CN115760052A - Operation and maintenance system and method based on intelligent work order and storage medium - Google Patents
Operation and maintenance system and method based on intelligent work order and storage medium Download PDFInfo
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Abstract
The invention relates to the field of operation and maintenance, and discloses an operation and maintenance system based on an intelligent work order, which comprises a storage module, a multi-database and an object repository, wherein the storage module is used for storing work order information, the storage module also comprises respective service data of different functional modules, the memory database stores hot data which are required to be frequently called by each functional module, and the object repository stores unstructured data; the microservice internal data interaction module is used for data interaction among a plurality of databases, a memory database and an object storage database; the training module carries out modeling and training on data stored in a multi-database, a memory database and an object storage database to obtain an early warning model, the detection module detects abnormal data, triggers the early warning model and sends the abnormal data to the AI worksheet module; and the AI work order module receives the abnormal data, generates a new work order according to the completed abnormal event portrait by a preset algorithm and distributes the new work order to the salesman. The method and the system can realize dual linkage of the operation and maintenance system data and each functional module and the AI work order system.
Description
Technical Field
The invention relates to the field of operation and maintenance, in particular to an operation and maintenance system based on an intelligent work order.
Background
The operation and maintenance system is management software for reporting and managing operation problems of the service, accepting the problems, circulating the problems, checking the problems, processing the problems, filing closed orders of the problems and maintaining and inquiring a knowledge base, the operation and maintenance duty runs through the life cycle of the product, and an intelligent system is needed to help an operation and maintenance engineer to complete service delivery and service quality guarantee facing users at the lowest cost and the highest speed.
The operation and maintenance systems in the market at present have different emphasis points. Some emphasis on security protection, some emphasis on service repair, and some emphasis on asset statistics, for example, the emphasis on security protection is basically only used for host computer defense; the basis of the emphasis on asset statistics is only to perform asset statistics and life cycle management; the heavy work order basically only makes the work order and reports the repair; most of the monitoring is focused on monitoring and simple asset statistics, and even if part of operation and maintenance products with rich functions are produced, all functional modules are independent from each other, and data sharing and function intercommunication cannot be effectively carried out. Therefore, the operation and maintenance support work of enterprises needs to be done, and a plurality of products have to be used at the same time, so that the workload of operation and maintenance personnel is increased, the operation and maintenance learning cost is improved, the operation and maintenance efficiency is reduced, and the enterprise expenditure is increased. No matter how many systems are added, it is difficult to smoothly realize the closed loop of the data and business flow inside the enterprise.
Therefore, an operation and maintenance system capable of fusing each functional module is needed to realize the closed loop of data and service flow inside an enterprise.
Disclosure of Invention
The invention aims to provide an operation and maintenance system, method and storage medium based on an intelligent work order so as to realize the fusion of all functional modules of the operation and maintenance system.
In order to achieve the purpose, the invention adopts the following technical scheme:
an operation and maintenance system based on an intelligent work order is characterized by comprising:
the storage module is used for storing the work order information;
the memory module further includes:
the multi-database is used for storing respective service data of different functional modules;
the memory database is used for storing the hot data which needs to be frequently called by each functional module;
an object store to store unstructured data;
the microservice internal data interaction module: the method is used for data interaction among multiple databases, a memory database and an object storage database;
the training module is used for modeling and training data stored in a multi-database, a memory database and an object storage database to obtain an early warning model;
the detection module is used for detecting abnormal data of each functional module and the host, triggering the early warning model and sending the abnormal data to the AI work order module;
and the AI work order module is used for receiving the abnormal data, generating a new work order according to the completed abnormal event portrait by a preset algorithm and distributing the new work order to the salesman.
