System and method for dynamically identifying value of monitoring index and electronic equipment

Abstract

The invention provides a system and method for dynamically identifying the value of a monitoring index and electronic equipment. The system obtains the monitoring index of each monitoring task in a monitoring system, calculates the value score of each monitoring index according to a preset monitoring index value scoring rule, and performs task adjustment on the monitoring task based on the calculated value score. Since the preset monitoring index value scoring rule is obtained according to the setting of the time attenuation coefficient of the monitoring index, the value score of the monitoring index and the time attenuation coefficient of the monitoring index are in a negative correlation relationship, and the time attenuation coefficient represents the effective duration of the monitoring index, if the effective duration of a certain monitoring index is longer, the value score of the monitoring index is higher. The value of the corresponding monitoring index is lower. By selecting the embodiment of the invention, the monitoring index of the monitoring task can be automatically obtained and the monitoring task can be adaptively adjusted, so that the effects of dynamically identifying the value of the monitoring index, adaptively controlling the computing resource occupied by the monitoring system and saving the computing resource consumed by the monitoring system are realized.

Description

Technical Field

[0001] The present application relates to the field of system operation and maintenance technology, and in particular to a system, method and electronic device for dynamically identifying the value of monitoring indicators. Background Art

[0002] In the field of Internet technology, various enterprises or institutions provide Internet services to the public by operating software systems developed by themselves (hereinafter referred to as production systems). Among them, various software systems mostly use distributed systems (hereinafter referred to as monitoring systems) for operation and maintenance management, and usually require a powerful distributed monitoring system to monitor the performance of the production system. With the increase in the types and number of services provided by the production system, the performance indicators that need to be monitored by the monitoring system will also increase, and the frequency and timeliness of collection will also be higher and higher.

[0003] Existing mainstream monitoring systems often use regular expressions to match logs and generate corresponding monitoring indicator data based on the extraction of specified tags. This means that the more complex the regular expression and the larger the number of logs, the greater the consumption of corresponding computing resources. Once the production system and the operation and maintenance systems around the production system are repeatedly iterated, the consumption of computing resources will gradually worsen. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a system, method and electronic device for dynamically identifying the value of monitoring indicators, so as to dynamically identify the value of monitoring indicators and save computing resources consumed by the monitoring system.

[0005] In a first aspect, an embodiment of the present application provides a system for dynamically identifying the value of a monitoring indicator, wherein the system includes:

[0006] The monitoring server is used to obtain the monitoring indicators of each monitoring task in the monitoring system;

[0007] An indicator value analysis module, used to obtain each of the monitoring indicators from the monitoring service end, and calculate the value score of each of the monitoring indicators according to a preset monitoring indicator value scoring rule; wherein the preset monitoring indicator value scoring rule is set according to the time decay coefficient of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator;

[0008] The monitoring collection module is used to adjust each monitoring task based on the value score of each monitoring indicator.

[0009] In some possible embodiments, the indicator value analysis module is further used to:

[0010] According to the value points of each monitoring indicator, each monitoring indicator is graded to obtain different adjustment priorities;

[0011] The monitoring collection module is also used to adjust each of the monitoring tasks according to each of the adjustment priorities.

[0012] In some possible embodiments, the monitoring indicators are divided into: core alarm indicators, fault location indicators, risk inspection indicators, and undefined indicators according to their application scenarios. The application scenarios to which each monitoring indicator belongs are not unique. The indicator value analysis module is also used to:

[0013] Determine the digital level of each monitoring indicator according to the application scenario to which each monitoring indicator belongs;

[0014] Based on the digital level score of each monitoring indicator, combined with the time decay coefficient of each monitoring indicator and the request frequency of each monitoring indicator, a weighted sum is performed to obtain the value score of each monitoring indicator.

[0015] In some possible embodiments, the digital level score based on each of the monitoring indicators is combined with the time decay coefficient of each of the monitoring indicators and the request frequency of each of the monitoring indicators for weighted summation to obtain the value score of each of the monitoring indicators, including:

[0016] The value score is calculated based on the following formula:

[0017]

[0018] Where Level is the digital level of the monitoring indicator, f qt [i] is the request frequency of the monitoring indicator in the i-th time interval, n is the total number of time intervals, and w(i) is the time attenuation coefficient of the monitoring indicator in the i-th time interval.

[0019] In some possible embodiments, the time attenuation coefficient is calculated by the following formula:

[0020]

[0021] Wherein, w(i) is the time attenuation coefficient of the monitoring indicator in the i-th time interval, and n is the total number of time intervals.

[0022] In some possible embodiments, the monitoring collection module is further used to:

[0023] Receive the manual labeling information of the target monitoring indicator transmitted by the user interaction interface, and adjust the target monitoring task in combination with the value score of the target monitoring indicator.

[0024] In a second aspect, an embodiment of the present application provides a method for dynamically identifying the value of a monitoring indicator, wherein the method is applied to the system for dynamically identifying the value of a monitoring indicator as described in the first aspect, wherein the method includes:

[0025] Obtain monitoring indicators of each monitoring task in the monitoring system;

[0026] According to the preset monitoring indicator value scoring rules, the value score of each monitoring indicator is calculated; wherein the preset monitoring indicator value scoring rules are set according to the time decay coefficient of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator;

[0027] Based on the value points of each monitoring indicator, each monitoring task is adjusted.

