CN115086147A - Business data monitoring and early warning method, device, medium and electronic equipment - Google Patents
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Abstract
The invention belongs to the field of data monitoring, and provides a service data monitoring and early warning method, a device, a medium and electronic equipment. The method comprises the following steps: receiving a monitoring request sent by a service end; responding to the monitoring request and sending the rule code to the service terminal; receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code; and monitoring the target service parameters of the monitoring source data according to the service rule parameters, and generating alarm information when the target service parameters meet alarm conditions. The service data monitoring and early warning method can realize real-time monitoring of service data.
Description
Technical Field
The present invention relates to a monitoring method, and in particular, to a method, an apparatus, a medium, and an electronic device for monitoring and warning service data.
Background
In recent years, with the continuous development of internet technology and the change of living habits of people, more and more enterprises choose to manage and operate services through the internet, which results in the continuous increase of the amount of service data in the network. For enterprises, the online data can be normally and stably monitored by monitoring the service data in real time, so that high-reliability and stable service experience is provided for users, and the online data monitoring system has important significance. However, unlike other data, the service data has the characteristics of various types, complex application scenarios, and the like, so that the conventional monitoring system is difficult to monitor the service data, and a real-time monitoring technology for the service data is not available in the market at present. Therefore, how to provide a scheme capable of monitoring and early warning service data has become one of the technical problems that needs to be solved urgently by technical personnel in the related field.
Disclosure of Invention
In view of the above drawbacks of the prior art, an object of the present invention is to provide a method, an apparatus, a medium, and an electronic device for monitoring and warning service data, which are used to solve the problem that the prior art cannot perform real-time monitoring on the service data.
In order to achieve the above and other related objects, a first aspect of the present invention provides a service data monitoring and early warning method, applied to a service data monitoring and early warning end, where the service data monitoring and early warning method includes: receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring early warning end, the types of the rule codes are multiple, and each rule code corresponds to a service rule parameter of a type of monitoring service; responding to the monitoring request, sending the rule code to the service end so that the service end configures service rule parameters of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, wherein the monitoring source data comprises service data; receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code; and monitoring the target service parameters of the monitoring source data according to the service rule parameters, and generating alarm information when the target service parameters meet alarm conditions.
A second aspect of the present invention provides a service data monitoring and early warning apparatus, which is applied to a service data monitoring and early warning terminal, and the service data monitoring and early warning apparatus includes: the monitoring request receiving module is used for receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring early warning end, the types of the rule codes are multiple, and each rule code corresponds to a service rule parameter of one type of monitoring service; a monitoring request response module, configured to send the rule code to the service end in response to the monitoring request, so that the service end configures a service rule parameter of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, where the monitoring source data includes service data; the monitoring source data receiving module is used for receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code; and the monitoring and early warning module is used for monitoring the target service parameters of the monitoring source data according to the service rule parameters and generating warning information when the target service parameters meet warning conditions.
A third aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for monitoring and warning business data according to the first aspect of the present invention.
A fifth aspect of the present invention provides an electronic apparatus, comprising: a memory storing a computer program; and the processor is in communication connection with the memory and executes the service data monitoring and early warning method in the first aspect of the invention when the computer program is called.
As described above, the service data monitoring and early warning method, device, medium, and electronic device according to one or more embodiments of the present invention have the following beneficial effects:
the business data monitoring and early warning method can monitor monitoring source data in real time and generate warning information when preset conditions are met, wherein the monitoring source data can be business data which needs to be focused by a business end. Therefore, the service data monitoring and early warning method can solve the problem of short board in the monitoring of the service data by the existing monitoring platform. In addition, the service data monitoring and early warning method can also store the service data uploaded by the service terminal in a classified manner so as to provide a data source for the subsequent data analysis and decision process.
Drawings
Fig. 1 is a flowchart illustrating a service data monitoring and early warning method according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating monitoring of target service parameters according to an embodiment of the present invention.
Fig. 3 is a flowchart illustrating a process of determining whether a target service parameter satisfies an alarm condition according to an embodiment of the present invention.
Fig. 4 is a detailed flowchart illustrating the process of determining whether the target service parameter satisfies the alarm condition according to the embodiment of the present invention.
FIG. 5 is a flowchart illustrating obtaining a target parameter value according to an embodiment of the present invention.
