CN112561385A - Risk monitoring method and system - Google Patents
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Abstract
The invention relates to the field of cloud monitoring, and provides a risk monitoring method, which comprises the following steps: acquiring a test stage, a real-time progress, a fault node and a standing time of the fault node of each basic test data from a plurality of subsystems through a real-time interface; comparing the test stage and the real-time progress of each basic test data and the standing time of the fault node according to the index dimension set in the corresponding test stage so as to judge whether each basic test data is abnormal; when the comparison result exceeds the standard value corresponding to the index dimension, determining that the basic test data corresponding to the comparison result is abnormal; and alarming according to the abnormity, and sending the alarm information to the terminal where the corresponding manager is located so that the manager can follow up to process the abnormity in time. According to the invention, the problems existing at present can be intelligently monitored and judged aiming at each scene in the life cycle of demand research and development, the management efficiency of managers can be greatly improved, and the demand production risk is reduced.
Description
Technical Field
The embodiment of the invention relates to the technical field of cloud monitoring, in particular to a risk monitoring method and system.
Background
In the process of research and development to online demand, various problems are often accompanied, including manpower, time, accidental risks, external factors, team management problems and the like. These risks are often accompanied by a demand that cannot be brought online on time.
At present, only a demand management tool, a code management tool and a case defect management tool exist in the market, but no tool for intelligently judging the current problems according to each scene in the demand research and development life cycle exists, and warning risks and reminding personnel to solve the problems in time. Based on the above, the invention aims to intelligently monitor and judge the current problems in each scene in the life cycle aiming at the requirements.
Disclosure of Invention
In view of the above, it is desirable to provide a risk monitoring method, system, computer device and readable storage medium, which can monitor and determine the current problems according to the needs of developing each scenario in the life cycle.
In order to achieve the above object, an embodiment of the present invention provides a risk monitoring method, where the method includes:
acquiring a test stage, a real-time progress, a fault node and a standing time of the fault node of each basic test data from a plurality of subsystems through a real-time interface;
comparing the test stage and the real-time progress of each basic test data and the standing time of the fault node according to index dimensions set in the corresponding test stage to judge whether each basic test data is abnormal, wherein the index dimensions comprise a time dimension and a completion rate dimension;
when the comparison result exceeds the standard value corresponding to the index dimension, determining that the basic test data corresponding to the comparison result is abnormal; and
and alarming according to the abnormity, and sending alarm information to a terminal where a corresponding manager is located so that the manager can follow up to process the abnormity in time.
Optionally, the method further comprises:
when the basic test data is judged to be abnormal, generating corresponding abnormal information; and
and marking the abnormal information according to the subsystem corresponding to the basic test data to obtain abnormal marking information.
Optionally, each subsystem is preset with corresponding marking information, and the marking of the abnormal information according to the subsystem corresponding to the basic test data to obtain abnormal marking information includes:
and adding the mark information corresponding to the subsystem into the abnormal information to obtain the abnormal mark information.
Optionally, the step of performing an alarm according to the abnormality includes:
respectively counting the abnormal information of each subsystem to obtain a target subsystem with the abnormal information, and an abnormal result and abnormal information counted by aiming at each target subsystem;
and displaying colors corresponding to the abnormal result and the abnormal information on a target subsystem module of a display interface of a risk monitoring system according to the target subsystem, the abnormal result and the abnormal information.
Optionally, different subsystems are set to different importance levels according to different services, and the method further includes:
acquiring preset importance levels corresponding to the subsystems;
and placing the subsystem modules belonging to the same importance level in a display area corresponding to a display interface of the risk monitoring system.
Optionally, the alarming according to the abnormality and sending alarm information to a corresponding manager so that the manager can follow up processing the abnormality in time includes:
identifying the anomaly marking information;
determining target abnormal information corresponding to each subsystem according to the identification result, wherein the target abnormal information comprises: testing stage and fault reason;
and displaying the target abnormal information in each subsystem, and displaying an alarm in a test stage module in which the target abnormal information appears in each subsystem.
Optionally, the method further comprises:
after each subsystem displays the target abnormal information and alarms in the module of each subsystem with the target abnormal information, if the abnormal processing operation information of the administrator is received, the corresponding name of the administrator and the abnormal processing operation result information corresponding to the administrator are displayed at the corresponding position where the target abnormal information is displayed.
In order to achieve the above object, an embodiment of the present invention provides a risk monitoring system, including:
the acquisition module is used for acquiring the test stage, the real-time progress, the fault node and the standing time of the fault node of each basic test data from the plurality of subsystems through the real-time interface;
the judging module is used for comparing the testing stage and the real-time progress of each basic testing data and the standing time of the fault node according to index dimensions set in the corresponding testing stage so as to judge whether each basic testing data is abnormal or not, wherein the index dimensions comprise a time dimension and a completion rate dimension;
the determining module is used for determining that the basic test data corresponding to the comparison result is abnormal when the comparison result exceeds the standard value corresponding to the index dimension; and
and the alarm module is used for giving an alarm according to the abnormity and sending alarm information to a terminal where a corresponding manager is located so that the manager can follow up to process the abnormity in time.