[0028] In a third aspect, an embodiment of the present application provides an electronic device, wherein the electronic device includes:

[0029] Processor; and

[0030] Memory for storing programs,

[0031] Wherein, the program includes instructions, and when the instructions are executed by the processor, the processor executes the method for dynamically identifying the value of monitoring indicators described in the second aspect.

[0032] In a fourth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium storing computer instructions, characterized in that the computer instructions are used to enable a computer to execute the method for dynamically identifying the value of monitoring indicators described in the second aspect.

[0033] Beneficial effects of this application:

[0034] The present application provides a system, method and electronic device for dynamically identifying the value of monitoring indicators, wherein the system obtains the monitoring indicators of each monitoring task in the monitoring system, and then calculates the value score of each monitoring indicator according to the preset monitoring indicator value scoring rule, and adjusts the monitoring task based on the calculated value score. Among them, since the preset monitoring indicator value scoring rule is obtained according to the time decay coefficient setting of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator. In this way, the longer the effective time of a certain monitoring indicator, the lower the value of the corresponding monitoring indicator. By selecting the embodiment of the present application, the monitoring indicators of the monitoring task can be automatically obtained and the monitoring task can be adaptively adjusted, thereby realizing the effect of dynamically identifying the value of the monitoring indicator, adaptively controlling the computing resources occupied by the monitoring system, and saving the computing resources consumed by the monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0036] Figure 1 A schematic diagram showing a logical structure of a system for dynamically identifying the value of monitoring indicators provided by an embodiment of the present application is shown;

[0037] Figure 2 Another logical structure diagram of the system for dynamically identifying the value of monitoring indicators provided by an embodiment of the present application is shown;

[0038] Figure 3 A schematic diagram of digital level division provided by an embodiment of the present application is shown;

[0039] Figure 4 A schematic diagram of a process of dynamically identifying the value of monitoring indicators provided by an embodiment of the present application is shown;

[0040] Figure 5 A structural block diagram of an exemplary electronic device that can be used to implement an embodiment of the present application is shown. DETAILED DESCRIPTION

[0041] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0042] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0043] The term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0044] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0045] As described in the background technology, the current mainstream monitoring system matches logs through regular expressions. The more complex the regular expression and the larger the number of logs, the more computing resources the monitoring system consumes. In actual production practice, the resource overhead generated by the monitoring system is several times the resource overhead occupied by the business logic processing in the production system. With the repeated iterations of the production system and the surrounding operation and maintenance systems, the resource consumption will gradually worsen, resulting in necessary waste of resources and additional economic costs. In the case where the computing resources consumed by the monitoring system are greater than those consumed by the production system, the existing processing methods usually include the following steps:

[0046] 1. Statistically analyze all program systems with large monitoring resource overhead.

[0047] 2. For a program system with high overhead, list all monitoring tasks in the program system with high overhead, analyze the content of the monitoring tasks, and screen out monitoring tasks with potential high resource overhead.

[0048] 3. Conduct a necessity analysis on the monitoring tasks corresponding to the roles of various parties in the production system and clear unnecessary monitoring tasks. For example, conduct a necessity analysis on the monitoring tasks in R&D, testing, operation and maintenance, etc.

[0049] 4. For monitoring tasks that cannot be cleaned up, analyze whether there are commonalities with other monitoring tasks. If so, merge the monitoring tasks.

[0050] The above steps usually rely on manual analysis and optimization, which consumes high manpower costs, and the number of monitoring tasks that need to be analyzed is large. After a period of time, the analysis and optimization need to be repeated. For some monitoring tasks, due to the limitations of manual technical level and the complexity of actual scenarios, the optimization effect of monitoring tasks is poor.

[0051] In view of this, the present application provides a system, method and electronic device for dynamically identifying the value of monitoring indicators, wherein the system dynamically evaluates the value of monitoring indicators of monitoring tasks, and optimizes the monitoring tasks according to the dynamic value evaluation results, thereby reducing the consumption of computing resources by low-value monitoring tasks, so as to achieve the effect of saving computing resources consumed by monitoring tasks in the monitoring system. In the first aspect, the present application provides a system for dynamically identifying the value of monitoring indicators, such as Figure 1 As shown, the system includes: monitoring server, indicator value analysis module, monitoring collection module. Among them:

[0052] The monitoring server is used to obtain the monitoring indicators of each monitoring task in the monitoring system;

[0053] An indicator value analysis module, used to obtain each of the monitoring indicators from the monitoring service end, and calculate the value score of each of the monitoring indicators according to a preset monitoring indicator value scoring rule; wherein the preset monitoring indicator value scoring rule is set according to the time decay coefficient of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator;

[0054] The monitoring collection module is used to adjust each monitoring task based on the value score of each monitoring indicator.

[0055] In an embodiment of the present application, the system obtains the monitoring indicators of each monitoring task in the monitoring system, and then calculates the value score of each monitoring indicator according to the preset monitoring indicator value scoring rule, and adjusts the monitoring task based on the calculated value score. Among them, since the preset monitoring indicator value scoring rule is set according to the time decay coefficient of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator. In this way, the longer the effective time of a certain monitoring indicator, the lower the value of the corresponding monitoring indicator.

