Multi-dimensional service monitoring method fusing system and service view angles

Abstract

The invention relates to a multi-dimensional service monitoring method fusing system and service view angles, and relates to the technical field of data analysis, monitoring data burying points are added at key nodes in a service link, monitoring data are collected according to three dimensions of a product, a system and service, the collected monitoring data are divided to obtain monitoring data of three dimensions, and the monitoring data of the three dimensions are stored in the service link. Analyzing the monitoring data of the three dimensions, presetting an alarm condition according to data analysis results of different dimensions, judging whether a service link meets the preset alarm condition according to the preset alarm condition, performing comprehensive judgment according to the monitoring data of the three dimensions of products, systems and services, and when the service link meets the preset alarm condition, sending the service link to the system. Alarm information is sent to terminal equipment, a visualized monitoring big disk is designed, monitoring data and service states of three dimensions are displayed, and system operation conditions and service development conditions are quickly known by displaying real-time data, a trend chart and key index information on the monitoring big disk.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and more specifically, to a multi-dimensional business monitoring method integrating system and business perspectives. Background Art

[0002] With the rapid development of information technology, the business data of enterprises is becoming more and more abundant and diversified, including sales data, customer data, production data, etc. Traditional monitoring methods may not be able to effectively process and utilize these large amounts of data. In order to ensure the stability and reliability of the business, it is necessary to monitor the business link.

[0003] However, there are two commonly used monitoring methods: system perspective and business perspective. The first system perspective refers to monitoring from the system level, focusing on indicators such as system resource usage and system operation status. This monitoring method can effectively detect system failures and abnormal situations, but cannot accurately assess the impact on the business.

[0004] The second business perspective refers to monitoring from the business level, focusing on indicators such as the performance and availability of business links. This monitoring method can more accurately assess the impact on the business, but it requires considering the data interaction between multiple systems, which is more difficult.

[0005] In addition, existing technologies mostly focus on monitoring in a single dimension, such as system dimension or business dimension, and lack comprehensive consideration of monitoring in different dimensions. Summary of the invention

[0006] In view of the technical problems existing in the prior art, the present invention provides a multi-dimensional business monitoring method integrating system and business perspectives to solve the problems raised in the above background technology.

[0007] The technical solution of the present invention to solve the above technical problems is as follows: a multi-dimensional business monitoring method integrating system and business perspectives, specifically comprising the following steps:

[0008] Step 101: Add monitoring data points at key points in the business chain, and collect monitoring data based on the three dimensions of product, system and business;

[0009] Step 102: divide the collected monitoring data to obtain monitoring data in three dimensions, analyze the monitoring data in the three dimensions, and preset alarm conditions according to the data analysis results in different dimensions;

[0010] Step 103: According to the preset alarm condition, determine whether the service link meets the preset alarm condition, make a comprehensive judgment based on the monitoring data of the three dimensions of product, system and service, and send an alarm message to the terminal device when the service link meets the preset alarm condition;

[0011] Step 104: Design a visual monitoring dashboard to display monitoring data and business status in three dimensions. By displaying real-time data, trend charts, and key indicator information on the monitoring dashboard, you can quickly understand the system operation status and business development status.

[0012] In a preferred embodiment, in step 101, monitoring data points are added at key nodes in the business link, and monitoring data is collected according to the three dimensions of product, system and business. The key nodes of the product dimension include user behavior nodes and page loading nodes; the key nodes of the system dimension include interface call nodes and database operation nodes; the key nodes of the business dimension include transaction flow nodes and data processing nodes. The specific steps are as follows:

[0013] Step A1: Product-level monitoring data collection: Track and analyze user behavior by embedding tracking code in the product page and add log records;

[0014] Step A2: Collect monitoring data from the system dimension: Use performance monitoring tools to monitor various performance indicators of the system, including CPU utilization, memory usage, network traffic, and real-time monitoring of the system's operating status;

[0015] Step A3: Business dimension monitoring data collection: Add transaction monitoring code, record the execution of business processes, and perform transaction volume statistics.

