[0134] When it is determined that there is a faulty service in the target power grid, the faulty service is analyzed to obtain the cause of the service failure, and the service failure type is determined based on the cause of the service failure;

[0135] Based on the data change information and the preset grid data conditions, the grid configuration information of the target grid is determined, including:

[0136] Based on the business fault type and combined with the preset power grid data conditions, the power grid configuration information of the target power grid is determined.

[0137] In this optional embodiment, optionally, when it is determined that there is no faulty service in the target power grid, the process may be terminated.

[0138] In this optional embodiment, optionally, analyzing the faulty service to obtain the service fault cause includes: inputting the faulty service into a preset fault analysis model to obtain a fault analysis result, and determining the service fault cause according to the fault analysis result. In this way, the faulty service can be analyzed by the preset fault analysis model to obtain the fault analysis result, which can improve the accuracy and reliability of the fault analysis result, and thus help improve the accuracy of obtaining the service fault cause.

[0139] In this optional embodiment, optionally, determining the type of the service failure based on the cause of the service failure includes: determining a cause keyword of the service failure cause, searching for a target keyword matching the cause keyword in a preset failure type database based on the cause keyword, and determining the failure type corresponding to the target keyword as the service failure type. In this way, the target keyword can be determined based on the determined cause keyword and the preset failure type database, and then the service failure type can be determined, which can improve the accuracy and reliability of determining the target keyword, and thus help improve the accuracy of determining the service failure type.

[0140] In this optional embodiment, when the service fault type is insufficient capacity, the service system is dynamically expanded; when the service fault type is excess capacity, the service system is dynamically reduced. In this way, the service system can be dynamically expanded or reduced based on the service fault type, which can help improve the stability of system operation and ensure the stability of data processing, save system memory resources and operating resources, and thus help improve the efficiency of system operation.

[0141] It can be seen that the implementation of this optional embodiment can determine whether there is a faulty business in the target power grid based on the data change information. If so, the faulty business is analyzed to obtain the cause of the business failure, and the business failure type is determined based on the cause of the business failure. Based on the business failure type combined with the preset power grid data conditions, the power grid configuration information of the target power grid is determined, and the faulty business can be analyzed through a preset fault analysis model to obtain a fault analysis result, which can improve the accuracy and reliability of the fault analysis result, and thus help improve the accuracy of obtaining the cause of the business failure, and help improve the accuracy of determining the type of business failure. The business system can be dynamically expanded or reduced based on the business failure type, which can help improve the stability of system operation and ensure the stability of data processing, and help save the system's memory resources and operating resources, and thus help improve the efficiency of system operation, and help improve the intelligence and accuracy of determining the power grid configuration information of the target power grid.

[0142] In yet another optional embodiment, determining whether the required service parameters match the preset system resources includes:

[0143] Determine the service demand resources corresponding to the demand service parameters;

[0144] Determine whether the service demand resources are less than or equal to the preset system resources;

[0145] When it is determined that the service demand resources are less than or equal to the preset system resources, determining that the demand service parameters match the system resources;

[0146] When it is determined that the service demand resources are greater than the preset system resources, it is determined that the demand service parameters do not match the system resources.

[0147] In this optional embodiment, optionally, the service demand resources include one or more of substation resources, line resources, transformer resources, and collection device channel resources.

[0148] In this optional embodiment, optionally, the preset system resources include maximum resource parameters included in the business system, wherein the maximum resource parameters included in the business system include one or more of maximum resource parameters of substation resources, maximum resource parameters of line resources, maximum resource parameters of transformer resources, and maximum resource parameters of collection device channel resources.

[0149] It can be seen that implementing this optional embodiment can determine the service demand resources corresponding to the demand service parameters, and determine whether the service demand resources are less than or equal to the preset system resources. If so, it is determined that the demand service parameters match the system resources; if not, it is determined that the demand service parameters do not match the system resources. It can be determined whether the demand service parameters match the preset system resources through the determined service demand resources, which can improve the accuracy and reliability of judging whether the demand service parameters match the preset system resources, and can improve the intelligence of whether the demand service parameters match the preset system resources, thereby facilitating improving the accuracy and reliability of determining the grid configuration information of the target grid and performing processing operations on the processing cluster.