[0056] By selecting the embodiment of the present application, it is possible to automatically obtain the monitoring indicators of the monitoring tasks and adaptively adjust the monitoring tasks, thereby dynamically identifying the value of the monitoring indicators, adaptively controlling the computing resources occupied by the monitoring system, and saving the computing resources consumed by the monitoring system.

[0057] The following will explain in detail the above system for dynamically identifying the value of monitoring indicators with specific examples:

[0058] In the embodiments of the present application, the monitoring system refers to a software system developed and maintained by an enterprise or organization for the production system to ensure the normal operation of the production system. The core is to use the monitoring system to monitor the operating status of the production system. As an implementation method, the monitoring system is a software system independent of the production system. As another implementation method, the monitoring system can be a subsystem in the production system. The subsystem is isolated from other functional subsystems in the production system and interacts only through a set API.

[0059] In the embodiment of the present application, the monitoring system uses the monitoring task as the operation unit to monitor the operation status of the production system. For example, the developer or operation and maintenance personnel need to monitor the performance of the physical device responsible for the payment function in the production system. At this time, the developer or operation and maintenance personnel can input or write an operation condition of a monitoring task in the monitoring system, and specify the physical device object to be monitored, the required monitoring duration, and the performance indicators to be monitored for the physical device object, etc. After the monitoring system runs the monitoring task, it can automatically obtain the specific operation performance indicators of the physical device within the corresponding monitoring duration.

[0060] As an implementation method, the monitoring task can be a monitoring script or a monitoring thread. The specific form can be flexibly designed by developers or operation and maintenance personnel according to actual needs. However, regardless of the type of monitoring task, the monitoring system is required to provide various resources required for the operation of the monitoring task, such as computing resources, storage resources, and data interface resources. Among them, computing resources are specifically reflected in CPU processing resources, storage resources are reflected in memory resources and disk resources, and data interface resources are reflected in data IO throughput. Based on this, as an implementation method, the monitoring index of the monitoring task can refer to the resources occupied by the monitoring task, specifically, the number of CPU cores, memory size, and IO size occupied by the monitoring task.

[0061] As another implementation method, the monitoring indicators of the monitoring task can be set according to the specific application scenario. Specifically, the monitoring indicators are divided into core alarm indicators, fault location indicators, risk inspection indicators, and undefined indicators according to the application scenarios to which they belong.

[0062] Among them, the core alarm indicators refer to the most critical indicators to ensure the normal use of the production system. Once the core alarm indicators are warned, it means that the production system cannot work normally. The identification of such core alarm indicators is usually carried out by using the alarm strategy in the monitoring system. If an indicator of a monitoring task in the monitoring system is marked as "serious" or "important", it means that the monitoring indicator corresponding to the monitoring task belongs to the core alarm indicator. In an embodiment of the present application, the core alarm indicators can be further subdivided into four categories according to the severity of the alarm from high to low: serious core alarm indicators, important core alarm indicators, warning core alarm indicators, and notification alarm indicators.

[0063] For example, the payment function module in the production system is extremely important, and device cluster A is responsible for supporting the normal operation of the payment function module. The monitoring system issues monitoring task A to monitor the operation status of device cluster A. During the process, monitoring indicator a is the number of processing cores of monitoring device cluster A, monitoring indicator b is the number of remaining memory of monitoring device cluster A, and monitoring indicator c is the number of IO of monitoring device cluster A. Before starting the monitoring, if the operation and maintenance personnel or developers believe that monitoring indicator a is extremely important, that is, the number of processing cores of device cluster A must be guaranteed to be within a safe range, once it exceeds the safe range, it will directly affect the normal operation of the payment function. At this time, the operation and maintenance personnel or developers can set a label for monitoring indicator a: "Serious". At this time, monitoring indicator a is a core alarm indicator, and it is a serious-level core alarm indicator.

[0064] In the embodiment of the present application, the fault location indicator refers to the fact that after a fault occurs during the business operation of the production system, the monitoring system can automatically analyze the specific cause of the fault through such fault location indicators. Among them, the possible application scenarios of the fault location indicator are as follows:

[0065] Scenario 1: A monitoring indicator dashboard that has been configured in advance summarizes the fault types corresponding to various fault location indicators. If a fault occurs, relevant personnel can browse the monitoring indicator dashboard as needed to obtain the required location information.

[0066] Scenario 2: The intelligent fault location system automatically retrieves the monitoring indicators required for query based on human experience, fault location rule algorithms, and other models, and gives the fault cause analysis results based on the monitoring indicators. In other words, the monitoring indicators called by the intelligent fault location system can be classified as fault location indicators.

[0067] As an example, the monitoring indicator c in the payment function module in the aforementioned production system is also used to monitor the IO quantity in the equipment cluster A. However, the monitoring indicator c is predefined that when the IO quantity is greater than the preset IO quantity threshold, the monitoring system will output a warning signal corresponding to the monitoring indicator c and the specific reason for the monitoring indicator c. The monitoring system can automatically analyze and obtain the problem of insufficient IO in the payment function module, and IO expansion is required.

