Call chain monitoring system and method

Abstract

The present invention provides a call chain monitoring system and method, which can be used in the field of distributed technology. The system includes: a distributed microservice subsystem, which is used to obtain the call relationship data between microservices for each business request, generate a call chain log corresponding to each business request, and paste the source deployment group information in the call chain log, and push the call chain log after pasting the source to Kafka of the product operation monitoring subsystem; product operation monitoring subsystem: Kafka, which is used to store the call chain log; a parsing module, which is used to query the information of each call link from the unitized code table based on the deployment group information of the source pasted in the call chain log, paste the source of each call link information queried to the call chain log, form the parsed call chain log and store it back to Kafka; a calculation module, which is used to calculate and display indicator data and store it back to Kafka; an operation and maintenance service end module, which is used to generate call relationship data. The present invention can monitor the call chain of multiple call links.

Description

Technical Field

[0001] The present invention relates to the field of distributed technology, and in particular to a call chain monitoring system and method. Background Art

[0002] In large enterprises such as banks, in order to adapt to the processing needs of massive data and massive transactions, some products (such as core banking) will adopt a "microservice + unitized" deployment architecture. Under the unitized architecture, business data is divided into multiple units, each service will deploy multiple units, and each transaction is routed to a specific unit based on certain customer factors (such as core customer numbers). Therefore, when tracking call relationship data, it is necessary not only to know which services the transaction passes through, but also to know the deployment unit where the service is located. Traditional call chain tracking tools can only reflect which microservices a transaction passes through, but cannot reflect the unit and product to which the microservice belongs, which is not conducive to the operation and maintenance personnel to accurately locate the problem. Summary of the invention

[0003] The embodiment of the present invention provides a call chain monitoring system for monitoring a call chain of multiple call links. The system includes:

[0004] Distributed microservice subsystem and product operation monitoring subsystem; among them,

[0005] The distributed microservice subsystem is used to obtain the call relationship data between microservices for each business request, generate the call chain log corresponding to each business request, and paste the source deployment group information in the call chain log, and push the call chain log with the source to Kafka of the product operation monitoring subsystem;

[0006] The product operation monitoring subsystem includes Kafka, parsing module, computing module and operation and maintenance server module. Kafka is used to store call chain logs.

[0007] The parsing module is used to extract the call chain log from Kafka; based on the deployment group information attached to the call chain log, query the information of each call link from the unitized code table, attach the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka. The unitized code table is used to store the association relationship between each call link;

[0008] The calculation module is used to calculate and display indicator data based on the parsed call chain log and store it back to Kafka;

[0009] The operation and maintenance server module is used to generate call relationship data based on the parsed call chain logs and indicator data.

[0010] An embodiment of the present invention provides a call chain monitoring method for monitoring a call chain of multiple call links. The method includes:

[0011] Extract the call chain log from Kafka. The call chain log is the distributed microservice subsystem that obtains the call relationship data between microservices for each business request, generates a call chain log corresponding to each business request, and pastes the source deployment group information in the call chain log. Then, the call chain log with the source pasted is pushed to Kafka.

[0012] Based on the deployment group information of the source in the call chain log, query the information of each call link from the unitized code table, paste the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka. The unitized code table is used to store the association relationship between each call link;

[0013] According to the parsed call chain log, calculate and display indicator data and store it back to Kafka;

[0014] Generate call relationship data based on the parsed call chain logs and indicator data.

[0015] An embodiment of the present invention further proposes a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned call chain monitoring method when executing the computer program.

[0016] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for executing the above-mentioned call chain monitoring method.

[0017] In an embodiment of the present invention, a distributed microservice subsystem is used to obtain the call relationship data between microservices for each business request, generate a call chain log corresponding to each business request, and paste the source deployment group information in the call chain log, and push the call chain log after pasting the source to Kafka of the product operation monitoring subsystem; the product operation monitoring subsystem includes Kafka, a parsing module, a computing module and an operation and maintenance server module, wherein Kafka is used to store the call chain log; the parsing module is used to extract the call chain log from Kafka; based on the deployment group information pasted in the call chain log, the information of each call link is queried from the unitized code table, and the queried information of each call link is pasted to the call chain log to form a parsed call chain log and store it back to Kafka, and the unitized code table is used to store the association relationship between each call link; the computing module is used to calculate and display indicator data according to the parsed call chain log and store it back to Kafka; the operation and maintenance server module is used to generate call relationship data according to the parsed call chain log and indicator data. In the above process, the call chain log corresponding to each business request can be obtained. By attaching the information of each call link, the call chain log can track the call links and indicator data involved in each business request, thereby realizing multi-call link tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] 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 prior art descriptions. 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 creative work. In the drawings:

