Inspection and processing apparatus, methods, equipment and media based on distributed storage clusters

Abstract

This application discloses an inspection and processing apparatus, method, device, and medium based on a distributed storage cluster, relating to the field of computer technology. It includes: a process control module, an inspection module, and a data analysis module. The inspection module is located at each target node. The process control module generates a preset list of inspection items, groups the target nodes into preset node groups, and determines the management node for each preset node group. The inspection module obtains inspection commands sent by the management node, inspects the target nodes based on the inspection commands and the preset list of inspection items, and sends the inspection information to the management node so that the management node can identify abnormal information from the inspection information. The data analysis module obtains abnormal information sent by the management node, and sends the corresponding processing solutions to the management node based on a preset abnormal information processing solution library so that the management node can automatically process the abnormal information. This application can complete the inspection and processing of a distributed storage cluster, improving the success rate of cluster upgrades.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a detection and processing apparatus, method, device, and medium based on a distributed storage cluster. Background Technology

[0002] Currently, with the continuous development and application of distributed storage technology in recent years, regular system upgrades and maintenance are necessary to improve system stability and the functional features of application system versions. Ensuring normal business operations during upgrades, ensuring efficient upgrade execution, and preventing the impact of unforeseen events or potential cluster problems on cluster upgrades have become urgent issues to address.

[0003] In summary, how to perform inspections and processing of distributed storage clusters to improve the success rate of cluster upgrades is an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide an inspection and processing device based on a distributed storage cluster, which can complete the inspection and processing of the distributed storage cluster to improve the success rate of cluster upgrades.

[0005] The specific plan is as follows:

[0006] In a first aspect, this application discloses an inspection and processing device based on a distributed storage cluster, comprising: a process control module, an inspection module, and a data analysis module; wherein the inspection module is located in each target node of the distributed storage cluster, and

[0007] The process control module is used to generate a list of preset check items before upgrading the distributed storage cluster, group each target node into several preset node groups, and then determine the management node in each preset node group.

[0008] The inspection module is used to obtain the inspection command sent by each of the management nodes, and to inspect several target nodes based on the inspection command and the preset inspection item list, and send the inspection information to the corresponding management node so that the management node can determine the abnormal information from the inspection information;

[0009] The data analysis module is used to acquire the abnormal information sent by several management nodes, and send the processing scheme corresponding to the abnormal information to the management nodes based on a preset abnormal information processing scheme library, so that the management nodes can automatically process the abnormal information according to the processing scheme.

[0010] Optionally, the data analysis module is further configured to provide repair suggestions for the abnormal information if there is no corresponding processing solution in the preset abnormal information processing solution library, so that the client can manually repair it based on the repair suggestions.

[0011] Optionally, the data analysis module is also used to automatically learn the manual processing schemes for manual repair and store the manual processing schemes in the preset abnormal information processing scheme library so as to automatically repair the abnormal information based on the manual processing schemes.

[0012] Optionally, the process control module is used to generate target check items based on the first cluster information of the distributed storage cluster before upgrading the distributed storage cluster, and to generate the preset check item list based on the target check items and fixed check items; the first cluster information includes the current cluster status, cluster historical alarm information and the abnormal information in the historical upgrade process of the distributed storage cluster.

[0013] Optionally, the data analysis module is further configured to generate an upgrade prediction report based on the second cluster information of the distributed storage cluster; the cluster information includes the current cluster status, service status, and business pressure; the upgrade prediction report includes upgrade success rate, potential anomaly information, business performance analysis during the upgrade, overall upgrade time analysis, and single node upgrade time analysis.

[0014] Optionally, the process control module summarizes the inspection information corresponding to each target node in the distributed storage cluster and the processing results of the abnormal information, and sends them to the client.

[0015] Secondly, this application discloses an inspection and processing method based on a distributed storage cluster, applied to an inspection and processing device based on a distributed storage cluster. The device includes a process control module, an inspection module, and a data analysis module; the inspection module is located in each target node of the distributed storage cluster; the method includes:

[0016] The process control module generates a list of preset check items before upgrading the distributed storage cluster, groups each target node into several preset node groups, and then determines the management node in each preset node group.

