Business health degree evaluation method and device, electronic equipment and program product

Abstract

The invention is suitable for the technical field of computers, and provides a business health degree evaluation method and device, electronic equipment and a program product. The business health degree assessment method comprises the steps of for a target business, obtaining a to-be-assessed business index; based on the service index, a decision flow is executed, a decision path of the decision flow comprises a plurality of decision nodes, and each decision node is used for determining a node state according to an index result of the service index when the decision flow is executed; and when an abnormal node exists in the decision path, determining that the target service is abnormal, and the abnormal node is a decision node of which the node state is an abnormal state. According to the embodiment of the invention, the business abnormity can be deeply evaluated, and an enterprise is helped to make an intelligent decision based on data.

Description

Technical Field

[0001] This application belongs to the field of computer technology, and particularly relates to a method, device, electronic device, and program product for evaluating service health. Background Art

[0002] In modern enterprise operations, business monitoring systems have become important tools for enterprise management and decision-making. However, the existing monitoring systems on the market mainly focus on the basic monitoring and alert functions of business activities, and it is difficult to deeply evaluate business anomalies and help enterprises make intelligent decisions based on data. Summary of the Invention

[0003] Embodiments of this application provide a method, device, electronic device, and program product for evaluating service health, which helps to deeply evaluate business anomalies and helps enterprises make intelligent decisions based on data.

[0004] In a first aspect of the embodiments of this application, a method for evaluating service health is provided, including: for a target service, obtaining service metrics to be evaluated; based on the service metrics, executing a decision flow, where multiple decision nodes are included on the decision path of the decision flow, and each of the decision nodes is used to determine the node state according to the metric results of the service metrics when the decision flow is executed; when there is an abnormal node in the decision path, it is confirmed that the target service has an anomaly, and the abnormal node is a decision node whose node state is an abnormal state.

[0005] In some embodiments of the first aspect, the executing a decision flow based on the service metrics includes: in response to a configuration operation of the user on the decision flow, determining service metrics associated with the decision variables of the decision nodes; binding service data to the decision variables to determine the metric results of the service metrics based on the service data; and determining the node state of the decision nodes according to the metric results.

[0006] In some embodiments of the first aspect, after determining the service metrics associated with the decision variables of the decision nodes, it further includes: validating the decision flow.

[0007] In some embodiments of the first aspect, the service metrics include basic metrics and derived metrics, and the determining the metric results of the service metrics based on the service data includes: determining the metric results of the basic metrics based on the service data; and determining the metric results of the derived metrics based on the metric results of the basic metrics.

[0008] In some embodiments of the first aspect, after confirming that the target service has an anomaly, it further includes: determining an error code bound to the abnormal node; and executing an exception handling operation associated with the operation code.

[0009] In some embodiments of the first aspect, the exception handling operation includes at least one of the following: isolating the business module of the target service; turning off the service switch of the target service; reducing the number of requests for the target service; and sending an exception alarm notification.

[0010] In some embodiments of the first aspect, when the exception handling operation is to isolate the business module of the target service, it further includes: re-determining the node status of the exception node; and when the node status of the exception node switches to the normal state, resuming the operation of the business module.

[0011] An apparatus for evaluating the service health provided in the second aspect of the embodiments of the present application includes: an acquisition unit configured to acquire service metrics to be evaluated for a target service; a decision flow execution unit configured to execute a decision flow based on the service metrics, where each decision node of the decision flow is configured to determine the node status according to the metric result of the service metrics; and an evaluation unit configured to confirm that the target service has an exception when there is an exception node in the decision flow, where the exception node is a decision node whose node status is the abnormal state.

[0012] The third aspect of the embodiments of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where when the processor executes the computer program, the steps of the above-mentioned method for evaluating service health are implemented.

[0013] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program, where when the computer program is executed by a processor, the steps of the above-mentioned method for evaluating service health are implemented.

[0014] The fifth aspect of the embodiments of the present application provides a computer program product, which when run, causes the above-mentioned method for evaluating service health to be executed.