[0019] Figure 1 A schematic diagram of a call chain monitoring system according to an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of a call chain monitoring system in an embodiment of the present invention;

[0021] Figure 3 Another schematic diagram of the call chain monitoring system in an embodiment of the present invention;

[0022] Figure 4 This is an example of a call chain log after pasting the source in an embodiment of the present invention;

[0023] Figure 5 This is an example of a parsed call chain log in an embodiment of the present invention;

[0024] Figure 6 An example of display indicator data calculated in an embodiment of the present invention;

[0025] Figure 7 A schematic diagram of call relationship data of a tree link structure in an embodiment of the present invention;

[0026] Figure 8 A schematic diagram of call relationship data of a table structure in an embodiment of the present invention;

[0027] Fig. 9 A schematic diagram of call relationship data of a unit-level topological structure in an embodiment of the present invention;

[0028] Fig.10 A schematic diagram of call relationship data of a microservice-level topology structure in an embodiment of the present invention;

[0029] Fig.11 A flowchart of a call chain monitoring method according to an embodiment of the present invention;

[0030] Fig.12 Schematic diagram of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0032] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps is not limited and can be appropriately adjusted as needed.

[0033] First, the terms involved in the present invention are explained.

[0034] Call chain: In a distributed microservice architecture, a transaction will be processed by multiple microservices. Call chain tracing technology can obtain the tree relationship of calls between services in a transaction through traceid and spanid mechanisms, so as to quickly locate problems and understand the dependency topology between services.

[0035] TraceId: A unique ID used to identify each call chain, called a call chain ID. TraceId is passed throughout the call chain and remains unchanged.

[0036] SpanId: Each link in the call chain is a Span. Each Span has a SpanId to identify it, called a link identifier. A parent-child relationship is formed between the previous and next spans. A link can be an application, microservice, or unit.

[0037] Unitized architecture: Unitized architecture takes the unit as the basic unit of system deployment. Several units are deployed in all computer rooms of the entire site. The number of units in each computer room is not fixed. Any unit is deployed with all the core business applications required by the system, and the data is a part of the full data divided according to a certain dimension (or multiple dimensions).

[0038] Unit: Also known as DCN (Data Center Node), refers to a self-contained set that can complete all core (critical) business operations. This set includes all services required for the core business and the data assigned to this unit. It can be generally understood that a DCN is an online virtual branch of a bank, which only carries a part of the customers of a certain business of the bank. Different data is divided into different DCNs through certain data sharding keys (such as customer number, institution number, business field, etc.) and sharding rules (such as segmentation, hash, random, minimum number of customers, etc.). Once the data carried by a DCN reaches the specified upper limit, the capacity can be expanded horizontally by deploying a new DCN to ensure the continuous and rapid development of the business.

[0039] Deployment group: It is a logical concept for TSF to perform batch deployment of applications. A deployment group includes multiple application instances, and the same application runs on each application instance.

[0040] TSF: Tencent Service Framework, Tencent distributed microservice framework, is a PaaS platform centered around applications and microservices, providing functions such as application full life cycle management, data-based operations and three-dimensional monitoring. In the present invention, when the application is deployed to the TSF platform, the TSF platform obtains the service call chain based on zipkin and pushes the call chain log (Tracelog) to POMP for subsequent processing.

[0041] POMP: A product operation monitoring platform developed by the enterprise, which includes a call chain monitoring function. In the present invention, POMP performs secondary processing based on the tracelog delivered by TSF to provide users with a call chain monitoring function that adapts to the unitized architecture.

[0042] Product: An enterprise-specific concept, referring to a system that provides certain functions or services to the outside world. A product usually contains multiple modules (corresponding to multiple services in operation). Under the unitized architecture, a product will be deployed in multiple units, and all microservices of the product will be deployed in each unit.

