Alarm processing method and device based on computing power equipment, server and storage medium

Abstract

The invention provides an alarm processing method and device based on computing power equipment, a server and a storage medium. The method comprises the following steps: receiving device alarm data sent by a plurality of computing power devices; wherein each equipment alarm data carries an equipment type and an equipment model; according to the equipment type and the equipment model, obtaining a mapping rule from a pre-constructed alarm mapping rule base; converting the equipment alarm data into standard equipment alarm data according to a mapping rule; identifying an equipment alarm event with an association relationship from the standard equipment alarm data; carrying out aggregation processing on the equipment alarm events with the incidence relation to obtain at least one comprehensive alarm event; and outputting the comprehensive alarm event. According to the method provided by the invention, the equipment alarm data integration efficiency and accuracy are improved, and the alarm reason positioning efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of multi-component computing equipment, and in particular to an alarm processing method, device, server and storage medium based on computing equipment. Background Art

[0002] In the digital age, the convergence of diverse computing power is becoming a trend. In scenarios like data centers, the collaborative operation of multiple heterogeneous computing devices generates a large amount of alarm data. However, because these devices come from different manufacturers, the alarm data varies, making it difficult to uniformly manage, analyze, and process them. This makes it difficult for administrators to quickly and accurately understand the operating status of the entire computing system, hindering the timely identification and resolution of potential issues.

[0003] Currently, when integrating alarm data from different computing devices, existing technologies directly display the alarm data after performing a large amount of manual conversion and adaptation work.

[0004] However, this method of the prior art has the following problems: on the one hand, the integration efficiency is low and it is prone to errors, resulting in low integration accuracy; on the other hand, the alarm data is directly displayed, resulting in a large amount of redundant alarm data, which reduces the efficiency of locating the cause of the alarm. Summary of the Invention

[0005] The embodiments of the present application provide an alarm processing method, device, server and storage medium based on computing power equipment to improve integration efficiency and accuracy, as well as improve the efficiency and effectiveness of locating the cause of the alarm.

[0006] In the first aspect, an embodiment of the present application provides an alarm processing method based on computing power equipment, which is applied to a server, including: receiving equipment alarm data sent by multiple computing power devices; wherein each equipment alarm data carries the equipment type and equipment model; according to the equipment type and equipment model, obtaining mapping rules from a pre-built alarm mapping rule library; according to the mapping rules, converting each equipment alarm data into standard equipment alarm data; from the standard equipment alarm data, identifying equipment alarm events with associated relationships; aggregating the equipment alarm events with associated relationships to obtain at least one comprehensive alarm event; and outputting the comprehensive alarm event.

[0007] In one possible implementation, the mapping rules include field mapping rules and semantic conversion rules; accordingly, according to the device type and device model, the mapping rules are obtained from a pre-built alarm mapping rule library, including: obtaining the mapping rules corresponding to the device type from the pre-built alarm mapping rule library; obtaining the field mapping rules and semantic conversion rules corresponding to the device model from the mapping rules corresponding to the device type.

[0008] In one possible implementation, each device alarm data is converted into standard device alarm data according to a mapping rule, including: mapping the fields in each device alarm data into fields in a pre-built alarm model according to a field mapping rule to obtain initial standard device alarm data; wherein the fields in the pre-built alarm model include alarm content; and converting the alarm content in the initial standard device alarm data according to a semantic conversion rule to obtain standard device alarm data.

[0009] In one possible implementation, identifying device alarm events with associated relationships from standard device alarm data includes: obtaining at least one main alarm event from the standard device alarm data according to pre-constructed alarm association rules; obtaining at least one secondary alarm event associated with any main alarm event from the standard device alarm data according to pre-constructed alarm association rules; determining whether any main alarm event has an associated relationship with at least one associated secondary alarm event; and if it is determined that an associated relationship exists, determining any main alarm event and at least one associated secondary alarm event as device alarm events with an associated relationship.