[0016] In a preferred embodiment, in step 102, the collected monitoring data is divided to obtain monitoring data in three dimensions, and the monitoring data in the three dimensions is analyzed, and alarm conditions are preset for the data analysis results in different dimensions. The specific steps are as follows:

[0017] Step B1, Dimension Division: The monitoring data is divided into three dimensions: product, system and business to form different data sets. The product dimension includes user activity and functional abnormality indicators; the system dimension includes performance indicators and fault prediction indicators; the business dimension includes revenue and cost, and user growth indicators;

[0018] Step B2, data analysis: using data analysis and mining techniques, analyze the monitoring data in three dimensions, including product dimension, system dimension, and business dimension;

[0019] Step B3, preset alarm conditions: according to the data analysis results of the three dimensions of product, system and business, preset alarm conditions, further including the following steps:

[0020] Step B301: Product dimension alarm conditions include user activity and functional abnormality. The user activity is determined by setting a threshold for user activity. When the activity is lower than the threshold, an alarm is triggered, indicating that the popularity of the product has declined. The functional abnormality is determined by page loading time. When it exceeds a set value, an alarm is triggered.

[0021] Step B302, the system dimension alarm conditions include: performance indicators and fault prediction. The performance indicators are thresholds set according to the system performance indicators. When the response time and error rate exceed the set values, an alarm is triggered. The fault prediction is to use a machine learning model to predict faults and set a probability threshold for the occurrence of faults. When the threshold exceeds the set value, an alarm is triggered and measures are taken in advance to avoid the occurrence of faults.

[0022] Step B303, business dimension alarm conditions include: revenue and cost and user growth. The revenue and cost are determined by setting a threshold of the ratio of revenue and cost. When the ratio exceeds the set ratio, an alarm is triggered, indicating that there is a problem with the profitability of the business. The user growth is determined by setting a threshold of the user growth rate. When the growth rate is lower than the set value, an alarm is triggered, indicating that the demand for the product has decreased.

[0023] In a preferred embodiment, in step 103, according to the preset alarm condition, it is determined whether the service link meets the preset alarm condition, and a comprehensive judgment is made according to the monitoring data of the three dimensions of product, system and service. When the service link meets the preset alarm condition, an alarm message is sent to the terminal device. The specific steps are as follows:

[0024] Step C1, product dimension monitoring data: track the number of daily active users, calculate the month-on-month change rate, record the system function abnormality log, and count the number of daily abnormalities. When the daily user activity drops by more than 10% and the number of abnormalities exceeds 1.5 times the daily average, it is determined that the business link of the product dimension meets the alarm condition. The specific calculation formula of the month-on-month change rate is as follows:

[0025]

[0026] Among them, AH represents the month-on-month change rate, which is an indicator to measure the degree of change between two adjacent time periods, and AU t Indicates the number of daily active users in the current time period, AU t-1 Indicates the number of daily active users in the previous time period. The month-on-month change rate indicator is used to determine the growth or decline of the number of daily active users. When the month-on-month change rate is a positive number, it means that the number of daily active users has increased; when the month-on-month change rate is a negative number, it means that the number of daily active users has decreased.

[0027] Step C2, system dimension monitoring data: monitor system memory usage. When the CPU utilization exceeds the threshold, determine whether the service link of the system dimension meets the alarm condition.

[0028] Step C3, business dimension monitoring data: track real-time data of revenue and cost, count the number of users, and compare the growth rate with expectations. When revenue cannot cover costs and the user growth rate is lower than the expected growth rate, it is determined that the business link of the business dimension meets the alarm conditions.