To achieve the above object, an embodiment of the present invention further provides a computer device, a memory of the computer device, a processor, and a computer program stored on the memory and executable on the processor, where the computer program, when executed by the processor, implements the steps of the risk monitoring method as described above.
To achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored, where the computer program is executable by at least one processor to cause the at least one processor to execute the steps of the risk monitoring method described above.
According to the risk monitoring method, the risk monitoring system, the computer device and the computer readable storage medium provided by the embodiment of the invention, the test stage, the real-time progress and the standing time of the fault node of each basic test data are compared according to the index dimension set in the corresponding test stage, so as to judge whether each basic test data is abnormal or not; when the comparison result exceeds the standard value corresponding to the index dimension, judging that the basic test data corresponding to the comparison result is abnormal; according to the method and the system, the alarm is given according to the abnormity, and the alarm information is sent to the terminal where the corresponding manager is located, so that the manager can timely follow up the abnormity, and the method and the system can intelligently monitor and judge the current problems aiming at each scene in the life cycle of the demand research and development, can greatly improve the management efficiency of the manager, and can reduce the demand production risk.
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FIG. 1 is a schematic diagram of an exemplary application environment of a risk monitoring method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating exemplary steps of a risk monitoring method according to an embodiment of the present invention;
FIG. 3 is a flow chart illustrating another exemplary step of a risk monitoring method according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating an exemplary step of alerting based on the anomaly at step S104 of FIG. 2;
FIG. 5 is a schematic view of a risk monitoring system display interface;
FIG. 6 is a flowchart illustrating exemplary steps of step S104 of FIG. 2;
FIG. 7 is a diagram of the display effect of an exemplary PACES-CCMS-CORE subsystem;
FIG. 8 is a block diagram of a risk monitoring system according to an embodiment of the present invention;
FIG. 9 is a diagram of a hardware architecture of a computer device according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the description relating to "first", "second", etc. in the present invention is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
Fig. 1 is a schematic diagram of an exemplary application environment of the risk monitoring method according to the embodiment of the invention. Basic test data are obtained from the subsystem 1 and the subsystem 2 in a timing jobb mode, and are obtained from the subsystem 3, the subsystem 4 and the subsystem 5 in a data direct connection mode. And then sending the acquired basic test data of each subsystem to a high-performance/central data processor for data processing/risk monitoring to obtain risk monitoring data, caching the risk monitoring data to a Remote Dictionary service (Redis) or persistently storing the risk monitoring data in a DataBase (DataBase, DB), and finally rendering the risk monitoring data to a risk billboard, so that a user can intuitively acquire the basic test data condition of each subsystem in the test process from a display interface (risk billboard) of the risk monitoring system, and convenience is provided for the billboard. Redis is an open source log-type and Key-Value database which is written by using ANSI C language, supports network, can be based on memory and can also be persisted, and provides Application Programming Interface (API) of multiple languages. The invention can realize digital and comprehensive system management, data series connection and optimized resource management, avoids the need of actively acquiring risk data by users, improves research and development efficiency, realizes intelligent early warning, one-key distribution of to-be-processed items and real-time follow-up of processing various risk services.
Example one
Referring to fig. 2, a flowchart illustrating steps of a risk monitoring method according to an embodiment of the present invention is shown. It is to be understood that the flow charts in the embodiments of the present method are not intended to limit the order in which the steps are performed. It should be noted that the present embodiment is exemplarily described with a computer device as an execution subject, and the computer device may include a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palm computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation device, a wearable device, a smart band, a pedometer, and a fixed terminal such as a Digital TV, a desktop computer, and the like. The method specifically comprises the following steps:
step S101: and acquiring the test stage, the real-time progress, the fault node and the standing time of the fault node of each basic test data from the plurality of subsystems through the real-time interface.
The testing stage comprises smoking testing, system testing, safety testing and regression testing. The real-time schedule includes a test process and a test schedule completion percentage, for example: the current test item has completed testing 50%. The standing time of the fault node refers to a time length of waiting for processing when the fault node is in a fault state, for example: the time for a certain test node to fail and wait for human processing is 30 minutes. In an actual application scenario, after a certain node fails in a test, active discovery and processing of a manager need to be waited, and if the failed node is not discovered or processed by the manager for a long time, the test progress is seriously affected, so that the production of a product is affected.
In an exemplary embodiment, the real-time progress of each basic test data, the failed node, and the standing time of the failed node may be obtained from a plurality of the test systems through a software development management tool, for example, a case management tool, an automation management tool, a log tool, and the like. The test system can be any one of the subsystems 1-5 in the figure, and comprises a use case management system, a Bug (Bug) system, a configuration management system, a UI layer animation system, a reporting system, a Cat analysis rate system and the like.