The principle and the advantages of the scheme are as follows: in practical application, an operation and maintenance system based on an intelligent work order comprises a plurality of functional modules, each functional module creates a database of the functional module, namely a multi-database, different functional modules respectively store respective service data in the multi-database, high cohesion of the service data of each functional module is realized, and management, isolation and horizontal extension of the respective service data of each functional module are facilitated; considering that the operation and maintenance system has many functional modules, large data volume and time delay in data transfer, the storage module is further provided with a memory database for storing the thermal data which needs to be frequently transferred by each functional module, namely, the thermal data which is frequently transferred and corresponds to each functional module is obtained from the database and is put into the memory database, so that the rapid access of each functional module is facilitated, the access efficiency is improved, and the sharing of the thermal data is facilitated; in addition to business data corresponding to each functional module, an operation and maintenance system based on an intelligent work order also has some large unstructured files, such as audio, video, files and the like, the data structure of unstructured data is irregular or incomplete, no predefined data model exists, and a database two-dimensional logic table, namely a data table expressed by the combination of rows and columns, is inconvenient to use, so that the data is independently stored in an object repository, the unstructured data is independently stored through the object repository, a large amount of complicated unstructured data is uniformly and centrally managed, the access rate is optimized, and convenience is provided for data extraction and analysis.
The microservice internal data interaction module provides a flexible internal data access interface for data interaction among multiple databases, a memory database and an object storage database, and data among all functional modules can be flexibly acquired and aggregated; the training module is used for modeling and training data stored in a plurality of databases, a memory database and an object storage database to obtain an early warning model; a detection module: the early warning module is used for detecting abnormal data of each functional module and the host, triggering the early warning model and sending the abnormal data to the AI work order module; AI work order module: the early warning system is used for receiving abnormal data, finishing abnormal event portrayal according to a preset algorithm, generating a new work order and distributing the work order to the salesperson, so that the salesperson can timely process early warning and abnormal events, and the working efficiency is improved.
Compared with the prior art, 1, the functional modules of the traditional operation and maintenance system are independent from each other, so that data sharing and function intercommunication cannot be effectively realized, and the working efficiency is low; the method and the system have the advantages that the service data of each functional module are respectively stored through the multiple databases, so that the isolation and high cohesion of the data are realized, and the management efficiency of the data is improved; the data sharing of each function plate is realized through a flexible internal data access interface provided by the micro-service internal data interaction module, and then modeling and training are carried out on data called by each database corresponding to each function module, so that the function intercommunication of each function module is realized; namely, the double linkage on the data and on each functional module and the work order system is realized.
2. The hot data of each functional module is stored through the memory database, so that the calling time of each functional module to the hot data is reduced, the flexible acquisition of the data is realized, and the access efficiency and the hot data sharing efficiency are improved.
3. The performance of the whole database is reduced due to the fact that the relational database stores unstructured data, the unstructured data are stored independently through the object storage library, the access rate of the unstructured data is optimized, and meanwhile the extraction and analysis efficiency of the unstructured data is improved.
4. The same data can be used by different functional modules in this application, and different modules are different to the same data use emphasis, through setting up hot database, avoid the storage data redundancy can be comprehensive again in detail, can also promote the efficiency of access efficiency and hot data sharing.
Preferably, as an improvement, the thermal data includes user information, license information, and a memory lock; the thermal data can also be input by customization.
The technical effects are as follows: the hot data is data acquired by a developer from a development angle, and is also data which is frequently used by a system or needs high access efficiency, and comprises user information, permission information, a memory lock and the like.
Preferably, as an improvement, the unstructured data includes text, files, audio, and video of different functional modules.
The technical effects are as follows: unstructured data such as texts, files, audio and video are irregular or incomplete and are numerous and complicated, however, the unstructured data are acquired, comprehensive and detailed operation and maintenance system data are facilitated, and the accuracy and the efficiency of work orders are improved.
Preferably, as an improvement, the system further comprises a data updating module, configured to update data stored in multiple databases, the memory database, and the object repository;
the system also comprises a synchronous tracking module which is used for tracking the data related to the data updated by the data updating module and synchronously updating the tracked related data.
The technical effects are as follows: in order to ensure the precision of data, only one part of data is stored in the whole operation and maintenance system, and the use focus and the attention point of different functional modules on the same data are different, so that business data in databases correspondingly stored by different functional modules have certain relevance, when one database is updated, the related data in other databases needs to be updated synchronously, thereby avoiding conflict and error report, avoiding updating all data in other databases, and improving the efficiency of synchronous updating of the related data.