Fig. 6 is a flowchart illustrating monitoring of target service parameters according to an embodiment of the present invention.
Fig. 7 is a schematic structural diagram of a service data monitoring and early warning apparatus in an embodiment of the present invention.
Fig. 8 is a schematic structural diagram of the electronic device according to the embodiment of the present invention.
Description of the element reference numerals
700 service data monitoring and early warning device
710 monitor request receiving module
720 monitor request response module
730 monitoring source data receiving module
740 monitoring and early warning module
800 electronic device
810 memory
820 processor
830 display
S11-S14
S21-S22
S31-S32
S41-S43
S51-S52
S61-S64
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than being drawn according to the number, shape and size of the components in actual implementation, and the type, number and proportion of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated. Moreover, in this document, relational terms such as "first," "second," and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The currently used platforms such as troy allow developers to perform operations such as log search, quick positioning of problem causes and the like, and support real-time monitoring of interface granularity, thereby greatly facilitating daily operations of the developers. However, the monitoring information presentation functions provided by these platforms are often tedious and crude, do not reflect problems visually, and are not friendly enough for non-technical personnel.
For data monitoring, no matter what monitoring means is adopted, the purpose is to ensure normal stability of online data so as to provide high-reliability and stable service experience for users. The inventor finds in practical application that there is currently a gap in the prior art for monitoring the latitude of business data. For example, due to the requirement of business prevention, order quantity data in a certain time period needs to be monitored in real time, and report data can be generated, so that longitudinal change of the data is intuitively reflected; when the early warning condition is met, the early warning information needs to be sent to the data attention personnel in time through a communication means, so that the data attention personnel can quickly respond and process various early warning information quickly. However, unlike other data, the service data has the characteristics of various types, complex application scenarios, and the like, so that the conventional monitoring system is difficult to monitor the service data, and a real-time monitoring technology for the service data is not available in the market at present. Therefore, how to provide a scheme capable of monitoring and early warning service data has become one of the technical problems that needs to be solved urgently by technical personnel in the related art.
At least aiming at the problems, the invention provides a service data monitoring and early warning method. The service data monitoring and early warning method comprises the following steps: receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring early warning end, the types of the rule codes are multiple, and each rule code corresponds to a service rule parameter of a type of monitoring service; responding to the monitoring request, sending the rule code to the service end so that the service end configures service rule parameters of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, wherein the monitoring source data comprises service data; receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code; and monitoring the target service parameters of the monitoring source data according to the service rule parameters, and generating alarm information when the target service parameters meet alarm conditions. The business data monitoring and early warning method can monitor monitoring source data in real time and generate warning information when preset conditions are met, wherein the monitoring source data can be business data which needs to be focused by a business end. Therefore, the service data monitoring and early warning method can solve the problem of short board in the monitoring of the service data by the existing monitoring platform.
The method for monitoring and warning service data will be described in detail with reference to the accompanying drawings by way of specific embodiments.
Fig. 1 is a detailed flowchart of a service data monitoring and early warning method according to an embodiment of the present invention. In this embodiment, the service data monitoring and early warning method is applied to a service data monitoring and early warning end. The service data monitoring and early warning end can be a high-performance computer, comprises a processor, a hard disk, a memory, a database and other structures, and is used for providing service of service data monitoring with high stability, high reliability and high safety for users. In this embodiment, the service data monitoring and early warning end includes, but is not limited to, a file server, a database server, an application server, a WEB server, a local server, a cloud server, and the like. Specifically, as shown in fig. 1, the service data monitoring and early warning method in this embodiment includes the following steps S11 to S14.
In step S11, a monitoring request sent by a service end is received, where the monitoring request is used to request a rule code from the service data monitoring and early warning end, where the rule code is of multiple types, and each type of the rule code corresponds to a service rule parameter of a type of monitoring service. The service end may be a device on the service side, for example, a device used by a manager or a salesperson, and the service end may also be a device on the user side, which is not limited in this embodiment of the present invention. The rule code refers to a standard code predefined by the service data monitoring and early warning end. In this embodiment, the service data monitoring and early warning end is only used to provide a monitoring and early warning service for monitoring source data carrying a legal rule code, and does not monitor monitoring source data not carrying the rule code or monitoring source data carrying an illegal rule code, for example, the service data monitoring and early warning end may be directly discarded when receiving such monitoring source data.