[0043] Figure 1 Schematic diagram of a call chain monitoring system in an embodiment of the present invention. Figure 1 As shown, the system includes: a distributed microservice subsystem 101 and a product operation monitoring subsystem 102; wherein,

[0044] The distributed microservice subsystem 101 is used to obtain the call relationship data between microservices for each business request, generate a call chain log corresponding to each business request, paste the source deployment group information in the call chain log, and push the call chain log with the source pasted to Kafka of the product operation monitoring subsystem;

[0045] The product operation monitoring subsystem 102 includes Kafka 1021, a parsing module 1022, a computing module 1023 and an operation and maintenance server module 1024, wherein:

[0046] Kafka1021, used to store call chain logs;

[0047] The parsing module 1022 is used to extract the call chain log from Kafka; based on the deployment group information of the call chain log, query the information of each call link from the unitized code table, paste the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka, and the unitized code table is used to store the association relationship between each call link;

[0048] The calculation module 1023 is used to calculate the display indicator data according to the parsed call chain log and store it back to Kafka;

[0049] The operation and maintenance server module 1024 is used to generate call relationship data based on the parsed call chain log and indicator data.

[0050] When implementing it specifically, Figure 2 This is a schematic diagram of the call chain monitoring system in the embodiment of the present invention. The distributed microservice subsystem is developed based on the TSF platform, and the product operation monitoring subsystem is developed based on POMP. The distributed microservice subsystem is based on Zipkin point tracking to obtain the call relationship data between microservices for each business request.

[0051] Figure 3 10 is another schematic diagram of the call chain monitoring system in an embodiment of the present invention. In one embodiment, the product operation monitoring subsystem further includes an operation and maintenance display terminal module 1025 for displaying the call relationship data.

[0052] In one embodiment, the call relationship data includes a call chain identifier traceid and a link identifier spanid of each call link in the call chain;

[0053] The call relationship data is represented by at least one of the following structures: a tree link structure, a topological structure, and a table structure.

[0054] In one embodiment, the display indicators include the average response time and / or average success rate of each calling link.

[0055] When calculating the display indicators, they are aggregated by dimension to form indicator data per second, which can be based on the calling link dimension, for example, including the average response time and / or average success rate of microservices, and the average response time and / or average success rate of units.

[0056] In one embodiment, the system further includes an automatic deployment subsystem 103, which is used to reference the SDK provided by the distributed microservice subsystem to deploy the application of each product to the distributed microservice subsystem.

[0057] In one embodiment, the product operation monitoring subsystem further includes a configuration management module 1026 for storing the unitized code table.

[0058] In one embodiment, the system further includes a unitized management subsystem 104 for establishing a unitized deployment model of a product and pushing it to a unitized code table of a configuration management module of a product operation monitoring subsystem.

[0059] The above push process is carried out in real time to ensure data synchronization.

[0060] The above-mentioned unitized deployment model can be established by guiding the user through page navigation.

[0061] In one embodiment, the product operation monitoring subsystem further includes a storage module 1027, which is used to read the parsed call chain log and indicator data from Kafka and persist them in ES for storage;

[0062] The operation and maintenance server module is specifically used to query the parsed call chain logs and indicator data from ES and form call relationship data.

[0063] In the above embodiment, the call relationship data can not only reflect the call relationship between microservices, but also accurately identify the unit and product where the microservice is located.

[0064] In one embodiment, the calling links include cluster, product, unit, deployment group and application. Of course, it is understandable that there may be other calling links, such as region, etc.

[0065] A specific embodiment is given below to illustrate the specific application of the system proposed by the present invention.

[0066] First, the unitized management subsystem pushes the unitized deployment model of each product to the unitized code table of the configuration management module of the product operation monitoring subsystem.

[0067] The distributed microservice subsystem obtains the call relationship data between microservices for each business request, generates the call chain log tracelog corresponding to each business request, and pastes the source deployment group information in the call chain log, and then pushes the call chain log tracelog with the source pasted to Kafka of the product operation monitoring subsystem. For an example of the call chain log with the source pasted, see Figure 4 .

[0068] The parsing module extracts the call chain log from Kafka; based on the deployment group information in the call chain log, it queries the information of each call link (unit, product, etc.) from the unitized code table, and pastes the queried information of each call link to the call chain log to form a parsed call chain log and store it back to Kafka. For an example of the parsed call chain log, see Figure 5 .

[0069] The calculation module calculates the display indicator data per second based on the parsed call chain log and stores it back to Kafka, such as the average processing time per second and the average success rate per second of serviceA. For an example of the calculated display indicator data, see Figure 6 .

