Tracking method for realizing cross-application logs based on SpringBoot

Abstract

The invention discloses a method for realizing cross-application log tracking based on SpringBoot, and relates to the technical field of data processing.The method comprises the steps that an AOP mechanism of the SpringBoot is applied, an inbound request is intercepted, a unique server ID is generated according to a service IP, a port number and a log file path, the MDC context of Slf4j is injected based on the generated unique traceID, the log output format is adjusted, each log automatically carries the traceID, and the tracking efficiency is improved. The server ID is stored in a local file system, the response also comprises the traceID, and the client initiates a query request by means of the traceID, analyzes the server ID and generates a timestamp, and performs local retrieval or forwarding query according to a target service condition. If the log contains the upstream service calling information, a new traceID is extracted for recursive query until the complete link log is obtained, the method has the advantages of being free of centralized storage, low in invasiveness, capable of achieving real-time local retrieval and the like, the operation and maintenance cost is reduced, and the observability of the system is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method for tracing cross-application logs based on SpringBoot. Background Art

[0002] With the widespread application of distributed systems and microservice architectures, the complexity of cross-application calls and the traceability of the system have gradually become prominent. In this architecture, various services communicate through the network, generating a large amount of log data. In the process of troubleshooting, performance analysis and business monitoring, traditional solutions usually rely on centralized logging systems and use log aggregation, storage and analysis tools to track logs. These tools can unify the logs of multiple services, query and display them, greatly improving the efficiency of log analysis. However, these solutions usually bring additional storage and operation and maintenance costs, and when the service scale is large, they may face performance bottlenecks and complex system maintenance challenges. Therefore, it is particularly important to invent a method for tracking cross-application logs based on SpringBoot.

[0003] The existing technology also has the following drawbacks, specifically: 1. In existing technologies, log tracking technology is heavily dependent on external storage. This means that the system needs to maintain a dedicated database to store log information. On the one hand, the introduction of an additional database significantly increases the complexity of the system architecture. On the other hand, database maintenance also involves multiple aspects such as data backup, recovery, and performance optimization, increasing the cost and difficulty of system management. Once a database failure or data loss occurs, the normal operation of the entire log tracking system may be affected.

[0004] 2. Existing log tracking technology has the significant drawback of being highly invasive. To implement log tracking, tracking logic must be explicitly injected into the business code. When business requirements change, not only does the business logic code need to be modified, but the associated tracking logic code must also be modified simultaneously. This increases the difficulty of code maintenance and the risk of errors. Different business systems may have different architectures and implementation methods, resulting in extremely high adaptation costs, which seriously affects development efficiency and project progress.

[0005] 3. Traditional log tracking technology suffers from significant inflexibility. Its log storage format is typically fixed and lacks sufficient scalability. This results in the inability to accurately record and track critical business information in certain situations, impacting the effectiveness and practicality of log tracking. When business needs change, it's difficult to quickly adjust the log storage format, making it difficult for the system to adapt to the ever-changing business environment and limiting its development and application. Summary of the Invention

[0006] The purpose of the present invention is to provide a cross-application log tracing method based on SpringBoot, which solves the problems existing in the background technology.

[0007] To solve the above technical problems, the present invention adopts the following technical solution: The present invention provides a cross-application log tracking method based on SpringBoot, including: Step 1, request interception and identifier generation: intercept inbound requests through SpringBoot's AOP mechanism, and generate or register a unique serverID based on the current service's IP, port number and log file path.

[0008] Step 2: Generate and inject traceID: Generate a unique traceID based on serverID and a specific algorithm, and inject the traceID into the MDC context of Slf4j.

[0009] Step 3: Log output association: Adjust the log output format so that each log automatically carries the traceID, store the log in the local file system, and include the traceID in the response.

[0010] Step 4. Log query processing: The client initiates a query request through the traceID, parses the serverID and generation timestamp. If the target service is the current service, the log file is directly located according to the generation timestamp and log file path, and the log content is retrieved based on the traceID. If the target service is another service, the query request is forwarded to the target service, which performs local log retrieval and returns the results.

[0011] Step 5. Nested call processing: If the log content contains upstream service call information, extract the new traceID and recursively call the log query interface until the complete link log is obtained.

