A Dynamic Storage Configuration Method and System Based on KV Database

Abstract

The present invention discloses a dynamic storage configuration method based on a KV database, which includes the following steps: Deploy a KV database and a configuration manager on each node of the distributed system cluster; Set configuration data in the form of key-value pairs required by the service in the KV database; Define a configuration change threshold C_th, continuously monitor the change of the configuration data, bring the configuration data into the historical change rate formula to calculate the current change rate, and when it is detected that the change rate CR exceeds the preset threshold C_th, trigger the configuration update process; Adjust the cache policy and execute the configuration update process; Send instructions to the relevant services or application programs connected to reload the configuration, wherein, the execution of the configuration update process specifically includes the following steps: Read the latest configuration data in the KV database according to the preset configuration template in the configuration manager; Generate a configuration file by combining the configuration template Tpl and the latest configuration data CD; Distribute the generated configuration file to each node of the system cluster.

Description

Technical Field

[0001] The present invention relates to the field of dynamic storage configuration of KV databases, and specifically provides a dynamic storage configuration method and system based on a KV database. Background Art

[0002] With the rapid development of Internet technology, the information age has fully arrived. Under this background, data processing, transmission, and storage have become key technical links. All industries are actively seeking efficient and stable data processing solutions to improve business efficiency and user experience. Especially driven by emerging technologies such as distributed systems, cloud computing, and big data, the demand for data management and configuration update is becoming increasingly urgent, prompting continuous innovation and development in related technical fields.

[0003] In the current technical environment, configuration management and automated deployment have become important means to improve system flexibility and maintainability. Configuration management tools such as Spring Cloud Config are widely used in distributed systems to achieve centralized management and dynamic update of configurations. At the same time, event bus technologies such as Spring Cloud Bus also provide strong support for the propagation and refresh of configurations, making it possible to update configurations without affecting the operation of services.

[0004] When performing configuration updates using current existing technologies, it generally includes the following steps: First, set and store configuration information on the configuration server; Second, the client integrates the configuration management tool and the event bus to receive configuration update notifications; Then, when the configuration changes, send a refresh instruction to all connected clients through the event bus; Finally, after receiving the instruction, the client obtains the latest configuration from the configuration server and reloads it to complete the configuration update process.

[0005] However, traditional systems often lack an efficient caching mechanism and cannot effectively reduce the direct access of configuration data read requests to the configuration server, resulting in high system latency. Especially in high-concurrency scenarios, the load on the configuration server is too heavy, affecting the stable operation of the system. Secondly, existing technologies usually fail to intelligently allocate caching resources and lack a strategy for caching based on the usage frequency of configuration data, resulting in unnecessary cache occupation, low memory usage efficiency, and low resource utilization. In addition, existing technologies often lack a mechanism for regularly evaluating cache efficiency and cannot dynamically adjust the cache strategy according to the evaluation results, making the cache state unable to always remain optimal, further affecting the system performance and resource utilization. Summary of the Invention

[0006] Based on this, the purpose of the present invention is to provide a dynamic storage configuration method and system based on a KV database to solve the technical problem that existing methods have a lot of unnecessary cache occupation.

[0007] In view of the above problems, the present application provides a dynamic storage configuration method and system based on a KV database.

[0008] The present application provides a dynamic storage configuration method based on a KV database, including the following steps: deploying a KV database and a configuration manager on each node of a distributed system cluster; setting configuration data in the form of key-value pairs required by the business in the KV database; defining a threshold C_th for configuration changes, continuously monitoring the changes in the configuration data, and substituting the configuration data into a change rate formula to calculate the current change rate, where the change rate formula is as follows:

[0009]

[0010] where CR represents the current change rate, ΔVal represents the difference between the current configuration value and the previous configuration value, and ΔT represents the time interval between two changes in the configuration value, so as to evaluate the changes in the configuration data; when it is detected that the change rate CR exceeds the preset threshold C_th, trigger the configuration update process; adjust the cache policy and execute the configuration update process; send an instruction to the relevant services or application programs connected to reload the configuration;

[0011] wherein, the execution of the configuration update process specifically includes the following steps: reading the latest configuration data in the KV database according to a preset configuration template in the configuration manager; generating a configuration file by combining the configuration template Tpl and the latest configuration data CD; distributing the generated configuration file to each node of the system cluster.

