Monitoring method, device and equipment based on CAT monitoring system and storage medium

Abstract

This invention relates to the field of distributed monitoring technology, and in particular to a monitoring method, device, equipment, and storage medium based on a CAT monitoring system. The method first obtains the construction configuration file of the network management project, introduces the CAT client dependency package into the construction configuration file to obtain the target project, then performs client initialization configuration processing on the target project to obtain the initial business application, then performs multi-dimensional data tracking processing on the initial business application to obtain the target business application, performs multi-dimensional data monitoring based on the target business application to obtain the target monitoring dataset, and finally sends the target monitoring dataset to the CAT server for data analysis. The aim is to simplify CAT integration and deployment, solve the problems of complex traditional monitoring integration, coarse granularity, poor real-time performance, and difficulty in distributed tracing, and achieve multi-dimensional real-time monitoring.

Description

Technical Field

[0001] This invention relates to the field of distributed monitoring technology, and in particular to a monitoring method, device, equipment and storage medium based on a CAT monitoring system. Background Technology

[0002] With the rapid development of internet applications, microservice architecture has been widely adopted in various business systems, highlighting the limitations of traditional monitoring systems, which are increasingly unable to meet the monitoring needs of modern distributed applications. Traditional monitoring systems generally suffer from coarse-grained monitoring, providing only relatively basic performance metrics and failing to achieve detailed tracing of application internal call chains. Furthermore, they lack real-time data, exhibiting significant data latency and failing to provide near real-time performance data feedback. Under a microservice architecture, the difficulty of tracing cross-service calls and locating problems increases significantly, and the lack of distributed tracing capabilities has become a prominent pain point in the industry. In addition, traditional monitoring systems have relatively simple alarm mechanisms, lacking intelligent anomaly detection and early warning capabilities, and their monitoring data visualization is low, with unintuitive display methods, making it difficult for operations and maintenance personnel to quickly identify the root cause of problems. CAT monitoring system, as an open-source real-time distributed monitoring system, possesses significant technical advantages. It employs an asynchronous, non-blocking, high-performance data acquisition method, minimizing its impact on application performance. It also supports cross-service and cross-node call chain tracing, boasts comprehensive distributed tracing capabilities, and can cover various monitoring types such as transactions, events, and heartbeats. Its rich indicator system also supports custom monitoring indicators and plugin extensions, offering a flexible extension mechanism. Coupled with a comprehensive visualization interface, it can intuitively present and analyze monitoring data. Despite these advantages, the deployment and application of current monitoring systems still commonly suffer from cumbersome configuration and high integration difficulty. Summary of the Invention

[0003] In order to overcome the shortcomings of the prior art, the present invention aims to provide a monitoring method, device, equipment and storage medium based on a CAT monitoring system, which aims to solve the problems of complex integration, coarse granularity, poor real-time performance and difficulty in distributed tracking of traditional monitoring, simplify CAT integration deployment and realize multi-dimensional real-time monitoring.

[0004] The first aspect of this invention provides a monitoring method based on a CAT monitoring system, comprising: obtaining a construction configuration file for a network management project; introducing a CAT client dependency package into the construction configuration file to obtain a target project; performing client initialization configuration processing on the target project to obtain an initial business application; performing multi-dimensional data tracking processing on the initial business application to obtain a target business application; performing multi-dimensional data monitoring based on the target business application to obtain a target monitoring dataset; and sending the target monitoring dataset to a CAT server for data analysis.

[0005] Optionally, in a first implementation of the first aspect of the present invention, the step of introducing the CAT client dependency package into the build configuration file to obtain the target project includes: constructing a dependency configuration item in the dependency management area of ​​the build configuration file; configuring the organization identifier parameter, module identifier parameter, and version number parameter in the dependency configuration item to obtain a modified dependency configuration item; and performing a project dependency update operation based on the modified dependency configuration item to introduce the CAT client dependency package and obtain the target project.

[0006] Optionally, in a second implementation of the first aspect of the present invention, the step of performing client initialization configuration processing on the target project to obtain the initial business application includes: introducing initialization logic into the system startup entry class of the target project; configuring a unique business domain identifier parameter in the initialization logic to obtain initialization configuration logic; and executing the initialization configuration logic to establish a communication connection between the target project and the CAT server to obtain the initial business application.

[0007] Optionally, in a third implementation of the first aspect of the present invention, the step of performing multi-dimensional data tracking on the initial business application to obtain the target business application includes: determining the business processing logic node, user operation entry node, and business operation indicator node of the initial business application; performing monitoring logic configuration operations in the business processing logic node, the user operation entry node, and the business operation indicator node respectively to obtain target transaction monitoring logic, target event monitoring logic, and target indicator collection logic; and integrating the target transaction monitoring logic, the target event monitoring logic, and the target indicator collection logic in the initial business application to obtain the target business application.

[0008] Optionally, in a fourth implementation of the first aspect of the present invention, the step of performing monitoring logic configuration operations in the business processing logic node, the user operation entry node, and the business operation indicator node to obtain target transaction monitoring logic, target event monitoring logic, and target indicator collection logic includes: introducing initial transaction monitoring logic in the business processing logic node, and configuring business type identifier, execution status recording rules, and distributed tracking identifier in the initial transaction monitoring logic to obtain the target transaction monitoring logic; introducing initial event monitoring logic in the user operation entry node, and configuring event type, operation name, and execution status in the initial event monitoring logic to obtain the target event monitoring logic; and introducing initial indicator collection logic in the business operation indicator node, and configuring indicator name, statistical type, and data association mapping rules in the initial indicator collection logic to obtain the target indicator collection logic.