Step S102: and comparing the test stage and the real-time progress of each basic test data and the standing time of the fault node according to index dimensions set in the corresponding test stage to judge whether each basic test data is abnormal, wherein the index dimensions comprise a time dimension and a completion rate dimension.
In the testing process, each basic test data is tested according to the corresponding index dimension to judge whether the abnormity occurs. Wherein the testing stage is judged according to the time dimension. For example, one smoking test in the smoking test stage needs to be completed within two days, and whether the smoking test in the corresponding basic test data is completed within two days is determined. The real-time progress is judged according to the time dimension and the completion rate dimension. For example, it is preset that a system test should complete 50% of tests at 10:00 am on xx month xx in xx years, and whether the real-time progress of the system test phase is abnormal or not is determined by comparing the real-time progress of the system test phase in each piece of basic test data with the preset value. And comparing the standing time lengths of the fault nodes according to the time dimension. For example, if the preset standing time of each fault node is not more than 1 hour, comparing the standing time of the fault node in each basic test data with the preset standing time to determine whether the standing time of each fault node is abnormal, that is, the basic test data has a risk.
Step S103: and when the comparison result exceeds the standard value corresponding to the index dimension, determining that the basic test data corresponding to the comparison result is abnormal.
Specifically, according to preset product production time and preset latest completion time of each node test, the test completion time of the test service can be estimated according to the test progress, then whether the estimated test completion time is before the test latest completion time is judged, and if the estimated test completion time is after the test latest completion time, the test service can be determined to have risk. For example, if the smoking test is not completed within two days, it is determined that the corresponding basic test data is abnormal. And if the standing time of the fault node exceeds the preset standing time, judging that the corresponding basic data is abnormal.
In an exemplary embodiment, as shown in fig. 3, the method further includes steps S201 and S202:
step S201: and when the basic test data is judged to be abnormal, generating corresponding abnormal information.
Step S202: and marking the abnormal information according to the subsystem corresponding to the basic test data to obtain abnormal marking information.
The marking method can be as follows: and adding the marking information corresponding to the subsystem to the abnormal information. For example: and (3) generating abnormal information A when the basic test data in the subsystem 1 is abnormal, wherein the marked abnormal marking information is' subsystem 1: exception information a "or" subsystem 1-exception information a ". Of course, the corresponding identifier of each subsystem may be preset, and the corresponding identifier is added to the abnormal information, for example, the identifier corresponding to the subsystem 1 is preset to be "1", the abnormal information a is marked, and the marked abnormal marking information is "1 abnormal information" or "abnormal information 1". The form of the abnormality marking information includes, but is not limited to, the form of "subsystem + character + abnormality information" described above, and may also be the form of "abnormality information + superscript/subscript subsystem", or may also be any other combination form, and is not limited in the present invention. By marking the corresponding subsystem information to the anomaly, it is possible to determine the subsystem to which the anomaly belongs, i.e. which subsystem has the anomaly.
In an exemplary embodiment, the method further comprises: and uploading the abnormal mark information to a block chain. The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product services layer, and an application services layer.
Step S104: and alarming according to the abnormity, and sending alarm information to a terminal where a corresponding manager is located so that the manager can follow up to process the abnormity in time.
In an exemplary embodiment, when the comparison result exceeds the standard value corresponding to the index dimension, the alarming specifically includes the following steps: and when the comparison result exceeds the standard value corresponding to the index dimension, the comparison result is linked to corresponding early warning information in a hyperlink mode to give an alarm. Illustratively, if the comparison result exceeds a standard value corresponding to the index dimension, the risk is present, and the high-risk warning information is linked by means of a hyperlink.
In an exemplary embodiment, the base test data may also include automated formation power. And when the automatic success rate is lower than a preset value, sending the failure reason to a risk monitoring system in a hyperlink mode so that the manager can perform corresponding processing according to the failure reason.
In an exemplary embodiment, as shown in fig. 4, the alarming according to the abnormality in step S104 includes steps S301 and S302:
step S301: and respectively counting the abnormal information of each subsystem to obtain a target subsystem with the abnormal information, and an abnormal result and abnormal information counted by aiming at each target subsystem.
Step S302: and displaying colors corresponding to the abnormal result and the abnormal information on a target subsystem module of a display interface of a risk monitoring system according to the target subsystem, the abnormal result and the abnormal information.
In practical application, all subsystem modules are displayed on a display interface of the risk monitoring system, and each subsystem module corresponds to one subsystem. And determining the test state of each subsystem according to different display colors. When one subsystem is tested abnormally, the basic test data of the subsystem is judged to be abnormal information, and a display interface of the risk monitoring system displays that the subsystem is abnormal or risky. For example: and counting that the subsystem 1 is abnormal according to the statistical result, and displaying the subsystem 1 in red on a display interface of the risk monitoring system to show that the subsystem is abnormal or risky.