[0012] In summary, the present invention mainly has the following beneficial effects:

[0013] 1. By introducing a cache sub-module and adopting an LRU cache eviction policy, the system can process read requests for configuration data more efficiently. The cache mechanism reduces the number of direct accesses to the configuration server, thereby reducing system latency and improving overall performance. Especially in high-concurrency scenarios, the adjustment of the cache policy can significantly reduce the load on the configuration server and ensure the stable operation of the system.

[0014] 2. By manually setting a frequency value and caching the parsing results of configuration templates and the latest configuration data higher than this value, the system can allocate cache resources more intelligently. This strategy avoids unnecessary cache occupation, optimizes memory usage, and improves resource utilization. At the same time, regularly evaluating the cache efficiency and adjusting the strategy according to the evaluation results can ensure that the cache always remains in the best state. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the main logic of the present invention;

[0016] Figure 2 This is the logic diagram of step S500 of the present invention. Specific embodiments

[0017] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. The embodiments described below by referring to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention.

[0018] Next, the embodiments of the present invention will be described according to the overall structure of the present invention.

[0019] A dynamic storage configuration method based on a KV database includes the following steps:

[0020] S100: Deploy a KV database and a configuration manager on each node of the distributed system cluster;

[0021] The KV database is a Key-Value database. In a distributed system, in order to improve the scalability, reliability, and performance of the system, services are usually deployed on multiple nodes. The KV database and the configuration manager are common components in a distributed system. The KV database is used to store and manage key-value pair data and has the characteristics of high efficiency and simplicity; the configuration manager is used to centrally manage and distribute configuration information to ensure the consistency and dynamic configuration update of each node.

[0022] Exemplarily, in a distributed system cluster composed of 5 nodes. In order to deploy a KV database and a configuration manager on each node, install the corresponding software, configure the network, and ensure that the nodes can communicate with each other on each node.

[0023] Among them, deploying a KV database and a configuration manager on each node of the distributed system cluster further includes the following steps:

[0024] S110: Select ETCD as the KV database and configure it in cluster mode;

[0025] S120: Ensure the balanced distribution of data in the ETCD cluster through the consistent hashing algorithm to improve data access efficiency.

[0026] ETCD is a highly available distributed key-value storage system and is commonly used for configuration management, service discovery, synchronization, etc. ETCD supports cluster mode, that is, multiple ETCD instances can work together to provide services jointly, thereby improving the reliability and availability of the system. In cluster mode, ETCD selects a leader through a mechanism to be responsible for processing write operations and replicates these operations to other nodes to ensure data consistency.

[0027] The consistent hashing algorithm is a commonly used data distribution strategy in distributed systems. It can ensure the balanced distribution of data in the cluster, reducing problems such as data migration and uneven node loads. In an ETCD cluster, using the consistent hashing algorithm can evenly distribute key-value pairs across each node, thereby improving data access efficiency and avoiding certain nodes becoming hotspots, resulting in performance bottlenecks.

[0028] S200: Set the configuration data in the form of key-value pairs required by the service in the KV database;

[0029] The configuration data in the form of key-value pairs allows us to flexibly store and manage various configuration information. Whether it is simple parameter settings or complex configuration structures, they can be stored in the form of key-value pairs.

[0030] When the service requirements change, update the corresponding key-value pairs in the KV database. The KV database stores data in the form of key-value pairs. Through the key, the corresponding value can be directly located without traversing the entire data set.