In step S12, in response to the monitoring request, the rule code is sent to the service end, so that the service end configures the service rule parameter of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, where the monitoring source data includes service data. The monitoring source data refers to original service data which is requested by the service terminal to monitor by the service data monitoring and early warning terminal, for example, sales volume or search volume of target commodities in a certain time period. It should be noted that, in some other embodiments, the monitoring source data may also include non-business data, which is not limited in the present invention.
In step S13, the monitoring source data sent by the service end is received, a rule code carried by the monitoring source data is obtained, and a service rule parameter of the monitoring source data is extracted from the rule code.
Optionally, the service end may send the monitoring source data to the service data monitoring and early warning end at any time according to a requirement, or may send the monitoring source data to the service data monitoring and early warning end according to a specific period. The two modes can realize the real-time monitoring of the monitoring source data.
In step S14, a target service parameter of the monitoring source data is monitored according to the service rule parameter, and an alarm message is generated when the target service parameter meets an alarm condition. The target business parameter refers to a business parameter to be monitored, for example, the target business parameter may be a sales volume of a target commodity in a certain time period, a response delay of a web page, and the like. The type of the target service parameter may be a numerical value, a character string, a boolean value, and the like, which is not limited in the present invention. Specifically, in this embodiment, in step S14, the service rule corresponding to the monitoring source data may be obtained according to the rule code, and then the target service parameter is extracted from the monitoring source data according to the service rule.
Optionally, in step S14, a natural language processing technique may be used to extract the target service parameter.
Optionally, in step S14, the warning message may be sent to the staff member in various manners, including but not limited to short message and email. In addition, the staff can also configure the sending mode of the alarm information in a one-key configuration mode.
Optionally, the service end may send the monitoring request before sending the monitoring source data each time, so as to obtain the rule code from the service data monitoring and warning end. In addition, the service end may also send the monitoring request once to obtain the rule code, and then the service end stores the rule code in a local memory, and then may directly read the rule code from the local memory when sending the monitoring source data.
As can be seen from the above description, the service data monitoring and early warning method according to this embodiment can perform real-time monitoring on monitoring source data sent by a service end, and generate an alarm signal when a target service parameter in the monitoring source data triggers an alarm condition. Therefore, the service data monitoring and early warning method can realize real-time monitoring of the service data.
Due to the characteristics of various types and complex application scenes of the service data, the universality of the service data monitoring and early warning end is poor due to the characteristics. For this problem, in this embodiment, all monitoring service data may be abstracted into corresponding service rules according to the types of the monitoring indexes, and a corresponding rule code is configured for each service rule. Based on this, for all types of service ends and all types of service data, as long as the service end configures the monitoring source data according to the service rule and the rule code, the service data monitoring and early warning end can perform real-time monitoring and early warning on the monitoring source data sent by the service end. Therefore, the service data monitoring and early warning end can realize once coding and then zero coding to access a new service end and new service data and immediately put into use, and has good universality.
Optionally, in this embodiment, all the service data may be abstracted into one of the following three service rules according to the type of the monitoring indicator of the service data: integer (int) type, string (string) type, and boolean (boolean) type.
The integer type of the business rule indicates that the monitoring index of the business data is a digital type value, and the value is qualified if the value is located in a given standard interval, otherwise, the value is unqualified.
The service rule of the character string type indicates that the monitoring index of the service data is a character string, the character string is qualified when being positioned in a given character string list, and the character string is unqualified otherwise.
The boolean type of business rule indicates that the monitoring index of the business data is a designated numeric type with a value of 0 or 1, where 0 indicates failing and 1 indicates passing. Alternatively, the default value of the boolean type of business rule may be configured to be 0, i.e., fail by default.
Through practical tests, the three business rules can basically cover more than 90% of scenes in practical application. However, besides the three business rules, the related technical personnel can also customize the business rules of corresponding types according to the actual requirements, and the invention does not limit the number and types of the business rules.