[0015] In the embodiments of the present application, for a target service, by acquiring service metrics to be evaluated and executing a decision flow based on the service metrics, each decision node on the decision path determines the node status according to the metric result of the service metrics. When there is a decision node with an abnormal node status in the decision path, it is confirmed that the target service has an exception. Thus, the target service can be converted into quantifiable service metrics, and correlation analysis of multiple decision nodes can be performed through the decision flow, which helps to deeply evaluate service exceptions and helps enterprises make data-based intelligent decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for use in the embodiments or the description of the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0017] Figure 1 It is a schematic flowchart of the implementation of a method for evaluating the business health degree provided by an embodiment of the present application;

[0018] Figure 2 It is a schematic structural diagram of a business health degree evaluation system provided by an embodiment of the present application;

[0019] Figure 3 It is a schematic flowchart of the specific implementation for determining business indicators provided by an embodiment of the present application;

[0020] Figure 4 It is a schematic flowchart of the specific implementation for business indicator collection provided by an embodiment of the present application;

[0021] Figure 5 It is a schematic timing diagram of the evaluation of the business health degree provided by an embodiment of the present application;

[0022] Figure 6 It is a schematic structural diagram of an apparatus for evaluating a business health degree provided by an embodiment of the present application;

[0023] Figure 7 It is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0024] In order to make the objectives, technical solutions and advantages of the present application more clear, the following further details the present application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present application.

[0025] In modern enterprise operations, the business monitoring system has become an important tool for enterprise management and decision-making. However, the existing monitoring systems on the market mainly focus on the basic monitoring and warning functions of business activities, and it is difficult to deeply evaluate business anomalies and help enterprises make data-based intelligent decisions.

[0026] In view of this, the present application proposes a method for evaluating the business health degree, which can convert the target business into quantifiable business indicators and perform correlation analysis of multiple decision nodes through a decision flow, helping to deeply evaluate business anomalies and assisting enterprises in making data-based intelligent decisions.

[0027] To illustrate the technical solution of the present application, the following will be described by means of specific embodiments.

[0028] Figure 1 The figure shows a schematic implementation flow diagram of a method for evaluating the business health provided by an embodiment of the present application. This method can be applied to an electronic device. The above-mentioned electronic device can be an intelligent device such as a computer, a tablet computer, a mobile phone, etc., and the present application does not limit this.

[0029] Specifically, the above-mentioned method for evaluating the business health can include the following steps S101 to step S103.

[0030] Step S101: For the target business, obtain the business metrics to be evaluated.

[0031] Among them, the target business can be any business that needs to be evaluated for health. For the target business, the business metrics to be evaluated can be obtained. Such business metrics can characterize the execution situation of the target business. For example, the business metric can be the number of requests generated by the target business in the first preset time period, the number of failures occurred in the second preset time period, etc.

[0032] Step S102: Based on the business metrics, execute the decision flow.

[0033] In the embodiment of the present application, the decision flow can include one or more decision paths. There are multiple decision nodes on the decision path of the decision flow. Each decision node on the decision path is connected in sequence to form a decision path. During the execution of the decision flow, the calculation logics of each decision node can be run along the decision path. When the decision flow is executed, each decision node is used to determine the node state according to the metric result of the business metric.

[0034] Exemplarily, the decision node can be configured to determine whether the number of failures occurred in the second preset time period is greater than the number threshold. If so, it enters the abnormal state.

[0035] It should be noted that for the decision node located later in the decision path, when determining the node state, it can also refer to the decision nodes before it.

[0036] Step S103: When there is an abnormal node in the decision path, confirm that the target business is abnormal.

[0037] Among them, an abnormal node is a decision node with an abnormal node status. Specifically, the node status can at least include a normal status and an abnormal status. After the decision node performs corresponding logical calculations based on the index results of the service metrics, if the obtained result does not meet the corresponding index requirements, it can enter the abnormal status. If the obtained result can meet the corresponding index requirements, it can enter the normal status. Along the decision path, during the process of running the calculation logic of each decision node, if an abnormal node appears, it can be confirmed that there is an abnormality in the target service. If there are no abnormal nodes in each decision path, it can be confirmed that the target service is currently in a healthy state.