In an exemplary embodiment, different subsystems are set to different importance levels depending on the service. The method further comprises the following steps: acquiring preset importance levels corresponding to the subsystems; and placing the subsystem modules belonging to the same importance level in a display area corresponding to a display interface of the risk monitoring system. As shown in fig. 5, a schematic interface diagram is displayed for the risk monitoring system. In fig. 5, the importance level of the PABO2O-CP subsystem and the CNBS-CORE subsystem is 1, the importance level of the PACES-CCMS-CORE subsystem is 2, the PABO2O-CP subsystem module and the CNBS-CORE subsystem module are placed in the display area a of the display interface of the risk monitoring system, and the PACES-CCMS-CORE subsystem module is placed in the display area B of the display interface of the risk monitoring system. By placing the subsystem modules with different importance levels in different display areas of a display interface of the risk monitoring system, the subsystems with different importance levels can be monitored, and management personnel can be promoted to quickly process the subsystems with high importance levels.
In an exemplary embodiment, as shown in fig. 6, the step S104 may further include steps S401 to S403:
step S401: and identifying the abnormal mark information.
Step S402: determining target abnormal information corresponding to each subsystem according to the identification result, wherein the target abnormal information comprises: a test phase and a cause of failure.
Step S403: and displaying the target abnormal information in each subsystem, and displaying an alarm in a test stage module in which the target abnormal information appears in each subsystem.
The test phase module may include a smoke test module, a system test module, a security test module, and a regression test module.
Specifically, by counting the target abnormal information of each subsystem, displaying the target abnormal information in each subsystem and displaying an alarm in a module of each subsystem, relevant management personnel can conveniently perform corresponding processing operation according to the target abnormal information and the alarm. FIG. 7 is a diagram showing the effects of an exemplary PACES-CCMS-CORE subsystem. And if the abnormal information of the basic test data of the PACES-CCMS-CORE subsystem is that a compatibility test machine type is not configured before a regression report is sent and the regression test report is not sent in a regression test stage, displaying that the compatibility test machine type is not configured before the regression report is sent and the regression test report is not sent, and displaying red by a regression test module, wherein the red indicates that the risk degree of the regression test is high risk.
In an exemplary embodiment, after each subsystem performs alarm display in a module that displays the target abnormal information and that in which the target abnormal information occurs in each subsystem, if abnormal processing operation information of the administrator is received, a corresponding administrator name and abnormal processing operation result information corresponding to the administrator are displayed at a corresponding position where the target abnormal information is displayed. By displaying the operation result information corresponding to the management personnel, the risk monitoring can be more transparent, so that the risk monitoring result and the corresponding processing result of each subsystem can be checked in real time. With continuing reference to fig. 7, the PACES-CCMS-CORE subsystem displays that "the compatibility test machine type has not been configured before the regression report is sent" and that "the regression test report is not sent", and after receiving the operation information that the administrator has configured the compatibility test machine type, displays the corresponding administrator name and that "the compatibility machine has been configured, the QA commander has a problem and needs to be repaired later" below the display that "the compatibility test machine type has not been configured before the regression report is sent", and displays the corresponding administrator name and that "the compatibility machine has been sent and is to be synchronized" below the display that "the regression test report is not sent".
In an exemplary embodiment, after all the exceptions of the subsystem receive the exception handling operation information of the administrator, the corresponding production state result is displayed according to the handling result.
It should be noted that some minor problems may occur in the testing stage before commissioning, but if the manual confirmation does not affect the normal operation of the product, the display interface of the subsystem may display that the manual confirmation is commissionable. With continuing reference to fig. 7, after receiving the abnormal processing operation information of the manager, it still shows that "QA commander has a problem and needs to be repaired later", and after the manager confirms that the normal operation of the product is not affected, it can display "production state" on the display interface of the PACES-CCMS-CORE subsystem: manually confirm that production can be put in production "and display green. Green indicates that all tests of the subsystem passed. Of course, different production statuses are displayed according to different test stages and different test results. For example: when the test is not completed and there is no risk so far, the commissioning status can be shown as: carrying out the following steps; when the test is not completed and there is a risk so far, the commissioning status can be shown as: is risky. Through displaying the production state information, related personnel can carry out product production operation according to the display result intuitively, and the normal online of the product is ensured.
According to the risk monitoring method provided by the embodiment of the invention, the test stage and the real-time progress of each basic test data and the standing time of the fault node are compared according to the index dimension set in the corresponding test stage, so as to judge whether each basic test data is abnormal; when the comparison result exceeds the standard value corresponding to the index dimension, judging that the basic test data corresponding to the comparison result is abnormal; and alarming is carried out according to the abnormity, and alarming information is sent to a terminal where a corresponding manager is located, so that the manager can timely follow up the abnormity, and can intelligently monitor and judge the current problems aiming at each scene in the life cycle of demand research and development, thereby greatly improving the management efficiency of the manager and reducing the demand production risk.