[0068] Risk inspection indicators are used for daily fault risk inspections to detect potential fault hazards and management omissions in advance. The usage scenarios of such indicators can also be divided into manual scenarios and automated scenarios. Among them, for manual scenarios, people browse the special inspection indicator dashboard every day, find abnormal information from the inspection indicator dashboard, and arrange corresponding work orders for repair and processing. For automated scenarios, an automatic inspection system can be established with the help of personnel experience and inspection rule algorithms. The automatic inspection system automatically retrieves the required monitoring indicators, automatically generates work orders, and assigns corresponding personnel to handle them.

[0069] Undefined indicators refer to other monitoring indicators of the monitoring task that do not belong to the above-mentioned core alarm indicators, fault location indicators, and risk inspection indicators.

[0070] In the embodiment of the present application, the application scenarios to which the monitoring indicators belong may overlap. In other words, the application scenarios to which the monitoring indicators belong are not unique. As an implementation method, the monitoring server can obtain the monitoring indicators of each monitoring task through the corresponding monitoring indicator interface under different application scenarios. Figure 2 As shown, the monitoring server can be the server of an existing monitoring system, which is responsible for implementing various requirements of routine monitoring, including but not limited to monitoring data display, anomaly detection and inspection analysis. Among them, anomaly detection includes indicator anomaly detection and alarm, and inspection analysis includes daily inspection analysis and directional inspection analysis. In an embodiment of the present application, the monitoring server needs to organize and output the actual operating conditions of the various monitoring indicators obtained to the indicator value analysis module, and the indicator value analysis module performs indicator value analysis based on the actual operating conditions of the various monitoring indicators received.

[0071] In the embodiment of the present application, the indicator value analysis module is a key module in the system for dynamically identifying the value of monitoring indicators provided in the embodiment of the present application. It mainly obtains the usage of various monitoring indicators in actual scenarios from the monitoring service end, and analyzes the monitoring indicators according to preset rules. Specifically, the indicator value analysis module is used to calculate the value points of each monitoring indicator according to the preset monitoring indicator scoring rules. Among them, the preset monitoring indicator value scoring rules are set according to the time decay coefficient of the monitoring indicator, and the value points of the monitoring indicator are negatively correlated with the time decay coefficient of the monitoring indicator. The time decay coefficient represents the effective duration of the monitoring indicator. In other words, in the embodiment of the present application, the shorter the effective duration of the monitoring indicator, the higher its value score.

[0072] As an implementation method, the indicator value analysis module is specifically used to:

[0073] Determine the digital level of each monitoring indicator according to the application scenario to which each monitoring indicator belongs;

[0074] Based on the digital level score of each monitoring indicator, combined with the time decay coefficient of each monitoring indicator and the request frequency of each monitoring indicator, a weighted sum is performed to obtain the value score of each monitoring indicator.

[0075] Among them, according to the application scenario to which the monitoring indicator belongs, the digital level of each monitoring indicator is determined. It can be understood that after the monitoring indicators of the monitoring task are divided according to the application scenario, they are further subdivided on the application scenario, and different application scenario levels are divided for each application scenario to realize the digital processing of the application scenario, and a number is obtained, and the number is used to represent different application scenarios. In other words, the digital level is used to distinguish the application scenarios to which the monitoring indicators belong, and different numbers represent different application scenarios.

[0076] Specifically, taking the above four application scenarios as an example, the application indicators can be digitized into: Level 1 - core alarm indicators; Level 2 - fault location indicators; Level 3 - risk inspection indicators; Level 4 - undefined indicators. Different numbers represent the level of monitoring indicators in the corresponding application scenarios. Then, when subdivided again, each level can be mapped to a binary bit, as shown in the following example. Figure 3As shown, the number mapped to the core alarm indicator of level 1 is 8, the number mapped to the fault location indicator of level 2 is 4, and so on, the corresponding digital values ​​of levels 1-4 are 8, 4, 2, and 1 respectively. In actual application, monitoring indicators may belong to multiple levels at the same time. For example, a monitoring indicator may belong to both core alarm indicators, fault location indicators, and risk inspection indicators. At this time, when the indicator value analysis module determines the numerical level of each monitoring indicator according to the application scenario to which each monitoring indicator belongs, it can calculate the superimposed values ​​under each application scenario according to all application scenarios to which each monitoring indicator belongs, and determine the superimposed values ​​as the digital level of the monitoring indicator.

[0077] For example, Figure 3 According to the division method shown, if a monitoring indicator belongs to both the core alarm indicator, the fault location indicator, and the risk inspection indicator, the digital level of the monitoring indicator is divided into: 8+4+2=14 by superimposing the numerical values. If a monitoring indicator belongs to both the core alarm indicator and the fault location indicator, the digital level of the monitoring indicator is divided into: 8+4=12.

[0078] Based on the digital level score of the monitoring indicator calculated in this way, the indicator value analysis module combines the time decay coefficient of each monitoring indicator and the request frequency of each monitoring indicator to perform weighted summation to obtain the value score of each monitoring indicator. Specifically, the value score of each monitoring indicator can be calculated based on the following formula:

[0079]

[0080] Where Level is the digital level of the monitoring indicator, f qt [i] is the request frequency of the monitoring indicator in the i-th time interval, n is the total number of time intervals, and w(i) is the time attenuation coefficient of the monitoring indicator in the i-th time interval. In the embodiment of the present application, the total number of time intervals constitutes the monitoring cycle of the monitoring indicator. For example, if the monitoring cycle is 3 days, the monitoring indicator is monitored as 1 hour as a time interval. In this case, n is 72.