[0029] In a preferred embodiment, in step 104, a visual monitoring dashboard is designed to display monitoring data and business status in three dimensions. By displaying real-time data, trend charts, and key indicator information on the monitoring dashboard, the specific steps are as follows:

[0030] Step D1, design the monitoring dashboard layout: divide the monitoring dashboard into three areas, corresponding to the monitoring data of the three dimensions of product, system and business respectively. A hierarchical structure is adopted within each area to display real-time data, trend charts and key indicator information, and dimension switching and filtering functions are provided on the side, allowing users to choose to view monitoring data of different dimensions;

[0031] Step D2, highlight key indicators: highlight key indicators on the monitoring dashboard, highlight key indicators by color, and quickly locate problems;

[0032] The top of the product dimension area displays real-time data of the product dimension, including the number of active users, visits, and order volume; the middle part displays historical trend charts related to the product, including user growth trends and changes in visits, so as to quickly understand product performance; the bottom part displays key indicators related to the product, including conversion rate and user retention rate, to help evaluate the health status of the product;

[0033] The top of the system dimension area displays real-time data of the system dimension, including server load, response time, and error rate; the middle part displays the historical trend chart of system performance, including server load changes and response time trends, to help identify system performance problems; the bottom part displays key indicators related to system operation, including system availability and number of failures, to help evaluate system stability;

[0034] The top of the business dimension area displays real-time data of the business dimension, including sales, profits, and customer satisfaction; the middle part displays historical trend charts of business indicators, including sales changes and profit trends, to help understand the business development status; the bottom part displays key indicators related to business operations, including customer complaint rate and market share, to help evaluate business health.

[0035] The beneficial effects of the present invention are as follows: monitoring data points are added at key nodes in the business link, monitoring data is collected according to the three dimensions of product, system and business, the collected monitoring data is divided to obtain monitoring data of three dimensions, and the monitoring data of three dimensions is analyzed, alarm conditions are preset for data analysis results of different dimensions, and according to the preset alarm conditions, it is judged whether the business link meets the preset alarm conditions, and a comprehensive judgment is made according to the monitoring data of the three dimensions of product, system and business. When the business link meets the preset alarm conditions, an alarm message is sent to the terminal device, and a visual monitoring dashboard is designed to display the monitoring data and business status of the three dimensions. By displaying real-time data, trend charts, and key indicator information on the monitoring dashboard, the system operation status and business development status can be quickly understood, and by real-time monitoring and analysis of system operation data and business indicators, potential problems and anomalies can be quickly discovered, and timely responses and processing can be performed to reduce the scope and time of the impact of failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0038] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0039] In the description of the present application, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details to obscure the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0040] Example 1

[0041] This embodiment provides Figure 1 A multi-dimensional business monitoring method integrating system and business perspectives is shown, which specifically includes the following steps:

[0042] Step 101: Add monitoring data points at key points in the business chain, and collect monitoring data based on the three dimensions of product, system and business;

[0043] Step 102: divide the collected monitoring data to obtain monitoring data in three dimensions, analyze the monitoring data in the three dimensions, and preset alarm conditions according to the data analysis results in different dimensions;

[0044] Step 103: According to the preset alarm condition, determine whether the service link meets the preset alarm condition, make a comprehensive judgment based on the monitoring data of the three dimensions of product, system and service, and send an alarm message to the terminal device when the service link meets the preset alarm condition;

[0045] Step 104: Design a visual monitoring dashboard to display monitoring data and business status in three dimensions. By displaying real-time data, trend charts, and key indicator information on the monitoring dashboard, you can quickly understand the system operation status and business development status.

[0046] Preferably, in step 101, monitoring data embedding points are added at key nodes in the business link, and monitoring data is collected according to the three dimensions of product, system and business. Among them, the key nodes of the product dimension include user behavior nodes and page loading nodes; the key nodes of the system dimension include interface call nodes and database operation nodes; the key nodes of the business dimension include transaction flow nodes and data processing nodes. The specific steps are as follows:

[0047] Step A1: Product dimension monitoring data collection: Tracking and analyzing user behavior is achieved by embedding tracking code in the product page, and adding log records, further including the following steps:

[0048] Step A101, user behavior node: monitor the user's button clicking and form filling operations in the product through the front-end tracking technology;