[0009] Optionally, in a fifth implementation of the first aspect of the present invention, the step of performing multi-dimensional data monitoring based on the target business application to obtain a target monitoring dataset includes: collecting system operation data of the target business application based on the target transaction monitoring logic; collecting user behavior data of the target business application based on the target event monitoring logic; collecting business operation data of the target business application based on the target indicator collection logic; integrating the system operation data, the user behavior data, and the business operation data to obtain an initial monitoring dataset; and standardizing the initial monitoring dataset using a standardization tool to obtain the target monitoring dataset.

[0010] Optionally, in a sixth implementation of the first aspect of the present invention, sending the target monitoring dataset to a CAT server for data analysis includes: obtaining a preset communication protocol; sending the target monitoring dataset to the CAT server based on the communication protocol, so that the CAT server performs data analysis based on the target monitoring dataset and obtains data analysis results; obtaining the data analysis results and optimizing the operating parameters of the target business application based on the data analysis results.

[0011] A second aspect of the present invention provides a monitoring device based on a CAT monitoring system, comprising: a file acquisition module for acquiring a construction configuration file for a network management project; a CAT import module for importing a CAT client dependency package into the construction configuration file to obtain a target project; an initialization module for performing client initialization configuration processing on the target project to obtain an initial business application; a data tracking module for performing multi-dimensional data tracking processing on the initial business application to obtain a target business application; a data monitoring module for performing multi-dimensional data monitoring based on the target business application to obtain a target monitoring dataset; and a data sending module for sending the target monitoring dataset to a CAT server for data analysis.

[0012] A third aspect of the present invention provides a monitoring device based on a CAT monitoring system, the monitoring device based on a CAT monitoring system comprising: a memory and at least one processor, the memory storing instructions; at least one processor calling the instructions in the memory to cause the monitoring device based on the CAT monitoring system to execute the various steps of the monitoring method based on the CAT monitoring system described above.

[0013] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed by a processor, implement the steps of the monitoring method based on the CAT monitoring system described in any of the preceding claims.

[0014] In the technical solution of this invention, the construction configuration file of the network management project is first obtained, and the CAT client dependency package is introduced into the construction configuration file to obtain the target project. Then, the target project is processed for client initialization configuration to obtain the initial business application. Next, the initial business application is processed for multi-dimensional data tracking to obtain the target business application. Based on the target business application, multi-dimensional data monitoring is performed to obtain the target monitoring dataset. Finally, the target monitoring dataset is sent to the CAT server for data analysis. This invention aims to solve the problems of complex traditional monitoring integration, coarse granularity, poor real-time performance, and difficulty in distributed tracing, simplify CAT integration and deployment, and realize multi-dimensional real-time monitoring. Attached Figure Description

[0015] Figure 1 This is a first flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 2 This is a second flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 3 This is a third flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 4 This is a fourth flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 5 This is a fifth flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 6 This is a sixth flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 7 This is the seventh flowchart of a monitoring method based on a CAT monitoring system provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of the structure of a monitoring device based on a CAT monitoring system provided in an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of a monitoring device based on a CAT monitoring system provided in an embodiment of the present invention. Detailed Implementation

[0016] This invention provides a monitoring method, apparatus, device, and storage medium based on a CAT monitoring system. In this invention, the terms "first," "second," "third," "fourth," etc. (if applicable) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0017] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1 One embodiment of the monitoring method based on the CAT monitoring system in this invention includes: 101. Obtain the build configuration file for the Branch Manager project; In this embodiment, the CAT server environment needs to be set up before reading the build configuration file of the Network Point Manager project. First, basic environment preparation is completed, using a Linux server, installing a Java runtime environment, and configuring the network environment to ensure network connectivity between nodes. Second, database deployment is completed, installing a MySQL database and creating a dedicated CAT database with a specified utf8mb4 character set. Next, CAT server deployment is performed, downloading the server installation package, configuring files such as datasources.xml and server.xml, setting database connection information, service ports, and cluster-related parameters, starting the CAT service after configuration, and finally configuring the cluster by grouping multiple CAT servers into a cluster to improve availability and setting load balancing strategies to ensure even distribution of monitoring data. Only after completing all the above CAT server environment setup operations can the build configuration file of the Network Point Manager project be located and read. This file, as the core carrier of project dependency management and the build process, carries key information such as dependency import rules and compilation / packaging logic, providing a precise configuration entry and operational basis for subsequently importing CAT client dependency packages, ensuring the stability and efficiency of the integration between the CAT monitoring system and the Network Point Manager project.

[0018] 102. Add the CAT client dependency package to the build configuration file to obtain the target project; In this embodiment, after reading the build configuration file of the Network Manager project, dependency configuration items are built in the dependency management area of ​​the build configuration file. According to the CAT client integration specification, the organization identifier parameter, module identifier parameter, and version number parameter are configured in this configuration item to clarify the organization affiliation, module name, and specified version of the CAT client dependency, thus completing the modification of the dependency configuration item. Based on the modified dependency configuration item, a project dependency update operation is performed, triggering the build tool to automatically pull and import the corresponding version of the CAT client dependency package. This enables the Network Manager project to have the basic ability to interact with the CAT server, ultimately resulting in a target project that can support subsequent monitoring integration operations. Through a standardized dependency configuration process, the introduction of CAT client dependencies is ensured to be accurate and controllable, avoiding integration failures caused by dependency version incompatibility or chaotic configuration, ensuring the stability and reproducibility of the project build, and providing reliable dependency support for subsequent client initialization configuration, multi-dimensional data tracking, and monitoring data collection and reporting. This simplifies the integration process between the CAT monitoring system and business projects, improves the efficiency and reliability of building a distributed application monitoring system, effectively compensates for the shortcomings of traditional monitoring system integration complexity and cumbersome configuration, and adapts to the distributed monitoring needs under a microservice architecture.