[0150] Embodiment 3

[0151] See also Figure 3 , Figure 3 Schematic diagram of a cluster intelligent processing device based on automatic perception disclosed in an embodiment of the present invention. Figure 3 As shown, the cluster intelligent processing device based on automatic perception may include:

[0152] An acquisition module 301 is used to acquire power grid service parameters of a target power grid;

[0153] The determination module 302 is used to determine the data change information of the target power grid within a preset time period according to the power grid service parameters;

[0154] The determination module 302 is further used to determine the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions;

[0155] The processing module 303 is used to perform a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information.

[0156] It can be seen that the implementation Figure 3The described device can obtain the grid business parameters of the target grid, determine the data change information of the target grid within a preset time period according to the grid business parameters, determine the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions, and perform processing operations matching the grid configuration information on the cluster to be processed in the target grid according to the grid configuration information. It can realize rapid perception and rapid response of clusters based on automatic perception technology to dispatch resources to serve each cluster, which is conducive to improving the intelligence of the processing cluster and the accuracy of the processing cluster.

[0157] In an optional embodiment, if Figure 4 As shown, the determination module 302 is further used to determine the data change trend of the target power grid according to the data change information before determining the power grid configuration information of the target power grid based on the data change information and in combination with the preset power grid data conditions, wherein the data change trend includes the power grid resource change trend of the target power grid;

[0158] The device also includes:

[0159] A determination module 304 is used to determine whether the data change trend is used to indicate that the grid resources of the target grid are on a downward trend;

[0160] The determination module 302 is further configured to determine the business service parameters of the target power grid according to the data change trend and the preset system resources when the determination module 304 determines that the data change trend is used to indicate that the power grid resources of the target power grid are on a downward trend;

[0161] The specific manner in which the determination module 302 determines the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions includes:

[0162] Based on the business service parameters and the preset power grid data conditions, the power grid configuration information of the target power grid is determined.

[0163] It can be seen that the implementation Figure 4The described device can determine the data change trend of the target power grid according to the data change information, and judge whether the data change trend is used to indicate that the power grid resources of the target power grid are on a downward trend. If so, the business service parameters of the target power grid are determined according to the data change trend and the preset system resources, and the power grid configuration information of the target power grid is determined based on the business service parameters and the preset power grid data conditions. The power grid trend can be determined according to the data change trend of the target power grid and then the power grid configuration information of the target power grid can be determined. When the power grid resources of the target power grid are reduced, the number of business services can be reduced accordingly, which is conducive to saving system resources, improving the efficiency of system operation, and saving the system's operating memory and system storage space. It can improve the accuracy and reliability of determining the trend of the power grid resources of the target power grid, thereby improving the accuracy and intelligence of determining the business service parameters of the target power grid, and then helping to improve the accuracy and reliability of determining the power grid configuration information of the target power grid, and helping to improve the accuracy and reliability of subsequent processing operations on the cluster to be processed in the target power grid, and helping to improve the intelligence and efficiency of processing operations on the cluster to be processed in the target power grid.

[0164] In another optional embodiment, Figure 4 As shown, the determination module 302 is further used to determine the demand service parameters matching the data change trend in the target power grid according to the data change trend and the preset system resources when the determination module 304 determines that the data change trend is used to indicate that the power grid resources of the target power grid are on an upward trend;

[0165] The judgment module 304 is also used to judge whether the demand service parameters match the preset system resources; when it is judged that the demand service parameters match the preset system resources, the determination module 302 is triggered to execute the operation of determining the grid configuration information of the target grid based on the data change information and the preset grid data conditions.