[0017] The inspection module obtains the inspection commands sent by each management node, and inspects several target nodes based on the inspection commands and the preset inspection item list, and sends the inspection information to the corresponding management node so that the management node can determine the abnormal information from the inspection information.

[0018] The data analysis module obtains the abnormal information sent by several management nodes, and sends the processing scheme corresponding to the abnormal information to the management nodes based on the preset abnormal information processing scheme library, so that the management nodes can automatically process the abnormal information according to the processing scheme.

[0019] Optionally, the process control module generates a preset checklist before upgrading the distributed storage cluster, including:

[0020] Before upgrading the distributed storage cluster, the process control module generates target check items based on the first cluster information of the distributed storage cluster, and generates the preset check item list based on the target check items and fixed check items; the first cluster information includes the current cluster status, cluster historical alarm information, and the abnormal information in the historical upgrade process of the distributed storage cluster.

[0021] Thirdly, this application discloses an electronic device, including a processor and a memory; wherein, when the processor executes a computer program stored in the memory, it implements the aforementioned disclosed inspection and processing method based on a distributed storage cluster.

[0022] Fourthly, this application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned inspection and processing method based on a distributed storage cluster.

[0023] As can be seen, the process control module described in this application is used to generate a preset check item list before upgrading the distributed storage cluster, and group each target node into several preset node groups, and then determine the management node in each preset node group; the check module is used to obtain the check command sent by each management node, and check several target nodes based on the check command and the preset check item list, and send the check information to the corresponding management node, so that the management node can determine the abnormal information from the check information; the data analysis module is used to obtain the abnormal information sent by several management nodes, and send the processing scheme corresponding to the abnormal information to the management node based on the preset abnormal information processing scheme library, so that the management node can automatically process the abnormal information according to the processing scheme. Therefore, this application can complete the inspection and processing of the distributed storage cluster, thereby improving the success rate of cluster upgrades; the grouping of each target node into several preset node groups can effectively improve inspection efficiency and reduce the impact of the inspection function on cluster performance and resources; the data analysis module of this application can automatically repair abnormal information based on the preset abnormal information processing scheme library, which can effectively improve the processing efficiency of abnormal information and avoid the waste of human resources. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0025] Figure 1 A structural diagram of an inspection and processing device based on a distributed storage cluster provided for this application;

[0026] Figure 2 A flowchart of a detection and processing method based on a distributed storage cluster provided for this application;

[0027] Figure 3 A flowchart illustrating a specific inspection and processing method based on a distributed storage cluster provided in this application;

[0028] Figure 4 This application provides a structural diagram of an electronic device. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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.

[0030] Currently, with the continuous development and application of distributed storage technology in recent years, regular system upgrades and maintenance are necessary to improve system stability and the functional features of application system versions. Ensuring normal business operations during upgrades, ensuring efficient upgrade execution, and preventing the impact of unforeseen events or potential cluster problems on cluster upgrades have become urgent issues to address.

[0031] To overcome the above problems, this application provides an inspection and processing device based on a distributed storage cluster, which can complete the inspection and processing of the distributed storage cluster to improve the success rate of cluster upgrades.

[0032] See Figure 1 As shown in the figure, this application discloses an inspection and processing device based on a distributed storage cluster, including: a process control module 11, an inspection module 12, and a data analysis module 13; the inspection module is located in each target node of the distributed storage cluster, wherein,

[0033] The process control module 11 is used to generate a list of preset check items before the upgrade of the distributed storage cluster, group each target node to obtain several preset node groups, and then determine the management node in each preset node group.

[0034] The inspection module 12 is used to obtain the inspection command sent by each of the management nodes, and to inspect several target nodes based on the inspection command and the preset inspection item list, and send the inspection information to the corresponding management node so that the management node can determine the abnormal information from the inspection information;

[0035] The data analysis module 13 is used to acquire the abnormal information sent by several management nodes, and send the processing scheme corresponding to the abnormal information to the management nodes based on a preset abnormal information processing scheme library, so that the management nodes can automatically process the abnormal information according to the processing scheme.