Optionally, the service rule parameter includes a monitoring time period, a monitoring step length, an substandard number alarm value, an alarm condition, an alarm mode, and/or an alarm object. The monitoring time period refers to a time period in which the service end requests the service data monitoring and early warning end to monitor the monitoring source data sent by the service end, for example, 19: 00-20: 00. the monitoring step length refers to the interval step length of the monitoring task, and the value of the interval step length is a positive integer. The non-standard number warning value is used for representing the tolerance degree of the non-standard number, and the value of the non-standard number warning value is a positive integer, for example, when the non-standard number warning value is 1, the warning signal is generated as soon as the non-standard target service parameter occurs, and when the non-standard number warning value is 2, the warning signal is generated as soon as the two non-standard target service parameters occur. The alarm condition corresponds to a specific business rule, for example, for an integer type of business rule, the corresponding alarm condition may include a maximum threshold and a minimum threshold, for a string type of business rule, the corresponding alarm condition is, for example, a string list, and for a boolean type of business rule, the corresponding alarm condition is, for example, 0 or 1. The alarm mode is, for example, mail, short message, telephone, etc. The alarm object refers to a sending object of the alarm information.
The business rule parameters will be explained next by three specific examples.
Example 1, in this example, a service rule corresponding to the monitoring source data is an integer type, and at this time, an example of a configured service rule parameter is:
{"heartDataList"：[{"maxValue"：20，"minValue"：10，"startTime"："24：00"，"endTime"："24：00"，"sentinelValue"：1}]"monitorMember"："19999999999"，"stepSize"：1}。
example 2, in this example, the service rule corresponding to the monitoring source data is a character string type, and at this time, an example of a configured service rule parameter is:
{"heartDataList"：[{"startTime"："24：00"，"endTime"："24：00"，"targetValue"：""}]，"monitorMember"："19999999999"，"stepSize"：1}。
example 3, in this example, the service rule corresponding to the monitoring source data is of a boolean type, and at this time, an example of a configured service rule parameter is:
{"heartDataList"：[{"startTime"："24：00"，"endTime"："24：00"，"sentinelValue"：1}]，"monitorMember"："19999999999"，"stepSize"：1}。
in each of the above examples, heartdatasist represents a service core parameter string, maxValue represents a maximum value of an integer type service rule qualified range, minValue represents a minimum value of the integer type service rule qualified range, targetValue represents an enumerated value of a string type service rule meeting the standard, startTime represents a monitoring validation start time, endTime represents a monitoring validation end time, sentinelValue represents an alarm value of the number of times of failing to meet the standard, 1 represents an immediate alarm, monitorMember represents an alarm notifier, and stepSize represents an interval step length of each task.
In an embodiment of the present invention, the service rule parameter includes a monitoring step size of the target service parameter. Referring to fig. 2, in the present embodiment, monitoring the target service parameter of the monitoring source data according to the service rule parameter includes the following steps S21 and S22.
In step S21, the target service parameter is obtained in real time and stored in a distributed memory or a cache of the service data monitoring and early warning end.
Specifically, since the service data monitoring and early warning end needs to frequently read the target service parameters so as to implement real-time monitoring of the service data, in order to save data reading time and ensure that the system has good real-time performance, the embodiment may store the service rule parameters in the distributed memory or the cache after extracting the service rule parameters. The distributed memory stores data on a plurality of independent devices in a dispersed manner, adopts an expandable system structure, shares storage load by a plurality of storage servers, and positions storage information by a position server. The distributed memory can improve the reliability, the availability and the access efficiency of the service data monitoring and early warning end and has the advantage of easy expansion. The cache is a memory which is contained in the service data monitoring and early warning end and can exchange high-speed data, and exchanges data with the CPU before the memory, so that the speed is high.
In step S22, the target service parameter is successively read from the distributed memory or the cache according to the monitoring step size, and it is determined whether the target service parameter meets the alarm condition. For example, if the monitoring compensation is 10 minutes, the target service parameter is read from the distributed memory or the cache every 5 minutes in step S22.
In this embodiment, since the target service parameter is stored in the distributed memory or the cache, in step S22, only data needs to be read from the distributed memory or the cache, and no call is involved in this process, so that millisecond-level response can be realized, and a user basically does not feel delay.
Optionally, referring to fig. 3, the step of determining whether the target service parameter satisfies the alarm condition in this embodiment includes a step S31 and a step S32.
In step S31, a plurality of parameter values of the target service parameter in a target time period are read from the distributed memory or the cache, where the target time period is a time period between the last reading and the current reading. For example, if the monitoring step is 5 minutes, at 16: 00, reading the target service parameter from the distributed memory or the cache once, and then, at 16: and 05, reading the target service parameters from the distributed memory or the cache again. In addition, since the target service parameter is obtained in real time in step S21 and stored in the distributed memory or the cache, at 16: 00-16: 05 there may be multiple parameter values written to the distributed memory or cache, so at 16: the data read at 05 may be 16: 00-16: 05 a plurality of parameter values of the target service parameter within the time period.