[0166] It can be seen that the implementation Figure 4The described device can, when it is judged that the data change trend is used to indicate that the power grid resources of the target power grid are on an upward trend, determine the demand service parameters in the target power grid that match the data change trend according to the data change trend and the preset system resources, and judge whether the demand service parameters match the preset system resources. If so, it triggers the execution of an operation to determine the power grid configuration information of the target power grid based on the data change information combined with the preset power grid data conditions. This can improve the stability of system operation, ensure the stability of data processing, and improve the accuracy and intelligence of determining the business service parameters of the target power grid, which is conducive to improving the accuracy and reliability of determining the power grid configuration information of the target power grid, as well as improving the accuracy and reliability of subsequent processing operations on the cluster to be processed in the target power grid, and is conducive to improving the intelligence and efficiency of processing operations on the cluster to be processed in the target power grid.

[0167] In yet another optional embodiment, Figure 4 As shown, the target power grid includes at least one cluster;

[0168] The acquisition module 301 is further used to acquire the grid cluster data of each cluster in the target grid before the processing module 303 performs the processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information;

[0169] The judgment module 304 is further used to judge, for each cluster, whether the cluster meets the preset processing conditions according to the power grid cluster data and power grid configuration information of the cluster;

[0170] The determination module 302 is further configured to determine the cluster as a to-be-processed cluster when the determination module 304 determines that the cluster satisfies a preset processing condition.

[0171] It can be seen that the implementation Figure 4 The described device can obtain the power grid cluster data of each cluster in the target power grid, and for each cluster, judge whether the cluster meets the preset processing conditions based on the power grid cluster data and power grid configuration information of the cluster. If so, the cluster is determined as a cluster to be processed. It can judge whether the preset processing conditions are met based on the power grid cluster data and power grid configuration information of each cluster, and can improve the intelligence of determining the cluster to be processed, as well as the accuracy and reliability of determining the cluster to be processed, which is conducive to improving the accuracy and reliability of executing corresponding processing operations on the cluster to be processed, and is conducive to improving the intelligence and efficiency of executing processing operations on the cluster to be processed in the target power grid.

[0172] In yet another optional embodiment, Figure 4As shown, the specific manner in which the processing module 303 performs the processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information includes:

[0173] According to the power grid configuration information, a target service interface matching the power grid configuration information is determined, and based on the target service interface and the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

[0174] It can be seen that the implementation Figure 4 The described device can determine the target service interface that matches the power grid configuration information based on the power grid configuration information, and based on the target service interface and the power grid configuration information, perform processing operations that match the power grid configuration information on the cluster to be processed in the target power grid. It can perform processing operations on the cluster to be processed in the target power grid based on the target service interface, and can improve the efficiency of performing processing operations on the cluster to be processed, as well as improve the intelligence of performing processing operations on the cluster to be processed, which is conducive to improving the timeliness of performing processing operations on the cluster to be processed.

[0175] In yet another optional embodiment, Figure 4 As shown, the judgment module 304 is also used to judge whether there is a fault service in the target power grid based on the data change information before the determination module 302 determines the power grid configuration information of the target power grid based on the data change information and the preset power grid data condition;

[0176] The device also includes:

[0177] The analysis module 305 is used to analyze the faulty service and obtain the cause of the service fault when the judgment module 304 judges that there is a faulty service in the target power grid;

[0178] The determination module 302 is further used to determine the type of service failure based on the cause of the service failure;

[0179] The specific manner in which the determination module 302 determines the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions includes:

[0180] Based on the business fault type and combined with the preset power grid data conditions, the power grid configuration information of the target power grid is determined.

[0181] It can be seen that the implementation Figure 4The described device can determine whether there is a faulty business in the target power grid based on data change information. If so, it can analyze the faulty business to obtain the cause of the business fault, and determine the business fault type based on the cause of the business fault. Based on the business fault type combined with preset power grid data conditions, the power grid configuration information of the target power grid can be determined. The faulty business can be analyzed through a preset fault analysis model to obtain a fault analysis result, which can improve the accuracy and reliability of the fault analysis result, thereby helping to improve the accuracy of obtaining the cause of the business fault, helping to improve the accuracy of determining the business fault type, and can dynamically expand and shrink the business system based on the business fault type, which can help to improve the stability of system operation and ensure the stability of data processing, and help to save the system's memory resources and operating resources, thereby helping to improve the efficiency of system operation, and help to improve the intelligence and accuracy of determining the power grid configuration information of the target power grid.