[0019] 103. Perform client initialization configuration processing on the target project to obtain the initial business application; In this embodiment, after obtaining the target project by importing the CAT client dependency package, initialization logic is introduced into the system startup entry class of the target project. Specifically, this is achieved by calling `Cat.initializeByDomain` to load the initialization configuration. This initialization logic configures a unique business domain identifier parameter, clarifying business affiliation and data isolation dimensions, thus forming a complete initialization configuration logic. Subsequently, this initialization configuration logic is executed, establishing a communication link between the target project and the CAT server. This enables the target project to report monitoring data to the CAT server, ultimately resulting in an initial business application capable of supporting subsequent data tracking and monitoring operations. Through a standardized initialization process, the communication connection between the target project and the CAT server is ensured to be stable and reliable. The configuration of the business domain identifier enables monitoring data isolation and traceability across multiple business scenarios, avoiding confusion of monitoring data from different business modules, improving the readability of monitoring data and the efficiency of problem localization. Simultaneously, it lays the communication foundation for subsequent multi-dimensional data tracking, monitoring data collection, and analysis, simplifying the initial deployment of the distributed application monitoring system, ensuring efficient collaboration between the monitoring system and business projects, adapting to the distributed monitoring needs under a microservice architecture, and overcoming the shortcomings of traditional monitoring systems, such as complex integration and unstable communication links.

[0020] 104. Perform multi-dimensional data tracking on the initial business application to obtain the target business application; In this embodiment, after obtaining the initial business application, multi-dimensional data tracking is performed. First, initial transaction monitoring logic is introduced at the business processing logic node. A transaction monitoring instance is created by calling `Cat.newTransaction`, configuring the business type identifier and specific operation name. Status recording rules are embedded in the business logic execution flow. When the business execution is successful, the transaction is marked as successful; when an exception is captured, an exception is marked and an error log is recorded synchronously. Finally, the transaction is committed in the `finally` block, forming the target transaction monitoring logic, achieving full-process tracking and status control of the business execution chain. Next, initial event monitoring logic is introduced at the user operation entry node. `Cat.logEvent` is called to record user behavior events, configuring the event type, operation name, and execution status, and associating it with the corresponding business data identifier, forming the target event monitoring logic, achieving accurate collection and tracing of user operation behavior. Subsequently, initial indicator collection logic is introduced at the business operation indicator node. A custom indicator instance is created by calling `Cat.getProducer().newMetric`, configuring the indicator name and statistical type, and calling `addData` to complete the reporting of indicator data, forming the target indicator collection logic, achieving customized statistics and reporting of business operation data. By integrating target transaction monitoring logic, target event monitoring logic, and target metric collection logic into the initial business application, a target business application with multi-dimensional monitoring capabilities is obtained. The event tracking process, through the coordinated coverage of three monitoring dimensions—transactions, events, and metrics—achieves refined collection and end-to-end tracking of business execution processes, user behavior, and operational data. It can accurately capture business anomalies and performance bottlenecks, providing comprehensive and reliable data support for subsequent monitoring data analysis, problem localization, and performance optimization. Simultaneously, it improves the observability of distributed applications, effectively compensating for the shortcomings of traditional monitoring systems—coarse monitoring granularity and insufficient tracking capabilities—and adapting to the complex business monitoring needs under a microservice architecture.

[0021] 105. Perform multi-dimensional data monitoring based on the target business application to obtain the target monitoring dataset; In this embodiment, multi-dimensional data monitoring based on the target business application is a data collection and processing process carried out based on the previously configured multi-dimensional data tracking points. First, system operation data is collected through the target transaction monitoring logic, comprehensively covering the business execution chain, transaction execution status, and distributed tracing information, accurately capturing system performance and abnormal events. Next, user behavior data is collected through the target event monitoring logic, recording user operation types, execution status, and associated business identifiers, completely reconstructing user operation paths and behavioral characteristics. Finally, business operation data is collected through the target indicator collection logic, statistically analyzing the numerical changes and trends of custom business indicators to intuitively reflect the business operation status. The system operation data, user behavior data, and business operation data are integrated to form an initial monitoring dataset. Then, standardized tools are used to clean, unify the format, and align the dimensions of the initial monitoring dataset, removing redundant information and standardizing the data structure and field definitions to obtain a consistent and usable target monitoring dataset. The generated target monitoring dataset can provide comprehensive and reliable data support for subsequent performance bottleneck analysis, fault diagnosis and capacity planning. It not only realizes real-time observation of the entire chain and multiple dimensions of distributed applications, but also improves the quality and analysis efficiency of monitoring data. It effectively makes up for the shortcomings of traditional monitoring systems, such as coarse monitoring granularity, high data latency and low visualization. It adapts to the monitoring needs of complex business scenarios under microservice architecture, helps to build a complete monitoring closed loop and ensures the stable and efficient operation of the system.

[0022] 106. Send the target monitoring dataset to the CAT server for data analysis.