[0038] In an embodiment of the present application, for a target service, by obtaining service metrics to be evaluated and executing a decision flow based on the service metrics, each decision node on the decision path determines its node status according to the index results of the service metrics. When there is a decision node with an abnormal node status in the decision path, it is confirmed that there is an abnormality in the target service. Thus, the target service can be converted into quantifiable service metrics, and correlation analysis of multiple decision nodes can be performed through the decision flow, which helps to deeply evaluate service abnormalities and helps enterprises make data-based intelligent decisions.

[0039] Specifically, please refer to Figure 2 , Figure 2 which shows a schematic diagram of a service health assessment system provided by the present application. The service health assessment system may include a service metric module, a health decision module, and an exception handling strategy management module. Each of the above modules can interact with the database and simultaneously receive user operations from the Web page.

[0040] Among them, the service metric module is the basic part of the service health intelligent assessment management system, and is used to collect, calculate, and display key metrics reflecting the status, trend, and changes of the service system.

[0041] In some embodiments of the present application, for a target service, obtaining service metrics to be evaluated may include: in response to an index configuration operation triggered by a user on the Web page, determining the service metrics of the target service. Specifically, the user can flexibly define and modify service metrics through a custom metric definition language, so that the calculation engine parses these definitions and automatically generates corresponding calculation logics.

[0042] Among them, the calculation engine can perform real-time processing and analysis of service data based on the service data managed by each service metric to obtain index results. Among them, the calculation engine can be an engine such as Hdoop or MySql.

[0043] Such as Figure 3As shown, in some embodiments of the present application, the above business metrics may include basic metrics. The computing engine may obtain the metric results of the basic metrics based on business data by means of computing methods such as aggregation, filtering, grouping, and window operations. In some other embodiments of the present application, the above business metrics may further include derived metrics. The computing engine may determine the metric results of the derived metrics based on the metric results of the basic metrics. It can be understood that the derived metrics may also be specifically determined based on business data and / or the metric results of other derived metrics. Through in-memory computing and stream processing technologies, the computing engine can complete metric calculations within milliseconds, ensuring the real-time performance and efficiency of the system, generating multi-dimensional business metrics, and helping enterprises comprehensively understand the business status.

[0044] For the convenience of management, in some embodiments of the present application, the calculation process and metric results of the above business metrics can be displayed in real time on the metric management interface of the above Web page.

[0045] In some embodiments of the present application, business data may include data from different data sources. The computing engine may support distributed computing to process data from different data sources. Specifically, the business metric module may be configured with a unified data interface layer for enabling data from data sources such as DB and Hdoop to be processed and integrated using standardized data interfaces.

[0046] In some embodiments of the present application, the method for evaluating business health may further include: in response to the metric closing operation triggered by the user on the Web page, stopping the collection of the closed business metrics. Specifically, please refer to Figure 4 that the business metric module may periodically collect business metrics. After obtaining the business metrics configured by the user, based on the end time of the current collection in the current cycle, the start time of the next collection can be calculated, and when the start time of the next collection arrives, the business metric collection for the next cycle can be performed. When the start time of the next collection has not arrived, if the business metric is closed and at this time the business metric becomes invalid, a business metric collection order for the next cycle can be generated and the business metric collection order can be updated to the to-be-executed state. If the business metric is enabled, the business metric can be collected.

[0047] The health decision-making module is the core part of the business health evaluation system and is responsible for executing the decision flow to determine whether there are abnormalities in the business.

[0048] In some embodiments of the present application, executing the decision flow based on business metrics may include: in response to the user's configuration operation on the decision flow, determining the business metrics associated with the decision variables of the decision nodes; binding business data to the decision variables to determine the metric results of the business metrics based on the business data; and determining the node status of the decision nodes according to the metric results.