[0049] Step A102, page loading node: monitor each stage of page loading through front-end monitoring technology, including the stage of page loading start, DOM loading completion, and page resource loading completion, and add log records to record user operation behavior and input content information, so as to analyze user behavior and product usage later;

[0050] Step A2: Collect monitoring data from the system dimension: Use performance monitoring tools to monitor various performance indicators of the system, including CPU utilization, memory usage, network traffic, and real-time monitoring of the system's operating status;

[0051] Step A3, business dimension monitoring data collection: add transaction monitoring code, record the execution of business processes, and perform transaction volume statistics, further including the following steps:

[0052] Step A301, transaction monitoring: add transaction monitoring code at the transaction process node of the business process to record the execution status of the business process, including request processing time, request success rate, and error rate indicators;

[0053] Step A302, transaction volume statistics: through database query, regularly count the transaction volume and order volume business indicators of the business system to understand the scale and change trend of business activities.

[0054] Preferably, in step 102, the collected monitoring data is divided to obtain monitoring data in three dimensions, and the monitoring data in the three dimensions is analyzed, and alarm conditions are preset for the data analysis results in different dimensions. The specific steps are as follows:

[0055] Step B1, Dimension Division: The monitoring data is divided into three dimensions: product, system and business to form different data sets. The product dimension includes user activity and functional abnormality indicators; the system dimension includes performance indicators and fault prediction indicators; the business dimension includes revenue and cost, and user growth indicators;

[0056] Step B2, data analysis: using data analysis and mining technology, analyze the monitoring data in three dimensions, including product dimension, system dimension, and business dimension. The product dimension analysis includes: analyzing user behavior data, analyzing user preferences based on user access paths, page dwell time, and conversion rate information;

[0057] System dimension analysis includes: analyzing system performance indicator data, and timely discovering system failures and bottlenecks by monitoring the system's operating status and performance changes;

[0058] Business dimension analysis includes: analyzing the scale and trend of business activities based on business process execution and transaction volume data, and discovering business anomalies and bottlenecks;

[0059] Step B3, preset alarm conditions: according to the data analysis results of the three dimensions of product, system and business, preset alarm conditions, further including the following steps:

[0060] Step B301: Product dimension alarm conditions include user activity and functional abnormality. The user activity is determined by setting a threshold for user activity. When the activity is lower than the threshold, an alarm is triggered, indicating that the popularity of the product has declined. The functional abnormality is determined by page loading time. When it exceeds a set value, an alarm is triggered.

[0061] Step B302, the system dimension alarm conditions include: performance indicators and fault prediction. The performance indicators are thresholds set according to the system performance indicators. When the response time and error rate exceed the set values, an alarm is triggered. The fault prediction is to use a machine learning model to predict faults and set a probability threshold for the occurrence of faults. When the threshold exceeds the set value, an alarm is triggered and measures are taken in advance to avoid the occurrence of faults.

[0062] Step B303, business dimension alarm conditions include: revenue and cost and user growth. The revenue and cost are determined by setting a threshold of the ratio of revenue and cost. When the ratio exceeds the set ratio, an alarm is triggered, indicating that there is a problem with the profitability of the business. The user growth is determined by setting a threshold of the user growth rate. When the growth rate is lower than the set value, an alarm is triggered, indicating that the demand for the product has decreased.

[0063] Preferably, in step 103, according to the preset alarm condition, it is determined whether the service link meets the preset alarm condition, and a comprehensive judgment is made according to the monitoring data of the three dimensions of product, system and service. When the service link meets the preset alarm condition, an alarm message is sent to the terminal device. The specific steps are as follows:

[0064] Step C1, product dimension monitoring data: track the number of daily active users, calculate the month-on-month change rate, record the system function abnormality log, and count the number of daily abnormalities. When the daily user activity drops by more than 10% and the number of abnormalities exceeds 1.5 times the daily average, it is determined that the business link of the product dimension meets the alarm condition. The specific calculation formula of the month-on-month change rate is as follows:

[0065]

[0066] Among them, AH represents the month-on-month change rate, which is an indicator to measure the degree of change between two adjacent time periods, and AU t Indicates the number of daily active users in the current time period, AU t-1 Indicates the number of daily active users in the previous time period. The month-on-month change rate indicator is used to determine the growth or decline of the number of daily active users. When the month-on-month change rate is a positive number, it means that the number of daily active users has increased; when the month-on-month change rate is a negative number, it means that the number of daily active users has decreased.