[0012] Preferably, the AOP mechanism of SpringBoot intercepts the method annotated with @Controller or @RequestMapping through the @Around annotation, generates a traceID and injects MDC before the method is executed, and clears the MDC context after the method is executed.

[0013] Preferably, the specific algorithm generates a unique traceID, and the specific implementation method is: encoding and combining the serverID and the timestamp to form a unique string containing the service identifier and time information, and supporting the extraction of the serverID and the generation of the timestamp from the traceID through a reverse parsing algorithm.

[0014] Preferably, the log output format is adjusted, and the specific implementation method is: defining a log format template containing traceID in the log configuration file, obtaining the traceID in the context through MDC and injecting it into a fixed field of each log.

[0015] Preferably, the query request forwarding is specifically implemented by: obtaining the network address of the target service through the service registration and discovery mechanism, constructing an HTTP request containing the traceID and forwarding it to the log query interface of the target service.

[0016] Preferably, the local log retrieval is based on real-time file reading of the file system, and does not require a centralized log storage middleware, and directly retrieves the log containing the traceID in the log file through a string matching algorithm.

[0017] The beneficial effects of the present invention are as follows: 1. The present invention eliminates the need for a centralized log storage component, fundamentally simplifying the system architecture. In terms of hardware resources, there is no need to configure dedicated servers and storage devices for the centralized storage component, reducing hardware procurement and maintenance costs. In terms of software resources, there is no need for complex configuration and optimization of the centralized storage component, which reduces the workload and technical threshold for technicians, avoids the operational and maintenance risks and data loss risks caused by component failures, reduces the difficulty of system maintenance and emergency response costs, and improves resource utilization efficiency and the economic benefits of the enterprise.

[0018] 2. The present invention adopts a local log retrieval method to shorten the query response time. Through the optimized log storage structure and efficient retrieval algorithm, it can quickly locate and filter the required log information locally. Users can obtain query results in a short time, which improves the user experience. At the same time, it has powerful concurrent processing capabilities. In high-concurrency business scenarios, the system can run stably and can meet the log query needs of large-scale business systems, providing strong support for the decision-making and operation of enterprises.

[0019] 3. By leveraging Spring Boot's AOP mechanism and MDC context, this invention enables seamless integration of log tracking functionality without modifying business code. Both newly developed Spring Boot services and existing legacy systems can quickly and easily access the log tracking system of this invention. This greatly facilitates enterprise system upgrades and renovations, lowers the barrier to entry and costs of technology upgrades, and enhances the company's technological competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 The figure is a schematic flow chart of the steps for implementing the method of the present invention. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the present invention provides a cross-application log tracing method based on SpringBoot, including: Step 1, request interception and identification generation: intercepting inbound requests through SpringBoot's AOP mechanism, and generating or registering a unique serverID based on the current service's IP, port number and log file path.

[0024] In a specific embodiment, the AOP mechanism of SpringBoot intercepts the method annotated with @Controller or @RequestMapping through the @Around annotation, generates a traceID and injects MDC before the method is executed, and clears the MDC context after the method is executed.

[0025] This invention leverages Spring Boot's AOP mechanism and MDC context to seamlessly integrate log tracking functionality without modifying business code. Both newly developed Spring Boot services and existing legacy systems can quickly and easily access the log tracking system. This greatly facilitates enterprise system upgrades and renovations, lowers the barrier to entry and costs of technology upgrades, and enhances a company's technological competitiveness.

[0026] Step 2: Generate and inject traceID: Generate a unique traceID based on serverID and a specific algorithm, and inject the traceID into the MDC context of Slf4j.

[0027] In a specific embodiment, the specific algorithm generates a unique traceID, and the specific implementation method is: encoding and combining the serverID and the timestamp to form a unique string containing the service identifier and time information, and supporting the extraction of the serverID and the generation of the timestamp from the traceID through a reverse parsing algorithm.

[0028] Step 3: Log output association: Adjust the log output format so that each log automatically carries the traceID, store the log in the local file system, and include the traceID in the response.

[0029] In a specific embodiment, the log output format is adjusted by defining a log format template including a traceID in a log configuration file, obtaining the traceID in the context through MDC, and injecting it into a fixed field of each log.

[0030] It should be noted that the log format includes the service identifier serverID, request source IP, client user identifier, and business transaction serial number.