Preferably, as an improvement, the functional modules include asset services, business services, middleware services, and network services.
The technical effects are as follows: the asset service has the functions of asset information acquisition, service recording and safety control; the business service comprises a business system used in an enterprise; the network service has the function of monitoring the network condition of the intranet system where the operation and maintenance system is located; the middleware services comprise Redis, mySQL and Tomcat services for supporting an operation and maintenance system; the integration of the functions of the functional modules can be realized through the linkage of the AI work order system and the functional modules.
Preferably, as an improvement, the AI work order module uses a naive bayes method to generate a new work order for the abnormal event and dispatch the new work order to the service staff.
The technical effects are as follows: compared with a decision tree algorithm, the naive Bayes method is more stable in classification efficiency, few in parameters to be estimated and simple in algorithm, and different new work orders are generated for different abnormal events by the naive Bayes method, so that the processing accuracy is improved.
Preferably, as an improvement, the system further comprises an alarm module, configured to send alarm information to an administrator when an abnormal event is detected;
the detection module is also used for detecting whether the new work order is abnormal or not to obtain a secondary detection result, and when the secondary detection result is abnormal, the alarm module is started.
The technical effects are as follows: considering that the condition of causing the work order abnormity may also be the influence of external factors of the operation and maintenance system, such as the influence of system setting of a computer using the operation and maintenance system, the work order cannot be normally circulated without human response for a long time, and the like, at the moment, an alarm is sent to a manager to remind the manager to check and adjust, so that the normal operation of the operation and maintenance system is ensured.
Preferably, as an improvement, the system further comprises an evaluation module, configured to evaluate a data type, a data length, and a table combination of the service data in the multiple databases, evaluate performance of the data, obtain a comprehensive evaluation result, and obtain the thermal data in the in-memory database according to the comprehensive evaluation result.
The technical effects are as follows: the data structure of the service data is reasonably designed, the reduction of efficiency caused by the storage redundancy of frequently called hot data is avoided, and meanwhile, the service data stored in the multiple databases are comprehensive and detailed.
An operation and maintenance method based on an intelligent work order comprises the following steps:
a storage step of storing work order information; the multi-database stores respective service data of different functional modules; the memory database stores the hot data which are frequently called by each functional module; the object repository stores unstructured data;
and (3) micro-service internal data interaction: performing data interaction among multiple databases, a memory database and an object storage database;
a data updating step, namely updating data stored in a plurality of databases, a memory database and an object repository;
a synchronous tracking step, tracking the data associated with the updated data, and synchronously updating the tracked associated data;
a training step, modeling and training data stored in a plurality of databases, a memory database and an object storage database to obtain an early warning model;
detecting abnormal data of each functional module and the host, triggering an early warning model and sending the abnormal data to an AI work order module;
an AI work order step, which is used for receiving abnormal data, generating a new work order according to the completed abnormal event portrait by a preset algorithm and distributing the new work order to a salesman;
an alarm step, when an abnormal event is detected, alarm information is sent to an administrator;
and a detection step, namely detecting whether the new work order is abnormal or not to obtain a secondary detection result, and starting an alarm step when the secondary detection result is abnormal.
An intelligent work order-based operation and maintenance storage medium for storing computer-executable instructions, which when executed implement an intelligent work order-based operation and maintenance method as claimed in claim 9.
Drawings
Fig. 1 is a schematic view illustrating functional fusion of an AI work order system and each functional module according to an embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
as shown in fig. 1, an operation and maintenance system based on an intelligent work order includes a plurality of functional modules, such as a business service, a middleware service, a network service, an asset service, a log service, a flow service, a file service, a core service, a user authentication service, and the like, in which the business service, the middleware service, the network service, and the asset service are preferably interpreted and do not represent only the business service, the middleware service, the network service, and the asset service functional modules. The asset service has the functions of asset information acquisition, service recording and safety control; the business service comprises a business system used in an enterprise; the network service has the function of monitoring the network condition of the intranet system where the operation and maintenance system is located; the middleware services comprise Redis, mySQL and Tomcat services for supporting an operation and maintenance system; the integration of the functions of the functional modules can be realized through the linkage of the AI work order system and the functional modules.