In step S32, it is determined whether the target service parameter satisfies the alarm condition according to the plurality of parameter values.
Optionally, referring to fig. 4, in this embodiment, the step of determining whether the target service parameter satisfies the alarm condition according to the plurality of parameter values includes the following steps S41 to S43.
In step S41, the mean and variance of the plurality of parameter values are obtained. Wherein the mean is a number representing a trend in the plurality of parameter values set, calculated as a sum of each of the parameter values divided by the number of the parameter values. The variance is used to represent the degree of deviation between the plurality of parameter values and their mathematical expectations (i.e., means) calculated as the mean of the squared values of the difference between each of the parameter values and the mean of all of the parameter values.
In step S42, a target parameter value is selected from the plurality of parameter values according to the mean and variance of the plurality of parameter values.
In step S43, it is determined whether the target service parameter satisfies the alarm condition according to the target parameter value. Because the target parameter value can well reflect the overall state of the plurality of parameter values, whether the target service parameter meets the alarm condition or not is judged according to the target parameter value, so that the accuracy is higher, and the problem of false alarm can be well avoided.
Alternatively, referring to fig. 5, selecting a target parameter value from the plurality of parameter values according to the mean and the variance of the plurality of parameter values includes the following steps S51 and S52.
In step S51, an upper limit value and a lower limit value are obtained according to the mean and the variance of the parameter values, wherein the upper limit value is proportional to the mean and proportional to the variance, and the lower limit value is proportional to the mean and inversely proportional to the variance. For example, in this embodiment, the upper limit value may be upper mean + N × var, and the lower limit value may be lower mean-N × var, where mean is a mean of the plurality of parameter values, var is a variance of the plurality of parameter values, and N is an integer.
In step S52, the parameter value between the upper limit value and the lower limit value is acquired as the target parameter value.
In an embodiment of the present invention, the service rule parameter further includes a standard range of the target service parameter and a warning value of the number of times of reaching standards, and determining whether the target service parameter satisfies the warning condition includes: if the times that the target service parameter exceeds the standard range is larger than or equal to the alarm value of the standard times, judging that the target service parameter meets the alarm condition, otherwise, judging that the target service parameter does not meet the alarm condition.
Referring to fig. 6, in an embodiment of the present invention, the service rule parameters further include monitoring time periods, the number of the target service parameters is at least two, and monitoring the target service parameters of the monitoring source data according to the service rule parameters includes the following steps S61 to S64.
In step S61, a monitoring task corresponding to each of the target service parameters is generated.
In step S62, an execution time scale of each monitoring task is obtained according to the monitoring time period and the monitoring step size of each monitoring task. The execution time scale of the monitoring task refers to a time when the monitoring task reads the target service parameter in the execution process, and the execution time scale can be obtained according to the monitoring time period and the monitoring compensation calculation of the monitoring task.
In step S63, if there is a conflict in the execution time scales of the monitoring tasks, the monitoring start time of one or more of the monitoring tasks is adjusted to ensure that there is no conflict in the execution time scales of the monitoring tasks. Specifically, for any two monitoring tasks a and B, if a and B read the distributed memory or the cache at a certain time t simultaneously, a read conflict of the distributed memory or the cache may be caused, that is, the monitoring tasks a and B conflict at the time t. To address this problem, in step S63, the monitoring start time of task a may be appropriately adjusted to avoid the monitoring tasks a and B from conflicting on the execution time scale.
In step S64, the monitoring tasks are independently executed according to the execution time scale of each monitoring task to achieve monitoring of the target service parameter. By the method, the time slice distribution principle of the operating system can be fully utilized, so that the execution efficiency of the system is improved.
In an embodiment of the present invention, the service data monitoring and early warning end is configured with a gateway interface, a rest interface and/or a dubbo interface, and these interfaces are used to meet the requirements of uploading monitoring source data in different scenes and different service ends. The gateway interface and the rest interface may be used for front-end call, for example, if it is necessary to monitor whether a certain request is successful, the gateway interface or the rest interface may be called after the request is completed to notify the service data monitoring and early warning end of a call result of the request. The dubbo interface may be used for server invocation by a business party, for example, assuming that business data does not require front-end participation but only requires server participation, interaction may be performed through the dubbo interface at this time.