[0010] In a possible implementation, before receiving the device alarm data sent by multiple computing devices, it also includes: collecting historical device alarm data of multiple computing devices; obtaining device information of each computing device; and obtaining pre-built alarm association rules based on the historical device alarm data and the device information of each computing device.

[0011] In one possible implementation, device alarm events with associated relationships are aggregated to obtain at least one comprehensive alarm event, including: determining whether a main alarm event among the device alarm events with associated relationships has been resolved; if the main alarm event has not been resolved, aggregating the device alarm events with associated relationships to obtain at least one comprehensive alarm event.

[0012] In a second aspect, an embodiment of the present application provides an alarm processing device based on a computing device, applied to a server, including:

[0013] A receiving module is used to receive device alarm data sent by multiple computing devices; each device alarm data carries the device type and model;

[0014] The acquisition module is used to obtain mapping rules from a pre-built alarm mapping rule library based on device type and device model;

[0015] The conversion module is used to convert the alarm data of each device into standard device alarm data according to the mapping rules;

[0016] An identification module is used to identify device alarm events with associated relationships from standard device alarm data;

[0017] an aggregation module, configured to aggregate associated device alarm events to obtain at least one comprehensive alarm event;

[0018] Output module, used to output comprehensive alarm events

[0019] In a third aspect, an embodiment of the present application provides a server, comprising: a memory, a processor;

[0020] memory for storing computer programs;

[0021] A processor is used to implement the above first aspect and / or various possible implementations of the first aspect when executing the computer program.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0023] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0024] The embodiments of the present application provide an alarm processing method, device, server, and storage medium based on computing power equipment, which obtain mapping rules from a pre-built alarm mapping rule library according to the device type and device model of different computing power devices; according to the mapping rules, the alarm data of each device is converted into standard device alarm data, which improves the integration efficiency on the one hand, and on the other hand, the automatic conversion according to the mapping rules is not prone to errors, thereby improving the accuracy of the integration; aggregates the device alarm events with related relationships to obtain at least one comprehensive alarm event, and outputs the comprehensive alarm event; reduces redundant alarm data, thereby providing a high-quality data basis for locating the cause of the alarm, thereby improving the efficiency of locating the cause of the alarm. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0026] Figure 1 A schematic diagram of a scenario of an alarm processing method based on computing power equipment provided in an embodiment of the present application;

[0027] Figure 2 Schematic diagram of the process of the alarm processing method based on computing power equipment provided in the embodiment of the present application Figure 1 ;

[0028] Figure 3 Schematic diagram of the process of the alarm processing method based on computing power equipment provided in the embodiment of the present application Figure 2 ;

[0029] Figure 4 A schematic diagram of the structure of an alarm processing device based on computing power equipment provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of the structure of the server provided in an embodiment of the present application.

[0031] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0032] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0033] Figure 1 A schematic diagram of a scenario of an alarm processing method based on computing power equipment provided in an embodiment of the present application, such as Figure 1 As shown, it includes: multiple computing devices 101, a server 102 and a display platform 103.

[0034] It is understood that the structure illustrated in the embodiment of the present application does not constitute a specific limitation on the alarm processing method based on computing power equipment. In other feasible implementations of the present application, the above architecture may include more or fewer components than shown in the figure, or combine or split certain components, or arrange the components differently. The specific configuration can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0035] During the specific implementation process, when multiple computing devices 101 fail, device alarm data will be generated, and the multiple computing devices 101 will send the device alarm data to the server 102; the server 102 performs a series of processing on the device alarm data to obtain at least one comprehensive alarm event; the server 102 outputs the comprehensive alarm event to the display platform 103 for display.

[0036] In the digital age, the integration of diverse computing power is becoming a trend. In scenarios such as data centers, the collaborative work of multiple heterogeneous computing devices generates a large amount of alarm data. However, because the devices come from different manufacturers, the alarm data differs, making unified management, analysis, and processing difficult. This makes it difficult for administrators to quickly and accurately grasp the operating status of the entire computing system, and to promptly identify and resolve potential problems. Currently, when integrating alarm data from different computing devices, existing technologies directly display the alarm data after performing a large amount of manual conversion and adaptation work. However, this existing technology method is inefficient and prone to errors, resulting in low integration accuracy. Furthermore, the direct display of alarm data results in a large amount of redundant alarm data, which reduces the efficiency of locating the cause of the alarm.