[0081] In an embodiment of the present application, the closer the monitoring indicator is to the current moment, the more valuable the information it can express is. Therefore, in an embodiment of the present application, the value of the monitoring indicator in each time interval can be controlled by introducing a time decay coefficient. The time decay coefficient is essentially a weight coefficient. The weight coefficients of different time intervals are different, but the closer to the current moment, the greater the weight. The weight coefficient calculation formula corresponding to the time decay coefficient can be selected as needed, such as a linear formula, an exponential formula, etc. As an implementation method, the time decay coefficient is calculated by the following formula:

[0082]

[0083] In the embodiment of the present application, the time interval is each sub-range in the set time range, and the time range occupied by the specific time interval can be flexibly set according to actual needs. For example, for example, 72 hours are traced back to the current time, where each time interval can be 1 hour or 2 hours. If each time interval is 1 hour, the i-th time interval refers to the i-th hour in the 72 hours traced back to the current time.

[0084] For example, if i is 1, it means going back one hour. In the embodiment of the present application, the request frequency of the monitoring indicator in the i-th time interval can be obtained by reading the execution log record of the monitoring task by the monitoring server. As an example, the request frequency of the monitoring indicator obtained from the log record can be processed in the form of an array, such as the request frequency f qt [i] = f qt [20,25,17,···],f qt [1] = 20, which means the request frequency for monitoring indicators within one hour from now is 20 times per hour.

[0085] In the embodiment of the present application, the total number of time intervals n is equivalent to the total time range. For example, if the time interval is 1 hour, the value of n is 72. Based on this, the time decay coefficient w(i) is calculated by the above linear formula to obtain: The time decay coefficient at the current moment is: The time decay coefficient for the first hour is: By analogy, the time attenuation coefficient of each monitoring indicator within each hour of the 72-hour monitoring period can be calculated.

[0086] Based on the known digitization level, time attenuation coefficient, and request frequency of the monitoring indicator in the i-th time interval, the above can be used: Formula to calculate the value score of each monitoring indicator. For example, if the digital level of monitoring indicator d is 8, and the request frequency in the last 72 hours is: 20, 25, 17,..., the weights obtained based on the calculation are 1, 0.986,..., according to The formula calculated gives the value score S of the monitoring indicator d = 8×20×1+8×25×0.986+···.

[0087] Based on the value score of the monitoring indicator calculated in this way, the indicator value analysis module is used to classify each monitoring indicator according to its value score to obtain different adjustment priorities; the monitoring acquisition module is also used to adjust each monitoring task according to each adjustment priority. As an implementation method, the indicator value analysis module is specifically used to sort the value score results of each monitoring indicator, divide the value interval, and then fine-tune the time interval, time attenuation coefficient formula, value score calculation formula, etc. according to the sorting results, so as to obtain the expected value scoring results in combination with the actual situation.

[0088] Based on this, in some embodiments, the indicator value analysis module is also used to: grade each of the monitoring indicators according to the value points of each of the monitoring indicators to obtain different adjustment priorities; the monitoring acquisition module is also used to adjust each of the monitoring tasks according to the adjustment priorities.

[0089] As an example, the indicator value analysis module performs value grading on the sorted value points, wherein the specific value grading method can be set as needed, for example: 10,000 points or more are high-value indicators, 5,000-10,000 points are medium-value indicators, and 1,000-5,000 points are low-value indicators. The monitoring and acquisition module adjusts the monitoring tasks according to different adjustment priorities. For example, it gives priority to the operation requirements of high-value indicators, and can appropriately reduce the operation resources of medium-value indicators, and stop the operation of some low-value indicators.

[0090] In some application scenarios, some monitoring indicators need to be paid special attention to, or some special monitoring indicators cannot match the monitoring system, resulting in mismatch of monitoring indicator value. In view of this situation, as an implementation method, the monitoring acquisition module is also used to:

[0091] Receive the manual labeling information of the target monitoring indicator transmitted by the user interaction interface, and adjust the target monitoring task in combination with the value score of the target monitoring indicator.

[0092] Among them, the target monitoring indicators specifically refer to monitoring indicators that need to be focused on, or that are prone to mismatching of the monitoring system. Users can check and input the target monitoring indicators that need to be focused on on the user interaction interface, and add manual annotation information for the target monitoring indicators. The manual annotation information is used to distinguish the target monitoring indicators from other monitoring indicators. The monitoring and acquisition module receives the manual annotation information of the target monitoring indicators transmitted by the user interaction interface through the monitoring server, and then adjusts the target monitoring task in combination with the value score of the target monitoring indicators calculated by the indicator value analysis module. Exemplarily, for example, for a monitoring indicator e that belongs to the medium value, the user can set the manual annotation information of the monitoring indicator e on the user interaction interface. When the monitoring and acquisition module adjusts the monitoring task corresponding to the monitoring indicator e, it needs to give priority to ensuring the operating requirements of the monitoring indicator e.