In an embodiment of the present invention, after the target service parameter is obtained, the service data monitoring and early warning method may further include: and classifying and storing the target service parameters, wherein the classified and stored target service parameters can be used as data sources in subsequent data analysis or decision making. For example, in subsequent data analysis or decision making, a business report can be made according to the target business parameters stored in a classified manner, or a data statistical graph can be generated according to the target business parameters stored in a classified manner, so that the change trend of data can be visually displayed, and accurate data support can be provided for business decision making and trend analysis.
In an embodiment of the present invention, the service data early warning end includes a service module and a data module. The service module is used for abstracting the monitoring source data into service rules and acquiring service rule parameters of the monitoring source data, the data module is used for performing alarm analysis according to the service rule parameters and target service parameters, namely, the service module is used for realizing data acquisition, and the data module is used for realizing data abnormity alarm.
Optionally, the service data monitoring and early warning end monitors the monitoring source data in a distributed real-time monitoring manner. Specifically, the service data monitoring and early warning end realizes real-time data acquisition through the service module, and realizes data exception warning through the data module. Preferably, the service module and the data module are independent from each other, so as to realize the mutual separation of the data acquisition and data abnormality alarm functions in the service data monitoring and early warning end. In addition, the service module and the data module may be deployed on different devices or platforms, and communicate with each other through an interface, and preferably transmit data in a json format.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Based on the description of the service data monitoring and early warning method, the invention also provides a service data monitoring and early warning device which is applied to a service data monitoring and early warning end. Referring to fig. 7, in an embodiment of the present invention, the service data monitoring and warning apparatus 700 includes a monitoring request receiving module 710, a monitoring request responding module 720, a monitoring source data receiving module 730, and a monitoring and warning module 740.
The monitoring request receiving module 710 is configured to receive a monitoring request sent by a service end, where the monitoring request is used to request a rule code from the service data monitoring and early warning end, where the rule code is of multiple types, and each type of the rule code corresponds to a service rule parameter of a type of monitoring service.
The monitoring request response module 720 is configured to send the rule code to the service end in response to the monitoring request, so that the service end configures a service rule parameter of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, where the monitoring source data includes service data.
The monitoring source data receiving module 730 is configured to receive the monitoring source data sent by the service end, acquire a rule code carried by the monitoring source data, and extract a service rule parameter of the monitoring source data from the rule code.
The monitoring and early warning module 740 is configured to monitor a target service parameter of the monitoring source data according to the service rule parameter, and generate warning information when the target service parameter meets a warning condition.
In an embodiment of the present invention, the service rule parameter includes a monitoring step size of the target service parameter. In this embodiment, the monitoring and early warning module 740 is specifically configured to:
acquiring the target service parameters in real time and storing the target service parameters into a distributed memory or a cache;
and gradually reading the target service parameters from the distributed memory or the cache according to the monitoring step length and judging whether the target service parameters meet the alarm condition.
In an embodiment of the invention, the monitoring and warning module 740 is further configured to:
reading a plurality of parameter values of the target service parameter in a target time period from the distributed memory or the cache, wherein the target time period refers to a time period between the last reading and the current reading;
and judging whether the target service parameters meet the alarm conditions or not according to the parameter values.
In an embodiment of the invention, the monitoring and warning module 740 is further configured to:
obtaining the mean and variance of the plurality of parameter values;
selecting a target parameter value from the plurality of parameter values according to the mean and the variance of the plurality of parameter values;
and judging whether the target service parameters meet the alarm conditions or not according to the target parameter values.
In an embodiment of the invention, the monitoring and warning module 740 is further configured to:
obtaining an upper limit value and a lower limit value according to the mean and the variance of the parameter values, wherein the upper limit value is proportional to the mean and proportional to the variance, and the lower limit value is proportional to the mean and inversely proportional to the variance;
acquiring the parameter value between the upper limit value and the lower limit value as the target parameter value.
In an embodiment of the present invention, the service rule parameters further include a standard range of the target service parameter and a warning value of the number of times of reaching standards. The monitoring and pre-warning module 740 is further configured to:
judging whether the times of the target service parameter exceeding the standard range is greater than or equal to the alarm value of the standard times; if the times that the target service parameter exceeds the standard range is larger than or equal to the alarm value of the standard times, judging that the target service parameter meets the alarm condition, otherwise, judging that the target service parameter does not meet the alarm condition.
