Data center-based operation and maintenance monitoring method, device, equipment and storage medium

Abstract

The present invention discloses an operation and maintenance monitoring method, device, equipment and storage medium based on a data center. The method includes: obtaining original monitoring data collected by an associated monitoring system, each original monitoring data includes an original alarm level; standardizing the original alarm level, obtaining a standard alarm level and determining monitoring data to be processed; performing source detection on the monitoring data to be processed, obtaining a target source; performing validity detection on the monitoring data to be processed, obtaining a validity detection result, and determining the monitoring data to be processed whose validity detection result is that the alarm is valid as valid monitoring data; formatting based on the valid monitoring data and the target source corresponding to the valid monitoring data, obtaining the target monitoring data; based on the target source, automatically monitoring the target monitoring data, and obtaining the alarm monitoring result. The method can improve the efficiency of the data center in monitoring the target monitoring data collected by the associated monitoring system.

Description

Technical Field

[0001] The present invention relates to the field of data monitoring technology, and in particular to an operation and maintenance monitoring method, device, equipment and storage medium based on a data center. Background Art

[0002] Monitoring is an important part of the current business system operation and maintenance. Through monitoring, operation and maintenance personnel discover and locate fault events in the business system so as to maintain and update the business system according to the fault events. Generally speaking, enterprises (especially group enterprises) will configure multiple business systems. Operation and maintenance personnel use different monitoring systems to monitor multiple business systems separately and feed back the monitoring results to the enterprise's monitoring management center. Since the monitoring results collected by different monitoring systems are not compatible, it is impossible to effectively monitor and analyze the monitoring results collected by multiple monitoring systems, resulting in low monitoring and analysis efficiency. Summary of the invention

[0003] The embodiments of the present invention provide an operation and maintenance monitoring method, device, equipment and storage medium based on a data center to solve the problem that the monitoring results collected by different monitoring systems are currently incompatible, resulting in the inability to effectively monitor and analyze the monitoring results collected by multiple monitoring systems, resulting in low monitoring and analysis efficiency.

[0004] An operation and maintenance monitoring method based on a data center, comprising:

[0005] Obtaining original monitoring data corresponding to the business system collected by the associated monitoring system, each original monitoring data including an original alarm level;

[0006] The original alarm level is standardized to obtain a standard alarm level, and the original monitoring data whose standard alarm level is a target alarm level is determined as monitoring data to be processed;

[0007] Performing source detection on the monitoring data to be processed to obtain a target source corresponding to the monitoring data to be processed;

[0008] Performing a validity check on the monitoring data to be processed, obtaining a validity check result, and determining the monitoring data to be processed whose validity check result is alarm valid as valid monitoring data;

[0009] Performing formatting processing based on the valid monitoring data and the target source corresponding to the valid monitoring data to obtain target monitoring data;

[0010] Based on the target source, the target monitoring data is automatically monitored to obtain alarm monitoring results.

[0011] An operation and maintenance monitoring device based on a data center, comprising:

[0012] The original monitoring data acquisition module is used to obtain the original monitoring data corresponding to the business system collected by the associated monitoring system, and each original monitoring data includes the original alarm level;

[0013] A module for acquiring monitoring data to be processed, used for standardizing the original alarm level, acquiring a standard alarm level, and determining the original monitoring data whose standard alarm level is a target alarm level as monitoring data to be processed;

[0014] A target source acquisition module, used to perform source detection on the monitoring data to be processed and acquire the target source corresponding to the monitoring data to be processed;

[0015] An effective monitoring data acquisition module is used to perform validity detection on the monitoring data to be processed, obtain validity detection results, and determine the monitoring data to be processed with the validity detection results being alarm valid as effective monitoring data;

[0016] A target monitoring data acquisition module, used to perform formatting processing based on the valid monitoring data and the target source corresponding to the valid monitoring data, to acquire the target monitoring data;

[0017] The alarm monitoring result acquisition module is used to automatically monitor the target monitoring data based on the target source and obtain the alarm monitoring result.

[0018] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned operation and maintenance monitoring method based on a data center when executing the computer program.

[0019] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the operation and maintenance monitoring method based on a data center is implemented.

[0020] In the above-mentioned data center-based operation and maintenance monitoring method, device, equipment and storage medium, the data center is networked with the associated monitoring system so that the data center can obtain the original monitoring data corresponding to the business system collected by the associated monitoring system from the associated monitoring system, and realize unified monitoring and multi-level monitoring of all the original monitoring data collected by the associated monitoring system; the original alarm level of the original monitoring data is standardized to determine the standard alarm level, so as to screen out the monitoring data to be processed according to the standard alarm level, and ensure the pertinence of the screening of the monitoring data to be processed; the source of the monitoring data to be processed is detected to determine the target source to ensure the pertinence of subsequent automated monitoring; based on the validity detection result of the validity detection of the monitoring data to be processed, the effective monitoring data is screened to ensure the pertinence and timeliness of subsequent automated monitoring; based on the effective monitoring data and its corresponding target source, formatting is performed to obtain target monitoring data with a unified format to ensure the feasibility of the subsequent automated monitoring process; finally, the formatted target monitoring data corresponding to any target source is automatically monitored to obtain the alarm monitoring result output by the automated monitoring program, thereby improving the efficiency of the data center in monitoring the target monitoring data collected by at least one associated monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0022] Figure 1 It is a schematic diagram of an application environment of an operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0023] Figure 2 is a flow chart of an operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0024] Figure 3 is another flow chart of the operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0025] Figure 4 is another flow chart of the operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0026] Figure 5 is another flow chart of the operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0027] Figure 6 is another flow chart of the operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0028] Figure 7 is another flow chart of the operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0029] Figure 8 is another flow chart of the operation and maintenance monitoring method based on a data center in one embodiment of the present invention;

[0030] Fig. 9 is a schematic diagram of an operation and maintenance monitoring device based on a data center in one embodiment of the present invention;

[0031] Fig.10 is a schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0033] The operation and maintenance monitoring method based on a data center provided in an embodiment of the present invention can be applied as follows: Figure 1 Specifically, the data center-based operation and maintenance monitoring method is applied in a data center-based operation and maintenance monitoring system, and the data center-based operation and maintenance monitoring system includes: Figure 1 The data center shown is connected to at least one associated monitoring system that is connected to the data center in communication, and each associated monitoring system is connected to at least one business system, so that the associated monitoring system can collect the original monitoring data corresponding to the business system connected to it, and the data center can obtain all the original monitoring data from at least one associated monitoring system, and analyze and process all the original monitoring data to obtain the alarm monitoring results, so as to realize the automatic monitoring and analysis processing of the original monitoring data collected by all associated monitoring systems, realize the real-time and effective monitoring of multiple business systems, and improve the monitoring and analysis efficiency. Among them, the business system refers to a system that can realize a specific business that needs to be monitored. The business system is the monitored object, which can be a system of an application or application product. The associated monitoring system is a system connected to the business system for realizing the monitoring of the business system to realize the functions of whether there is a fault event and fault location. The data center refers to a processing center that communicates with at least one associated monitoring system to realize the automatic monitoring and analysis processing of the original monitoring data collected by all associated monitoring systems, and realizes the real-time and effective monitoring and analysis of multiple business systems.