An operation and maintenance system based on an intelligent work order comprises a storage module, a database and a database, wherein the storage module is used for storing work order information of the operation and maintenance system, and the storage module is also provided with multiple databases which are used for storing service data; the service data required by each functional module is different, so that each functional module creates its own database, and the different functional modules respectively store their respective service data in multiple databases, for example, the service data required by the asset service is A1, A2, and A3, and the database a is used for storing the data A1, A2, and A3; the service data required by the middleware service are B1, B2 and B3, and the database B is used for storing the data B1, B2 and B3; the service data required by the network service are C1, C2 and C3, and the database C is used for storing the data C1, C2 and C3; the service data required by the service are D1, D2, D3 and D4, and the database D is used for storing the data D1, D2, D3 and D4; the database A, B, C, D forms a plurality of databases, and by adopting the storage mode of the plurality of databases, the high cohesion of the service data of each functional module is realized, and the management, isolation and horizontal extension efficiency of the service data of each functional module is improved; the method comprises the steps that a memory database is established in a storage module, the operation and maintenance system has many functional modules and large service data volume, so that the data transferring time is long, the efficiency is low, the memory database is used for storing hot data which are frequently called by each functional module, for example, A1 and D3 are hot data, the A1 and D3 are extracted into the memory database, the A1 and D3 are not stored in multiple databases, namely, the hot data which are frequently transferred and correspond to each functional module are obtained from the multiple databases and are placed into the memory database, so that the access efficiency of the hot data is improved, and the high-efficiency sharing of the hot data is realized; the hot data comprises user information, license information and a memory lock; the thermal data can also be input in a self-defining mode; the object storage library is created in the storage module to store unstructured data, wherein the unstructured data comprises office documents, texts, pictures, HTML, various reports, images, audio and video information in all formats.
The system comprises an evaluation module, a data processing module and a data processing module, wherein the evaluation module is used for evaluating the data type, the data length and the table combination of the service data in the multiple databases, evaluating the performance of the data, obtaining a comprehensive evaluation result and obtaining the thermal data in the memory database according to the comprehensive evaluation result. The data stored in the multiple databases are comprehensive and detailed, but the data in the hot database should avoid the condition of long storage to improve the data acquisition efficiency during the operation of the system, so that on the basis of following the design model of the databases, the data types, the lengths and the table combinations of all the service data in the multiple databases are evaluated, the performance is evaluated, and the hot words are selected according to the evaluation condition.
The system comprises a microservice internal data interaction module, provides a flexible internal data access interface, is used for data interaction among a plurality of databases, a memory database and an object storage database, enables data among all functional modules to be flexibly acquired and aggregated, and realizes data sharing and function intercommunication of all functional blocks in an operation and maintenance system.
The device comprises a training module: the early warning system is used for modeling and training data stored in a multi-database, a memory database and an object storage database to obtain an early warning model; a detection module: the system comprises an AI work order module, a function module, a host computer, an early warning module and an early warning module, wherein the AI work order module is used for detecting abnormal data of each function module and the host computer, triggering the early warning module and sending the abnormal data to the AI work order module; the AI work order module receives the abnormal data, images the completed abnormal events according to a preset algorithm, generates a new work order and distributes the new work order to the service personnel, so that the service personnel can timely process early warning and abnormal events, and the working efficiency is improved; the AI work order module adopts a naive Bayes method to generate a new work order for early warning and abnormal events and distribute the new work order to a salesman, the naive Bayes method is a classification method based on Bayes theorem and independent assumptions of characteristic conditions, for a given training data set, namely the data set comprising abnormal work orders, early warning and abnormal events, firstly, the input/output joint probability distribution is learned based on the independent assumptions of the characteristic conditions, and the characteristic conditions are set by a manager at the initial time; and then based on the model, for given input, the output with the maximum posterior probability is calculated by using Bayes theorem, the naive Bayes method needs less estimated parameters and has simple algorithm, and different new worksheets are generated for different early warnings and abnormal events by using the naive Bayes method, so that the processing accuracy is improved. Due to the data sharing of all the functional modules, the asset service has the functions of information acquisition, service recording and safety control of assets, and can automatically submit a work order, perform performance early warning and automatic report, and perform host computer antivirus and automatic report by linking with an AI work order system; the network service can monitor the network condition of an intranet system where the operation and maintenance system is located, and can perform exception judgment and early warning report according to network flow through linkage with a work order; the middleware services not only support Redis, mySQL and Tomcat services of an operation and maintenance system, but also can be linked with an AI work order system by configuring various index parameters of the monitoring middleware, and further performs self-defined early warning and automatic order reporting through strategy configuration; the business service checks the health degree of the function plate in a mode of installing the probe, is linked with the AI work order system, and carries out early warning and automatic report based on the health degree threshold.