In an embodiment of the present invention, the service rule parameters further include a monitoring time period, and the number of the target service parameters is at least two. The monitoring and pre-warning module 740 is further configured to:
generating a monitoring task corresponding to each target service parameter;
acquiring the execution time scale of each monitoring task according to the monitoring time period and the monitoring step length of each monitoring task;
if the execution time scales of the monitoring tasks have conflicts, adjusting the monitoring starting time of one or more monitoring tasks to ensure that the execution time scales of the monitoring tasks have no conflicts;
and independently executing the monitoring tasks according to the execution time scales of the monitoring tasks to realize the monitoring of the target service parameters.
For specific limitations of the service data monitoring and early warning apparatus, reference may be made to the above limitations of the service data monitoring and early warning method, which is not described herein again. All modules in the service data monitoring and early warning device can be completely or partially realized through software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Based on the above description of the service data monitoring and early warning method, the present invention further provides a computer readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the service data monitoring and early warning method described in any of the above embodiments. Specifically, the computer-readable storage medium in the present embodiment may be understood by those skilled in the art as follows: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with a computer program, where the computer program may be stored in a computer readable storage medium, and when executed, performs the following steps:
receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring early warning end, the types of the rule codes are multiple, and each rule code corresponds to a service rule parameter of a type of monitoring service;
responding to the monitoring request, sending the rule code to the service end so that the service end configures service rule parameters of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, wherein the monitoring source data comprises service data;
receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code;
and monitoring the target service parameters of the monitoring source data according to the service rule parameters, and generating alarm information when the target service parameters meet alarm conditions.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
Based on the description of the service data monitoring and early warning method, the invention also provides electronic equipment. Fig. 8 is a schematic structural diagram of an electronic device 800 according to an embodiment of the invention. As shown in fig. 8, the electronic device 800 in this embodiment includes a memory 810 and a processor 820. The memory 810 may be, among other things, volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory, with a computer program stored thereon. The processor 820 is communicatively coupled to the memory 810, and when the computer program is invoked, performs the following steps:
receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring and early warning end, the types of the rule code are multiple, and each type of the rule code corresponds to a service rule parameter of a type of monitoring service;
responding to the monitoring request, sending the rule code to the service end so that the service end configures service rule parameters of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, wherein the monitoring source data comprises service data;
receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code;
and monitoring the target service parameters of the monitoring source data according to the service rule parameters, and generating alarm information when the target service parameters meet alarm conditions.
In this embodiment, the Processor 820 may be a general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
Optionally, the electronic device 800 may also include a display 830. The display 830 is communicatively coupled to the memory 810 and the processor 820, and is configured to display a GUI interactive interface related to the user behavior analysis method.
It should be noted that in the above-described embodiments, references in the specification to "the present embodiment," "one embodiment," "another embodiment," "in some exemplary embodiments," or "other embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some embodiments, but not necessarily all embodiments. The various appearances of the phrase "the present embodiment," "one embodiment," or "another embodiment" are not necessarily all referring to the same embodiment. In the embodiments described above, although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory structures (e.g., dynamic ram (dram)) may use the discussed embodiments. The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims.
The protection scope of the service data monitoring and early warning method of the present invention is not limited to the execution sequence of the steps listed in this embodiment, and all the schemes of increasing, decreasing, and replacing the steps in the prior art according to the principle of the present invention are included in the protection scope of the present invention.
In summary, the service data monitoring and early warning method according to one or more embodiments of the present invention can monitor monitoring source data in real time, and generate warning information when a preset condition is met, where the monitoring source data may be service data that a service end needs to pay attention to. Therefore, the service data monitoring and early warning method can solve the short board problem existing in the monitoring of the service data by the existing monitoring platform. In addition, the service data monitoring and early warning method can also store the service data uploaded by the service terminal in a classified manner so as to provide a data source for the subsequent data analysis and decision process. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A service data monitoring and early warning method is characterized in that the method is applied to a service data monitoring and early warning terminal, and the service data monitoring and early warning method comprises the following steps:
receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring early warning end, the types of the rule codes are multiple, and each rule code corresponds to a service rule parameter of a type of monitoring service;
responding to the monitoring request, sending the rule code to the service end so that the service end configures service rule parameters of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, wherein the monitoring source data comprises service data;
receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code;
and monitoring the target service parameters of the monitoring source data according to the service rule parameters, and generating alarm information when the target service parameters meet alarm conditions.