[0034] The business system, associated monitoring system and data center in this embodiment all include a server and a client that communicates with the server through a network. The client, also known as the user end, refers to a program that corresponds to the server and provides local services to customers. The client can be installed on, but is not limited to, various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented as an independent server or a server cluster consisting of multiple servers.

[0035] In one embodiment, if Figure 2 As shown, a data center-based operation and maintenance monitoring method is provided, and the method is applied in Figure 1 The following steps are used to illustrate the server in the data center of FIG. 1 :

[0036] S201: Acquire original monitoring data corresponding to the business system collected by the associated monitoring system, each original monitoring data includes an original alarm level.

[0037] Among them, the original monitoring data is the unprocessed data generated by the associated monitoring system during the operation of the monitoring business system. Specifically, it is the relevant data generated by the associated monitoring system when it identifies a failure event during the operation of the monitoring business system, including but not limited to data content, event occurrence time, monitoring log, original alarm level and other information.

[0038] The original alarm level is the level determined by the associated monitoring system based on the alarm level judgment standard preset by the system, which is used to rate and classify the fault events identified and occurred during the operation of the monitoring business system. As an example, the monitoring business system can use the alarm levels such as Blocker, Critical, Major, Minor and Info and the corresponding alarm level judgment standards with the severity decreasing in sequence, or use the alarm levels such as L1, L2, L3, L4 and L5 and the corresponding alarm level judgment standards; the associated monitoring system monitors the operating conditions formed during the operation of the business system in real time, and if the operating conditions meet the corresponding alarm level judgment standards, the alarm level corresponding to the alarm level judgment standard is determined as the original alarm level.

[0039] In this example, the data center can send data collection instructions to at least one associated monitoring system connected to the network in real time or at a scheduled time, and receive the original monitoring data of at least one business system connected to it collected by each associated monitoring system based on the data collection instructions, so as to automatically monitor the original monitoring data collected by all associated monitoring systems in the data center, thereby realizing real-time and effective monitoring of multiple business systems, improving monitoring efficiency, and saving monitoring costs.

[0040] S202: Standardize the original alarm level to obtain a standard alarm level, and determine the original monitoring data whose standard alarm level is a target alarm level as monitoring data to be processed.

[0041] Among them, standardizing the original alarm level means converting the original alarm levels determined by different alarm level judgment standards collected by all related monitoring systems into alarm levels corresponding to the unified alarm level judgment standards. Accordingly, the standard alarm level is the alarm level determined after the original alarm level is standardized. The target alarm level refers to the pre-set alarm level that needs to be monitored. For example, the alarm level with a more serious fault degree can be set as the target alarm level, so that the fault events corresponding to the target alarm level can be monitored at multiple levels through the data center to ensure monitoring efficiency.

[0042] As an example, after obtaining the original monitoring data collected by at least one associated monitoring system, the data center standardizes the original alarm levels corresponding to all the original monitoring data to determine the corresponding standard alarm levels; it determines whether the standard alarm level corresponding to each original monitoring data is the target alarm level; if the standard alarm level is the target alarm level, the original monitoring data corresponding to the standard alarm level is determined as the monitoring data to be processed, so as to carry out subsequent automated monitoring, thereby ensuring multi-level real-time monitoring of the original monitoring data corresponding to the target alarm level and improving the targeted monitoring.

[0043] S203: Perform source detection on the monitoring data to be processed, and obtain the target source corresponding to the monitoring data to be processed.

[0044] Among them, the target source is to perform source detection on the monitoring data to be processed to determine the source corresponding to the monitoring data to be processed, specifically a professional company or business team in the application business system, for example, professional company A or operation and maintenance responsibility group B.

[0045] As an example, after determining the monitoring data to be processed, the data center performs source detection on each monitoring data to be processed to determine its corresponding target source from the data content of the monitoring data to be processed, so as to conduct data automated monitoring and analysis in the subsequent monitoring and analysis dimension of the target source, thereby ensuring the effectiveness of unified monitoring of the monitoring data corresponding to a target source in the business system, so as to facilitate real-time and effective tracking of fault events.

[0046] S204: Perform validity detection on the monitoring data to be processed, obtain validity detection results, and determine the monitoring data to be processed with a validity detection result indicating that the monitoring data is alarm valid as valid monitoring data.

[0047] Among them, the validity check of the monitoring data to be processed is a process for real-time detection of whether the fault event corresponding to the monitoring data to be processed is legal and valid, so as to determine the validity check result. The validity check result is the result determined after the validity check of the monitoring data to be processed. In this example, the validity check result includes two situations: the alarm is valid and the alarm is invalid.

[0048] As an example, the data center performs a validity check on the monitoring data to be processed according to a pre-set validity check script to determine whether the validity check result corresponding to the monitoring data to be processed is an alarm valid or an alarm invalid; and screens out the monitoring data to be processed with valid alarms and determines them as valid monitoring data, so as to subsequently perform automated monitoring and processing on the valid monitoring data to ensure the pertinence and timeliness of the monitoring processing.

[0049] S205: Perform formatting processing based on the valid monitoring data and the target source corresponding to the valid monitoring data to obtain the target monitoring data.

[0050] As an example, after obtaining valid monitoring data, the data center uses the determined target source to format the valid monitoring data so as to format the valid monitoring data uploaded by all related monitoring systems. That is, the format of the incompatible valid monitoring data uploaded by different related monitoring systems is converted into data with a unified format that can be recognized by subsequent automated monitoring programs, so as to ensure the feasibility of subsequent automated monitoring processing, thereby helping to improve monitoring efficiency.

[0051] S206: Based on the target source, automatically monitor the target monitoring data to obtain alarm monitoring results.

[0052] As an example, a data center is pre-installed with an automated monitoring program. By executing the automated monitoring program, the formatted target monitoring data corresponding to any target source can be automatically monitored to obtain the alarm monitoring results output by the automated monitoring program, thereby improving the efficiency of the data center in monitoring the target monitoring data collected by at least one associated monitoring system. Since the target monitoring data has been formatted, the feasibility of the automated monitoring process can be guaranteed.