[0037] In order to solve the above technical problems, the present application proposes the following technical concept: Taking into account the need for a large amount of manual conversion and adaptation, which leads to reduced integration efficiency and accuracy. The inventors thought of obtaining mapping rules from a pre-built alarm mapping rule library based on the device type and device model of different computing power devices; according to the mapping rules, the alarm data of each device is converted into standard device alarm data, which improves the integration efficiency on the one hand, and on the other hand, the automatic conversion according to the mapping rules is not prone to errors, thereby improving the accuracy of integration. Considering that the alarm data is directly displayed, there is a large amount of redundant alarm data, which reduces the efficiency of locating the cause of the alarm. The inventors thought of aggregating the device alarm events with correlation to obtain at least one comprehensive alarm event and output the comprehensive alarm event; reducing redundant alarm data, thereby providing a data basis for locating the cause of the alarm and improving the efficiency of locating the cause of the alarm.

[0038] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0039] Figure 2 Schematic diagram of the process of the alarm processing method based on computing power equipment provided in the embodiment of the present application Figure 1 ,like Figure 2 As shown, the method includes:

[0040] S201: Receive device alarm data sent by multiple computing devices; each device alarm data carries the device type and device model.

[0041] In this embodiment, the computing power device includes a central processing unit, a graphics processing unit, a dedicated integrated circuit, and a field programmable gate array, etc.

[0042] In this embodiment, device alarm data sent by different computing devices is received. These device alarm data are proactively sent by each computing device when hardware failures, software anomalies, or resource overloads occur. Each alarm data item carries the device type, such as GPU and CPU, and the device model, such as XX-9000 and YY-7200.

[0043] S202: Acquire mapping rules from a pre-built alarm mapping rule library according to the device type and device model.

[0044] The mapping rules include field mapping rules and semantic conversion rules.

[0045] Specifically, the mapping rules corresponding to the device type are obtained from the pre-built alarm mapping rule library; and the field mapping rules and semantic conversion rules corresponding to the device model are obtained from the mapping rules corresponding to the device type.

[0046] In this embodiment, the pre-built alarm mapping rule library stores corresponding field mapping rules and semantic conversion rules for computing devices of different device types and device models, and classifies and indexes them according to the hierarchical structure of device type-device model. For example, the alarm rule library will establish field mapping rules and semantic conversion rules for GPU-model A, CPU-model B, etc. According to the device type, the corresponding mapping rule is located in the pre-built alarm rule library through the hierarchical index, and then the corresponding field mapping rule and semantic conversion rule are obtained according to the device model.

[0047] Optionally, the pre-built alarm mapping rule base can be dynamically updated based on new computing devices and device alarm data.

[0048] S203: Convert each device alarm data into standard device alarm data according to the mapping rule.

[0049] Specifically, the fields in the alarm data of each device are mapped into the fields in the pre-built alarm model according to the field mapping rules to obtain the initial standard device alarm data; the fields in the pre-built alarm model include the alarm content; according to the semantic conversion rules, the alarm content in the initial standard device alarm data is converted to obtain standard device alarm data.

[0050] In this embodiment, the pre-built alarm model defines a common model to uniformly describe the device alarm data generated by different computing devices, thereby solving problems such as confusing alarm formats and inconsistent semantics caused by different equipment manufacturers.

[0051] In this embodiment, the fields in the pre-built alarm model include: basic alarm information, device information, alarm content, alarm level, and occurrence time. The basic alarm information includes the alarm ID and alarm type, such as hardware failure, software anomaly, and resource overload; the device information includes the device type, model, IP address, and cluster to which it belongs; the alarm content details the specific circumstances of the alarm event, such as high temperature or memory usage exceeding a threshold; the alarm level is categorized according to a unified standard into emergency, severe, warning, and prompt; and the occurrence time records the specific time when the alarm event occurred.