[0023] In this embodiment, a preset communication protocol is first acquired, and a stable and efficient data transmission channel is established between the target business application and the CAT server based on this protocol. The integrated target monitoring dataset is then accurately reported to the CAT server cluster. After receiving the target monitoring dataset, the CAT server performs multi-dimensional in-depth data analysis. On the one hand, it uses call chain tracing to locate slow queries, analyzes transaction execution time distribution to identify system performance bottlenecks, quickly locates the cause of anomalies through error logs, and traces the fault propagation path based on the call chain. Simultaneously, it predicts system load based on historical monitoring data and analyzes resource usage trends to complete capacity planning, providing data support for system expansion. On the other hand, it links with the monitoring configuration optimization process, matching preset alarm rules, performance tuning strategies, and visualization configurations to generate data analysis results covering performance bottlenecks, root causes of faults, capacity recommendations, and directions for monitoring configuration optimization. Subsequently, the data analysis results are acquired, and the operating parameters of the target business application are optimized and adjusted based on the results. This includes adjusting the data sampling rate according to business characteristics, optimizing monitoring data storage strategies, configuring a reasonable data cleaning mechanism, and optimizing the layout of the monitoring panel and the display logic of key indicators to achieve coordinated optimization of monitoring configuration and business operation. It ensures the real-time and reliable transmission of monitoring data. The intelligent analysis capabilities of the CAT server can accurately capture performance problems and potential risks of distributed applications, providing data-driven decision-making basis for parameter optimization of target business applications. At the same time, the complete monitoring closed loop effectively makes up for the shortcomings of traditional monitoring systems, such as poor real-time performance, single alarm mechanism and low degree of visualization, improves the observability and operation and maintenance efficiency of distributed applications, ensures stable and efficient system operation, and adapts to the complex business monitoring needs under microservice architecture.

[0024] Please see Figure 2 In this embodiment of the invention, the step of introducing the CAT client dependency package into the build configuration file to obtain the target project includes: 201. In the dependency management area of ​​the build configuration file, build the dependency configuration items; 202. Configure the organization identifier parameter, module identifier parameter, and version number parameter in the dependency configuration item to obtain the modified dependency configuration item; 203. Based on the modified dependency configuration items, perform a project dependency update operation to introduce the CAT client dependency package and obtain the target project.

[0025] In this embodiment, a dependency configuration item is built within the dependency management area of ​​the build configuration file. This dependency configuration item is a configuration unit used to declare external dependencies in the project build configuration. It carries key information such as dependency source identifiers, module definitions, and version constraints, and is the basic carrier for achieving automatic dependency retrieval and version management. The dependency configuration item is configured with an organization identifier parameter, a module identifier parameter, and a version number parameter. The organization identifier parameter identifies the organization or development team to which the dependency package belongs, clarifies the repository source path of the dependency package, and ensures that the build tool can accurately locate the dependency repository of the corresponding organization. The build tool is mainly Apache Maven or Gradle, which are the core support for achieving automated project build, dependency retrieval, compilation, and packaging. They can automatically complete dependency parsing, downloading, and integration based on the dependency declarations in the configuration file. The module identifier parameter specifies the specific module name of the dependency package, distinguishing different functional modules under the same organization, and ensuring that the introduced dependency modules accurately match business monitoring requirements. The version number parameter limits the specific version of the dependency package, constraining the version range of the dependency package and avoiding compatibility issues caused by version differences, resulting in the modified dependency configuration item. Based on the modified dependency configuration items, the project dependency update operation is performed, triggering the build tool to automatically pull and import the CAT client dependency package. The CAT client dependency package is the core functional library required for integrating the CAT monitoring system, containing the implementation code for monitoring capabilities such as data collection, distributed tracing, and event reporting. It is the basic dependency for business applications to connect to the CAT server, ultimately resulting in the target project. Through a standardized dependency configuration process, the precise import and version control of the CAT client dependency package are achieved, effectively avoiding integration failures such as dependency conflicts and version incompatibility. This ensures the stability and reproducibility of the project build, provides reliable dependency support for subsequent client initialization configuration, multi-dimensional data tracking, and monitoring data collection and reporting, simplifies the integration process between the CAT monitoring system and business projects, and improves the efficiency and reliability of building a distributed application monitoring system.

[0026] Please see Figure 3 In this embodiment of the invention, the step of performing client initialization configuration processing on the target project to obtain the initial business application includes: 301. Introduce initialization logic into the system startup entry class of the target project; 302. Configure a unique service domain identifier parameter in the initialization logic to obtain the initialization configuration logic; 303. Execute the initialization configuration logic to establish a communication connection between the target project and the CAT server, and obtain the initial business application.

[0027] In this embodiment, initialization logic is introduced into the system startup entry class of the target project. The system startup entry class is the unit that carries the application startup process, typically containing the core execution entry point for application startup, responsible for initializing the application context and core components. Embedding the CAT client's initialization logic in this class ensures that the monitoring system integration is completed during the application startup phase. Specifically, the initialization logic is implemented by calling `Cat.initializeByDomain`, which is the core code snippet for completing the CAT client initialization, carrying the key logic for parameter configuration and underlying communication initialization. A unique business domain identifier parameter is configured in this initialization logic. This unique business domain identifier parameter is a globally unique identifier used to distinguish different business applications or modules. As an input parameter of `Cat.initializeByDomain`, it can assign the monitoring data of the current application to the specified business domain, achieving data isolation and traceability in multiple business scenarios, avoiding confusion of monitoring data from different business modules, and forming a complete initialization configuration logic. When executing this initialization configuration logic, `Cat.initializeByDomain` automatically completes underlying operations such as service discovery, data reporting channel initialization, and server configuration synchronization. By locating the CAT server cluster address, establishing an asynchronous non-blocking transmission channel, and synchronizing server monitoring configurations, it stably establishes a communication connection between the target project and the CAT server, enabling the target project to have the basic capabilities for monitoring data collection and reporting, ultimately resulting in the initial business application. The initialization process relies on the execution timing of the system startup entry class to ensure that the monitoring system is integrated when the application starts, avoiding the omission of monitoring data during the startup phase. The configuration of the unique business domain identifier parameter enables precise isolation and classification management of monitoring data, improving data readability and problem location efficiency. The standardized initialization method automatically completes the establishment of communication connections, ensuring the stability and reliability of the connection, simplifying the integration configuration process of the distributed monitoring system, and laying a solid foundation for subsequent multi-dimensional data tracking, monitoring data collection and analysis, adapting to the distributed application monitoring needs under a microservice architecture.