[0036] In this embodiment, to improve the success rate of cluster upgrades by inspecting and processing distributed storage clusters, a large-scale distributed cluster pre-upgrade inspection and processing device is provided. This device aims to quickly collect information on each node, service status, and hardware device status in the distributed storage, and comprehensively determine whether there are any abnormal problems that might affect the cluster upgrade based on the inspection results. It provides a device for inspecting and processing abnormal problems and potential problems that may affect the success of the cluster upgrade before the upgrade. By exposing and processing problems before the upgrade, the robustness of the cluster upgrade function is ensured.

[0037] In this embodiment, the process control module 11 is used to generate target check items based on the first cluster information of the distributed storage cluster before upgrading the distributed storage cluster, and to generate the preset check item list based on the target check items and fixed check items; the first cluster information includes the current cluster status, historical alarm information of the cluster, and the abnormal information during the historical upgrade process of the distributed storage cluster. The aforementioned dynamically generated and adjustable check item content enables the pre-upgrade check to accurately identify problems existing in the current cluster.

[0038] In this embodiment of the application, the process control module 11 summarizes the inspection information corresponding to each target node in the distributed storage cluster and the processing results of the abnormal information, and sends them to the client.

[0039] In summary, in this embodiment, the main functions of the process control module 11 are threefold: First, it dynamically generates a list of inspection items. In addition to fixed inspection items, the process control module can automatically generate corresponding inspection items by comprehensively considering the current cluster status, historical cluster alarm information, and abnormal issues that occurred during historical upgrades, and focuses on inspecting such abnormalities. Second, it generates node inspection groups (preset node groups) by (coordinating the division of node groups and receiving and forwarding information from inspection module nodes to the data analysis module). To improve overall inspection and processing efficiency and reduce the impact of inspection devices on cluster performance, large-scale cluster nodes are grouped for inspection. Each node group automatically elects a node as the management node, which summarizes the inspection results of other nodes in the node group and reports the abnormal results to the data analysis module. Third, it summarizes the inspection and abnormal handling results of each node group in the cluster and sends the processing results to the user.

[0040] In this embodiment of the application, the inspection module 12 is mainly distributed on each node, and its main function is to receive and execute the inspection commands issued by the node group management node, summarize the node inspection results, and feed the results back to the management node.

[0041] In this embodiment of the application, the data analysis module 13 is further configured to provide a repair suggestion for the abnormal information if there is no processing solution corresponding to the abnormal information in the preset abnormal information processing solution library, so that the client can manually repair it based on the repair suggestion.

[0042] In this embodiment, the data analysis module 13 is further configured to automatically learn manual processing schemes for manual repair and store these schemes in the preset anomaly information processing scheme library, so as to automatically repair the anomaly information based on the manual processing schemes. The automatic learning capability of the data analysis module allows it to automatically collect anomaly problem processing schemes and automatically repair them when the anomaly problem recurs.

[0043] In this embodiment, the data analysis module 13 is further configured to generate an upgrade prediction report based on the second cluster information of the distributed storage cluster; the cluster information includes the current cluster status, service status, and business pressure; the upgrade prediction report includes upgrade success rate, potential anomaly information, business performance analysis during the upgrade, overall upgrade time analysis, and single-node upgrade time analysis. The prediction function of the aforementioned data analysis module allows users to have a more intuitive understanding of the cluster performance, business impact, and upgrade time generated during the upgrade process.

[0044] In summary, the main functions of the data analysis module 13 in this application are fivefold: First, it statistically summarizes and processes the abnormal information pushed by the management nodes of each node group; second, it is equipped with an abnormal problem handling solution library, and the data analysis module can automatically repair abnormal problems based on the solutions to specific problems in the solution library; third, it summarizes the abnormal information for abnormalities without clear solutions and provides repair suggestions; fourth, the data analysis module can automatically explore and learn manual handling solutions and operation steps for complex problems or problems lacking solutions and update them to the abnormal problem handling solution library, so that it can automatically repair the abnormal problems when they reappear; fifth, it generates an upgrade prediction report based on the current cluster status, service status, business pressure, etc. The report mainly includes the upgrade success rate, potential abnormal problem points, business performance analysis during the upgrade, overall upgrade time analysis, and single node upgrade time analysis. In conclusion, the data analysis module 13 is mainly used to analyze and check various abnormal information reported by the inspection module, automatically repair abnormalities with clear solutions, and for abnormalities without clear solutions, it organizes the abnormal information, makes a comprehensive judgment, and provides general repair suggestions.