[0093] In an embodiment of the present application, the monitoring and acquisition module adjusts the monitoring tasks, and the core is that the monitoring and acquisition module executes the corresponding monitoring tasks according to the resources corresponding to the adjustment priority to which the value score belongs. Among them, in order to control the consumption of resources by low-value monitoring tasks or monitoring indicators and achieve the effect of controlling resource costs, specifically, the monitoring and acquisition module is used to reduce the resources allocated to the monitoring tasks below the preset value score threshold if the value score of the monitoring indicator is lower than the preset value score threshold. As an implementation method, it can be divided into three priority levels of monitoring indicators according to the value score as described above: high-value monitoring indicators, medium-value monitoring indicators, and low-value monitoring indicators. Among them, the monitoring and acquisition module uses three adjustment strategies to adjust the monitoring indicators of monitoring tasks with different adjustment priorities: resource adjustment strategy, notification strategy, and result collection and display strategy.

[0094] Among them, the resource adjustment strategy specifically refers to the computing resources, processing resources, and memory resources used by the monitoring collection module to collect monitoring indicators. The notification strategy specifically refers to the notification method used by the system provided by this application to notify users, developers, or operation and maintenance personnel. The result collection and display strategy specifically refers to how the system provided by this application summarizes and organizes information after receiving various optimized monitoring indicators, and how to display the summarized and organized information to users, developers, or operation and maintenance personnel.

[0095] As an implementation method, for the resource adjustment strategy, the monitoring collection module makes differentiated adjustments to the monitoring indicators of the above three priorities in the following ways:

[0096] For high-value monitoring indicators, the best effort resource guarantee strategy is adopted for adjustment. Among them, the best effort resource guarantee strategy does not impose any restrictions on operating resources and collects monitoring data according to the best monitoring effect.

[0097] A limited resource guarantee strategy is adopted to adjust the monitoring indicators with medium value, wherein the limited resource guarantee strategy sets expected resource expenditure. When the monitoring collection module collects indicators, it collects monitoring indicators according to the expected resource expenditure.

[0098] For low-value monitoring indicators, the minimum resource overhead strategy is adopted for adjustment. The minimum resource overhead means that the resource overhead used for the monitoring task is minimized. The monitoring and acquisition module collects monitoring indicators according to the minimized resource overhead regulations, thereby saving the processing resources of the monitoring and acquisition module as much as possible.

[0099] As an implementation method, for the notification strategy, after the monitoring and acquisition module adjusts the monitoring task according to different adjustment priorities, if the resources of the monitoring and acquisition module occupied by the monitoring task still cannot meet expectations, notification information is pushed according to different adjustment priorities so that users, developers or operation and maintenance personnel can further adjust the monitoring task.

[0100] As an implementation method, for the result collection and display strategy, after the monitoring collection module adjusts the collection resources for the monitoring tasks corresponding to different adjustment priorities, it summarizes the entire resource adjustment strategy adopted and the actual resource expenditure of each monitoring task, and reports it to the user interaction interface for display. After the indicator value analysis module collects statistics on the monitoring indicators and resource expenditures of different value points, it displays them through the user interaction interface to provide data reference for managers to adjust the monitoring tasks in the next step.

[0101] In the embodiment of the present application, the monitoring collection module optimizes and adjusts the monitoring task in the following manner:

[0102] The monitoring and collection module periodically obtains the monitoring indicator optimization strategy from the indicator value analysis module. The monitoring indicator optimization strategy is one or more of the above resource adjustment strategy, notification strategy, result collection and display strategy. Then, the resources required for the corresponding monitoring indicator collection task are adjusted according to the monitoring indicator optimization strategy, thereby optimizing resource overhead.

[0103] As an implementation method, when the monitoring collection module executes the above resource adjustment strategy: adopting the limited resource guarantee strategy for medium-value monitoring indicators and the minimum resource expenditure strategy for low-value monitoring indicators, the specific process is as follows:

[0104] For medium-value monitoring indicators: taking into account both the collection effect and saving the resources occupied by the monitoring collection module, this can be achieved through the following adoption mode, cycle reduction mode, and idle resource utilization mode:

[0105] Sampling mode: The generation of monitoring indicators is usually related to the amount of data generated in the actual environment. For example, in log monitoring, if the regular expression of log monitoring is fixed, but the more matching logs, the more computing resources the log monitoring indicator consumes. At this time, random sampling can be used for monitoring. For general indicator monitoring scenarios, sampling monitoring may reduce the accuracy of collection to a certain extent, but for fault scenarios, it usually does not affect the discovery and identification of faults. In this mode, users, developers or operation and maintenance personnel are required to pre-set a minimum acceptable sampling ratio range, such as a 5% sampling ratio. Then, when the monitoring indicator is executed for monitoring the production system, it will be dynamically adjusted between 5% and 100% to control resource overhead.

[0106] Cycle reduction mode: The generation of some monitoring indicators is related to the execution frequency of the monitoring tasks corresponding to the monitoring indicators. For such scenarios, the monitoring indicator producer is modified to support dynamic frequency adjustment. The user, developer or operation and maintenance personnel set the acceptable execution frequency range, and the monitoring indicator producer dynamically adjusts the frequency of its own production monitoring indicators when producing monitoring indicators, thereby achieving the purpose of resource conservation.