[0028] Please see Figure 4 In this embodiment of the invention, the step of performing multi-dimensional data tracking on the initial business application to obtain the target business application includes: 401. Determine the business processing logic nodes, user operation entry nodes, and business operation indicator nodes of the initial business application; 402. Perform monitoring logic configuration operations in the business processing logic node, the user operation entry node, and the business operation indicator node respectively to obtain the target transaction monitoring logic, the target event monitoring logic, and the target indicator collection logic; 403. Integrate the target transaction monitoring logic, the target event monitoring logic, and the target indicator collection logic into the initial business application to obtain the target business application.

[0029] In this embodiment, a set of monitoring nodes for the initial business application is determined. This set includes business processing logic nodes, user operation entry nodes, and business operation indicator nodes. Business processing logic nodes are code units that carry out the execution of core business processes. They typically correspond to core methods in business services and are used to encapsulate the implementation of specific business logic. They serve as the carrier for monitoring the business execution chain, performance, and abnormal states. User operation entry nodes are code units that respond to user interaction requests. They typically correspond to backend methods triggered by interfaces or frontend interactions and are used to record user operation behaviors and states. They are the key entry points for realizing user behavior tracking and problem tracing. Business operation indicator nodes are code units that carry out business operation data statistics and reporting. They typically correspond to key nodes for the generation or updating of business data and are used to collect custom business indicator data to reflect the business operation status and trends. The monitoring logic configuration operations are executed in the business processing logic node, user operation entry node, and business operation metric node, respectively. Specifically, in the business processing logic node, a transaction monitoring instance is created by calling `Cat.newTransaction`, the business type identifier and specific operation name are configured, and the business logic processing code is wrapped in a `try-catch-finally` block. When the business execution is successful, the transaction success status is marked; when an exception is caught, the exception status is marked and the error log is recorded synchronously. Finally, the transaction is committed in the `finally` block, resulting in the target transaction monitoring logic. In the user operation entry node, `Cat.logEvent` is called to record user behavior events, the event type, operation name, and execution status are configured, and the corresponding business data identifier is associated, resulting in the target event monitoring logic. In the business operation metric node, a custom metric instance is created by calling `Cat.getProducer().newMetric`, the metric name and statistical type are configured, and the `addData` method is called to complete the reporting of metric data, resulting in the target metric collection logic. Integrating target transaction monitoring logic, target event monitoring logic, and target metric collection logic into the initial business application, and embedding these three types of monitoring logic into the corresponding nodes of the application, enables the application to have multi-dimensional monitoring capabilities covering business execution, user behavior, and operational data, ultimately resulting in the target business application. By locating the three core monitoring nodes, full-link, multi-dimensional monitoring coverage of the distributed application is achieved. This not only tracks the complete chain of business execution and performance bottlenecks, but also reconstructs user operation paths and abnormal behaviors, and can also collect custom business operation metrics. This effectively makes up for the shortcomings of traditional monitoring systems, such as coarse monitoring granularity and insufficient distributed tracing capabilities. At the same time, standardized monitoring logic configuration ensures the consistency and traceability of monitoring data, providing comprehensive and reliable data support for subsequent monitoring data collection, analysis, and problem localization. This improves the observability and operational efficiency of distributed applications and adapts to the monitoring needs of complex business scenarios under a microservice architecture.

[0030] Please see Figure 5 In this embodiment of the invention, the step of executing monitoring logic configuration operations in the business processing logic node, the user operation entry node, and the business operation indicator node respectively to obtain target transaction monitoring logic, target event monitoring logic, and target indicator collection logic includes: 501. Introduce initial transaction monitoring logic into the business processing logic node, and configure business type identifier, execution status recording rules and distributed tracing identifier in the initial transaction monitoring logic to obtain the target transaction monitoring logic; 502. Introduce initial event monitoring logic into the user operation entry node, and configure event type, operation name and execution status in the initial event monitoring logic to obtain the target event monitoring logic; 503. Introduce initial indicator collection logic into the business operation indicator node, and configure indicator name, statistical type and data association mapping rules in the initial indicator collection logic to obtain the target indicator collection logic.