[0045] As can be seen, the process control module described in this application is used to generate a preset check item list before upgrading the distributed storage cluster, and group each target node into several preset node groups, and then determine the management node in each preset node group; the check module is used to obtain the check command sent by each management node, and check several target nodes based on the check command and the preset check item list, and send the check information to the corresponding management node, so that the management node can determine the abnormal information from the check information; the data analysis module is used to obtain the abnormal information sent by several management nodes, and send the processing scheme corresponding to the abnormal information to the management node based on the preset abnormal information processing scheme library, so that the management node can automatically process the abnormal information according to the processing scheme. Therefore, this application can complete the inspection and processing of the distributed storage cluster, thereby improving the success rate of cluster upgrades; the grouping of each target node into several preset node groups can effectively improve inspection efficiency and reduce the impact of the inspection function on cluster performance and resources; the data analysis module of this application can automatically repair abnormal information based on the preset abnormal information processing scheme library, which can effectively improve the processing efficiency of abnormal information and avoid the waste of human resources.

[0046] See Figure 2 As shown in the figure, this application discloses an inspection and processing method based on a distributed storage cluster, applied to an inspection and processing device based on a distributed storage cluster. The device includes a process control module, an inspection module, and a data analysis module; the inspection module is located in each target node of the distributed storage cluster; the method includes:

[0047] Step S11: Before the distributed storage cluster is upgraded, the process control module generates a list of preset check items, groups each target node into several preset node groups, and then determines the management node in each preset node group.

[0048] In this embodiment of the application, the large-scale cluster is split into multiple inspection node groups (preset node groups), which can effectively improve inspection efficiency and reduce the impact of inspection functions on cluster performance and resources.

[0049] In this embodiment, generating a preset checklist before upgrading the distributed storage cluster via the process control module includes: generating target checklists based on first cluster information of the distributed storage cluster before upgrading, and generating the preset checklist based on the target checklists and fixed checklists; the first cluster information includes the current cluster status, historical alarm information, and abnormal information during the historical upgrade process of the distributed storage cluster. It should be noted that the checklist content can be dynamically generated and adjusted to ensure that the pre-upgrade checks accurately identify problems existing in the current cluster.

[0050] In this embodiment of the application, the process control module summarizes the inspection information corresponding to each target node in the distributed storage cluster and the processing results of the abnormal information, and sends them to the client.

[0051] It should be noted that the process control module can accomplish three main tasks: First, dynamically generating a list of inspection items. In addition to fixed inspection items, the process control module can automatically generate corresponding inspection items by comprehensively considering the current cluster status, historical cluster alarm information, and abnormal issues that occurred during historical upgrades, and will focus on inspecting such anomalies. Second, (coordinating the division of node groups and receiving and forwarding information from inspection module nodes to the data analysis module) generating node inspection groups (preset node groups). To improve overall inspection and processing efficiency and reduce the impact of inspection devices on cluster performance, large-scale cluster nodes are grouped for inspection. Each node group automatically elects a node as the management node, which will summarize the inspection results of other nodes in the node group and report the abnormal results to the data analysis module. Third, (summarizing the results from the data analysis module) summarizing the inspection and anomaly handling results of each node group in the cluster and sending the processing results to the user.

[0052] Step S12: Obtain the inspection command sent by each of the management nodes through the inspection module, and inspect several target nodes based on the inspection command and the preset inspection item list, and send the inspection information to the corresponding management node so that the management node can determine the abnormal information from the inspection information.

[0053] In this embodiment of the application, the inspection module is located in each target node. The inspection module mainly receives and executes the inspection commands issued by the node group management node, summarizes the node inspection results, and feeds the results back to the management node.

[0054] Step S13: The data analysis module obtains the abnormal information sent by several management nodes, and sends the processing scheme corresponding to the abnormal information to the management nodes based on the preset abnormal information processing scheme library, so that the management nodes can automatically process the abnormal information according to the processing scheme.

[0055] In this embodiment, the automatic learning capability of the data analysis module can automatically collect solutions for handling abnormal problems, and can automatically repair them when the abnormal problems reappear.