[0067] Step C2, system dimension monitoring data: monitor system memory usage. When the CPU utilization exceeds the threshold, determine whether the service link of the system dimension meets the alarm condition.

[0068] Step C3, business dimension monitoring data: track real-time data of revenue and cost, count the number of users, and compare the growth rate with expectations. When revenue cannot cover costs and the user growth rate is lower than the expected growth rate, it is determined that the business link of the business dimension meets the alarm conditions.

[0069] Preferably, in step 104, a visual monitoring dashboard is designed to display monitoring data and business status in three dimensions, by displaying real-time data, trend charts, and key indicator information on the monitoring dashboard. The specific steps are as follows:

[0070] Step D1, design the monitoring dashboard layout: divide the monitoring dashboard into three areas, corresponding to the monitoring data of the three dimensions of product, system and business respectively. A hierarchical structure is adopted within each area to display real-time data, trend charts and key indicator information, and dimension switching and filtering functions are provided on the side, allowing users to choose to view monitoring data of different dimensions;

[0071] Step D2, highlight key indicators: highlight key indicators on the monitoring dashboard, highlight key indicators by color, and help users quickly locate problems and focus on important information;

[0072] The top of the product dimension area displays real-time data of the product dimension, including the number of active users, visits, and order volume; the middle part displays historical trend charts related to the product, including user growth trends and changes in visits, so as to quickly understand product performance; the bottom part displays key indicators related to the product, including conversion rate and user retention rate, to help evaluate the health status of the product;

[0073] The top of the system dimension area displays real-time data of the system dimension, including server load, response time, and error rate; the middle part displays the historical trend chart of system performance, including server load changes and response time trends, to help identify system performance problems; the bottom part displays key indicators related to system operation, including system availability and number of failures, to help evaluate system stability;

[0074] The top of the business dimension area displays real-time data of the business dimension, including sales, profits, and customer satisfaction; the middle part displays historical trend charts of business indicators, including sales changes and profit trends, to help understand the business development status; the bottom part displays key indicators related to business operations, including customer complaint rate and market share, to help evaluate business health.

[0075] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0076] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0077] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0078] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0079] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0080] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0081] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A multi-dimensional business monitoring method integrating system and business perspectives, characterized in that: The specific steps include: Step 101: Add monitoring data points at key nodes in the business chain, and collect monitoring data based on the three dimensions of product, system, and business. The key nodes of the product dimension include user behavior nodes and page loading nodes; the key nodes of the system dimension include interface call nodes and database operation nodes; the key nodes of the business dimension include transaction flow nodes and data processing nodes; Step 102: divide the collected monitoring data to obtain monitoring data in three dimensions, analyze the monitoring data in the three dimensions, and preset alarm conditions according to the data analysis results in different dimensions; Step 103: According to the preset alarm condition, determine whether the service link meets the preset alarm condition, make a comprehensive judgment based on the monitoring data of the three dimensions of product, system and service, and send an alarm message to the terminal device when the service link meets the preset alarm condition; Step 104: Design a visual monitoring dashboard to display monitoring data and business status in three dimensions. By displaying real-time data, trend charts, and key indicator information on the monitoring dashboard, you can quickly understand the system operation status and business development status.