[0052] For example, the device alarm data of the GPU of manufacturer A is in Json format, as follows:

[0053] {

[0054] "deviceType":"GPU",

[0055] "model":"Model 1",

[0056] "alertId":"A-001",

[0057] "message":"GPU temp 92℃, over limit",

[0058] "level":"serious",

[0059] "time":"Year A-Month B-Month CXX:XX:XX",

[0060] "ip":"URL-1",

[0061] "cluster":"Computing power cluster-1"

[0062] }

[0063] For example, deviceType is mapped to the device type, which is GPU; model is mapped to the device model, which is model 1; alertId is mapped to the alarm ID, which is A-001; message is mapped to the alarm content, which is GPU temp 92°C, over limit, indicating a hardware failure; level is mapped to the alarm level, which is severe; time is mapped to the alarm time, which is XX:XX:XX:XX:A year-month-month-month-month-month-month; ip is mapped to the device IP address, which is URL-1; cluster is mapped to the cluster to which it belongs, which is computing cluster-1. The device alarm data of manufacturer A's GPU is mapped to the fields in the pre-built alarm model according to the field mapping rules. The resulting initial standard device alarm data is:

[0064] {

[0065] "Basic alarm information":{

[0066] "Alarm ID":"A-001",

[0067] "Alarm Type": "Hardware Failure"

[0068] },

[0069] "Device Information":{

[0070] "Device Type": "GPU",

[0071] "Device Model":"Model 1",

[0072] "Device IP address":"URL-1",

[0073] "Cluster": "Computing Cluster-1"

[0074] },

[0075] "Alarm content": "GPU temp 92℃, over limit",

[0076] "Alarm Level": "Serious",

[0077] "Occurrence time": "Year A-Month B-Month C XX:XX:XX"

[0078] }

[0079] For example, according to the semantic conversion rule, the alarm content is restated, and GPU temp 92° C., overlimit is converted into GPU temperature is too high, exceeding the threshold.

[0080] For example, the device alarm data of the GPU of manufacturer B is in XML format, as follows:

[0081] <alertdata>

[0082] <devtype> GPU< / devtype>

[0083] <modelnum> Model 2< / modelnum>

[0084] <alertcode> B-002< / alertcode>

[0085] <description> VRAM usage 96%< / description>

[0086] <severity> urgent< / severity>

[0087] <occurtime> D year-E month-F day XX:XX:XX< / occurtime>

[0088] <ipaddr> URL-2< / ipaddr>

[0089] <clustername> Computing Cluster-1< / clustername>

[0090] < / alertdata>

[0091] For example, DevType maps to the device type, which is GPU; ModelNum maps to the device model, which is Model 2; AlertCode maps to the alarm ID, which is B-002; Description maps to the alarm content, which is VRAM usage 96%, indicating resource overload; Severity maps to the alarm level, which is Emergency; OccurTime maps to the alarm time, which is D-year-E-month-F-day XX:XX:XX; IPAddr maps to the device IP address, which is URL-2; ClusterName maps to the cluster to which it belongs, which is Compute Cluster-1. The device alarm data of manufacturer B's GPU is mapped to the fields in the pre-built alarm model according to the field mapping rules. The resulting initial standard device alarm data is:

[0092] {

[0093] "Basic alarm information":{

[0094] "Alarm ID":"B-002",

[0095] "Alarm Type": "Resource Overload"

[0096] },

[0097] "Device Information":{

[0098] "Device Type": "GPU",

[0099] "Device Model": "Model 2",

[0100] "Device IP address":"URL-2",

[0101] "Cluster": "Computing Cluster-1"

[0102] },

[0103] "Alarm content": "VRAM usage 96%",

[0104] "Alarm Level": "Emergency",

[0105] "Occurrence time": "D year-E month-F day XX:XX:XX"

[0106] }

[0107] For example, according to the semantic conversion rule, the alarm content is restated, and VRAM usage 96% is converted into GPU display memory usage being too high.