[0056] In this embodiment, the data analysis module can generate an upgrade prediction report based on the second cluster information of the distributed storage cluster. The cluster information includes the current cluster status, service status, and business pressure. The upgrade prediction report includes upgrade success rate, potential anomaly information, business performance analysis during the upgrade, overall upgrade time analysis, and single-node upgrade time analysis. It should be noted that the prediction function of the data analysis module allows users to have a more intuitive understanding of the cluster performance, business impact, and upgrade time generated during the upgrade process.

[0057] In this embodiment of the application, when the data analysis module does not have a corresponding processing solution for the abnormal information in the preset abnormal information processing solution library, it provides a repair suggestion for the abnormal information so that the client can manually repair it based on the repair suggestion.

[0058] In this embodiment, the data analysis module can automatically learn the manual handling schemes used for manual repair and store these schemes in the preset anomaly information handling scheme library, so as to automatically repair the anomaly information based on the manual handling schemes. It should be noted that the automatic learning capability of the data analysis module can automatically collect anomaly problem handling schemes, and can automatically repair the anomaly when it recurs.

[0059] As can be seen, this application generates a preset checklist before upgrading the distributed storage cluster through the process control module, and groups the target nodes into several preset node groups, then determines the management node in each preset node group; the check module obtains the check commands sent by each management node, and checks several target nodes based on the check commands and the preset checklist, sending the check information to the corresponding management node so that the management node can identify abnormal information from the check information; the data analysis module obtains the abnormal information sent by several management nodes, and sends the corresponding processing solution to the management node based on the preset abnormal information processing solution library, so that the management node can automatically process the abnormal information according to the processing solution. Therefore, this application can complete the inspection and processing of the distributed storage cluster, thereby improving the success rate of cluster upgrades; the grouping of the target nodes into several preset node groups can effectively improve inspection efficiency and reduce the impact of inspection functions on cluster performance and resources; the data analysis module of this application automatically repairs abnormal information based on the preset abnormal information processing solution library, which can effectively improve the processing efficiency of abnormal information and avoid the waste of human resources.

[0060] See Figure 3 The diagram illustrates a specific inspection and processing method based on a distributed storage cluster. The process control node sends inspection commands to the management node in each node group. The management node then sends the inspection commands to the inspection module. The inspection module inspects the corresponding node and sends the inspection information to the corresponding management node. The management node identifies anomalies from the inspection information and sends the anomalies to the data analysis module. The data analysis module, based on a preset anomaly handling scheme library, sends the corresponding handling scheme to the management node. The management node automatically processes the anomalies according to the handling scheme. Additionally, the data analysis module can generate an upgrade prediction report.

[0061] Furthermore, embodiments of this application also provide an electronic device. Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0062] Figure 4This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, an input / output interface 24, a communication interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the distributed storage cluster-based inspection and processing method disclosed in any of the foregoing embodiments.

[0063] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 25 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 24 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0064] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The memory 22 can be a random access memory that can be used as running memory and a non-volatile memory used for external memory storage. The storage resources on it include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0065] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 on the source host and the computer program 222. The operating system 221 can be Windows, Unix, Linux, etc. In addition to the computer program that can be used to perform the inspection and processing method based on the distributed storage cluster disclosed by the electronic device 20 in any of the foregoing embodiments, the computer program 222 may further include computer programs that can be used to perform other specific tasks.

[0066] In this embodiment, the input / output interface 24 may include, but is not limited to, a USB interface, a hard disk read interface, a serial interface, a voice input interface, a fingerprint input interface, etc.

[0067] Furthermore, embodiments of this application also disclose a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed inspection and processing method based on a distributed storage cluster.

[0068] For the specific steps of this method, please refer to the relevant content disclosed in the foregoing embodiments, which will not be repeated here.

[0069] The computer-readable storage medium referred to herein includes random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disks, magnetic disks, optical disks, or any other form of storage medium known in the art. When the computer program is executed by a processor, it implements the aforementioned inspection and processing method based on a distributed storage cluster. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0070] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. The apparatus disclosed in the embodiments is described simply because it corresponds to the inspection and processing method based on a distributed storage cluster disclosed in the embodiments; relevant parts can be referred to the method section.