2. According to claim 1, a multi-dimensional business monitoring method integrating system and business perspectives is characterized by: In step 101, monitoring data points are added at key nodes in the business link, and monitoring data is collected based on the three dimensions of product, system and business. The specific steps are as follows: Step A1: Product-level monitoring data collection: Track and analyze user behavior by embedding tracking code in the product page, and add log records to record user operation behaviors and input content information; Step A2: System-level monitoring data collection: Use performance monitoring tools to monitor various performance indicators of the system and monitor the operating status of the system in real time; Step A3: Business dimension monitoring data collection: Add transaction monitoring code, record the execution of business processes, and perform transaction volume statistics.

3. The multi-dimensional business monitoring method integrating system and business perspectives according to claim 1 is characterized in that: In step 102, the collected monitoring data is divided to obtain monitoring data in three dimensions, and the monitoring data in the three dimensions is analyzed. Alarm conditions are preset according to the data analysis results in different dimensions. The specific steps are as follows: Step B1: Dimension division: divide the monitoring data into three dimensions: product, system and business to form different data sets; Step B2, data analysis: Use data analysis and mining technology to analyze the monitoring data in three dimensions, including product dimension, system dimension, and business dimension. Among them, product dimension analysis is to analyze user behavior data, system dimension analysis is to analyze system performance indicators, and business dimension analysis is to analyze the scale and change trend of business activities based on business process execution and transaction volume data.

4. The multi-dimensional business monitoring method integrating system and business perspectives according to claim 3 is characterized in that: In the preset alarm conditions for the data analysis results of different dimensions, the specific steps include: presetting alarm conditions according to the data analysis results of the three dimensions of product, system and business, wherein the product dimension alarm conditions are based on the monitoring data of user activity and functional abnormalities, the system dimension alarm conditions are based on performance indicators, and the business dimension alarm conditions are based on the monitoring data of revenue, cost and user growth, and thresholds are set based on the monitoring indicators, and an alarm is triggered when the set value is exceeded.

5. The multi-dimensional business monitoring method integrating system and business perspectives according to claim 1 is characterized in that: In step 103, according to the preset alarm condition, it is determined whether the service link meets the preset alarm condition, and a comprehensive judgment is made based on the monitoring data of the three dimensions of product, system and service. When the service link meets the preset alarm condition, an alarm message is sent to the terminal device. The specific steps are as follows: Step C1, product dimension monitoring data: track the number of daily active users, calculate the month-on-month change rate, record system function abnormality logs, and count the number of daily abnormalities. When the daily user activity drops by more than 10% and the number of abnormalities exceeds 1.5 times the daily average, it is determined that the business link of the product dimension meets the alarm conditions; Step C2, system dimension monitoring data: monitor system memory usage. When the CPU utilization exceeds the threshold, determine whether the service link of the system dimension meets the alarm condition. Step C3, business dimension monitoring data: track real-time data of revenue and cost, count the number of users, and compare the growth rate with expectations. When revenue cannot cover costs and the user growth rate is lower than the expected growth rate, it is determined that the business link of the business dimension meets the alarm conditions.

6. A multi-dimensional business monitoring method integrating system and business perspectives according to claim 5, characterized in that: The specific calculation formula of the month-on-month change rate is as follows: Among them, AH represents the month-on-month change rate, which is an indicator to measure the degree of change between two adjacent time periods. t Indicates the number of daily active users in the current time period, AU t-1 Indicates the number of daily active users in the previous time period.

7. The multi-dimensional business monitoring method integrating system and business perspectives according to claim 1 is characterized in that: In step 104, a visual monitoring dashboard is designed to display monitoring data and business status in three dimensions. By displaying real-time data, trend charts, and key indicator information on the monitoring dashboard, the system operation status and business development status can be quickly understood. The specific steps are as follows: Step D1, design the monitoring dashboard layout: divide the monitoring dashboard into three areas, corresponding to the monitoring data of the three dimensions of product, system and business respectively. A hierarchical structure is adopted within each area to display real-time data, trend charts and key indicator information, and dimension switching and filtering functions are provided on the side, allowing users to choose to view monitoring data of different dimensions; Step D2, highlight key indicators: highlight key indicators on the monitoring dashboard, highlight key indicators by color, and quickly locate problems.

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