[0049] Specifically, in the above Web page, the Drools rule engine can be used to provide a graphical interface to realize the visual orchestration of the decision flow, for users to flexibly define and execute complex business logics. Users can easily create, modify, and manage decision nodes in the decision flow by dragging and arranging the graphics. In response to the user's configuration operation on the decision flow, the business metrics associated with the decision variables of the decision nodes can be determined. For example, any one of the business metrics determined in the foregoing step S101, or any one of the preset default metrics, can be used as the business metric associated with the decision variable.

[0050] Specifically, the health decision module can initialize the decision variables. Users can define decision variables in the rule file and bind business data to these decision variables through the working memory of the Drools engine, and then obtain the business metrics associated with the decision variables of the decision nodes.

[0051] At this time, the business metrics associated with the decision variables of the decision nodes can be collected in real time, and based on the business data, the metric results of the business metrics can be determined.

[0052] Specifically, as described above, determining the metric results of the business metrics based on the business data may include: determining the metric results of the basic metrics based on the business data, and determining the metric results of the derivative metrics based on the metric results of the basic metrics. Through the integration with the data source, the system can obtain the latest business data when the decision flow is executed, ensuring the real-time and accuracy of the decision.

[0053] In some embodiments of the present application, after determining the business metrics associated with the decision variables of the decision nodes, it further includes: validating the decision flow. Specifically, the above validation may refer to validating the parameters in the decision nodes. The above validation may also refer to pre-running the decision flow by using sample data as the business data to determine whether the pre-running result of the decision flow meets the expectations. The present application does not limit this.

[0054] In some embodiments of the present application, after confirming that the target business is abnormal, it may further include: determining the error code bound to the abnormal node; and executing the abnormal handling operation associated with the operation code.

[0055] During the execution of the decision flow, the health decision module can track and record the node status of each decision node. Each decision node will bind an error code. If the status of a certain decision node enters an abnormal state, the corresponding bound error code will be output. According to this error code, the execution result of the decision flow can be identified, and the corresponding abnormal handling operation can be executed. For the execution results of all decision flows, they can be periodically recorded in the database for subsequent backtracking and result query.

[0056] The exception handling strategy management module plays a key role in the business health assessment system. Its function implementation depends on the execution result of the decision flow, and it is used to take appropriate measures to ensure the stability and continuity of the business.

[0057] Specifically, the exception handling operations associated with the operation code may include at least one of the following:

[0058] 1. Isolate the business module of the target business. Specifically, if the exception handling operation associated with the operation code is to isolate the business module of the target business, it can be considered that a business interruption is required. The system automatically executes the interruption operation to isolate the affected business module and prevent the spread of exceptions.

[0059] 2. Turn off the business switch of the target business. When the system load is too high or some services are unavailable, some non-critical functions can be temporarily turned off to ensure the normal operation of the core functions, achieving degradation processing. Turning off the business switch supports flexible configuration.

[0060] 3. Reduce the number of requests for the target business. When the system load is too high or some services are unavailable, the business request volume can also be restricted to achieve degradation processing. Restricting the business request volume can be implemented based on Sentine, with default restriction configurations, or can be customized according to business interfaces.

[0061] 4. Perform exception alarm notifications. Specifically, it can automatically identify the exception events that need to be notified and real-time notify relevant business personnel through multiple channels (such as emails, text messages, instant messaging tools). The above channels can be configured according to the user's custom information to automatically generate and send notifications.

[0062] It can be understood that in other implementation manners, the user can also customize the exception handling scenario, and combined with the execution result of the decision flow, automatically select and execute the appropriate exception handling operation.

[0063] In some implementation manners of the present application, when the exception handling operation is to isolate the business module of the target business, it may further include: re-determining the node status of the exception node; when the node status of the exception node switches to the normal state, restoring the operation of the business module. Specifically, after isolating and interrupting the business module of the target business through the built-in automatic recovery mechanism, it monitors the changes in business data and business metrics in real-time, and then adjusts the node status of the exception node in real-time. When the node status of the exception node switches to the normal state, it restores the operation of the business module to ensure the rapid recovery of the business.