[0071] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0072] The steps of the algorithm described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0073] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0074] The foregoing has provided a detailed description of the inspection and processing apparatus, method, device, and medium based on a distributed storage cluster provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A detection and processing device based on a distributed storage cluster, characterized in that, include: The module includes a process control module, an inspection module, and a data analysis module. The inspection module is located in each target node of the distributed storage cluster, wherein, The process control module is used to generate a list of preset check items before upgrading the distributed storage cluster, group each target node into several preset node groups, and then determine the management node in each preset node group. The inspection module is used to obtain the inspection command sent by each of the management nodes, and to inspect several target nodes based on the inspection command and the preset inspection item list, and send the inspection information to the corresponding management node so that the management node can determine the abnormal information from the inspection information; The data analysis module is used to acquire the abnormal information sent by several management nodes, and send the processing scheme corresponding to the abnormal information to the management nodes based on a preset abnormal information processing scheme library, so that the management nodes can automatically process the abnormal information according to the processing scheme. The process control module is configured to generate target check items based on the first cluster information of the distributed storage cluster before upgrading the distributed storage cluster, and generate the preset check item list based on the target check items and fixed check items; the first cluster information includes the current cluster status, historical alarm information of the cluster, and the abnormal information in the historical upgrade process of the distributed storage cluster. The data analysis module is also used to generate an upgrade prediction report based on the second cluster information of the distributed storage cluster; the cluster information includes the current cluster status, service status, and business pressure; the upgrade prediction report includes upgrade success rate, potential anomaly information, business performance analysis during the upgrade, overall upgrade time analysis, and single node upgrade time analysis.

2. The inspection and processing device based on a distributed storage cluster according to claim 1, characterized in that, in, The data analysis module is also used to provide repair suggestions for the abnormal information if there is no corresponding processing solution in the preset abnormal information processing solution library, so that the client can manually repair it based on the repair suggestions.

3. The inspection and processing device based on a distributed storage cluster according to claim 2, characterized in that, in, The data analysis module is also used to automatically learn the manual processing schemes for manual repair and store the manual processing schemes in the preset abnormal information processing scheme library so as to automatically repair the abnormal information based on the manual processing schemes.

4. The inspection and processing apparatus based on a distributed storage cluster according to any one of claims 1 to 3, characterized in that, in, The process control module summarizes the inspection information corresponding to each target node in the distributed storage cluster and the processing results of the abnormal information, and sends them to the client.

5. A method for checking and processing based on a distributed storage cluster, characterized in that, An inspection and processing device based on a distributed storage cluster is provided, the device comprising a process control module, an inspection module, and a data analysis module; The inspection module is located in each target node of the distributed storage cluster; the method includes: The process control module generates a list of preset check items before upgrading the distributed storage cluster, groups each target node into several preset node groups, and then determines the management node in each preset node group. The inspection module obtains the inspection commands sent by each management node, and inspects several target nodes based on the inspection commands and the preset inspection item list, and sends the inspection information to the corresponding management node so that the management node can determine the abnormal information from the inspection information. The data analysis module obtains the abnormal information sent by several management nodes, and sends the processing scheme corresponding to the abnormal information to the management node based on the preset abnormal information processing scheme library, so that the management node can automatically process the abnormal information according to the processing scheme. The step of generating a preset check item list before upgrading the distributed storage cluster by the process control module includes: generating target check items based on the first cluster information of the distributed storage cluster before upgrading the distributed storage cluster by the process control module, and generating the preset check item list based on the target check items and fixed check items; the first cluster information includes the current cluster status, historical alarm information of the cluster, and the abnormal information in the historical upgrade process of the distributed storage cluster; The method further includes: generating an upgrade prediction report based on the second cluster information of the distributed storage cluster through the data analysis module; the cluster information includes the current cluster status, service status, and business pressure; the upgrade prediction report includes upgrade success rate, potential anomaly information, business performance analysis during the upgrade, overall upgrade time analysis, and single node upgrade time analysis.

6. An electronic device, characterized in that, It includes a processor and a memory; wherein, when the processor executes a computer program stored in the memory, it implements the inspection and processing method based on a distributed storage cluster as described in claim 5.

7. A computer-readable storage medium, characterized in that, Used to store computer programs; wherein, when the computer programs are executed by a processor, they implement the inspection and processing method based on a distributed storage cluster as described in claim 5.

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