Example two
Referring to fig. 8, a schematic diagram of program modules of a risk monitoring system according to an embodiment of the present invention is shown. The risk monitoring system can be applied to electronic equipment. In this embodiment, risk monitoring system 20 may include or be divided into one or more program modules, which are stored in a storage medium and executed by one or more processors to implement the present invention and implement the risk monitoring methods described above. The program modules referred to in the embodiments of the present invention refer to a series of computer program instruction segments capable of performing specific functions, and are more suitable than the programs themselves for describing the execution process of the risk monitoring system 20 in the storage medium. The following description will specifically describe the functions of the program modules of the present embodiment:
the obtaining module 201 is configured to obtain a test phase, a real-time progress, a fault node, and a standing time of the fault node of each basic test data from a plurality of subsystems through a real-time interface.
The testing stage comprises smoking testing, system testing, safety testing and regression testing. The real-time schedule includes a test process and a test schedule completion percentage, for example: the current test item has completed testing 50%. The standing time of the fault node refers to a time length of waiting for processing when the fault node is in a fault state, for example: the time for a certain test node to fail and wait for human processing is 30 minutes. In an actual application scenario, after a certain node fails in a test, active discovery and processing of a manager need to be waited, and if the failed node is not discovered or processed by the manager for a long time, the test progress is seriously affected, so that the production of a product is affected.
In an exemplary embodiment, the obtaining module 201 may obtain real-time progress of each basic test data, the failed node, and a standing time of the failed node from the plurality of test systems through a software development management tool, for example, a case management tool, an automation management tool, a log tool, and the like. The test system can be any one of the subsystems 1-5 in the figure, and comprises a use case management system, a Bug (Bug) system, a configuration management system, a UI layer animation system, a reporting system, a Cat analysis rate system and the like.
The determining module 202 is configured to compare the test stage, the real-time progress, and the standing time of the fault node of each basic test data according to an index dimension set in the corresponding test stage, so as to determine whether each basic test data is abnormal, where the index dimension includes a time dimension and a completion rate dimension.
In the testing process, each basic test data is tested according to the corresponding index dimension to judge whether the abnormity occurs. Wherein the testing stage is judged according to the time dimension. For example, one smoking test in the smoking test stage needs to be completed within two days, and whether the smoking test in the corresponding basic test data is completed within two days is determined. The real-time progress is judged according to the time dimension and the completion rate dimension. For example, it is preset that a system test should complete 50% of tests at 10:00 am on xx month xx in xx years, and whether the real-time progress of the system test phase is abnormal or not is determined by comparing the real-time progress of the system test phase in each piece of basic test data with the preset value. And comparing the standing time lengths of the fault nodes according to the time dimension. For example, if the preset standing time of each fault node is not more than 1 hour, comparing the standing time of the fault node in each basic test data with the preset standing time to determine whether the standing time of each fault node is abnormal, that is, the basic test data has a risk.
And the determining module 203 is configured to determine that the basic test data corresponding to the comparison result is abnormal when the comparison result exceeds the standard value corresponding to the index dimension.
Specifically, according to preset product production time and preset latest completion time of each node test, the test completion time of the test service can be estimated according to the test progress, then whether the estimated test completion time is before the test latest completion time is judged, and if the estimated test completion time is after the test latest completion time, the test service can be determined to have risk. For example, if the smoking test is not completed within two days, it is determined that the corresponding basic test data is abnormal. And if the standing time of the fault node exceeds the preset standing time, judging that the corresponding basic data is abnormal.
In an exemplary embodiment, the risk monitoring system 20 may include a generation module and a tagging module.
And the generating module is used for generating corresponding abnormal information when the basic test data is judged to be abnormal.
And the marking module is used for marking the abnormal information according to the subsystem corresponding to the basic test data to obtain abnormal marking information.
The marking method can be as follows: and adding the marking information corresponding to the subsystem to the abnormal information. For example: and (3) generating abnormal information A when the basic test data in the subsystem 1 is abnormal, wherein the marked abnormal marking information is' subsystem 1: exception information a "or" subsystem 1-exception information a ". Of course, the corresponding identifier of each subsystem may be preset, and the corresponding identifier is added to the abnormal information, for example, the identifier corresponding to the subsystem 1 is preset to be "1", the abnormal information a is marked, and the marked abnormal marking information is "1 abnormal information" or "abnormal information 1". The form of the abnormality marking information includes, but is not limited to, the form of "subsystem + character + abnormality information" described above, and may also be the form of "abnormality information + superscript/subscript subsystem", or may also be any other combination form, and is not limited in the present invention. By marking the corresponding subsystem information to the anomaly, it is possible to determine the subsystem to which the anomaly belongs, i.e. which subsystem has the anomaly.
In an exemplary embodiment, the risk monitoring system further includes an upload module configured to upload the anomaly flag information into a blockchain. The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product services layer, and an application services layer.
And the alarm module 204 is configured to alarm according to the abnormality and send alarm information to a terminal where a corresponding manager is located, so that the manager can follow up processing the abnormality in time.
In an exemplary embodiment, when the comparison result exceeds the standard value corresponding to the index dimension, the comparison result may be linked to corresponding warning information in a hyperlink manner to give an alarm. Illustratively, if the comparison result exceeds a standard value corresponding to the index dimension, the risk is present, and the high-risk warning information is linked by means of a hyperlink.