[0053] In the data center-based operation and maintenance monitoring method provided in the present embodiment, the data center is connected to the associated monitoring system so that the data center can obtain the original monitoring data corresponding to the business system collected by the associated monitoring system from the associated monitoring system, and realize unified monitoring and multi-level monitoring of all the original monitoring data collected by the associated monitoring system; the original alarm level of the original monitoring data is standardized to determine the standard alarm level, so as to filter out the monitoring data to be processed according to the standard alarm level, and ensure the pertinence of the screening of the monitoring data to be processed; the source of the monitoring data to be processed is detected to determine the target source to ensure the pertinence of the subsequent automated monitoring; the effective monitoring data is filtered based on the validity detection result of the validity detection of the monitoring data to be processed to ensure the pertinence and timeliness of the subsequent automated monitoring; the effective monitoring data and its corresponding target source are formatted to obtain target monitoring data with a unified format to ensure the feasibility of the subsequent automated monitoring process; finally, the formatted target monitoring data corresponding to any target source is automatically monitored to obtain the alarm monitoring result output by the automated monitoring program, thereby improving the efficiency of the data center in monitoring the target monitoring data collected by at least one associated monitoring system.

[0054] As an example, after step S206, the operation and maintenance monitoring method based on the data center further includes the following steps: based on the alarm monitoring result, executing a target monitoring reminder mechanism corresponding to the alarm monitoring result.

[0055] In this example, multiple original monitoring reminder mechanisms are pre-set in the data center, and each original monitoring reminder mechanism corresponds to a reminder condition. The original monitoring reminder mechanism is a pre-set mechanism for reminder processing, for example, it can be set to a telephone reminder, email reminder or other reminder processing mechanism for the operation and maintenance personnel.

[0056] Specifically, after obtaining the alarm monitoring results corresponding to any target source, the data center determines which reminder condition the alarm monitoring results meet, and determines the original monitoring reminder mechanism corresponding to the reminder condition it meets as the target reminder mechanism, executes the target monitoring reminder mechanism corresponding to the alarm monitoring results, and sends reminder information to the corresponding operation and maintenance personnel, thereby achieving timely response processing for all target monitoring data corresponding to the target source and improving response processing efficiency.

[0057] As an example, after step S206, the operation and maintenance monitoring method based on the data center also includes the following steps: displaying the alarm monitoring results corresponding to the target monitoring data according to the preset display interface. For example, the alarm monitoring results corresponding to the target monitoring data are displayed through a Web page; or, the alarm monitoring results corresponding to the target monitoring data are displayed through a regular report; or, the alarm monitoring results corresponding to the target monitoring data are displayed through an external interface. Accordingly, processing interfaces such as page query, regular report and data interface can be provided in the client of the data center to facilitate users to perform temporary query needs, regular inspections and checks through the client.

[0058] In one embodiment, if Figure 3 As shown, step S201, i.e., obtaining the original monitoring data corresponding to the business system collected by the associated monitoring system, specifically includes the following steps:

[0059] S301: Monitor the number of monitoring systems corresponding to the associated monitoring system in real time.

[0060] The number of monitoring systems is the number of associated monitoring systems connected to the data center. As an example, the data center may broadcast an http request to all associated monitoring systems, count the http responses corresponding to the http requests received within a preset time period, and determine the number of monitoring systems corresponding to the associated monitoring system according to the number of received http responses.

[0061] S302: Create data collection processes corresponding to the number of monitoring systems, and each data collection process corresponds to an associated monitoring system.

[0062] The data collection process is a process for collecting data created on a server corresponding to a data center. In this example, each data collection process corresponds to an associated monitoring system, so that the data collection process is dedicated to collecting the original monitoring data corresponding to the corresponding associated monitoring system, ensuring the pertinence of data collection. For example, the data collection process can be associated with the network address corresponding to the associated monitoring system, so that the data collection process can communicate with the associated monitoring system according to the network address, thereby obtaining the original monitoring data sent by the associated monitoring system.

[0063] S303: Execute all data collection processes in parallel to obtain the original monitoring data corresponding to the business system collected by each associated monitoring system in the current collection cycle.

[0064] The current collection period refers to the time period of this data collection, specifically, the period from the collection time of the last data collection to the current system time when the data center generates the data collection instruction.

[0065] As an example, the data center executes all data collection processes in parallel, so that each data collection process sends a data collection instruction to the corresponding associated monitoring system, and the data collection instruction carries the current collection cycle; after receiving the data collection instruction, each associated monitoring system sends all the original monitoring data with the event occurrence time within the data collection cycle to the data center, so that the data center can obtain the original monitoring data corresponding to the business system collected by each associated monitoring system within the current collection cycle, thereby ensuring the temporal continuity of the collected original monitoring data. Moreover, executing all data collection processes in parallel can realize the simultaneous collection of the original monitoring data generated by multiple associated monitoring systems during the operation of their corresponding business systems, thereby ensuring the collection efficiency and timeliness of the original monitoring data, and avoiding the data center collecting the original monitoring data of different associated monitoring systems late, resulting in failure to monitor and handle fault events in a timely manner.

[0066] In the data center-based operation and maintenance monitoring method provided in the present embodiment, corresponding data collection processes are created based on the number of monitoring systems corresponding to the associated monitoring systems, so that each data collection process can respectively obtain the original monitoring data collected by the associated monitoring system corresponding to it, thereby ensuring the targeted collection of the original monitoring data; all data collection processes are executed in parallel to collect the original monitoring data, thereby realizing the simultaneous collection of the original monitoring data generated during the operation of the corresponding business systems monitored by multiple associated monitoring systems, thereby ensuring the collection efficiency and timeliness of the original monitoring data; each data collection process can realize the collection of the original monitoring data generated by the associated monitoring system monitoring the business system during the current collection cycle, thereby ensuring the temporal continuity of the collected original monitoring data.

[0067] In one embodiment, if Figure 4 As shown, step S203, that is, performing source detection on the monitoring data to be processed to obtain the target source corresponding to the monitoring data to be processed, specifically includes the following steps:

[0068] S401: Using a keyword recognition algorithm to recognize the monitoring data to be processed, and determining whether the monitoring data to be processed contains a source key field.

[0069] The keyword recognition algorithm is an algorithm used to recognize whether a text content includes a specific keyword, and the keyword recognition algorithm includes but is not limited to a regular matching algorithm, a string interception algorithm, and a hybrid matching algorithm. The source key field is a field that can directly reflect the source of its data, for example, a source field or a system attribute field is pre-set as a source key field.

[0070] S402: If the monitoring data to be processed includes a source key field, the field content corresponding to the source key field is determined as the target source corresponding to the monitoring data to be processed.

[0071] As an example, the data center uses a keyword recognition algorithm to identify the monitoring data to be processed, and determines that the data content of the monitoring data to be processed contains source key fields such as source fields or system attribute fields. The field content corresponding to the source key field is used as its target source, thereby improving the efficiency and accuracy of determining the target source.