[0031] S300: Define the threshold C_th for configuration changes, and continuously monitor the changes in the configuration data. Substitute the configuration data into the change rate formula to calculate the current change rate. The change rate formula is as follows:

[0032]

[0033] Where CR represents the current change rate, ΔVal represents the difference between the current configuration value and the previous configuration value, and ΔT represents the time interval between two changes in the configuration value, so as to evaluate the changes in the configuration data;

[0034] It also includes:

[0035] S310: Obtain the change information of the configuration data by means of regular polling or event triggering;

[0036] S320: Calculate the change rate CR in real time and compare it with the preset threshold C_th to determine whether to trigger the configuration update process.

[0037] First, define a threshold C_th for configuration changes. This threshold is a standard for measuring the degree of change in configuration data. Then continuously monitor the changes in the configuration data to detect and handle abnormal changes in a timely manner. Exemplarily, for the maximum connection number of the configuration parameters of the service component, its normal change range is within 5%. Set C_th to 5%. Then, continuously monitor the changes in this configuration parameter.

[0038] To obtain the change information of the configuration data, we can adopt the methods of regular polling or event triggering. Regular polling means actively querying the current value of the configuration data at regular intervals and comparing it with the previous value. Event triggering means that when the configuration data changes, the system or application triggers an event and notifies the monitoring program of the change information.

[0039] Exemplarily, for the configuration parameter of the maximum number of connections, select to poll its current value every 1 minute and record it in the monitoring system. In another example, configure an event listener. When the "maximum number of connections" changes, the listener will receive a notification and send the change information to the monitoring program.

[0040] After obtaining the change information of the configuration data, calculate the change rate CR in real time. The change rate CR can be calculated by comparing the difference between the current value and the previous value. Then, we compare CR with the preset threshold C_th. If CR exceeds C_th, it means that the configuration data has changed abnormally and the configuration update process needs to be triggered.

[0041] Exemplarily, the value of the maximum number of connections is 100, and the value in the current poll is 110. We can calculate the change rate CR as (110 - 100) / 100 = 10%. Since 10% is greater than the preset threshold of 5%, the configuration update process needs to be triggered.

[0042] S400: When it is detected that the change rate CR exceeds the preset threshold C_th, trigger the configuration update process;

[0043] Among them, it also includes:

[0044] S410: During the process of inputting and modifying the configuration data, perform real-time verification on the user input through regular expressions and logical expressions;

[0045] S420: Use the error detection rate formula to evaluate the input quality, where the error detection rate formula is as follows:

[0046]

[0047] Among them, ER represents the error rate, NE represents the number of incorrect inputs, and TI represents the total number of inputs;

[0048] S430: According to the error rate, retrieve the corresponding error prompts and correction suggestions.

[0049] To prevent users from inputting incorrect or unreasonable data, during the process of inputting and modifying the configuration data, use regular expressions and logical expressions for real-time verification. This can effectively intercept illegal characters, format errors, or logical contradictions.

[0050] Among them, regular expressions and logical expressions are two common types of expressions in programming and data processing.

[0051] Regular expressions, abbreviated as regex, are patterns used to match specific character combinations in strings. They can help us quickly and accurately find, replace, or verify the content in strings. Exemplarily, use regular expressions to find all the numbers in an email address and verify whether an input is a valid mobile phone number.

[0052] Logical expressions, on the other hand, are expressions used to represent logical relationships, including logical operators (such as AND, OR, NOT) and logical variables. The result of a logical expression is usually a boolean value (true or false), used to determine whether a certain condition holds. Exemplarily, in programming, use logical expressions to determine whether a user has permission to access a certain page or the magnitude relationship between two numbers.

[0053] Exemplarily, when a user attempts to set the price of a product, the system will use a regular expression to ensure that the input is a legal number and use a logical expression to check whether the price is within a reasonable range, such as not being lower than the cost price.

[0054] Adopt an error detection rate formula to quantify the error degree of the user input. If the system detects that the price entered by the user is negative or exceeds the preset maximum value, it will calculate the error degree according to the error detection rate formula and decide whether to allow saving or prompt the user to correct it based on this. Optionally, the system intelligently provides error prompts and correction suggestions according to the result of the error detection rate. This helps the user quickly locate the problem and make corrections with reference to the suggestions.