[0182] In yet another optional embodiment, Figure 4 As shown, the specific manner in which the determination module 304 determines whether the required service parameters match the preset system resources includes:

[0183] Determine the service demand resources corresponding to the demand service parameters;

[0184] Determine whether the service demand resources are less than or equal to the preset system resources;

[0185] When it is determined that the service demand resources are less than or equal to the preset system resources, determining that the demand service parameters match the system resources;

[0186] When it is determined that the service demand resources are greater than the preset system resources, it is determined that the demand service parameters do not match the system resources.

[0187] It can be seen that the implementation Figure 4 The described device can determine the service demand resources corresponding to the demand service parameters, and judge whether the service demand resources are less than or equal to the preset system resources. If so, it is determined that the demand service parameters match the system resources; if not, it is determined that the demand service parameters do not match the system resources. It can judge whether the demand service parameters match the preset system resources through the determined service demand resources, and can improve the accuracy and reliability of judging whether the demand service parameters match the preset system resources, and can improve the intelligence of whether the demand service parameters match the preset system resources, which is beneficial to improve the accuracy and reliability of determining the grid configuration information of the target grid and performing processing operations on the processing cluster.

[0188] Embodiment 4

[0189] See also Figure 5 , Figure 5FIG. 1 is a schematic diagram of the structure of another cluster intelligent processing device based on automatic perception disclosed in an embodiment of the present invention. Figure 5 As shown, the cluster intelligent processing device based on automatic perception may include:

[0190] A memory 401 storing executable program codes;

[0191] a processor 402 coupled to the memory 401;

[0192] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the cluster intelligent processing method based on automatic perception described in the first embodiment of the present invention or the second embodiment of the present invention.

[0193] Embodiment 5

[0194] An embodiment of the present invention discloses a computer storable medium, which stores computer instructions. When the computer instructions are called, they are used to execute the steps of the automatic perception-based cluster intelligent processing method described in Embodiment 1 or Embodiment 2 of the present invention.

[0195] Embodiment 6

[0196] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the automatic perception-based cluster intelligence processing method described in Embodiment 1 or Embodiment 2.

[0197] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0198] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0199] Finally, it should be noted that the automatic perception-based cluster intelligent processing method and device disclosed in the embodiment of the present invention only discloses the preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A cluster intelligent processing method based on automatic perception, characterized in that: The method comprises: Acquire power grid service parameters of the target power grid, and determine data change information of the target power grid within a preset time period according to the power grid service parameters; Based on the data change information, combined with the preset power grid data conditions, the power grid configuration information of the target power grid is determined; wherein the preset power grid data conditions include K8S elastic expansion and contraction, and the power grid configuration information of the target power grid includes one or more of the type of instance of the target power grid, the number of instances, the source of the instance status data, and the application configuration information of the instance; According to the power grid configuration information, executing a processing operation matching the power grid configuration information on the to-be-processed cluster in the target power grid; Before determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions, the method further includes: Determining a data change trend of the target power grid according to the data change information, wherein the data change trend includes a power grid resource change trend of the target power grid; Determining whether the data change trend is used to indicate that the grid resources of the target grid are on a downward trend; When it is determined that the data change trend is used to indicate that the grid resources of the target grid are in the downward trend, determining the business service parameters of the target grid according to the data change trend and preset system resources; The determining the grid configuration information of the target grid based on the data change information and in combination with preset grid data conditions includes: Based on the business service parameters and in combination with preset power grid data conditions, determine the power grid configuration information of the target power grid; The method further comprises: When it is determined that the data change trend is used to indicate that the grid resources of the target grid are on an upward trend, determining a demand service parameter in the target grid that matches the data change trend according to the data change trend and preset system resources; Determining whether the required service parameters match the preset system resources; When it is determined that the demand service parameter matches the preset system resource, the operation of determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions is triggered.