[0072] S403: If the monitoring data to be processed does not contain the source key field, a keyword recognition algorithm is used to recognize the monitoring data to be processed, and it is determined whether the monitoring data to be processed contains the associated key field.

[0073] The associated key field is a field that cannot directly reflect the data source but is related to the data source, for example, the eventName field or the department field.

[0074] As an example, the data center uses a keyword recognition algorithm to identify the monitoring data to be processed. When it is determined that the data content of the monitoring data to be processed does not contain the source key field, the keyword recognition algorithm is then used to identify whether the monitoring data to be processed contains associated key fields, so as to perform subsequent processing based on the judgment result, thereby determining the target source corresponding to the monitoring data to be processed.

[0075] S404: If the monitoring data to be processed includes an associated key field, data processing is performed on the field content corresponding to the associated key field to obtain a target source corresponding to the monitoring data to be processed.

[0076] As an example, step S404, i.e., performing data processing on the field content corresponding to the associated key field to obtain the target source corresponding to the monitoring data to be processed, specifically includes the following steps: using the processing logic corresponding to the associated key field to perform data processing on the field content corresponding to the associated key field to determine the target source corresponding to the monitoring data to be processed. Among them, the processing logic corresponding to the associated key field is used to process the field content corresponding to the associated key field to obtain the processing logic of the target source. For example, the field content corresponding to the associated key field can be split, merged or otherwise processed to quickly and accurately determine the target source from the associated key field to ensure the efficiency of determining the target source.

[0077] As an example, step S404, i.e., performing data processing on the field content corresponding to the associated key field to obtain the target source corresponding to the monitoring data to be processed, specifically includes the following steps: splitting and extracting the field content corresponding to the associated key field to obtain the associated information; querying the associated mapping table based on the associated information, and determining the data source corresponding to the associated information in the associated mapping table as the target source corresponding to the monitoring data to be processed. Among them, splitting and extracting the field content corresponding to the associated key field refers to the process of splitting the field content of the associated key field and extracting the associated information related to the data source. The associated mapping table is a pre-set data table for storing associated information and its corresponding data source. It can be understood that this example can quickly determine its target source by performing table lookup processing based on the associated information extracted by splitting the associated key field, thereby ensuring the efficiency of determining the target source.

[0078] As another example, after step S403, that is, after using a keyword recognition algorithm to identify the monitoring data to be processed and determining whether the monitoring data to be processed contains associated key fields, if the monitoring data to be processed does not contain associated key fields, at this time, other processing logic for obtaining the target source (such as the processing logic corresponding to steps S501-S502) can be executed, or the monitoring data to be processed can be transferred to a manual processing mechanism, and the operation and maintenance personnel can manually calibrate its target source for subsequent processing. Other processing logics here can include calling a data source interface, determining the monitoring system information corresponding to the associated monitoring system that transmits the monitoring data to be processed, querying a pre-set source mapping table based on the monitoring system information, and determining the target source corresponding to the monitoring data to be processed.

[0079] In the data center-based operation and maintenance monitoring method provided in this embodiment, keyword recognition algorithms are used in turn to identify whether the monitoring data to be processed contains source key fields and associated key fields, so as to determine its target source according to the field contents corresponding to the source key fields and the associated key fields, thereby ensuring the accuracy and efficiency of the target source determination.

[0080] In one embodiment, if Figure 5 As shown, step S203, that is, performing source detection on the monitoring data to be processed to obtain the target source corresponding to the monitoring data to be processed, specifically includes the following steps:

[0081] S501: Use a preset source identification model to perform source detection on the monitoring data to be processed, and obtain at least one identification source and an identification probability corresponding to each identification source.

[0082] The preset source identification model is a pre-trained model for identifying the data source of monitoring data. Identifying the source is to use the preset source identification model to perform source detection on the monitoring data to be processed, and the data source is identified. The identification probability corresponding to the identified source refers to the probability that the preset source identification model identifies the monitoring data to be processed and determines that it belongs to a certain data source.

[0083] As an example, before step S201, the data center-based operation and maintenance monitoring method further includes a process of training a preset source identification model, which specifically includes the following steps:

[0084] (1) Based on the historical monitoring data, obtain model training samples and divide the model training samples into a training set and a test set. The historical monitoring data is the monitoring data collected before executing step S201, that is, before the current time of the system when the original monitoring data is obtained. The model training samples are samples for model training formed by pre-labeling the historical monitoring data with corresponding data sources.

[0085] (2) Using the model training samples in the training set to train the neural network model, update the model parameters in the neural network model, and obtain the original source identification model. As an example, the model training samples in the training set can be input into a CNN, RNN or other neural network model for model training to update the model parameters in the neural network model, thereby forming an original source identification model.

[0086] (3) The original source identification model is tested using the model training samples in the test set to obtain the model test results. If the model test results meet the preset standard, the original source identification model is determined as the preset source identification model. The model test results refer to the use of the model training samples in the test set to test the original source identification model to determine the test accuracy of the model training samples in the test set. For example, each model training sample in the test set is input into the original source identification model for identification to obtain its identification result; if the identification result is consistent with the data source marked by the model training sample, the identification is determined to be accurate; if the identification result is inconsistent with the data source marked by the model training sample, the identification is determined to be inaccurate; the test accuracy is determined based on the number of model training samples in the test set whose identification results are accurate and the number of all model training samples. The preset standard is a pre-set standard for evaluating whether the original source identification model meets the standard for being determined to have a high accuracy rate, for example, it can be set to 90%.

[0087] S502: Compare the maximum recognition probability with a preset probability threshold. If the maximum recognition probability is greater than the preset probability threshold, determine the recognition source corresponding to the maximum recognition probability as the target source corresponding to the monitoring data to be processed.

[0088] Among them, the maximum recognition probability is the maximum value of the recognition probabilities corresponding to the multiple recognition sources recognized by the preset source recognition model. Generally speaking, the greater the recognition probability, the more likely it is that the recognition source recognized by the preset source recognition model is the target source of the monitoring data to be processed. The preset probability threshold is a pre-set probability threshold used to evaluate whether the recognition probability reaches the target source.

[0089] As an example, the data center can use a pre-trained preset source identification model to perform source detection on the monitoring data to be processed, and obtain the detection result output by the preset source identification model, which includes at least one identification source and the identification probability corresponding to each identification source. Then, the identification probabilities corresponding to all identification sources are sorted, and the maximum identification probability is compared with the preset probability threshold. If the maximum identification probability is greater than the preset probability threshold, the identification source corresponding to the maximum identification probability is determined as the target source corresponding to the monitoring data to be processed. If the maximum identification probability is not greater than the preset probability threshold, other processing logic for obtaining the target source can be executed, or the monitoring data to be processed can be transferred to the manual processing mechanism, and the operation and maintenance personnel manually calibrate its target source for subsequent processing.