[0108] In this embodiment, through field mapping rules and semantic conversion rules, the device alarm data of computing devices from different manufacturers are uniformly converted into device alarm data that conforms to the standards of the pre-built alarm model.

[0109] Optionally, the converted standard device alarm data is stored in an alarm database.

[0110] S204: Identify device alarm events with associated relationships from standard device alarm data.

[0111] Specifically, step S204 includes S2041 to S2044:

[0112] S2041: Obtain at least one main alarm event from standard device alarm data according to pre-built alarm association rules.

[0113] In this embodiment, the main alarm event is a root cause or triggering alarm event, and is the source that causes other related alarm events to occur.

[0114] S2042: Acquire at least one secondary alarm event associated with any primary alarm event from standard device alarm data according to pre-built alarm association rules.

[0115] In this embodiment, alarm events are analyzed for correlation based on pre-built alarm correlation rules. When a primary alarm event is detected, such as a server power module failure, the system automatically searches for and matches associated secondary alarm events, such as abnormal alarms generated by computing devices such as the CPU and GPU on the server node.

[0116] In the subsequent embodiments, the process of constructing alarm association rules is introduced.

[0117] S2043: Determine whether there is an association relationship between any primary alarm event and at least one associated secondary alarm event.

[0118] S2044: If it is determined that there is an association relationship, any primary alarm event and at least one associated secondary alarm event are determined as device alarm events with an association relationship.

[0119] For example, a determination is made as to whether a correlation exists between a server power module failure and abnormal alarms generated by computing devices such as the CPU and GPU on the server node. If so, the server power module failure and the abnormal alarms generated by computing devices such as the CPU and GPU on the server node are determined to be device alarm events with a correlation.

[0120] S205: Aggregate the associated device alarm events to obtain at least one comprehensive alarm event.

[0121] Specifically, it is determined whether the main alarm event among the associated device alarm events is resolved; if the main alarm event is not resolved, the associated device alarm events are aggregated to obtain at least one comprehensive alarm event.

[0122] In this embodiment, the aggregation processing methods include merging alarms and suppressing slave aggregation. Merging alarms is to merge device alarm events with related relationships into a comprehensive alarm event, which includes all relevant device alarm data, making it convenient for administrators to quickly understand the overall situation of the alarm; suppressing slave alarms is to temporarily suppress the display of slave alarm events when the main alarm event has been processed, so as to avoid redundant data interfering with the administrator.

[0123] Optionally, a unique comprehensive alarm ID is generated for each aggregated comprehensive alarm event, and information such as the association relationship and processing time during the aggregation process is recorded.

[0124] S206: Output a comprehensive alarm event.

[0125] In summary, mapping rules are obtained from the pre-built alarm mapping rule library according to the device type and device model of different computing power devices; according to the mapping rules, the alarm data of each device is converted into standard device alarm data, which improves the integration efficiency on the one hand, and on the other hand, automatic conversion according to the mapping rules is not prone to errors, thereby improving the accuracy of integration; device alarm events with related relationships are aggregated to obtain at least one comprehensive alarm event, and the comprehensive alarm event is output; redundant alarm data is reduced, thereby providing a data basis for locating the cause of the alarm, thereby improving the efficiency of locating the cause of the alarm.

[0126] Based on the above embodiment, in this embodiment, the process of constructing alarm association rules is introduced. Figure 3 Schematic diagram of the process of the alarm processing method based on computing power equipment provided in the embodiment of the present application Figure 2 ,like Figure 3 Shown, including:

[0127] S301: Collect historical device alarm data of multiple computing devices.

[0128] In this embodiment, the historical device alarm data of multiple computing power devices are used to explore the occurrence patterns of alarms of different computing power devices, such as which computing power devices will generate alarms when a certain type of alarm occurs.

[0129] S302: Obtain device information of each computing device.