In an exemplary embodiment, the base test data may also include automated formation power. And when the automatic success rate is lower than a preset value, sending the failure reason to a risk monitoring system in a hyperlink mode so that the manager can perform corresponding processing according to the failure reason.
In an exemplary embodiment, the plurality of subsystems includes a first subsystem, and the alarm module 204 may include a statistics unit and a display unit.
The statistical unit is used for respectively carrying out statistics on the abnormal information of each subsystem to obtain a target subsystem with the abnormal information and an abnormal result and abnormal information which are counted by aiming at each target subsystem.
And the display unit is used for displaying colors corresponding to the abnormal result and the abnormal information on a target subsystem module of a display interface of the risk monitoring system according to the target subsystem, the abnormal result and the abnormal information.
In practical application, all subsystem modules are displayed on a display interface of the risk monitoring system, and each subsystem module corresponds to one subsystem. And determining the test state of each subsystem according to different display colors. When one subsystem is tested abnormally, the basic test data of the subsystem is judged to be abnormal information, and a display interface of the risk monitoring system displays that the subsystem is abnormal or risky. For example: and counting that the subsystem 1 is abnormal according to the statistical result, and displaying the subsystem 1 in red on a display interface of the risk monitoring system to show that the subsystem is abnormal or risky.
In an exemplary embodiment, different subsystems are set to different importance levels depending on the service. The method further comprises the following steps: acquiring preset importance levels corresponding to the subsystems; and placing the subsystem modules belonging to the same importance level in a display area corresponding to a display interface of the risk monitoring system. As shown in fig. 5, a schematic interface diagram is displayed for the risk monitoring system. In fig. 5, the importance level of the PABO2O-CP subsystem and the CNBS-CORE subsystem is 1, the importance level of the PACES-CCMS-CORE subsystem is 2, the PABO2O-CP subsystem module and the CNBS-CORE subsystem module are placed in the display area a of the display interface of the risk monitoring system, and the PACES-CCMS-CORE subsystem module is placed in the display area B of the display interface of the risk monitoring system. By placing the subsystem modules with different importance levels in different display areas of a display interface of the risk monitoring system, the subsystems with different importance levels can be monitored, and management personnel can be promoted to quickly process the subsystems with high importance levels.
In an exemplary embodiment, the alarm module 204 may further include an identification unit, a determination unit, and a display unit.
The identification unit is used for identifying the abnormal mark information.
The determining unit is configured to determine target anomaly information corresponding to each subsystem according to the identification result, where the target anomaly information includes: a test phase and a cause of failure.
The display unit is used for displaying the target abnormal information in each subsystem and displaying an alarm in a test stage module in which the target abnormal information appears in each subsystem.
The test phase module may include a smoke test module, a system test module, a security test module, and a regression test module.
Specifically, by counting the target abnormal information of each subsystem, displaying the target abnormal information in each subsystem and displaying an alarm in a module of each subsystem, relevant management personnel can conveniently perform corresponding processing operation according to the target abnormal information and the alarm. FIG. 7 is a diagram showing the effects of an exemplary PACES-CCMS-CORE subsystem. And if the abnormal information of the basic test data of the PACES-CCMS-CORE subsystem is that a compatibility test machine type is not configured before a regression report is sent and the regression test report is not sent in a regression test stage, displaying that the compatibility test machine type is not configured before the regression report is sent and the regression test report is not sent, and displaying red by a regression test module, wherein the red indicates that the risk degree of the regression test is high risk.
In an exemplary embodiment, after each subsystem performs alarm display in a module that displays the target abnormal information and that in which the target abnormal information occurs in each subsystem, if abnormal processing operation information of the administrator is received, a corresponding administrator name and abnormal processing operation result information corresponding to the administrator are displayed at a corresponding position where the target abnormal information is displayed. By displaying the operation result information corresponding to the management personnel, the risk monitoring can be more transparent, so that the risk monitoring result and the corresponding processing result of each subsystem can be checked in real time. With continuing reference to fig. 7, the PACES-CCMS-CORE subsystem displays that "the compatibility test machine type has not been configured before the regression report is sent" and that "the regression test report is not sent", and after receiving the operation information that the administrator has configured the compatibility test machine type, displays the corresponding administrator name and that "the compatibility machine has been configured, the QA commander has a problem and needs to be repaired later" below the display that "the compatibility test machine type has not been configured before the regression report is sent", and displays the corresponding administrator name and that "the compatibility machine has been sent and is to be synchronized" below the display that "the regression test report is not sent".
In an exemplary embodiment, after all the exceptions of the subsystem receive the exception handling operation information of the administrator, the corresponding production state result is displayed according to the handling result.