[0107] Idle resource utilization mode: Sometimes there are idle resources in the production environment of the online production system, and it is no longer necessary to compress the monitoring resources. In this mode, the idle resource utilization mode is enabled, and sampling and cycle reduction are no longer performed, and the collection of such indicators is upgraded to the best effort guarantee strategy.

[0108] Among them, when the monitoring and collection module takes the minimum resource expenditure strategy for low-value monitoring indicators, it can refer to the several working modes adopted for medium-value monitoring indicators. However, in terms of specifying parameters, users, developers or operation and maintenance personnel can specify the maximum sampling ratio and production frequency. When the monitoring and collection module collects monitoring indicators, it works under the specified parameters. When the overall resource expenditure is too large, it can temporarily suspend the collection of low-value monitoring indicators to protect resources.

[0109] In addition, the monitoring and acquisition module can regularly obtain the adjustment priority and corresponding strategy of the monitoring indicator from the indicator value analysis module, and compare them with the currently executed strategy. If it is found that the adjustment priority and parameters corresponding to the monitoring indicator have changed, it can be adjusted and updated in time. Moreover, for the situation where expected resources are set, the resources can be dynamically adjusted through the self-feedback mechanism. If the monitoring and acquisition module starts to collect monitoring indicators, the self-feedback mechanism will be in a cycle of: resource collection, strategy adjustment, resource collection, strategy adjustment...

[0110] Specifically, resource collection includes: collecting the remaining resources of the server where the service is located, and collecting the resource consumption of each priority-adjusted monitoring indicator.

[0111] The remaining resources of the server where the collection service is located include: focusing on statistics and estimating the resources that can be used for monitoring. If there are a lot of idle resources, the monitoring enters the best effort guarantee state to make full use of resources. If resources are very tight, the collection strategy is downgraded to save resource overhead.

[0112] Collecting the resource consumption of monitoring indicators at each adjustment priority level includes: collecting the resource usage of best effort guarantee, resource guarantee and minimum resource cost in turn, and estimating the resources that will be increased or decreased after the policy adjustment at each level.

[0113] Policy adjustments include: resource upgrade, resource downgrade, and unchanged policy.

[0114] Resource upgrade includes: when the remaining resources of the server are sufficient, such as the CPU idle rate of the whole machine is greater than 60%, then the monitoring collection quality can be improved and resource overhead can be increased. The specific steps are as follows:

[0115] Evaluate target resources: if the idle rate is 60%, adjust the target to 50%;

[0116] Adjust resource requirements at the evaluation level: For example, if the sampling rate is adjusted from 10% to 20%, the resource requirement is 1% of the CPU resources;

[0117] Evaluation level satisfaction: First gradually increase the resource guarantee level parameters and calculate the estimated resource cost. If the calculation result meets the expected resources, the adjustment is complete. If the resource guarantee level has been adjusted to the maximum, no further adjustment is made.

[0118] Resource degradation includes: when the remaining resources of the server are tight or the overall monitoring resource usage exceeds expectations, it is necessary to reduce the collection quality of some indicators and reduce resource overhead. The specific steps are as follows:

[0119] Evaluate target resources: For example, if the monitored CPU resource usage is 20%, adjust the target to 15%;

[0120] Adjust resource requirements at the assessment level: if the sampling rate is adjusted from 20% to 10%, resource consumption is expected to reduce 1% of CPU resources;

[0121] Evaluation level satisfaction: If the sampling rate and other parameters are adjusted to meet resource expectations, the adjustment is complete. If resource expectations are still not met, the collection of the collection indicators at the lowest resource overhead level is suspended to release resources.

[0122] Strategy unchanged: If the collection is relatively stable, resource consumption is in line with expectations, or there are sufficient remaining resources and the best quality collection is already used, there is no need to adjust the collection strategy.

[0123] Finally, the monitoring and collection module reports the collection parameters and resource consumption of each indicator to the indicator value analysis module to facilitate users, developers or operation and maintenance personnel to evaluate the effect of the adjustment strategy in order to optimize the configuration parameters.

[0124] Based on the system for dynamically identifying the value of monitoring indicators provided in the first aspect, in the second aspect, the present application provides a method for dynamically identifying the value of monitoring indicators, which is applied to any electronic device with the function of dynamically identifying the value of monitoring indicators, including but not limited to personal mobile terminals, computers or servers, etc. Figure 4 As shown, the method comprises the following steps:

[0125] S41, obtaining monitoring indicators of each monitoring task in the monitoring system;

[0126] S42, calculating the value score of each monitoring indicator according to the preset monitoring indicator value scoring rule;

[0127] The preset monitoring indicator value scoring rule is obtained according to the time decay coefficient of the monitoring indicator. The value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator. The time decay coefficient represents the effective time of the monitoring indicator.

[0128] S43: Based on the value points of the monitoring indicators, adjust the monitoring tasks.

[0129] Among them, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with the relevant laws and regulations and do not violate public order and good morals.