[0090] The data center-based operation and maintenance monitoring method provided in this embodiment uses a pre-trained preset source identification model to perform source detection on the monitoring data to be processed, so as to quickly and effectively determine its target source according to the data content in the monitoring data to be processed, thereby ensuring the accuracy and efficiency of the target source determination.

[0091] In one embodiment, if Figure 6 As shown, step S204, i.e., performing validity detection on the monitoring data to be processed and obtaining the validity detection result, specifically includes the following steps:

[0092] S601: Query the legal source mapping table based on the target source of the monitoring data to be processed to obtain the legality verification result.

[0093] Among them, the legal source mapping table is a pre-set data table used to evaluate whether the data source is legal. The legality check result is the result of the legality check of the target source of the monitoring data to be processed. The legality check result includes two results: legal source and illegal source. Among them, legal source means that the target source of a certain monitoring data to be processed is a legal data source that the data center needs to monitor; illegal source means that the target source of a certain monitoring data to be processed is an illegal data source that the data center does not need to monitor.

[0094] As an example, the source information of all legal sources can be stored in a legal source mapping table, and the legal source mapping table can be queried based on the target source identified by the monitoring data to be processed. If the target source is in the legal source mapping table, the legality verification result of the legal source is obtained; if the target source is not in the legal source mapping table, the legality verification result of the illegal source is obtained.

[0095] As another example, multiple data sources and the source attributes corresponding to each data source can be stored in a legal source mapping table, and the source attributes include legal sources and illegal sources; the legal source mapping table is queried based on the target source identified based on the monitoring data to be processed, and the corresponding legality verification result is determined according to the source attributes of the target source in the legal source mapping table.

[0096] S602: Query the alarm status information table based on the monitoring data to be processed to obtain the alarm status result.

[0097] The alarm status information table is a pre-set data table used to evaluate whether the alarm event in the monitoring data is valid. The alarm status result is the result of determining whether a certain monitoring data to be processed is still in a valid state according to the alarm status information table.

[0098] As an example, since there is a time difference between the time when the associated monitoring system collects the original monitoring data and the time when the data center obtains the original monitoring data from the associated monitoring system, the status of the monitoring data to be processed may change during the time difference. Therefore, after obtaining the monitoring data to be processed, the data center needs to query the alarm status information table based on the monitoring log recorded in the monitoring data to be processed to determine whether this monitoring log is still identified as a fault event that needs to be monitored; based on the judgment result, the alarm status result is obtained. That is, if the alarm status information table is queried based on the monitoring log and it is determined that it is a fault event that still needs to be monitored, the alarm status result obtained is a valid state; if the alarm status information table is queried based on the monitoring log and it is determined that it is a fault event that does not need to be monitored, the alarm status result obtained is an invalid state.

[0099] S603: If the legality check result is that the source is legal and the alarm status result is valid, then obtain the validity check result that the alarm is valid.

[0100] As an example, when the data center is performing validity check on the monitoring data to be processed, if it is determined that the legitimacy check result is that the source is legal and the alarm status result is valid, then it means that the target source of the monitoring data to be processed is a legal data source that the data center needs to monitor, and the fault event corresponding to the monitoring data to be processed is a fault event that the data center needs to continue to monitor. At this time, the validity check result of the alarm being valid is obtained so that the monitoring data to be processed with valid alarms can be further processed.

[0101] S604: If the legality check result is that the source is illegal, or the alarm status result is invalid, then obtain the validity check result of the alarm being invalid.

[0102] As an example, when the data center is performing validity check on the monitoring data to be processed, if it is determined that the result of the legitimacy check is that the source is illegal, or the alarm status result is a valid status, then it means that the target source of the monitoring data to be processed is not an illegal data source that the data center needs to monitor, or the fault data corresponding to the monitoring data to be processed is not a fault event that the data center needs to continue to monitor. At this time, the validity check result of the alarm being invalid is obtained, so that the data center does not need to continue monitoring and analyzing the monitoring data to be processed.

[0103] The data center-based operation and maintenance monitoring method provided in this embodiment queries the legal source mapping table and the alarm status information table based on the monitoring data to be processed to obtain the legality verification results and the alarm status results; the alarm is determined to be valid if the legality verification result is that the source is legal and the alarm status result is a valid state, otherwise, the alarm is determined to be invalid, thereby ensuring the accuracy and timeliness of the validity test results.

[0104] In one embodiment, if Figure 7 As shown, step S205, i.e., formatting the valid monitoring data and the target source corresponding to the valid monitoring data to obtain the target monitoring data, specifically includes the following steps:

[0105] S701: Encode and format the effective monitoring data to obtain standard monitoring data.

[0106] The encoding conversion of the effective monitoring data refers to the process of converting all effective monitoring data into a unified encoding. The standard monitoring data refers to the monitoring data determined after the effective monitoring data is encoded and formatted.

[0107] The data center can uniformly convert the valid monitoring data uploaded by different associated monitoring systems into a target encoding format, such as the UTF-8 encoding format, to ensure the feasibility of subsequent data monitoring and analysis processing, thereby improving the efficiency and accuracy of monitoring and analysis. As an example, the data center identifies the current encoding format of the valid monitoring data; if the current encoding format is the target encoding format of the UTF-8 encoding format, no encoding conversion processing is required; if the current encoding format is not the target encoding format of the UTF-8 encoding format, but is the Unicode encoding format, then based on the format conversion rules corresponding to the current encoding format and the target encoding format, the current encoding format is converted to obtain standard monitoring data that matches the target encoding mode, thereby ensuring the consistency of the encoding format of the standard monitoring data, so as to facilitate the feasibility of subsequent automated monitoring and analysis.

[0108] S702: Using a keyword recognition algorithm to recognize the standard monitoring data, and determining whether the standard monitoring data includes a core format field.

[0109] The core format field refers to a field whose content needs to be in a specific format.

[0110] As an example, after obtaining standard monitoring data, the data center can use a keyword recognition algorithm to identify the data content in the standard monitoring data to determine whether all fields in the standard monitoring data contain core format fields, so as to determine whether further format conversion is required based on the judgment results, thereby ensuring the targetedness of the format conversion.

[0111] S703: If the standard monitoring data contains a core format field, a format conversion script corresponding to the core format field is used to convert the format of the original field content corresponding to the core format field, obtain the target field content, replace the original field content with the target field content, add a source field and the corresponding target source, and obtain the target monitoring data.

[0112] The format conversion script corresponding to the core format field is a pre-set script for realizing format conversion of the field content corresponding to the core format field.

[0113] As an example, if the standard monitoring data contains the core format field eventName (event name), the format conversion script corresponding to the core format field is used to uniformly convert the original field content corresponding to the core format field in the standard monitoring data into the target field content corresponding to the specific format of "ObjName (project name) -ObjType (project type) -Source (source) -Desc (team)", and then replace the target field content with the original field content.