It should be noted that some minor problems may occur in the testing stage before commissioning, but if the manual confirmation does not affect the normal operation of the product, the display interface of the subsystem may display that the manual confirmation is commissionable. With continuing reference to fig. 7, after receiving the abnormal processing operation information of the manager, it still shows that "QA commander has a problem and needs to be repaired later", and after the manager confirms that the normal operation of the product is not affected, it can display "production state" on the display interface of the PACES-CCMS-CORE subsystem: manually confirm that production can be put in production "and display green. Green indicates that all tests of the subsystem passed. Of course, different production statuses are displayed according to different test stages and different test results. For example: when the test is not completed and there is no risk so far, the commissioning status can be shown as: carrying out the following steps; when the test is not completed and there is a risk so far, the commissioning status can be shown as: is risky. Through displaying the production state information, related personnel can carry out product production operation according to the display result intuitively, and the normal online of the product is ensured.
According to the risk monitoring system provided by the embodiment of the invention, the test stage and the real-time progress of each basic test data and the standing time of the fault node are compared according to the index dimension set in the corresponding test stage, so as to judge whether each basic test data is abnormal; when the comparison result exceeds the standard value corresponding to the index dimension, judging that the basic test data corresponding to the comparison result is abnormal; and alarming is carried out according to the abnormity, and alarming information is sent to a terminal where a corresponding manager is located, so that the manager can timely follow up the abnormity, and can intelligently monitor and judge the current problems aiming at each scene in the life cycle of demand research and development, thereby greatly improving the management efficiency of the manager and reducing the demand production risk.
EXAMPLE III
Referring to fig. 9, a hardware architecture diagram of a computer device according to a third embodiment of the present invention is shown. The computer device 2 includes, but is not limited to, a memory 21, a processor 22, and a network interface 23 communicatively coupled to each other via a system bus, and FIG. 6 illustrates only the computer device 2 having components 21-23, but it is to be understood that not all of the illustrated components are required and that more or fewer components may alternatively be implemented. In the present embodiment, the computer device 2 is a device capable of automatically performing numerical calculation and/or information processing in accordance with a preset or stored instruction. For example, a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server, or a rack server (including an independent server or a server cluster composed of a plurality of servers) that can execute programs, and the like.
The memory 21 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 21 may be an internal storage unit of the computer device 2, such as a hard disk or a memory of the computer device 2. In other embodiments, the memory may also be an external storage device of the computer device 2, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the computer device 2. Of course, the memory 21 may also comprise both an internal storage unit of the computer device 2 and an external storage device thereof. In this embodiment, the memory 21 is generally used for storing an operating system installed in the computer device 2 and various application software, such as program codes of the risk monitoring system 20. Further, the memory 21 may also be used to temporarily store various types of data that have been output or are to be output.
The processor 22 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 22 is typically used to control the overall operation of the computer device 2. In this embodiment, the processor 22 is configured to execute the program codes stored in the memory 21 or process data, such as operating the risk monitoring system 20.
The network interface 23 may comprise a wireless network interface or a wired network interface, and the network interface 23 is generally used for establishing communication connection between the computer device 2 and other electronic devices. For example, the network interface 23 is used to connect the computer device 2 to an external terminal through a network, establish a data transmission channel and a communication connection between the computer device 2 and the external terminal, and the like. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a Global System of Mobile communication (GSM), Wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, Bluetooth (Bluetooth), Wi-Fi, and the like.
It is noted that fig. 9 only shows the computer device 2 with components 21-23, but it is to be understood that not all shown components are required to be implemented, and that more or less components may be implemented instead.
Example four
The present embodiments also provide a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the risk monitoring method of the embodiments.
In this embodiment, the computer-readable storage medium includes a Flash memory, a hard disk, a multimedia Card, a Card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc., and in other embodiments, the computer-readable storage medium may also be an external storage device of the computer apparatus, such as a plug-in hard disk equipped on the computer apparatus, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card), etc. Of course, the computer-readable storage medium may also include both internal and external storage devices of the computer device. In this embodiment, the computer-readable storage medium is generally used for storing an operating system and various types of application software installed in the computer device, for example, the program codes of the risk monitoring method in the embodiment, and the like. Further, the computer-readable storage medium may also be used to temporarily store various types of data that have been output or are to be output.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A method of risk monitoring, the method comprising:
acquiring a test stage, a real-time progress, a fault node and a standing time of the fault node of each basic test data from a plurality of subsystems through a real-time interface;
comparing the test stage and the real-time progress of each basic test data and the standing time of the fault node according to index dimensions set in the corresponding test stage to judge whether each basic test data is abnormal, wherein the index dimensions comprise a time dimension and a completion rate dimension;
when the comparison result exceeds the standard value corresponding to the index dimension, determining that the basic test data corresponding to the comparison result is abnormal; and
and alarming according to the abnormity, and sending alarm information to a terminal where a corresponding manager is located so that the manager can follow up to process the abnormity in time.
2. The risk monitoring method of claim 1, wherein the method further comprises:
when the basic test data is judged to be abnormal, generating corresponding abnormal information; and
and marking the abnormal information according to the subsystem corresponding to the basic test data to obtain abnormal marking information.