[0130] In this embodiment, the architecture and business logic of the computing system, as well as the physical connection relationships, business dependencies, and causal relationships between the computing devices are analyzed from the device information of each computing device.

[0131] For example, physical connection relationships, such as the hardware connection between the server and the power module, CPU and GPU; business dependency relationships, such as an application relying on specific GPU resources to run; and causal relationships, such as A alarm will inevitably lead to B alarm.

[0132] S303: Obtain pre-built alarm association rules based on historical device alarm data and device information of each computing device.

[0133] In this embodiment, based on the architecture and business logic of the computing system, as well as the physical connection relationships, business dependencies and causal relationships between various computing devices, historical device alarm data is analyzed and alarm association rules are constructed.

[0134] For example, by analyzing historical device alarm data, it was found that after the server power module failed, the CPU and GPU of the node often generated alarms due to insufficient power supply. An association rule can be established: when the server power module generates an abnormal alarm, it is highly likely that the CPU and GPU on the node will generate abnormal alarms.

[0135] In summary, we can collect historical device alarm data from multiple computing devices, obtain device information for each computing device, and then generate pre-built alarm association rules based on historical device alarm data and device information for each computing device. By building alarm association rules, we can quickly identify alarm events with related relationships, providing a basis for subsequent aggregation processing, thereby reducing redundant device alarm data and improving the efficiency of locating the cause of the alarm.

[0136] Figure 4 A schematic diagram of the structure of the alarm processing device based on computing power equipment provided in the embodiment of the present application is shown as follows: Figure 4 As shown, the alarm processing device based on computing power equipment provided in this embodiment includes: a receiving module 401, an acquisition module 402, a conversion module 403, an identification module 404, an aggregation module 405 and an output module 406.

[0137] The receiving module 401 is used to receive device alarm data sent by multiple computing devices; each device alarm data carries the device type and device model.

[0138] The acquisition module 402 is configured to acquire mapping rules from a pre-built alarm mapping rule library according to the device type and device model.

[0139] The conversion module 403 is used to convert each device alarm data into standard device alarm data according to the mapping rule.

[0140] The identification module 404 is configured to identify device alarm events with associated relationships from standard device alarm data.

[0141] The aggregation module 405 is configured to aggregate the associated device alarm events to obtain at least one comprehensive alarm event.

[0142] The output module 406 is used to output comprehensive alarm events.

[0143] In one possible implementation, the mapping rules include field mapping rules and semantic conversion rules; accordingly, the acquisition module 402 is specifically used to: obtain the mapping rules corresponding to the device type from the pre-built alarm mapping rule library; and obtain the field mapping rules and semantic conversion rules corresponding to the device model from the mapping rules corresponding to the device type.

[0144] In one possible implementation, the conversion module 403 is specifically used to: map the fields in each device alarm data into fields in a pre-built alarm model according to field mapping rules to obtain initial standard device alarm data; wherein the fields in the pre-built alarm model include alarm content; and convert the alarm content in the initial standard device alarm data according to semantic conversion rules to obtain standard device alarm data.

[0145] In one possible implementation, the identification module 404 is specifically used to: obtain at least one main alarm event from standard equipment alarm data according to pre-constructed alarm association rules; obtain at least one secondary alarm event associated with any main alarm event from standard equipment alarm data according to pre-constructed alarm association rules; determine whether there is an association relationship between any main alarm event and at least one associated secondary alarm event; if it is determined that there is an association relationship, determine any main alarm event and at least one associated secondary alarm event as equipment alarm events with an association relationship.

[0146] In a possible implementation, the alarm processing device based on computing power equipment also includes a construction module, which is specifically used to: collect historical equipment alarm data of multiple computing power equipment; obtain equipment information of each computing power equipment; and obtain pre-constructed alarm association rules based on historical equipment alarm data and equipment information of each computing power equipment.

[0147] In a possible implementation, the aggregation module 405 is specifically used to: determine whether the main alarm event among the associated device alarm events has been resolved; if the main alarm event has not been resolved, aggregate the associated device alarm events to obtain at least one comprehensive alarm event.