The system also comprises an alarm module used for sending alarm information to an administrator when an abnormal event is detected; the detection module is also used for detecting whether the new work order is abnormal or not to obtain a secondary detection result, and when the secondary detection result is abnormal, the alarm module is started. The abnormal work order may be caused by external factors of the operation and maintenance system, for example, the system setting of a computer using the operation and maintenance system, or the failure of normal circulation caused by the unmanned response of the work order, and at this time, an alarm is sent to the manager to remind the manager to check and adjust, so as to promote the normal use of the operation and maintenance system.
The system also comprises a data updating module used for updating the data stored in the multiple databases, the memory database and the object repository; in the using process, a lot of historical data can be accumulated in each database, each database is updated according to the historical data, and the training module is used for modeling depending on the data in each database, so that the updating of the model is realized.
The system also comprises a synchronous tracking module which is used for tracking the data related to the data updated by the data updating module and synchronously updating the tracked related data. In order to ensure the precision of data, only one part of data is stored in the whole operation and maintenance system, and the use emphasis points and the attention points of different functional modules on the same data are different, so that business data in databases correspondingly stored by different functional modules have certain relevance, when a certain database is updated, the related data in other databases needs to be updated synchronously, thereby avoiding conflict and error reporting, and not updating all data in other databases, so as to improve the efficiency of synchronous updating of the related data. For example, A1 in the database a of the asset service is associated with B1 in the database B of the middleware service, for example, A1 is basic data for obtaining B1, while the database a needs frequent updating to maintain timeliness, the database B does not need trivial updating, and when the database a is updated, if the database B is also updated completely, the efficiency is lost, and only the tracking module needs to track and update the associated data. Common ways of query tracing include: one of database transaction, rollback, distributed transaction, exception capture, interface callback, and timed task. The method for searching and tracking the interface call-back mode is preferably selected, and comprises the following steps: the database A has 1 data1, the database B has 1 data2, the data2 is related to the data1, when the data1 changes, and the micro-service internal data interaction module calls an interface to inquire whether data associated with the data1 exist in the database B, at the moment, the existence of the data2 is inquired, then the data2 is synchronously updated, and when the data2 is updated, the data1 is updated.
An operation and maintenance method based on an intelligent work order comprises the following steps:
a storage step of storing work order information; the multi-database stores respective service data of different functional modules; the memory database stores the hot data which needs to be frequently called by each functional module; the object repository stores unstructured data;
and (3) micro-service internal data interaction: performing data interaction among multiple databases, a memory database and an object storage database;
a data updating step, namely updating data stored in a plurality of databases, a memory database and an object repository;
a synchronous tracking step, tracking the data associated with the updated data, and synchronously updating the tracked associated data;
training: modeling and training data stored in a multi-database, a memory database and an object storage database to obtain an early warning model;
a detection step: detecting abnormal data of each functional module and the host, triggering an early warning model, and sending the abnormal data to an AI work order module;
AI work order step: receiving abnormal data, generating a new work order according to a preset algorithm to finish the abnormal event portrait and distributing the new work order to a salesman;
an alarm step, when an abnormal event is detected, alarm information is sent to an administrator;
and a detection step, namely detecting whether the new work order is abnormal or not to obtain a secondary detection result, and starting an alarm step when the secondary detection result is abnormal.