[0114] As an example, if the standard monitoring data contains the core format field tags.department (tag department), the format conversion script corresponding to the core format field is used to perform character length verification on the original field content corresponding to the core format field in the standard monitoring data. If the character length meets the standard length, no format conversion is required; if the character length does not meet the standard length, new content is spliced ​​and added and replaced according to established rules to obtain the target field content whose character length meets the standard length, and then the target field content is replaced with the original field content.

[0115] As an example, if the standard monitoring data contains a core format field called duration (alarm duration), the format conversion script corresponding to the core format field is used to convert the time unit of the original field content corresponding to the core format field in the standard monitoring data, and it will be converted into a unified time unit to facilitate subsequent automated monitoring of time-related monitoring data and improve monitoring efficiency.

[0116] In this example, when the standard monitoring data contains core format fields, the format conversion script is used to convert the format of the original field content corresponding to the core format field. After replacing the original field content with the target field content, it is necessary to add the source field and the target source corresponding to the source field to the standard monitoring data, so that the target monitoring field finally obtained adopts a unified format to ensure the feasibility of subsequent automatic monitoring and analysis; and each target monitoring data carries information such as the target source, so that all target monitoring data can be automatically monitored and analyzed based on the target source to ensure the effectiveness of monitoring.

[0117] S704: If the standard monitoring data does not include the core format field, a source field and a corresponding target source are added to obtain the target monitoring data.

[0118] In this example, when the standard monitoring data does not contain the core format field, there is no need to convert the format of the original field content corresponding to the core format field. The source field and the target source corresponding to the source field are directly added to the standard monitoring data so that each target monitoring data carries information such as the target source, so that all target monitoring data can be automatically monitored and analyzed based on the target source to ensure the effectiveness of monitoring.

[0119] The data center-based operation and maintenance monitoring method provided in this embodiment encodes and formats effective monitoring data to ensure the identifiability of standard monitoring data obtained by encoding and formatting, so that the automated monitoring program of the data center can accurately and effectively identify the data content in the standard monitoring data; when the standard monitoring data contains core format fields, a format conversion script is required to perform format conversion, and the target field content replaces the original field content, so that the target field content corresponding to the core format field adopts a unified format to ensure the feasibility of subsequent automatic monitoring and analysis; a source field and a target source corresponding to the source field are added to the standard format field, so that each target monitoring data carries information such as the target source, so that all target monitoring data can be automatically monitored and analyzed based on the target source to ensure the effectiveness of monitoring.

[0120] In one embodiment, if Figure 8 As shown, step S206, that is, based on the target source, automatically monitoring the target monitoring data to obtain the alarm monitoring result, specifically includes the following steps:

[0121] S801: Start the automated monitoring task, which includes a monitoring cycle and target monitoring indicators.

[0122] Among them, the automated monitoring task is a pre-set computer executable task for realizing automatic monitoring. The monitoring data cycle refers to the time interval of the monitoring data collected from the business data that needs to be monitored in the data center. The target monitoring index refers to the index that needs to be monitored by the automated monitoring task, including but not limited to the alarm processing rate, alarm timeout rate, alarm processing timeliness and user utilization rate.

[0123] S802: Divide all target monitoring data with event occurrence time within the monitoring period according to target sources, and determine the monitoring data to be analyzed corresponding to each target source.

[0124] As an example, the data center can compare the event occurrence time of the target monitoring data with the monitoring period to determine whether the event occurrence time is within the monitoring period, thereby screening out all target monitoring data whose event occurrence time is within the monitoring period as data that needs to be automatically monitored; then, all target monitoring data whose event occurrence time is within the monitoring period are divided according to the target sources in the target monitoring data, thereby dividing all target monitoring data into different data sets to be monitored according to the number of target sources, each data set to be monitored corresponds to a target source, and each data set to be monitored specifically includes monitoring data to be analyzed corresponding to a certain target source, and the monitoring data to be analyzed is specifically the target monitoring data whose event occurrence time corresponds to the target source within the monitoring period.

[0125] S803: Call the indicator operation script corresponding to the target monitoring indicator, read the variable factor value corresponding to the target variable factor from the monitoring data to be analyzed, calculate the variable factor value using the indicator operation logic, and obtain the alarm monitoring result corresponding to each target source.

[0126] Among them, the indicator operation script is a script that can be run on a computer for calculating the target monitoring indicator. The indicator operation script is a script written in a computer language that can execute the indicator operation formula corresponding to a certain target monitoring indicator. Generally speaking, the indicator operation formula includes indicator variable factors and indicator operation logic, wherein the indicator variable factors are variable factors used to calculate the target monitoring indicator, and the indicator operation logic is the processing logic used to perform mathematical operations on all indicator variable factors. For example, alarm timeout rate = timeout alarm quantity / total occurrence quantity. Alarm processing rate = 1-alarm timeout rate, wherein, if an alarm event lasts for more than 30 minutes without being processed, it is considered to have timed out. Monitoring processing timeliness = total alarm duration / total occurrence quantity, note: total alarm duration = the sum of the duration of each alarm in the total occurrence quantity; the unit of monitoring processing timeliness: minutes. User usage = core URLs that have reached a certain number of visits / all core URLs.

[0127] As an example, the data center can execute the indicator calculation script corresponding to the target monitoring indicator set in the automated monitoring task. Since each monitoring data to be analyzed is a formatted target monitoring indicator, the indicator calculation script can quickly obtain the variable factor value corresponding to the target variable factor in the indicator calculation formula from the monitoring data to be analyzed, and then use the indicator calculation logic in the indicator calculation formula to calculate the variable factor value, thereby obtaining the alarm monitoring result corresponding to each target source, so as to realize automated monitoring of all target monitoring data corresponding to each target source, improve the efficiency of data monitoring, and reduce the cost of data monitoring.

[0128] The data center-based operation and maintenance monitoring method provided in the present embodiment makes it feasible to divide the monitoring data to be analyzed based on the event occurrence time and the target source because the formatted target monitoring data all contain the event occurrence time and the target source, thereby facilitating the subsequent processing of all target monitoring data based on the target source analysis dimension; calling the indicator calculation script corresponding to the target monitoring indicator can realize automatic and rapid use of the indicator calculation logic to calculate the corresponding variable factor values ​​obtained from the monitoring data to be analyzed, so as to obtain the alarm monitoring results corresponding to each target source, so as to realize automatic monitoring of all target monitoring data corresponding to each target source, improve the efficiency of data monitoring, and reduce the cost of data monitoring.