[0064] For ease of understanding, Figure 5The timing flowchart of the service health assessment method provided by this application is shown. The user configures service metrics through the Web interface of the user system, and the service health metric configuration service of the service metric module responds to the configuration operation to determine the service metrics. The service health metric configuration service can extract service data from the service system and call the calculation engine based on the service data to generate metric results. Correspondingly, the user can configure the decision flow through the Web interface. The service health analysis service of the health decision module responds to the user's configuration operation, executes the decision flow, determines the node status of each decision node through the calculation engine, and when there is an abnormal status, outputs an error code to the exception handling policy management module, and the service exception handling service of the exception handling policy management module generates a service exception order and stores it in the database. Subsequently, the service exception handling service can process the service exception order, call the processing engine to execute the exception handling operation associated with the operation code. For example, isolate the service module of the service system, or control the service module according to the user-defined exception handling scenario, or notify the service personnel.

[0065] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences.

[0066] As Figure 6 shown is the structural schematic diagram of an evaluation device 600 for service health provided by an embodiment of this application. The evaluation device 600 for service health is configured on an electronic device.

[0067] Specifically, the evaluation device 600 for service health may include:

[0068] An acquisition unit 601, configured to acquire service metrics to be evaluated for a target service;

[0069] A decision flow execution unit 602, configured to execute a decision flow based on the service metrics, and each decision node of the decision flow is used to determine the node status according to the metric result of the service metrics;

[0070] An evaluation unit 603, configured to confirm that the target service has an abnormality when there is an abnormal node in the decision flow, and the abnormal node is a decision node whose node status is an abnormal status.

[0071] In some embodiments of the present application, the decision flow execution unit 602 may specifically be configured to: in response to a user's configuration operation on the decision flow, determine business metrics associated with the decision variables of the decision node; bind business data to the decision variables to determine the metric results of the business metrics based on the business data; and determine the node status of the decision node according to the metric results.

[0072] In some embodiments of the present application, the decision flow execution unit 602 may specifically be configured to: verify the decision flow.

[0073] In some embodiments of the present application, the business metrics include basic metrics and derivative metrics, and the decision flow execution unit 602 may specifically be configured to: determine the metric results of the basic metrics based on the business data; and determine the metric results of the derivative metrics based on the metric results of the basic metrics.

[0074] In some embodiments of the present application, the evaluation device 600 for business health may further include an exception handling module, which is specifically configured to: determine the error code bound to the exception node; and execute the exception handling operation associated with the operation code.

[0075] In some embodiments of the present application, the exception handling module may specifically be configured to perform at least one of the following: isolate the business module of the target business; turn off the business switch of the target business; reduce the number of requests for the target business; and send an exception warning notification.

[0076] In some embodiments of the present application, the exception handling module may specifically be configured to: re-determine the node status of the exception node; and when the node status of the exception node switches to the normal state, resume the operation of the business module.

[0077] It should be noted that, for the sake of convenience and brevity of description, the specific working process of the above-mentioned evaluation device 600 for business health may refer to Figures 1 to 5 the corresponding process of the method, which will not be elaborated here.

[0078] As Figure 7 shown, it is a schematic diagram of an electronic device provided by an embodiment of the present application. Specifically, the electronic device 7 may include: a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and executable on the processor 70, such as an evaluation program for business health. When the processor 70 executes the computer program 72, the steps in the above-mentioned various embodiments of the evaluation method for business health are implemented, such as Figure 1 the steps S101 to S103 shown. Or, when the processor 70 executes the computer program 72, the functions of each module / unit in the above-mentioned various device embodiments are implemented, such asFigure 6 The functions of the acquisition unit 601, the decision flow execution unit 602, and the evaluation unit 603 shown.

[0079] The computer program can be divided into one or more modules / units, and the one or more modules / units are stored in the memory 71 and executed by the processor 70 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the electronic device.