[0055] Among them, the above-mentioned intelligence corresponds to the input text content recognized by combining cloud data or a preset response text database and retrieves the corresponding text and outputs the retrieved text.

[0056] S500: Adjust the cache policy and execute the configuration update process;

[0057] Among them, the adjustment of the cache policy includes the following steps:

[0058] S511: Introduce a cache sub-module in the configuration manager and use the LRU cache eviction policy, where LRU stands for Least Recently Used;

[0059] S512: Manually set the frequency value;

[0060] S513: Cache the parsing results and the latest configuration data of the configuration templates higher than the frequency value;

[0061] S514: Regularly evaluate the cache efficiency using the cache hit rate formula and adjust the cache policy according to the evaluation results. Among them, the cache hit rate formula is as follows:

[0062]

[0063] Among them, HR represents the cache hit rate, NH represents the number of cache hits, and TR represents the total number of requests.

[0064] The cache sub-module is used to store frequently accessed configuration data. When the cache reaches the preset size according to the LRU policy, it will automatically evict the least recently used cache item to make room for storing new data.

[0065] A frequency value is manually set to determine which parsing results of configuration templates and the latest configuration data need to be cached. This frequency value can be adjusted according to actual business requirements and system performance.

[0066] The system will cache the parsing results of configuration templates and the latest configuration data whose access frequency is higher than this value according to the set frequency value. This can ensure that frequently accessed configuration data can be quickly retrieved from the cache, improving system performance.

[0067] The cache efficiency is regularly evaluated using the cache hit rate formula. If the cache hit rate is low, it indicates that the cache policy may need to be adjusted, such as increasing the cache size, adjusting the frequency value, etc. By continuously optimizing the cache policy, system performance and resource utilization can be improved.

[0068] Among them, the execution of the configuration update process specifically includes the following steps:

[0069] S521: Read the latest configuration data in the KV database according to the preset configuration template in the configuration manager;

[0070] S522: Generate a configuration file by combining the configuration template Tpl and the latest configuration data CD;

[0071] S523: Distribute the generated configuration file to each node of the system cluster.

[0072] When the configuration data is updated, the configuration manager will read the latest configuration data from the KV database according to the preset configuration template to ensure that the configuration manager always obtains the latest configuration information.

[0073] The configuration manager will combine the read latest configuration data with the configuration template to generate a new configuration file. This configuration file will contain all the configuration information required by the system. Use Confd as the configuration manager and configure its parameters to read configuration data from ETCD. This can ensure that Confd can correctly obtain configuration data from ETCD. Among them, ETCD is a distributed key-value storage system.

[0074] Among them, S522 also includes:

[0075] S522-1: The configuration manager selects Confd and configures its parameters for reading configuration data from ETCD.

[0076] S522-2: Utilize the concurrency control mechanism of Confd to manage the generation and distribution process of configuration files.

[0077] During the process of generating and distributing configuration files, the concurrency control mechanism of Confd is used to ensure that multiple nodes do not simultaneously attempt to modify the same configuration file, thus avoiding conflicts and data inconsistency issues. Finally, the configuration manager distributes the generated configuration files to each node of the system cluster. In this way, each node can obtain the latest configuration information and make corresponding adjustments and optimizations based on this information.

[0078] S600: Send instructions to the connected relevant services or application programs to reload the configuration.

[0079] A dynamic storage configuration system based on a KV database, which is used to carry and run all the above steps. This system includes:

[0080] KV database module, which is used to store system configuration data in the form of key-value pairs, supports the cluster mode, and ensures the balanced distribution of data through the consistent hashing algorithm.

[0081] Cache sub-module, as part of the configuration manager module, uses the LRU algorithm to cache the parsing results of common configuration templates and the latest configuration data to reduce the direct access times to the KV database and improve the efficiency of configuration generation and distribution.

[0082] Preferably, it also includes:

[0083] Configuration manager module, which is connected to the KV database module and is used to execute the configuration update process, including reading the latest configuration data from the KV database according to the preset configuration template, generating configuration files and distributing them to each node of the system cluster, and at the same time supporting the concurrency control mechanism to improve efficiency.