[0130] The names of the messages or information exchanged between multiple devices in the embodiments of the present application are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0131] In a third aspect, the exemplary embodiments of the present application further provide an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program that can be executed by the at least one processor, and the computer program is used to enable the electronic device to perform a method according to an embodiment of the present application when executed by the at least one processor.

[0132] The exemplary embodiment of the present application further provides a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to perform a method according to an embodiment of the present application.

[0133] The exemplary embodiments of the present application further provide a computer program product, including a computer program, wherein when the computer program is executed by a processor of a computer, it is used to enable the computer to execute the method according to the embodiment of the present application.

[0134] refer to Figure 5 , the structural block diagram of the electronic device 500 that can be used as the server or client of the present application will now be described, which is an example of hardware devices that can be applied to various aspects of the present application. The electronic device is intended to represent various forms of digital electronic computer equipment, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0135] like Figure 5 As shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0136] A plurality of components in the electronic device 500 are connected to the I / O interface 505, including: an input unit 506, an output unit 507, a storage unit 508, and a communication unit 509. The input unit 506 may be any type of device capable of inputting information to the electronic device 500, and the input unit 506 may receive input digital or character information, and generate key signal inputs related to user settings and / or function control of the electronic device. The output unit 507 may be any type of device capable of presenting information, and may include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 508 may include, but is not limited to, a disk, an optical disk. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and may include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0137] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above. For example, in some embodiments, the aforementioned method for dynamically identifying the value of a monitoring indicator may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 500 via the ROM 502 and / or the communication unit 509. In some embodiments, the computing unit 501 may be configured to perform the aforementioned method for dynamically identifying the value of a monitoring indicator by any other appropriate means (e.g., by means of firmware).

[0138] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0139] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0140] As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0141] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0142] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0143] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

Claims

1. A system for dynamically identifying the value of monitoring indicators, characterized in that: The system comprises: The monitoring server is used to obtain the monitoring indicators of each monitoring task in the monitoring system; An indicator value analysis module, used to obtain each of the monitoring indicators from the monitoring service end, and calculate the value score of each of the monitoring indicators according to a preset monitoring indicator value scoring rule; wherein the preset monitoring indicator value scoring rule is set according to the time decay coefficient of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator; The monitoring collection module is used to adjust each monitoring task based on the value score of each monitoring indicator.

2. The system according to claim 1, characterized in that The indicator value analysis module is also used for: According to the value points of each monitoring indicator, each monitoring indicator is graded to obtain different adjustment priorities; The monitoring collection module is also used to adjust each of the monitoring tasks according to each of the adjustment priorities.

3. The system according to claim 1 or 2, characterized in that: The monitoring indicators are divided into core alarm indicators, fault location indicators, risk inspection indicators, and undefined indicators according to their application scenarios. The application scenarios to which each monitoring indicator belongs are not unique. The indicator value analysis module is also used to: Determine the digital level of each monitoring indicator according to the application scenario to which each monitoring indicator belongs; Based on the digital level score of each monitoring indicator, combined with the time decay coefficient of each monitoring indicator and the request frequency of each monitoring indicator, a weighted sum is performed to obtain the value score of each monitoring indicator.

4. The system according to claim 3, characterized in that The digital level score based on each of the monitoring indicators is weighted and summed in combination with the time decay coefficient of each of the monitoring indicators and the request frequency of each of the monitoring indicators to obtain the value score of each of the monitoring indicators, including: The value score is calculated based on the following formula: Value Points Where Level is the digital level of the monitoring indicator, f qt [i] is the request frequency of the monitoring indicator in the i-th time interval, n is the total number of time intervals, and w(i) is the time attenuation coefficient of the monitoring indicator in the i-th time interval.

5. The system according to claim 1, characterized in that The time attenuation coefficient is calculated by the following formula: Wherein, w(i) is the time attenuation coefficient of the monitoring indicator in the i-th time interval, and n is the total number of time intervals.

6. The system according to claim 1, characterized in that The monitoring and acquisition module is also used for: Receive the manual labeling information of the target monitoring indicator transmitted by the user interaction interface, and adjust the target monitoring task in combination with the value score of the target monitoring indicator.

7. The system according to claim 1, characterized in that The monitoring and acquisition module is specifically used for: If the value score of the monitoring indicator is lower than a preset value score threshold, the resources allocated to the monitoring task lower than the preset value score threshold are reduced.

8. A method for dynamically identifying the value of monitoring indicators, characterized in that: The method is applied to the system for dynamically identifying the value of monitoring indicators as claimed in any one of claims 1 to 6, wherein the method comprises: Obtain monitoring indicators of each monitoring task in the monitoring system; According to the preset monitoring indicator value scoring rules, the value score of each monitoring indicator is calculated; wherein the preset monitoring indicator value scoring rules are set according to the time decay coefficient of the monitoring indicator, the value score of the monitoring indicator is negatively correlated with the time decay coefficient of the monitoring indicator, and the time decay coefficient represents the effective time of the monitoring indicator; Based on the value points of each monitoring indicator, each monitoring task is adjusted.

9. An electronic device, characterized in that: The electronic device comprises: Processor; and Memory for storing programs, The program includes instructions, which, when executed by the processor, cause the processor to perform the method according to claim 8.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to make a computer execute the method according to claim 8.

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