2. The cluster intelligent processing method based on automatic perception according to claim 1 is characterized in that: The target power grid includes at least one cluster; Before performing a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information, the method further includes: Acquiring grid cluster data of each of the clusters in the target grid; For each of the clusters, whether the cluster meets a preset processing condition is determined based on the power grid cluster data of the cluster and the power grid configuration information. When it is determined that the cluster meets the preset processing condition, the cluster is determined as a cluster to be processed.

3. The cluster intelligent processing method based on automatic perception according to claim 2 is characterized in that: The performing, according to the power grid configuration information, a processing operation matching the power grid configuration information on the to-be-processed cluster in the target power grid includes: According to the power grid configuration information, a target service interface matching the power grid configuration information is determined, and based on the target service interface and the power grid configuration information, a processing operation matching the power grid configuration information is performed on the to-be-processed cluster in the target power grid.

4. The cluster intelligent processing method based on automatic perception according to claim 3 is characterized in that: Before determining the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions, the method further includes: Based on the data change information, determining whether there is a faulty service in the target power grid; When it is determined that the faulty service exists in the target power grid, analyzing the faulty service to obtain a service fault cause, and determining a service fault type based on the service fault cause; The determining the grid configuration information of the target grid based on the data change information and in combination with preset grid data conditions includes: Based on the service fault type and in combination with preset power grid data conditions, power grid configuration information of the target power grid is determined.

5. The automatic perception-based cluster intelligent processing method according to claim 4 is characterized in that: The determining whether the required service parameters match the preset system resources includes: Determine the service demand resources corresponding to the demand service parameters; Determining whether the service demand resources are less than or equal to the preset system resources; When it is determined that the service demand resource is less than or equal to the preset system resource, determining that the demand service parameter matches the system resource; When it is determined that the service demand resources are greater than the preset system resources, it is determined that the demand service parameters do not match the system resources.

6. A cluster intelligent processing device based on automatic perception, characterized in that: The device comprises: An acquisition module, used to acquire power grid service parameters of a target power grid; A determination module, used to determine data change information of the target power grid within a preset time period according to the power grid service parameters; The determination module is further used to determine the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions; wherein the preset grid data conditions include K8S elastic expansion and contraction, and the grid configuration information of the target grid includes one or more of the type of instance of the target grid, the number of instances, the source of the instance status data, and the application configuration information of the instance; A processing module, configured to perform a processing operation matching the grid configuration information on the to-be-processed cluster in the target grid according to the grid configuration information; The determination module is further configured to determine a data change trend of the target power grid according to the data change information before determining the power grid configuration information of the target power grid based on the data change information and in combination with the preset power grid data condition, wherein the data change trend includes a power grid resource change trend of the target power grid; The device also includes: A judgment module, used for judging whether the data change trend is used to indicate that the grid resources of the target grid are on a downward trend; The determination module is further configured to determine the business service parameters of the target power grid according to the data change trend and preset system resources when the determination module determines that the data change trend is used to indicate that the power grid resources of the target power grid are in the downward trend; The specific manner in which the determination module determines the grid configuration information of the target grid based on the data change information and in combination with the preset grid data conditions includes: Based on the business service parameters and in combination with preset power grid data conditions, determine the power grid configuration information of the target power grid; The determination module is further configured to determine, when the determination module determines that the data change trend is used to indicate that the grid resources of the target grid are on an upward trend, a demand service parameter in the target grid that matches the data change trend according to the data change trend and preset system resources; The judgment module is also used to judge whether the demand service parameters match the preset system resources; when it is judged that the demand service parameters match the preset system resources, the determination module is triggered to execute the operation of determining the grid configuration information of the target grid based on the data change information and combined with the preset grid data conditions.

7. A cluster intelligent processing device based on automatic perception, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the automatic perception-based cluster intelligent processing method as described in any one of claims 1-5.

8. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the automatic perception-based cluster intelligent processing method as described in any one of claims 1-5.

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