[0148] The alarm processing device based on computing power equipment provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar, and are not described in detail in this embodiment.

[0149] Figure 5 This is a schematic diagram of the structure of the server provided in the embodiment of the present application. Figure 5 As shown, the server provided in this embodiment includes: at least one processor 501 and a memory 502. Optionally, the server also includes a communication component 503. The processor 501, the memory 502 and the communication component 503 are connected via a bus.

[0150] In a specific implementation process, at least one processor 501 executes the computer-executable instructions stored in the memory 502, so that the at least one processor 501 performs the above method.

[0151] The specific implementation process of the processor 501 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0152] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0153] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0154] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0155] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0156] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0157] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0158] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0159] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0160] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0161] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0162] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0163] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0164] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. An alarm processing method based on computing power equipment, characterized in that: Applicable to servers, including: Receive device alarm data sent by multiple computing devices; each device alarm data carries the device type and model; Obtaining mapping rules from a pre-built alarm mapping rule library according to the device type and the device model; According to the mapping rule, converting the alarm data of each device into standard device alarm data; Identifying device alarm events with associated relationships from the standard device alarm data; Aggregating the associated device alarm events to obtain at least one comprehensive alarm event; Output the comprehensive alarm event.

2. The method according to claim 1, characterized in that The mapping rules include field mapping rules and semantic conversion rules; Accordingly, the obtaining of mapping rules from a pre-built alarm mapping rule library according to the device type and the device model includes: Obtaining a mapping rule corresponding to the device type from the pre-built alarm mapping rule library; The field mapping rule and the semantic conversion rule corresponding to the device model are obtained from the mapping rule corresponding to the device type.

3. The method according to claim 2, characterized in that The converting the device alarm data into standard device alarm data according to the mapping rule includes: Mapping the fields in the device alarm data to the fields in the pre-built alarm model according to the field mapping rule to obtain initial standard device alarm data; wherein the fields in the pre-built alarm model include alarm content; According to semantic conversion rules, the alarm content in the initial standard device alarm data is converted to obtain standard device alarm data.

4. The method according to claim 1, wherein The step of identifying device alarm events having an associated relationship from the standard device alarm data includes: According to pre-established alarm association rules, obtaining at least one main alarm event from the standard device alarm data; According to the pre-built alarm association rule, obtaining at least one secondary alarm event associated with any primary alarm event from the standard device alarm data; Determining whether any one of the primary alarm events has an association relationship with the associated at least one secondary alarm event; If it is determined that there is an association relationship, any one of the main alarm events and the at least one associated secondary alarm event are determined as device alarm events with an association relationship.

5. The method according to claim 4, characterized in that Before receiving the device alarm data sent by the plurality of computing devices, the method further includes: Collect historical device alarm data from multiple computing devices; Obtain device information of each computing device; A pre-built alarm association rule is obtained based on the historical device alarm data and the device information of each computing device.

6. The method according to any one of claims 1 to 5, characterized in that The aggregating the associated device alarm events to obtain at least one comprehensive alarm event includes: Determining whether the main alarm event among the associated device alarm events has been resolved; If the main alarm event is not resolved, the associated device alarm events are aggregated to obtain at least one comprehensive alarm event.

7. An alarm processing device based on computing power equipment, characterized in that: Applicable to servers, including: A receiving module is used to receive device alarm data sent by multiple computing devices; each device alarm data carries the device type and model; An acquisition module, configured to acquire a mapping rule from a pre-built alarm mapping rule library according to the device type and the device model; A conversion module, configured to convert the device alarm data into standard device alarm data according to the mapping rule; An identification module, configured to identify device alarm events having associated relationships from the standard device alarm data; an aggregation module, configured to aggregate the associated device alarm events to obtain at least one comprehensive alarm event; The output module is used to output the comprehensive alarm event.

8. A server, characterized in that: include: memory for storing computer programs; A processor, configured to implement the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when the computer program is executed by a processor.

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