[0080] For example, the computer program can be divided into: an acquisition unit, a decision flow execution unit, and an evaluation unit. The specific functions of each unit are as follows: The acquisition unit is used to acquire business metrics to be evaluated for a target business; the decision flow execution unit is used to execute a decision flow based on the business metrics, and each decision node of the decision flow is used to determine the node state according to the metric results of the business metrics; the evaluation unit is used to confirm that the target business has an anomaly when there is an abnormal node in the decision flow, and the abnormal node is a decision node whose node state is an abnormal state.

[0081] The electronic device may include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art can understand that Figure 7 These are only examples of the electronic device and do not constitute a limitation on the electronic device. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0082] The so-called processor 70 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0083] The memory 71 may be an internal storage unit of the electronic device, such as the hard disk or memory of the electronic device. The memory 71 may also be an external storage device of the electronic device, such as a plug-in hard disk equipped on the electronic device, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 71 may also include both the internal storage unit and the external storage device of the electronic device. The memory 71 is used to store the computer program and other programs and data required by the electronic device. The memory 71 may also be used to temporarily store the data that has been output or will be output.

[0084] It should be noted that for the convenience and brevity of description, the structure of the above electronic device may also refer to the specific description of the structure in the method embodiments, which will not be elaborated here.

[0085] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working processes of the units and modules in the above system can refer to the corresponding processes in the foregoing method embodiments, which will not be elaborated here.

[0086] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not elaborated or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0087] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0088] In the embodiments provided in the present application, it should be understood that the disclosed device / electronic device and method can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0089] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0090] In addition, each functional unit in the various embodiments of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0091] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present application, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0092] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for evaluating service health, characterized in that It includes: For a target service, obtain service metrics to be evaluated; Based on the service metrics, execute a decision flow. Multiple decision nodes are included on the decision path of the decision flow. When the decision flow is executed, each of the decision nodes is used to determine the node status according to the metric results of the service metrics; When there is an abnormal node in the decision path, confirm that there is an abnormality in the target service. The abnormal node is a decision node whose node status is in an abnormal state.

2. The method for evaluating business health according to claim 1, wherein: The executing the decision flow based on the service metrics includes: In response to a user's configuration operation on the decision flow, determine the service metrics associated with the decision variables of the decision node; Bind service data to the decision variables to determine the metric results of the service metrics based on the service data; According to the metric results, determine the node status of the decision node.

3. The method for evaluating the service health according to claim 2, wherein After determining the service metrics associated with the decision variables of the decision node, it further includes: Verify the decision flow.

4. The method for evaluating the service health as claimed in claim 2, wherein The service metrics include basic metrics and derivative metrics. The determining the metric results of the service metrics based on the service data includes: Based on the service data, determine the metric results of the basic metrics; Based on the metric results of the basic metrics, determine the metric results of the derivative metrics.

5. The method for evaluating the service health as described in claim 1, wherein After confirming that there is an abnormality in the target service, it further includes: Determine the error code bound to the abnormal node; Execute the exception handling operation associated with the operation code.

6. The method for evaluating the service health as described in claim 5, wherein, The exception handling operation includes at least one of the following: Isolate the service module of the target service; Turn off the service switch of the target service; Reduce the number of requests for the target service; Send an exception alarm notification.

7. The evaluation method for service health as described in claim 6, characterized in that, In the case where the exception handling operation is to isolate the service module of the target service, it further includes: Redetermine the node status of the abnormal node; When the node status of the abnormal node switches to the normal state, resume the operation of the service module.

8. An evaluation device for service health, characterized in that It includes: An acquisition unit for obtaining service metrics to be evaluated for a target service; A decision flow execution unit for executing a decision flow based on the service metrics. Each decision node of the decision flow is used to determine the node status according to the metric results of the service metrics; An evaluation unit for confirming that there is an abnormality in the target service when there is an abnormal node in the decision flow. The abnormal node is a decision node whose node status is in an abnormal state.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the service health evaluation method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, It includes a computer program. When the computer program is run, the service health evaluation method according to any one of claims 1 to 7 is executed.

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