An intelligent work order-based operation and maintenance storage medium for storing computer-executable instructions, which when executed implement an intelligent work order-based operation and maintenance method as claimed in claim 9.
The foregoing is merely an example of the present invention and common general knowledge in the art of designing and/or characterizing particular aspects and/or features is not described in any greater detail herein. It should be noted that, for those skilled in the art, without departing from the technical solution of the present invention, several variations and modifications can be made, and these should also be considered as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. An operation and maintenance system based on an intelligent work order is characterized by comprising:
the storage module is used for storing the work order information;
the memory module further includes:
the multi-database is used for storing respective service data of different functional modules;
the memory database is used for storing the hot data which needs to be frequently called by each functional module;
an object store to store unstructured data;
the microservice internal data interaction module is used for data interaction among a plurality of databases, a memory database and an object storage database;
the training module is used for modeling and training data stored in a multi-database, a memory database and an object storage database to obtain an early warning model;
the detection module is used for detecting abnormal data of each functional module and the host, triggering the early warning model and sending the abnormal data to the AI work order module;
and the AI work order module is used for receiving the abnormal data, representing the completed abnormal event according to a preset algorithm, generating a new work order and distributing the new work order to the service personnel.
2. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein: the hot data comprises user information, license information and a memory lock; the thermal data can also be input by customization.
3. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein: the non-structural data comprises texts, files, audio and video of different functional modules.
4. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein: the system also comprises a data updating module used for updating the data stored in the multi-database, the memory database and the object storage library;
the system also comprises a synchronous tracking module which is used for tracking the data related to the data updated by the data updating module and synchronously updating the tracked related data.
5. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein: the functional modules comprise asset services, business services, middleware services and network services.
6. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein: and the AI work order module generates a new work order by adopting a naive Bayes method for early warning and abnormal events and distributes the new work order to the service personnel.
7. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein:
the system also comprises an alarm module used for sending alarm information to an administrator when an abnormal event is detected;
the detection module is also used for detecting whether the new work order is abnormal or not to obtain a secondary detection result, and when the secondary detection result is abnormal, the alarm module is started.
8. The operation and maintenance system based on the intelligent work order as claimed in claim 1, wherein: the system also comprises an evaluation module used for evaluating the data type, the data length and the table combination of the service data in the multiple databases, evaluating the performance of the data, obtaining a comprehensive evaluation result and obtaining the thermal data in the memory database according to the comprehensive evaluation result.
9. An operation and maintenance method based on an intelligent work order is characterized by comprising the following steps:
a storage step of storing work order information; the multi-database stores respective service data of different functional modules; the memory database stores the hot data which needs to be frequently called by each functional module; the object repository stores unstructured data;
and (3) micro-service internal data interaction: performing data interaction among multiple databases, a memory database and an object storage database;
a data updating step, namely updating data stored in the multi-database, the memory database and the object repository;
a synchronous tracking step, tracking the data associated with the updated data, and synchronously updating the tracked associated data;
training, namely modeling and training data stored in a multi-database, a memory database and an object storage database to obtain an early warning model;
detecting abnormal data of each functional module and the host, triggering an early warning model, and sending the abnormal data to an AI work order module;
an AI work order step, which is used for receiving abnormal data, generating a new work order according to the completed abnormal event portrait by a preset algorithm and distributing the new work order to a salesman;
an alarm step, when an abnormal event is detected, alarm information is sent to an administrator;
and a detection step, namely detecting whether the new work order is abnormal or not to obtain a secondary detection result, and starting an alarm step when the secondary detection result is abnormal.
10. An intelligent work order-based operation and maintenance storage medium for storing computer-executable instructions, comprising: the computer executable instructions when executed implement an intelligent work order based operation and maintenance method as claimed in claim 9.
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