[0129] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0130] In one embodiment, an operation and maintenance monitoring device based on a data center is provided, and the operation and maintenance monitoring device based on a data center corresponds one-to-one to the operation and maintenance monitoring method based on a data center in the above embodiment. Fig. 9 As shown, the data center-based operation and maintenance monitoring device includes an original monitoring data acquisition module 901, a to-be-processed monitoring data acquisition module 902, a target source acquisition module 903, an effective monitoring data acquisition module 904, a target monitoring data acquisition module 905, and an alarm monitoring result acquisition module 906. The functional modules are described in detail as follows:

[0131] The original monitoring data acquisition module 901 is used to acquire the original monitoring data corresponding to the business system collected by the associated monitoring system, and each original monitoring data includes an original alarm level.

[0132] The monitoring data to be processed acquisition module 902 is used to perform standardization processing on the original alarm level, acquire the standard alarm level, and determine the original monitoring data whose standard alarm level is the target alarm level as the monitoring data to be processed.

[0133] The target source acquisition module 903 is used to perform source detection on the monitoring data to be processed and acquire the target source corresponding to the monitoring data to be processed.

[0134] The valid monitoring data acquisition module 904 is used to perform validity detection on the monitoring data to be processed, obtain the validity detection result, and determine the monitoring data to be processed with the validity detection result being alarm valid as valid monitoring data.

[0135] The target monitoring data acquisition module 905 is used to perform formatting processing based on the valid monitoring data and the target source corresponding to the valid monitoring data to acquire the target monitoring data.

[0136] The alarm monitoring result acquisition module 906 is used to automatically monitor the target monitoring data based on the target source and obtain the alarm monitoring result.

[0137] Preferably, the original monitoring data acquisition module includes a monitoring system quantity acquisition unit, a data acquisition process creation unit and an acquisition process parallel execution unit.

[0138] The monitoring system quantity acquisition unit is used to monitor the number of monitoring systems corresponding to the associated monitoring system in real time.

[0139] The data collection process creation unit is used to create data collection processes corresponding to the number of monitoring systems, and each data collection process corresponds to an associated monitoring system.

[0140] The collection process parallel execution unit is used to execute all data collection processes in parallel to obtain the original monitoring data corresponding to the business system collected by each associated monitoring system in the current collection cycle.

[0141] Preferably, the target source acquisition module includes a first keyword recognition unit, a first source determination unit, a second keyword recognition unit and a second source determination unit.

[0142] The first keyword recognition unit is used to recognize the monitoring data to be processed by using a keyword recognition algorithm, and determine whether the monitoring data to be processed contains a source key field.

[0143] The first source determination unit is used to determine the field content corresponding to the source key field as the target source corresponding to the monitoring data to be processed if the monitoring data to be processed includes a source key field.

[0144] The second keyword recognition unit is used to use a keyword recognition algorithm to recognize the monitoring data to be processed if the monitoring data to be processed does not contain a source key field, and to determine whether the monitoring data to be processed contains an associated key field.

[0145] The second source determination unit is used to perform data processing on the field content corresponding to the associated key field if the monitoring data to be processed contains an associated key field, so as to obtain a target source corresponding to the monitoring data to be processed.

[0146] Preferably, the target source acquisition module includes a model recognition processing unit and a third source determination unit.

[0147] The model identification processing unit is used to use a preset source identification model to perform source detection on the monitoring data to be processed, and obtain at least one identification source and an identification probability corresponding to each identification source.

[0148] The third source determination unit is used to compare the maximum recognition probability with a preset probability threshold. If the maximum recognition probability is greater than the preset probability threshold, the recognition source corresponding to the maximum recognition probability is determined as the target source corresponding to the monitoring data to be processed.

[0149] Preferably, the effective monitoring data acquisition module includes a legality verification result acquisition unit, an alarm status result acquisition unit, a legal source result acquisition unit and an illegal source result acquisition unit.

[0150] The legality verification result acquisition unit is used to query the legal source mapping table based on the target source of the monitoring data to be processed to obtain the legality verification result.

[0151] The alarm status result acquisition unit is used to query the alarm status information table based on the monitoring data to be processed to obtain the alarm status result.

[0152] The legal source result acquisition unit is used to obtain the validity detection result of the alarm being valid if the legality check result is that the source is legal and the alarm status result is a valid status.

[0153] The illegal source result acquisition unit is used to obtain the validity detection result of the alarm invalid if the legality check result is that the source is illegal, or the alarm status result is invalid.

[0154] Preferably, the target monitoring data acquisition module includes a standard monitoring data acquisition unit, a core format field judgment unit, a first target data acquisition unit and a second target data acquisition unit.

[0155] The standard monitoring data acquisition unit is used to encode and format the effective monitoring data to obtain standard monitoring data.

[0156] The core format field judgment unit is used to use a keyword recognition algorithm to recognize the standard monitoring data and judge whether the standard monitoring data includes the core format field.

[0157] The first target data acquisition unit is used to, if the standard monitoring data contains a core format field, use a format conversion script corresponding to the core format field to perform format conversion on the original field content corresponding to the core format field, obtain the target field content, replace the original field content with the target field content, add a source field and the corresponding target source, and obtain the target monitoring data.

[0158] The second target data acquisition unit is used to add a source field and a corresponding target source to acquire target monitoring data if the standard monitoring data does not include a core format field.

[0159] Preferably, the alarm monitoring result acquisition module includes a monitoring task starting unit, a to-be-analyzed data determining unit and an alarm monitoring processing unit.

[0160] The monitoring task starting unit is used to start the automated monitoring task. The automated monitoring task includes a monitoring cycle and target monitoring indicators.

[0161] The unit for determining the data to be analyzed is used to divide all target monitoring data with event occurrence time within the monitoring period according to target sources, and determine the monitoring data to be analyzed corresponding to each target source.

[0162] The alarm monitoring processing unit is used to call the indicator operation script corresponding to the target monitoring indicator, read the variable factor value corresponding to the target variable factor from the monitoring data to be analyzed, calculate the variable factor value using the indicator operation logic, and obtain the alarm monitoring result corresponding to each target source.

[0163] For the specific definition of the operation and maintenance monitoring device based on the data center, please refer to the definition of the operation and maintenance monitoring method based on the data center above, which will not be repeated here. Each module in the above-mentioned operation and maintenance monitoring device based on the data center can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0164] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data used or generated in the process of executing the operation and maintenance monitoring method based on the data center. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an operation and maintenance monitoring method based on the data center is implemented.

[0165] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the operation and maintenance monitoring method based on the data center in the above embodiment is implemented, for example Figure 2 S201-S206 as shown, or Figures 3 to 8 Alternatively, when the processor executes the computer program, the functions of each module / unit in the embodiment of the operation and maintenance monitoring device based on the data center are realized, for example Fig. 9 The functions of the original monitoring data acquisition module 901, the to-be-processed monitoring data acquisition module 902, the target source acquisition module 903, the effective monitoring data acquisition module 904, the target monitoring data acquisition module 905 and the alarm monitoring result acquisition module 906 are not described here to avoid repetition.