[0031] The present invention adopts a local log retrieval method to shorten the query response time. Through the optimized log storage structure and efficient retrieval algorithm, it can quickly locate and filter the required log information locally. Users can obtain query results in a short time, which improves the user experience. At the same time, it has powerful concurrent processing capabilities. In high-concurrency business scenarios, the system can run stably and can meet the log query needs of large-scale business systems, providing strong support for the decision-making and operation of enterprises.

[0032] Step 4. Log query processing: The client initiates a query request through the traceID, parses the serverID and generation timestamp. If the target service is the current service, the log file is directly located according to the generation timestamp and log file path, and the log content is retrieved based on the traceID. If the target service is another service, the query request is forwarded to the target service, which performs local log retrieval and returns the results.

[0033] In a specific embodiment, the query request forwarding is specifically implemented by obtaining the network address of the target service through a service registration and discovery mechanism, constructing an HTTP request containing a traceID, and forwarding it to the log query interface of the target service.

[0034] Step 5. Nested call processing: If the log content contains upstream service call information, extract the new traceID and recursively call the log query interface until the complete link log is obtained.

[0035] In a specific embodiment, the local log retrieval is based on real-time file reading of the file system, and does not require a centralized log storage middleware. The log containing the traceID is directly retrieved in the log file through a string matching algorithm.

[0036] This invention eliminates the need for a centralized log storage component, fundamentally simplifying the system architecture. In terms of hardware resources, there's no need to configure dedicated servers and storage devices for the centralized storage component, reducing hardware procurement and maintenance costs. In terms of software resources, there's no need for complex configuration and optimization of the centralized storage component, reducing the workload and technical barriers for technicians. It also avoids operational and maintenance risks and data loss risks associated with component failures, lowers system maintenance complexity and emergency response costs, and improves resource utilization and the company's economic benefits.

[0037] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A cross-application log tracking method based on SpringBoot, characterized by: include: Step 1: Request interception and identifier generation: intercept inbound requests through SpringBoot's AOP mechanism, and generate or register a unique serverID based on the current service's IP, port number, and log file path; Step 2: Generate and inject traceID: Generate a unique traceID based on serverID and a specific algorithm, and inject the traceID into the MDC context of Slf4j; Step 3: Log output association: Adjust the log output format so that each log automatically carries the traceID, store the log in the local file system, and include the traceID in the response. Step 4: Log query processing: The client initiates a query request using the traceID, parses the serverID and generation timestamp. If the target service is the current service, the log file is directly located based on the generation timestamp and log file path, and the log content is retrieved based on the traceID. If the target service is another service, the query request is forwarded to the target service, which performs local log retrieval and returns the results; Step 5. Nested call processing: If the log content contains upstream service call information, extract the new traceID and recursively call the log query interface until the complete link log is obtained.

2. The method for tracing cross-application logs based on SpringBoot according to claim 1 is characterized in that: The AOP mechanism of SpringBoot intercepts the method annotated with @Controller or @RequestMapping through the @Around annotation, generates a traceID and injects MDC before the method is executed, and clears the MDC context after the method is executed.

3. The method for tracing cross-application logs based on SpringBoot according to claim 1 is characterized in that: The specific algorithm generates a unique traceID, and the specific implementation method is as follows: The serverID and timestamp are encoded and combined to form a unique string containing the service ID and time information. The serverID and timestamp can be extracted from the traceID through a reverse parsing algorithm.

4. The method for tracing cross-application logs based on SpringBoot according to claim 1 is characterized in that: The log output format is adjusted as follows: Define a log format template containing the traceID in the log configuration file, obtain the traceID in the context through MDC, and inject it into the fixed field of each log.

5. The method for tracing cross-application logs based on SpringBoot according to claim 1 is characterized in that: The query request forwarding is specifically implemented as follows: Obtain the network address of the target service through the service registration and discovery mechanism, construct an HTTP request containing the traceID and forward it to the log query interface of the target service.

6. The method for tracing cross-application logs based on SpringBoot according to claim 1 is characterized in that: The local log retrieval is based on real-time file reading of the file system, without the need for a centralized log storage middleware, and directly retrieves the log containing the traceID in the log file through a string matching algorithm.

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