[0031] In this embodiment, initial transaction monitoring logic is introduced into the business processing logic node. This logic is implemented by calling Cat.newTransaction. Within this logic, business type identifiers, execution status recording rules, and distributed tracing identifiers are configured. The business type identifier is a classification identifier used to distinguish different business categories or service types, allowing monitoring data to be categorized by business dimension, facilitating subsequent statistical analysis by business type. The execution status recording rule defines the specifications for the transaction execution result status. The setStatus method marks the transaction execution status; when the business logic executes successfully, it is set to a successful status; when an exception is captured, an exception status is marked and an error log is recorded synchronously, achieving accurate recording and exception tracking of transaction execution results. The distributed tracing identifier is a link identifier automatically generated by the CAT underlying layer. Through the creation and propagation of transactions, cross-service and cross-node call chain associations are achieved, linking various transactions in the same request chain to reconstruct the complete business execution path and obtain the target transaction monitoring logic. Initial event monitoring logic is introduced into the user operation entry node. This logic is implemented by calling `Cat.logEvent`. This logic configures the event type, operation name, and execution status. The event type is an identifier used to classify user behavior or system events, distinguishing different types of user operations or system events. The operation name is the name of the specific event, used to locate the specific user operation or system behavior. The execution status is an identifier for the event execution result, used to mark whether the event execution was successful or failed, facilitating the statistical analysis of event success rate and anomalies, thus obtaining the target event monitoring logic. Initial metric collection logic is introduced into the business operation metric node. This logic is implemented by calling `Cat.getProducer().newMetric`. This logic configures the metric name, statistical type, and data association mapping rules. The metric name is a unique identifier for the custom business metric, used to reflect the core operational status of the business. The statistical type defines the statistical method for the metric data, used to define the statistical rules for the metric data, achieving accurate statistical analysis of business data. The data association mapping rules are the specifications for associating metric data with corresponding business dimensions. `addData` binds specific values ​​to the metric, achieving accurate reporting and correlation analysis of metric data, thus obtaining the target metric collection logic. Through refined parameter definition and logic embedding, it achieves full-link, multi-dimensional monitoring coverage of distributed applications. It can accurately track business execution links and performance bottlenecks, fully reconstruct user operation paths and abnormal behaviors, and customize statistical business operation indicators. It effectively makes up for the shortcomings of traditional monitoring systems, such as coarse monitoring granularity, insufficient distributed tracing capabilities, and low visualization. It improves the standardization and traceability of monitoring data, provides reliable data support for subsequent monitoring data collection, analysis, and problem localization, ensures the observability and operational efficiency of distributed applications, and adapts to the complex business monitoring needs under microservice architecture.

[0032] Please see Figure 6 In this embodiment of the invention, the step of performing multi-dimensional data monitoring based on the target business application to obtain the target monitoring dataset includes: 601. Collect system operation data of the target business application based on the target transaction monitoring logic; 602. Collect user behavior data of the target business application based on the target event monitoring logic; 603. Collect the business operation data of the target business application based on the target indicator collection logic; 604. Integrate the system operation data, the user behavior data, and the business operation data to obtain an initial monitoring dataset; 605. The initial monitoring dataset is standardized using a standardization tool to obtain the target monitoring dataset.

[0033] In this embodiment, multi-dimensional data monitoring based on the target business application is a data collection and processing process carried out based on the pre-configured data entry points. First, system operation data is collected through the target transaction monitoring logic. This system operation data is the core data reflecting the operating status and performance of the target business application, covering transaction execution time, call chain information, exception logs, and service response status. The collection process relies on the try-catch-finally block of the transaction monitoring, automatically recording transaction creation, execution status, time consumption, and distributed tracing information during business processing logic execution. When exceptions are captured, error logs are recorded synchronously, fully reconstructing the business execution chain and system operating status. Next, user behavior data is collected through the target event monitoring logic. User behavior data is... The core data recording process of user interaction with the application includes user operation type, specific operation name, execution status, and associated business identifier. The collection process calls logEvent at the user operation entry node to encapsulate user interaction behavior into events, recording information such as event type, operation name, execution status, and associated user identifier, thus fully reconstructing the user operation path and behavioral characteristics. Business operation data is collected through target indicator collection logic. Business operation data is a set of custom statistical data reflecting the core operational status of the business, covering the values ​​and trends of business indicators such as order volume and user activity. The collection process creates custom indicator instances at the business operation indicator node, calls addData to report indicator data, and statistically analyzes the changes and distribution of values ​​in business operation dimensions. The system integrates operational data, user behavior data, and business operation data to obtain an initial monitoring dataset. This dataset is then standardized using standardization tools, which typically refer to professional data processing frameworks or scripts for data cleaning, format conversion, and dimension alignment. Standardization specifically includes cleaning the initial monitoring dataset, removing redundant, missing, and abnormal data, unifying data formats and field definitions, performing dimension alignment and data normalization, and standardizing data structures and timestamp formats. This ensures consistency and usability for monitoring data from different sources and of different types, ultimately yielding the target monitoring dataset. The standardization tools include basic utility libraries such as Apache Commons Lang and Google Guava, used for basic data cleaning operations such as data validation, null value detection, and string formatting. JSON serialization libraries such as Jackson and Gson are used to convert heterogeneous monitoring data into a standardized JSON structure, eliminating format differences caused by different tracking logics. The Java 8 DateTime API or Joda-Time is used to unify timestamp formats, standardize the time dimension alignment of data, and ensure the consistency of time-series data.The generated target monitoring dataset can provide comprehensive and reliable data support for subsequent performance bottleneck analysis, fault diagnosis and capacity planning. It not only realizes real-time observation of the entire chain and multiple dimensions of distributed applications, but also improves the quality and analysis efficiency of monitoring data. It effectively makes up for the shortcomings of traditional monitoring systems, such as coarse monitoring granularity, high data latency and low visualization. It adapts to the monitoring needs of complex business scenarios under microservice architecture, helps to build a complete monitoring closed loop and ensures the stable and efficient operation of the system.