[0166] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the operation and maintenance monitoring method based on a data center in the above embodiment is implemented, for example Figure 2 S201-S206 as shown, or Figures 3 to 8 Alternatively, when the computer program is executed by the processor, the functions of each module / unit in the above-mentioned operation and maintenance monitoring device based on the data center are realized, for example Fig. 9 The functions of the original monitoring data acquisition module 901, the to-be-processed monitoring data acquisition module 902, the target source acquisition module 903, the effective monitoring data acquisition module 904, the target monitoring data acquisition module 905 and the alarm monitoring result acquisition module 906 are not described here to avoid repetition.

[0167] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0168] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0169] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A data center-based operation and maintenance monitoring method, characterized in that: include: Obtaining original monitoring data corresponding to the business system collected by the associated monitoring system, each original monitoring data including an original alarm level; The original alarm level is standardized to obtain a standard alarm level, and the original monitoring data whose standard alarm level is a target alarm level is determined as monitoring data to be processed; Performing source detection on the monitoring data to be processed to obtain a target source corresponding to the monitoring data to be processed; Performing a validity check on the monitoring data to be processed, obtaining a validity check result, and determining the monitoring data to be processed whose validity check result is alarm valid as valid monitoring data; Encoding and formatting the effective monitoring data to obtain standard monitoring data; Using a keyword recognition algorithm to recognize the standard monitoring data, and determining whether the standard monitoring data includes a core format field; If the standard monitoring data includes a core format field, a format conversion script corresponding to the core format field is used to convert the format of the original field content corresponding to the core format field, the target field content is obtained, the target field content is used to replace the original field content, a source field and a corresponding target source are added, and the target monitoring data is obtained; If the standard monitoring data does not include the core format field, a source field and a corresponding target source are added to obtain the target monitoring data; Initiate an automated monitoring task, wherein the automated monitoring task includes a monitoring cycle and a target monitoring indicator; Divide all the target monitoring data within the monitoring period at the event occurrence time according to the target source, and determine the monitoring data to be analyzed corresponding to each target source; Call the indicator calculation script corresponding to the target monitoring indicator, read the variable factor value corresponding to the target variable factor from the monitoring data to be analyzed, calculate the variable factor value using the indicator calculation logic, and obtain the alarm monitoring result corresponding to each of the target sources.

2. The data center-based operation and maintenance monitoring method according to claim 1, characterized in that: The obtaining of original monitoring data corresponding to the business system collected by the associated monitoring system includes: Real-time monitoring of the number of monitoring systems corresponding to the associated monitoring system; Creating data collection processes corresponding to the number of the monitoring systems, each of the data collection processes corresponding to one of the associated monitoring systems; All the data collection processes are executed in parallel to obtain the original monitoring data corresponding to the business system collected by each of the associated monitoring systems in the current collection cycle.

3. The data center-based operation and maintenance monitoring method according to claim 1, characterized in that: The performing source detection on the monitoring data to be processed to obtain a target source corresponding to the monitoring data to be processed includes: Using a keyword recognition algorithm to recognize the monitoring data to be processed, and determining whether the monitoring data to be processed contains a source key field; If the monitoring data to be processed contains a source key field, the field content corresponding to the source key field is determined as the target source corresponding to the monitoring data to be processed; If the monitoring data to be processed does not contain the source key field, a keyword recognition algorithm is used to identify the monitoring data to be processed to determine whether the monitoring data to be processed contains the associated key field; If the monitoring data to be processed contains an associated key field, data processing is performed on the field content corresponding to the associated key field to obtain the target source corresponding to the monitoring data to be processed.

4. The data center-based operation and maintenance monitoring method according to claim 1, characterized in that: The performing source detection on the monitoring data to be processed to obtain a target source corresponding to the monitoring data to be processed includes: Using a preset source identification model to perform source detection on the monitoring data to be processed, and obtaining at least one identification source and an identification probability corresponding to each of the identification sources; The maximum recognition probability is compared with a preset probability threshold. If the maximum recognition probability is greater than the preset probability threshold, the recognition source corresponding to the maximum recognition probability is determined as the target source corresponding to the monitoring data to be processed.

5. The data center-based operation and maintenance monitoring method according to claim 1, characterized in that: The performing validity detection on the monitoring data to be processed and obtaining the validity detection result includes: Based on the target source of the monitoring data to be processed, query the legal source mapping table to obtain a legality verification result; Querying the alarm status information table based on the monitoring data to be processed to obtain the alarm status result; If the validity check result is that the source is legal and the alarm status result is valid, then obtain the validity check result that the alarm is valid; If the legality check result is that the source is illegal, or the alarm status result is invalid, then the validity check result of the alarm being invalid is obtained.

6. An operation and maintenance monitoring device based on a data center, characterized in that: include: The original monitoring data acquisition module is used to obtain the original monitoring data corresponding to the business system collected by the associated monitoring system, and each original monitoring data includes the original alarm level; A module for acquiring monitoring data to be processed, used for standardizing the original alarm level, acquiring a standard alarm level, and determining the original monitoring data whose standard alarm level is a target alarm level as monitoring data to be processed; A target source acquisition module, used to perform source detection on the monitoring data to be processed and acquire the target source corresponding to the monitoring data to be processed; An effective monitoring data acquisition module is used to perform validity detection on the monitoring data to be processed, obtain validity detection results, and determine the monitoring data to be processed with the validity detection results being alarm valid as effective monitoring data; A target monitoring data acquisition module is used to encode and format the effective monitoring data to obtain standard monitoring data; Using a keyword recognition algorithm to recognize the standard monitoring data, and determining whether the standard monitoring data includes a core format field; If the standard monitoring data includes a core format field, a format conversion script corresponding to the core format field is used to convert the format of the original field content corresponding to the core format field, the target field content is obtained, the target field content is used to replace the original field content, a source field and a corresponding target source are added, and the target monitoring data is obtained; If the standard monitoring data does not include the core format field, a source field and a corresponding target source are added to obtain the target monitoring data; An alarm monitoring result acquisition module is used to start an automated monitoring task, wherein the automated monitoring task includes a monitoring cycle and a target monitoring indicator; Divide all the target monitoring data within the monitoring period at the event occurrence time according to the target source, and determine the monitoring data to be analyzed corresponding to each target source; Call the indicator calculation script corresponding to the target monitoring indicator, read the variable factor value corresponding to the target variable factor from the monitoring data to be analyzed, calculate the variable factor value using the indicator calculation logic, and obtain the alarm monitoring result corresponding to each of the target sources.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the operation and maintenance monitoring method based on the data center as described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the operation and maintenance monitoring method based on a data center as described in any one of claims 1 to 5 is implemented.

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