[0084] Configuration verification module, which is used to perform real-time verification during the input and modification of configuration data, provide error prompts and correction suggestions to ensure the correctness of configuration data.

[0085] Preferably, it also includes:

[0086] Monitoring and warning module, which is used to continuously monitor the running status of the KV database and the configuration manager, discover potential problems through predefined performance metrics and warning rules, and perform corresponding operations or send warning notifications when faults or anomalies are detected.

[0087] The template management sub-module, as part of the configuration manager module, is used to manage and maintain configuration templates to ensure that the templates can be correctly parsed and applied when generating configuration files.

[0088] Preferably, it further includes:

[0089] The front-end page or API interface module is used to provide an interface for operation and maintenance personnel to input and modify configuration data, and supports data verification logic to ensure the correct input and modification of configuration data;

[0090] The log recording sub-module, as part of the monitoring and alerting module, is used to record key events and exception information during the operation of the system for fault troubleshooting and performance analysis.

[0091] A computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements a method for inverting and assembling tree-structured data; an electronic device includes a processor and a memory, and the memory stores a computer program, and when the computer program is executed by the processor, it implements a method for inverting and assembling tree-structured data.

[0092] Those of ordinary skill in the art can understand that the various numerical numbers such as the first and second involved in this application are only for the convenience of description and are not used to limit the scope of this application, nor do they represent the order of precedence. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one" means one or more. At least two means two or more. "At least one", "any one" or their similar expressions refer to any combination of these items, including any combination of single item (s) or plural item (s). For example, at least one (piece, kind) of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, c can be single or multiple.

[0093] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in this application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0094] The steps of the methods or algorithms described in this application can be directly embedded in hardware, software units executed by a processor, or a combination of both. The software units can be stored in a RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium in the art. Exemplarily, the storage medium can be connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and the storage medium can be provided in an ASIC, and the ASIC can be provided in a terminal. Optionally, the processor and the storage medium can also be provided in different components of the terminal. These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, thereby providing instructions executed on the computer or other programmable device for implementing the steps specified in Figure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0095] Although this application has been described in conjunction with specific features and their embodiments, it is obvious that various modifications and combinations can be made without departing from the spirit and scope of this application. Accordingly, this specification and the drawings are only exemplary descriptions of this application and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art can make various changes and modifications to this application without departing from the scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application is intended to include these changes and modifications.

Claims

1. A dynamic storage configuration method based on KV database, characterized in that: The following steps are involved: Deploy the KV database and configuration manager on each node of the distributed system cluster; Set the configuration data in the form of key-value pairs required by the business in the KV database; Define the configuration change threshold C_th, and continuously monitor the changes in configuration data. Substitute the configuration data into the change rate formula to calculate the current change rate. The change rate formula is as follows: Among them, CR represents the current change rate, ΔVal represents the difference between the current configuration value and the previous configuration value, and ΔT represents the time interval between two configuration value changes, which is used to evaluate the change of configuration data; When it is detected that the change rate CR exceeds the preset threshold C_th, the configuration update process is triggered; Adjust cache strategy and execute configuration update process; Send instructions to connected services or applications to reload configuration; The execution configuration update process specifically includes the following steps: In the configuration manager, read the latest configuration data in the KV database according to the preset configuration template; Generate a configuration file by combining the configuration template Tpl and the latest configuration data CD; Distribute the generated configuration file to each node in the system cluster; The adjusting the cache strategy also includes: Introduced a cache submodule in the configuration manager and used the LRU cache eviction strategy, where LRU stands for Least Recently Used; Manually set the frequency value; Cache the parsing results and latest configuration data of configuration templates that are higher than the frequency value; Use the cache hit rate formula to regularly evaluate cache efficiency and adjust the cache strategy based on the evaluation results. The cache hit rate formula is as follows: Among them, HR represents the cache hit rate, NH represents the number of cache hits, and TR represents the total number of requests; The execution configuration update process specifically includes the following steps: S521: Reading the latest configuration data in the KV database according to a preset configuration template in the configuration manager; S522: Generate a configuration file by combining the configuration template Tpl and the latest configuration data CD; S523: Distribute the generated configuration file to each node of the system cluster; S522 also includes: S522-1: The configuration manager selects Confd and configures its parameters for reading configuration data from ETCD; S522-2: Use the concurrency control mechanism of Confd to manage the generation and distribution process of configuration files.