[0034] Please see Figure 7 In this embodiment of the invention, sending the target monitoring dataset to the CAT server for data analysis includes: 701. Obtain the preset communication protocol; 702. Based on the communication protocol, the target monitoring dataset is sent to the CAT server, so that the CAT server can perform data analysis based on the target monitoring dataset and obtain data analysis results; 703. Obtain the data analysis results and optimize the operating parameters of the target business application based on the data analysis results.

[0035] In this embodiment, a preset communication protocol is obtained. The preset communication protocol is the transmission standard agreed upon between the CAT client and the server. It usually adopts a custom private protocol based on TCP, but it is also compatible with HTTP / HTTPS protocols. This protocol supports asynchronous batch data reporting and has the characteristics of high concurrency, low latency, and reliable transmission. It can ensure that the target monitoring dataset is sent stably and efficiently to the CAT server cluster in a distributed scenario.

[0036] In this embodiment, after the target monitoring dataset is sent to the CAT server based on the communication protocol, the CAT server performs multi-dimensional in-depth data analysis on the dataset. The data analysis specifically includes three core operations: performance bottleneck analysis, fault diagnosis, and capacity planning. In the performance bottleneck analysis stage, the call chain tracing function is used to locate slow query and slow service nodes, analyze transaction execution time distribution, and identify system performance bottlenecks. In the fault diagnosis stage, error logs are used to quickly locate the cause of anomalies, and the fault propagation path is analyzed in conjunction with the call chain to verify the effectiveness of fault repair. In the capacity planning stage, historical monitoring data is used to predict system load, analyze resource usage trends, provide data support for system expansion, and simultaneously link with the monitoring configuration optimization stage to match the optimization needs of alarm rules, performance tuning, and visualization configuration. The obtained data analysis results include a performance bottleneck report, a fault diagnosis report, a capacity planning report, and monitoring configuration optimization suggestions. The performance bottleneck report includes the specific nodes, execution time, and distribution of slow queries and slow services; the fault diagnosis report includes the cause of the anomaly, the fault propagation path, and the scope of impact; the capacity planning report includes system load prediction results, resource usage trends, and expansion suggestions; and the monitoring configuration optimization suggestions include alarm threshold adjustments, sampling rate optimization, and visualization panel layout updates.

[0037] After obtaining the data analysis results, optimizations are carried out on the operating parameters of the target business application. These operating parameters are core configurations that directly affect the performance, stability, and resource scheduling of the business application. Specifically, this includes optimizing the SQL statements or business logic corresponding to slow queries, adjusting the service thread pool configuration to improve concurrency processing capabilities, fixing exceptions in the code, adjusting service dependencies to block fault propagation paths, and adjusting the number of service instances to match business load requirements. These parameters directly affect the runtime behavior of the business application, determining business processing efficiency, fault tolerance, and resource utilization efficiency. At the same time, based on the monitoring configuration optimization suggestions, the monitoring system itself is adjusted, including adjusting the data sampling rate according to business characteristics, optimizing the monitoring data storage strategy and data cleaning mechanism, configuring alarm rules based on thresholds and trends, setting up multi-dimensional alarm notification channels, customizing the monitoring panel layout and key business indicator display, and setting the real-time data refresh frequency to achieve coordinated optimization of monitoring configuration and business operation. Relying on the preset communication protocol, the real-time and reliable transmission of monitoring data is guaranteed. The intelligent data analysis of the CAT server can accurately capture the performance problems and potential risks of distributed applications, providing data-driven decision-making basis for optimizing the operating parameters of target business applications. At the same time, the complete monitoring closed loop effectively makes up for the shortcomings of traditional monitoring systems, such as poor real-time performance, single alarm mechanism and low degree of visualization, improves the observability and operation and maintenance efficiency of distributed applications, ensures the stable and efficient operation of the system, and adapts to the complex business monitoring needs under the microservice architecture.

[0038] The monitoring method based on the CAT monitoring system in the embodiments of the present invention has been described above. The monitoring device based on the CAT monitoring system in the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 8 One embodiment of the monitoring device based on the CAT monitoring system in this invention includes: File Acquisition Module 801: Used to acquire the build configuration file for the Branch Manager project; CAT import module 802: Used to import the CAT client dependency package into the build configuration file to obtain the target project; Initialization module 803: Used to perform client initialization configuration processing on the target project to obtain the initial business application; The event tracking module 804 is used to perform multi-dimensional event tracking on the initial business application to obtain the target business application. Data monitoring module 805: used to perform multi-dimensional data monitoring based on the target business application to obtain the target monitoring dataset; Data sending module 806: Used to send the target monitoring dataset to the CAT server for data analysis.

[0039] above Figure 8 The monitoring device based on the CAT monitoring system in this embodiment of the invention will be described in detail from the perspective of modular functional entities. The monitoring equipment based on the CAT monitoring system in this embodiment of the invention will be described in detail from the perspective of hardware processing.

[0040] Figure 9 This is a schematic diagram of the structure of a monitoring device 900 based on a CAT monitoring system according to an embodiment of the present invention. The monitoring device 900 can vary significantly due to different configurations or performance characteristics. It may include one or more central processing units (CPUs) 910 (e.g., one or more processors) and a memory 920, and one or more storage media 930 (e.g., one or more mass storage devices) for storing application programs 933 or data 932. The memory 920 and storage media 930 can be temporary or persistent storage. The program stored in the storage media 930 may include one or more modules (not shown in the diagram), each module including a series of instruction operations on the monitoring device 900 based on the CAT monitoring system. Furthermore, the processor 910 may be configured to communicate with the storage media 930 and execute the series of instruction operations in the storage media 930 on the monitoring device 900 based on the CAT monitoring system to implement the steps of the monitoring method based on the CAT monitoring system provided in the above-described method embodiments.