[0070] The operation and maintenance server module generates call relationship data with a tree link structure based on the parsed call chain log and indicator data. Each time a business request passes through a microservice, the microservice will print a call chain log as a client and as a server, and record traceid, spanid, and parentspanid (call link identifier of the parent call link) in each call chain log. Figure 7 This is a schematic diagram of the call relationship data of the tree link structure in the embodiment of the present invention, which can display the call relationship between the passed microservices (service1, service2, service3, service4, service5), the units and products to which the microservices belong, and the average response time of each microservice. In this way, when a microservice is deployed in multiple units, it can be known in which unit the microservice that failed the transaction is located, so as to facilitate the operation and maintenance personnel to accurately troubleshoot the problem.

[0071] Figure 8 Schematic diagram of call relationship data of a table structure in an embodiment of the present invention. Fig. 9 is a schematic diagram of call relationship data of a unit-level topological structure in an embodiment of the present invention, Fig.10 It is a schematic diagram of the call relationship data of the topological structure of the microservice level in an embodiment of the present invention.

[0072] It can be seen that the system proposed in the embodiment of the present invention can display multiple levels of call relationship data.

[0073] To sum up, in the system proposed in the embodiment of the present invention, the distributed microservice subsystem is used to obtain the call relationship data of each business request between microservices, generate a call chain log corresponding to each business request, and paste the source deployment group information in the call chain log, and push the call chain log after pasting the source to Kafka of the product operation monitoring subsystem; the product operation monitoring subsystem includes Kafka, a parsing module, a computing module and an operation and maintenance server module, wherein Kafka is used to store the call chain log; the parsing module is used to extract the call chain log from Kafka; based on the deployment group information of the source pasted in the call chain log, query the information of each call link from the unitized code table, paste the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka, and the unitized code table is used to store the association relationship between each call link; the computing module is used to calculate and display indicator data according to the parsed call chain log and store it back to Kafka; the operation and maintenance server module is used to generate call relationship data according to the parsed call chain log and indicator data. In the above process, the call chain log corresponding to each business request can be obtained. By attaching the information of each call link, the call chain log can track the call links and indicator data involved in each business request, thereby realizing multi-call link tracking.

[0074] The embodiment of the present invention further proposes a call chain monitoring method, the principle of which is similar to that of the call chain monitoring system and will not be described in detail here.

[0075] Fig.11 This is a flowchart of a call chain monitoring method in an embodiment of the present invention, which specifically includes:

[0076] Step 1101, extracting the call chain log from Kafka, wherein the distributed microservice subsystem obtains the call relationship data between microservices for each business request, generates a call chain log corresponding to each business request, and pastes the source deployment group information in the call chain log, and then pushes the call chain log after the source is pasted to Kafka;

[0077] Step 1102: Based on the deployment group information of the call chain log, query the information of each call link from the unitized code table, paste the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka. The unitized code table is used to store the association relationship between each call link.

[0078] Step 1103: Calculate display indicator data based on the parsed call chain log and store it back to Kafka;

[0079] Step 1104, generating call relationship data according to the parsed call chain log and indicator data.

[0080] In one embodiment, the method further comprises:

[0081] The call relationship data is displayed.

[0082] In one embodiment, the call relationship data includes a call chain identifier and a link identifier of each call link in the call chain;

[0083] The call relationship data is represented by at least one of the following structures: a tree link structure, a topological structure, and a table structure.

[0084] In one embodiment, the display indicators include the average response time and / or average success rate of each calling link.

[0085] In one embodiment, the method further comprises:

[0086] Deploy the applications of each product.

[0087] In one embodiment, the method further comprises storing a unitized code table.

[0088] In one embodiment, the method further comprises:

[0089] Establish a unitized deployment model for the product and store it in a unitized code table.

[0090] In one embodiment, the method further comprises:

[0091] Read the parsed call chain logs and indicator data from Kafka and persist them in ES for storage;

[0092] Query the parsed call chain logs and indicator data from ES and form call relationship data.

[0093] In one embodiment, the calling link includes clusters, products, units, deployment groups and applications.

[0094] In summary, in the method proposed in the embodiment of the present invention, a call chain log is extracted from Kafka, and the call chain log is a distributed microservice subsystem that obtains the call relationship data between microservices for each business request, generates a call chain log corresponding to each business request, and pastes the source deployment group information in the call chain log, and then pushes the call chain log after the source is pasted to Kafka; based on the deployment group information of the source in the call chain log, the information of each call link is queried from the unitized code table, and the queried information of each call link is pasted to the call chain log to form a parsed call chain log and store it back to Kafka, and the unitized code table is used to store the association relationship between each call link; according to the parsed call chain log, the display indicator data is calculated and stored back to Kafka; according to the parsed call chain log and the indicator data, the call relationship data is generated. In the above process, the call chain log corresponding to each business request can be obtained, and by pasting the information of each call link, the call chain log can track the call links and indicator data involved in each business request, and realize multi-call link tracking.