3. The risk monitoring method according to claim 2, wherein each subsystem is preset with corresponding marking information, and the marking of the abnormal information according to the subsystem corresponding to the basic test data to obtain abnormal marking information comprises:
and adding the mark information corresponding to the subsystem into the abnormal information to obtain the abnormal mark information.
4. The risk monitoring method of claim 2, wherein said alerting based on said anomaly comprises:
respectively counting the abnormal information of each subsystem to obtain a target subsystem with the abnormal information, and an abnormal result and abnormal information counted by aiming at each target subsystem;
and displaying colors corresponding to the abnormal result and the abnormal information on a target subsystem module of a display interface of a risk monitoring system according to the target subsystem, the abnormal result and the abnormal information.
5. The risk monitoring method of claim 1, wherein different subsystems are set to different levels of importance depending on the business, the method further comprising:
acquiring preset importance levels corresponding to the subsystems;
and placing the subsystem modules belonging to the same importance level in a display area corresponding to a display interface of the risk monitoring system.
6. The risk monitoring method according to claim 3, wherein the alarming according to the abnormality and sending the alarming information to a corresponding manager so that the manager can follow up to process the abnormality in time, comprises:
identifying the anomaly marking information;
determining target abnormal information corresponding to each subsystem according to the identification result, wherein the target abnormal information comprises: testing stage and fault reason;
and displaying the target abnormal information in each subsystem, and displaying an alarm in a test stage module in which the target abnormal information appears in each subsystem.
7. The risk monitoring method of claim 1, wherein the method further comprises:
after each subsystem displays the target abnormal information and alarms in the module of each subsystem with the target abnormal information, if the abnormal processing operation information of the administrator is received, the corresponding name of the administrator and the abnormal processing operation result information corresponding to the administrator are displayed at the corresponding position where the target abnormal information is displayed.
8. A risk monitoring system, comprising:
the acquisition module is used for acquiring the test stage, the real-time progress, the fault node and the standing time of the fault node of each basic test data from the plurality of subsystems through the real-time interface;
the judging module is used for comparing the testing stage and the real-time progress of each basic testing data and the standing time of the fault node according to index dimensions set in the corresponding testing stage so as to judge whether each basic testing data is abnormal or not, wherein the index dimensions comprise a time dimension and a completion rate dimension;
the determining module is used for determining that the basic test data corresponding to the comparison result is abnormal when the comparison result exceeds the standard value corresponding to the index dimension; and
and the alarm module is used for giving an alarm according to the abnormity and sending alarm information to a terminal where a corresponding manager is located so that the manager can follow up to process the abnormity in time.
9. A computer device, characterized by a computer device memory, a processor and a computer program stored on the memory and executable on the processor, which computer program, when executed by the processor, carries out the steps of the risk monitoring method according to any one of claims 1-7.
10. A computer-readable storage medium, in which a computer program is stored which is executable by at least one processor to cause the at least one processor to perform the steps of the risk monitoring method according to any one of claims 1-7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113436419A (en) * | 2021-06-28 | 2021-09-24 | 南京吾爱网络技术有限公司 | Running risk monitoring statistics and process follow-up system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105790833A (en) * | 2014-12-23 | 2016-07-20 | 中富通股份有限公司 | Dynamic optical network monitoring system based on GIS technology |
| CN108401164A (en) * | 2018-02-12 | 2018-08-14 | 中国联合网络通信集团有限公司 | Fault handling method and device |
| WO2019223062A1 (en) * | 2018-05-22 | 2019-11-28 | 平安科技（深圳）有限公司 | Method and system for processing system exceptions |
| CN110851322A (en) * | 2019-10-11 | 2020-02-28 | 平安科技（深圳）有限公司 | Hardware equipment abnormity monitoring method, server and computer readable storage medium |
-
2020
- 2020-12-24 CN CN202011550085.2A patent/CN112561385A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105790833A (en) * | 2014-12-23 | 2016-07-20 | 中富通股份有限公司 | Dynamic optical network monitoring system based on GIS technology |
| CN108401164A (en) * | 2018-02-12 | 2018-08-14 | 中国联合网络通信集团有限公司 | Fault handling method and device |
| WO2019223062A1 (en) * | 2018-05-22 | 2019-11-28 | 平安科技（深圳）有限公司 | Method and system for processing system exceptions |
| CN110851322A (en) * | 2019-10-11 | 2020-02-28 | 平安科技（深圳）有限公司 | Hardware equipment abnormity monitoring method, server and computer readable storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 王士政: "电力系统运行控制与调度自动化", 河海大学出版社, pages: 276 - 281 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113436419A (en) * | 2021-06-28 | 2021-09-24 | 南京吾爱网络技术有限公司 | Running risk monitoring statistics and process follow-up system |
| CN113436419B (en) * | 2021-06-28 | 2022-04-19 | 南京吾爱网络技术有限公司 | Running risk monitoring statistics and process follow-up system |
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