[0041] The monitoring device 900 based on the CAT monitoring system may also include one or more power supplies 940, one or more wired or wireless network interfaces 950, one or more input / output interfaces 960, and / or one or more operating systems 931, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that... Figure 9 The structure of the monitoring equipment based on the CAT monitoring system shown does not constitute a limitation on the monitoring equipment based on the CAT monitoring system. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0042] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of a monitoring method based on a CAT monitoring system.

[0043] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system, device, or unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0044] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0045] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A monitoring method based on a CAT monitoring system, characterized by, include: Obtain the build configuration file for the Branch Manager project; The target project is obtained by including the CAT client dependency package in the build configuration file. Perform client initialization configuration processing on the target project to obtain the initial business application; The initial business application is processed with multi-dimensional data tracking to obtain the target business application; Based on the target business application, multi-dimensional data monitoring is performed to obtain the target monitoring dataset; The target monitoring dataset is sent to the CAT server for data analysis.

2. The monitoring method based on the CAT monitoring system according to claim 1, characterized in that, The process of introducing the CAT client dependency package into the build configuration file to obtain the target project includes: Within the dependency management area of ​​the build configuration file, build dependency configuration items; Configure the organization identifier parameter, module identifier parameter, and version number parameter in the dependency configuration item to obtain the modified dependency configuration item; Based on the modified dependency configuration items, a project dependency update operation is performed to introduce the CAT client dependency package and obtain the target project.

3. The monitoring method based on the CAT monitoring system according to claim 1, characterized in that, The process of initializing the target project into a client application to obtain the initial business application includes: Initialization logic is introduced into the system startup entry class of the target project; The initialization configuration logic is obtained by configuring a unique business domain identifier parameter in the initialization logic. The initialization configuration logic is executed to establish a communication connection between the target project and the CAT server, thereby obtaining the initial business application.

4. The monitoring method based on the CAT monitoring system according to claim 1, characterized in that, The process of performing multi-dimensional data tracking on the initial business application to obtain the target business application includes: Determine the business processing logic nodes, user operation entry nodes, and business operation indicator nodes of the initial business application; The monitoring logic configuration operation is executed in the business processing logic node, the user operation entry node and the business operation indicator node respectively to obtain the target transaction monitoring logic, the target event monitoring logic and the target indicator collection logic. The target business application is obtained by integrating the target transaction monitoring logic, the target event monitoring logic, and the target indicator collection logic into the initial business application.

5. The monitoring method based on the CAT monitoring system according to claim 4, characterized in that, The step of executing monitoring logic configuration operations in the business processing logic node, the user operation entry node, and the business operation indicator node respectively to obtain target transaction monitoring logic, target event monitoring logic, and target indicator collection logic includes: An initial transaction monitoring logic is introduced into the business processing logic node, and a business type identifier, execution status recording rules, and distributed tracing identifier are configured in the initial transaction monitoring logic to obtain the target transaction monitoring logic; An initial event monitoring logic is introduced into the user operation entry node, and the event type, operation name and execution status are configured in the initial event monitoring logic to obtain the target event monitoring logic; An initial indicator collection logic is introduced into the business operation indicator node, and the indicator name, statistical type and data association mapping rules are configured in the initial indicator collection logic to obtain the target indicator collection logic.

6. The monitoring method based on the CAT monitoring system according to claim 5, characterized in that, The multi-dimensional data monitoring based on the target business application yields a target monitoring dataset, including: Based on the target transaction monitoring logic, system operation data of the target business application is collected; Based on the target event monitoring logic, user behavior data of the target business application is collected; Based on the target indicator collection logic, business operation data of the target business application is collected; By integrating the system operation data, the user behavior data, and the business operation data, an initial monitoring dataset is obtained. The initial monitoring dataset is standardized using a standardization tool to obtain the target monitoring dataset.

7. The monitoring method based on the CAT monitoring system according to claim 1, characterized in that, Sending the target monitoring dataset to the CAT server for data analysis includes: Obtain the preset communication protocol; Based on the communication protocol, the target monitoring dataset is sent to the CAT server, so that the CAT server can perform data analysis based on the target monitoring dataset and obtain data analysis results. Obtain the data analysis results and optimize the operating parameters of the target business application based on the data analysis results.

8. A monitoring device based on a CAT monitoring system, characterized in that, include: File Acquisition Module: Used to retrieve the build configuration file for the Branch Manager project; CAT Import Module: Used to import the CAT client dependency package into the build configuration file to obtain the target project; Initialization module: used to perform client initialization configuration processing on the target project to obtain the initial business application; The event tracking module is used to perform multi-dimensional event tracking on the initial business application to obtain the target business application. Data monitoring module: used to perform multi-dimensional data monitoring based on the target business application to obtain the target monitoring dataset; Data sending module: used to send the target monitoring dataset to the CAT server for data analysis.

9. A monitoring device based on a CAT monitoring system, characterized in that, The monitoring device based on the CAT monitoring system includes: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the monitoring device based on the CAT monitoring system to perform the steps of the monitoring method based on the CAT monitoring system as described in any one of claims 1-7.

10. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement the various steps of the monitoring method based on the CAT monitoring system as described in any one of claims 1-7.

Images