[0095] An embodiment of the present invention further provides a computer device, Fig.12 Schematic diagram of a computer device in an embodiment of the present invention. The computer device can implement all steps in the call chain monitoring method in the above embodiment. The computer device specifically includes the following contents:

[0096] Processor (processor) 1201, memory (memory) 1202, communication interface (CommunicationsInterface) 1203 and communication bus 1204;

[0097] The processor 1201, the memory 1202, and the communication interface 1203 communicate with each other through the communication bus 1204; the communication interface 1203 is used to realize information transmission between relevant devices such as the server-side device, the detection device, and the user-side device;

[0098] The processor 1201 is used to call the computer program in the memory 1202, and when the processor executes the computer program, all the steps in the call chain monitoring method in the above embodiment are implemented.

[0099] An embodiment of the present invention also provides a computer-readable storage medium that can implement all the steps in the call chain monitoring method in the above embodiment. The computer-readable storage medium stores a computer program, which implements all the steps of the call chain monitoring method in the above embodiment when executed by a processor.

[0100] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program business systems. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program business system implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0101] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program business systems according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0102] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0103] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0104] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A call chain monitoring system, characterized in that: include: Distributed microservice subsystem and product operation monitoring subsystem; among them, The distributed microservice subsystem is used to obtain the call relationship data between microservices for each business request, generate the call chain log corresponding to each business request, and paste the source deployment group information in the call chain log, and push the call chain log with the source to Kafka of the product operation monitoring subsystem; The product operation monitoring subsystem includes Kafka, parsing module, computing module and operation and maintenance server module. Kafka, used to store call chain logs; The parsing module is used to extract the call chain log from Kafka; based on the deployment group information attached to the call chain log, query the information of each call link from the unitized code table, attach the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka. The unitized code table is used to store the association relationship between each call link; The calculation module is used to calculate and display indicator data based on the parsed call chain log and store it back to Kafka; The operation and maintenance server module is used to generate call relationship data based on the parsed call chain logs and indicator data; The product operation monitoring subsystem also includes a configuration management module for storing unitized code tables; The system also includes a unitized management subsystem for establishing a unitized deployment model of a product and pushing it to a unitized code table of a configuration management module of a product operation monitoring subsystem.

2. The call chain monitoring system according to claim 1, characterized in that: The product operation monitoring subsystem also includes an operation and maintenance display terminal module, which is used to display the call relationship data.

3. The call chain monitoring system according to claim 1, characterized in that: The call relationship data includes a call chain identifier and a link identifier of each call link in the call chain; The call relationship data is represented by at least one of the following structures: a tree link structure, a topological structure, and a table structure.

4. The call chain monitoring system according to claim 1, characterized in that: The display indicators include the average response time and / or average success rate of each calling link.

5. The call chain monitoring system according to claim 1, characterized in that: It also includes an automatic deployment subsystem, which is used to reference the SDK provided by the distributed microservice subsystem and deploy the applications of each product to the distributed microservice subsystem.

6. The call chain monitoring system according to claim 1, characterized in that: The product operation monitoring subsystem also includes a storage module, which is used to read the parsed call chain logs and indicator data from Kafka and persist them in ES for storage; The operation and maintenance server module is specifically used to query the parsed call chain logs and indicator data from ES and form call relationship data.

7. The call chain monitoring system according to claim 1, characterized in that: The calling process includes clusters, products, units, deployment groups and applications.

8. A call chain monitoring method, characterized in that: include: Extract the call chain log from Kafka. The call chain log is the distributed microservice subsystem that obtains the call relationship data between microservices for each business request, generates a call chain log corresponding to each business request, and pastes the source deployment group information in the call chain log. Then, the call chain log with the source pasted is pushed to Kafka. Based on the deployment group information of the source in the call chain log, query the information of each call link from the unitized code table, paste the queried information of each call link to the call chain log, form a parsed call chain log and store it back to Kafka. The unitized code table is used to store the association relationship between each call link; According to the parsed call chain log, calculate and display indicator data and store it back to Kafka; Generate call relationship data based on the parsed call chain log and indicator data; The method further comprises storing a unitized code table; The method further comprises: Establish a unitized deployment model for the product and store it in a unitized code table.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method of claim 8 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for executing the method of claim 8.

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