2. The dynamic storage configuration method based on the KV database according to claim 1 is characterized in that: The deployment of the KV database and configuration manager on each node of the distributed system cluster includes: Select ETCD as the KV database and configure it in cluster mode; The consistent hashing algorithm ensures balanced distribution of data in the etcd cluster and improves data access efficiency.

3. The dynamic storage configuration method based on KV database according to claim 2 is characterized in that: The configuration change threshold C_th is defined, and the configuration data change is continuously monitored, and the configuration data is brought into the change rate formula to calculate the current change rate, including: Use periodic polling or event triggering to obtain configuration data change information; The change rate CR is calculated in real time and compared with the preset threshold C_th to determine whether the configuration update process needs to be triggered.

4. The dynamic storage configuration method based on KV database according to claim 1 is characterized in that: When the change rate CR is detected to exceed a preset threshold value C_th, the configuration update process is triggered, including: During the process of entering and modifying configuration data, user input is verified in real time through regular expressions and logical expressions; The error detection rate formula is used to evaluate the input quality, where the error detection rate formula is as follows: Among them, ER represents the error rate, NE represents the number of incorrect inputs, and TI represents the total number of inputs; According to the error rate, the corresponding error prompts and correction suggestions are retrieved.

5. The dynamic storage configuration method based on KV database according to claim 1 is characterized in that: The step of combining the configuration template Tpl and the latest configuration data CD to generate a configuration file includes: The configuration manager selects Confd and configures its parameters for reading configuration data from etcd; Use Confd's concurrency control mechanism to manage the generation and distribution of configuration files.

6. A dynamic storage configuration system based on KV database, characterized in that: The system is used to carry and run the steps of a dynamic storage configuration method based on a KV database according to any one of claims 1 to 5 above, and the system includes: The KV database module is used to store system configuration data in the form of key-value pairs, supports high availability, high concurrency and strong consistency cluster mode, and ensures balanced data distribution through consistent hashing algorithm; The cache submodule, as part of the configuration manager module, uses the LRU algorithm to cache the parsing results and the latest configuration data of commonly used configuration templates to reduce the number of direct accesses to the KV database and improve the efficiency of configuration generation and distribution.

7. A dynamic storage configuration system based on KV database according to claim 6, characterized in that: Also includes: The configuration manager module is connected to the KV database module and is used to execute the configuration update process, including reading the latest configuration data in the KV database according to the preset configuration template, generating configuration files and distributing them to each node of the system cluster, and supporting concurrency control mechanisms to improve efficiency; The configuration verification module is used to perform real-time verification during the entry and modification of configuration data, provide error prompts and correction suggestions, and ensure the correctness of the configuration data.

8. A dynamic storage configuration system based on KV database according to claim 7, characterized in that: Also includes: The monitoring and alarm module is used to continuously monitor the operating status of the KV database and configuration manager, discover potential problems through predefined performance indicators and alarm rules, and perform corresponding operations or send alarm notifications when failures or anomalies are detected; The template management submodule, as part of the configuration manager module, is used to manage and maintain configuration templates to ensure that templates can be correctly parsed and applied when generating configuration files.

9. A dynamic storage configuration system based on a KV database according to claim 6, characterized in that: include: The front-end page or API interface module is used to provide operation and maintenance personnel with an interface for entering and modifying configuration data, and supports data verification logic to ensure the correct entry and modification of configuration data; The logging submodule, as part of the monitoring and alarm module, is used to record key events and abnormal information during system operation for troubleshooting and performance analysis.

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