2. The business data monitoring and early warning method according to claim 1, wherein the business rule parameters include monitoring step length of the target business parameters, and monitoring the target business parameters of the monitoring source data according to the business rule parameters includes:
acquiring the target service parameters in real time and storing the target service parameters into a distributed memory or a cache;
and gradually reading the target service parameters from the distributed memory or the cache according to the monitoring step length and judging whether the target service parameters meet the alarm condition.
3. The service data monitoring and early warning method according to claim 2, wherein the judging whether the target service parameter satisfies the warning condition comprises:
reading a plurality of parameter values of the target service parameter in a target time period from the distributed memory or the cache, wherein the target time period is a time period from the last reading time to the current reading time;
and judging whether the target service parameters meet the alarm conditions or not according to the plurality of parameter values.
4. The service data monitoring and early warning method according to claim 3, wherein the step of judging whether the target service parameter meets the warning condition according to the plurality of parameter values comprises the following steps:
obtaining the mean and variance of the plurality of parameter values;
selecting a target parameter value from the plurality of parameter values according to the mean and the variance of the plurality of parameter values;
and judging whether the target service parameters meet the alarm conditions or not according to the target parameter values.
5. The traffic data monitoring and early warning method according to claim 4, wherein selecting a target parameter value from the plurality of parameter values according to the mean and the variance of the plurality of parameter values comprises:
obtaining an upper limit value and a lower limit value according to the mean and the variance of the parameter values, wherein the upper limit value is proportional to the mean and proportional to the variance, and the lower limit value is proportional to the mean and inversely proportional to the variance;
acquiring the parameter value between the upper limit value and the lower limit value as the target parameter value.
6. The business data monitoring and early warning method of claim 2, wherein the business rule parameters further include a standard range and a number-of-standard warning value of the target business parameter, and the determining whether the target business parameter satisfies the warning condition comprises:
if the times that the target service parameter exceeds the standard range is larger than or equal to the alarm value of the standard times, judging that the target service parameter meets the alarm condition, otherwise, judging that the target service parameter does not meet the alarm condition.
7. The service data monitoring and early warning method according to claim 2, wherein the service rule parameters further include monitoring time periods, the number of the target service parameters is at least two, and monitoring the target service parameters of the monitoring source data according to the service rule parameters includes:
generating a monitoring task corresponding to each target service parameter;
acquiring the execution time scale of each monitoring task according to the monitoring time period and the monitoring step length of each monitoring task;
if the execution time scales of the monitoring tasks have conflicts, adjusting the monitoring starting time of one or more monitoring tasks to ensure that the execution time scales of the monitoring tasks have no conflicts;
and independently executing the monitoring tasks according to the execution time scales of the monitoring tasks to realize the monitoring of the target service parameters.
8. The utility model provides a business data control early warning device which characterized in that is applied to business data control early warning end, business data control early warning device includes:
the monitoring request receiving module is used for receiving a monitoring request sent by a service end, wherein the monitoring request is used for requesting a rule code to the service data monitoring early warning end, the types of the rule codes are multiple, and each rule code corresponds to a service rule parameter of one type of monitoring service;
a monitoring request response module, configured to send the rule code to the service end in response to the monitoring request, so that the service end configures a service rule parameter of the rule code according to monitoring source data and adds the configured rule code to the monitoring source data, where the monitoring source data includes service data;
the monitoring source data receiving module is used for receiving the monitoring source data sent by the service end, acquiring a rule code carried by the monitoring source data, and extracting a service rule parameter of the monitoring source data from the rule code;
and the monitoring and early warning module is used for monitoring the target service parameters of the monitoring source data according to the service rule parameters and generating warning information when the target service parameters meet warning conditions.
9. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program is executed by a processor to implement the service data monitoring and warning method of any one of claims 1 to 7.
10. An electronic device, characterized in that the electronic device comprises:
a memory storing a computer program;
a processor, communicatively coupled to the memory, for executing the method of monitoring and warning business data according to any one of claims 1 to 7 when the computer program is invoked.
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