Real-time intelligent operation and maintenance method and intelligent operation and maintenance system

Abstract

The invention relates to a real-time intelligent operation and maintenance method and an intelligent operation and maintenance system, the method is used for the intelligent operation and maintenance system, and the intelligent operation and maintenance system comprises a Kafka unit, an intelligent agent set unit and an RCA-Agent unit which are connected in sequence; the method comprises the following steps: actively reporting batch logs to enable a Kafka unit to contain the batch logs; consuming a batch log of the Kafka unit, and extracting text key content; based on the text key content, the agent set unit generates unified context information and sends the unified context information to the RCA-Agent unit; and generating a solution according to the unified context information, and storing the solution in a local knowledge base. The existing scheme can only solve surface problems and current problems, cannot prevent potential risks, and cannot perform pre-judgment based on the overall architecture of the operation and maintenance system. On one hand, potential risks can be prevented on the basis of solving surface problems, and on the other hand, pre-judgment can be performed based on the overall architecture of the operation and maintenance system.

Description

Technical Field

[0001] The present invention relates to the field of intelligent operation and maintenance, and in particular to a real-time intelligent operation and maintenance method and an intelligent operation and maintenance system. Background Art

[0002] With the rapid development of information technology, data assets have become one of the core assets of enterprises. More and more enterprises are entrusting the operation and maintenance of data assets to data teams for management and mining.

[0003] In their daily work, the operation and maintenance personnel of the data team will query the logs to find abnormal information in the logs and locate the root cause of the abnormality. However, in the face of massive logs, existing technologies can only solve superficial and current problems, but cannot prevent potential risks or make predictions based on the overall architecture of the operation and maintenance system. Therefore, the industry needs to design a technical solution for real-time intelligent operation and maintenance to solve the above technical problems. Summary of the invention

[0004] The technical problem to be solved by the present invention is: how to design a technical solution for real-time intelligent operation and maintenance that can make predictions based on the overall architecture of the operation and maintenance system.

[0005] To solve the above problems, the embodiments of the present invention propose a real-time intelligent operation and maintenance method and an intelligent operation and maintenance system, which have the beneficial effects of, on the one hand, preventing potential risks on the basis of solving surface problems, and on the other hand, making predictions based on the overall architecture of the operation and maintenance system.

[0006] In the first aspect, an embodiment of the present invention proposes a real-time intelligent operation and maintenance method, which is used in an intelligent operation and maintenance system, wherein the intelligent operation and maintenance system includes a Kafka unit, an intelligent agent collection unit, and an RCA-Agent unit connected in sequence; the real-time intelligent operation and maintenance method includes: S1, actively reporting batch logs so that the Kafka unit contains batch logs; S2, consuming the batch logs of the Kafka unit and extracting text key content; S3, based on the text key content, the intelligent agent collection unit generates unified context information and sends the unified context information to the RCA-Agent unit; S4, generating a solution based on the unified context information and storing the solution in a local knowledge base.

[0007] Its further technical solution is that the RCA-Agent unit of the intelligent operation and maintenance system is connected to the information auxiliary unit; the real-time intelligent operation and maintenance method also includes: S5, based on the information auxiliary unit receiving the abnormal dynamic problem of external input, obtaining abnormal feedback information, and then generating an operation and maintenance analysis report. In the above scheme, the abnormal dynamic problem can specifically be a problem of a surge in the number of transactions, or a system freeze, or similar problems. The definition of specific abnormal dynamic problems is known to those skilled in the art. Further, the information auxiliary unit is used to understand user input, formulate a PLAN, and perform root cause location analysis; wherein the role of the PLAN is to screen out a third number of Agent intelligent entities with corresponding relationships. Further, according to different abnormal dynamic problems (i.e., according to different representations), inquiring specific Agent intelligent entities will result in different PLANs.

[0008] A further technical solution is that the step S1, actively reporting the batch logs so that the Kafka unit contains the batch logs, includes: S101, actively reporting the batch logs of the first number of Serve service units to the Kafka unit so that the Kafka unit contains the batch logs. In the above solution, different types of Serve service units are stored according to corresponding topics. This architecture can be flexibly expanded, and adding or reducing services only requires adding or reducing topics on the Kafka unit.

[0009] Its further technical solution is that the step S2, consuming the batch log of the Kafka unit and extracting the key content of the text, includes: S102, using the flink framework to actively consume the batch log of the Kafka unit in the form of a stream, based on regular matching, real-time cleaning of the information content of the batch log, and extracting the key content of the text. In the above scheme, the use of the flink framework to actively consume the batch log of the Kafka unit in the form of a stream, that is, extracting the target from the batch log of the Kafka unit in the form of a stream; the specific definition of the active consumption is known to those skilled in the art.

[0010] Its further technical solution is that the agent collection unit includes a second number of Agent agents; the step S3, based on the key content of the text, the agent collection unit generates unified context information, and sends the unified context information to the RCA-Agent unit, including: S103, first taking the log information containing the key content of the text as the valid log information, and then aggregating the valid log information output by the second number of Agent agents within a preset time interval and generating unified context information, and sending the unified context information to the RCA-Agent unit. In the above scheme, the agent collection unit belongs to the upper unit of the Agent agent, the second number of Agent agents are all sub-units, and the second number of Agent agents are independent of each other.

[0011] Furthermore, all Agent intelligent bodies are based on the LLM model, and the knowledge base is implemented using a vector database; the fault type (i.e., service warning) is used as the key, and the log input is used as the value; based on the problem log input, the fault type is output, and both the input and output are stored in the vector database / local knowledge base through embedding to form an expert experience accumulation collection; subsequent outputs will first search the vector database / local knowledge base for the most similar alarm summary, i.e., the problem log, through the KNN algorithm, so that the fault type (i.e., service warning) can be quickly output; as the types of Serve service units increase, the types of the Agent intelligent bodies can be flexibly increased and dynamically arranged.

[0012] Its further technical solution is that the step S4 generates a solution based on the unified context information and stores the solution in the local knowledge base, including: S104, summarizing and analyzing all the unified context information through the RCA-Agent unit, and obtaining the solution corresponding to the unified context information through the root cause location module, and storing the solution in the local knowledge base in the form of key-value.

[0013] Its further technical solution is that the RCA-Agent unit includes an analysis and warning module, a root cause location module, and a local knowledge base, and the analysis and warning module and the root cause location module are both connected to the local knowledge base; the step S5, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, obtains abnormal feedback information, and then generates an operation and maintenance analysis report, including: S105, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, the abnormal dynamic problem is transmitted to the root cause location module of the RCA-Agent unit for divergence, and then the abnormal dynamic problem is distributed and drilled down to the second number of Agent intelligent agents through the root cause location module; S106, according to the corresponding relationship between the second number of Agent intelligent agents and the abnormal dynamic problem, a third number of Agent intelligent agents with a corresponding relationship are screened out from the second number of Agent intelligent agents, and the abnormal dynamic problem is converted into abnormal feedback information; S107, the RCA-Agent unit receives the abnormal feedback information sent by the third number of Agent intelligent agents, and then the analysis and warning module in the RCA-Agent unit analyzes the abnormal feedback information to generate an operation and maintenance analysis report. The analysis and warning module and the root cause location module share the same local knowledge base for accumulating expert experience.

[0014] In a second aspect, an embodiment of the present invention provides an intelligent operation and maintenance system, which is used to execute the real-time intelligent operation and maintenance method as described in the first aspect. The functions of the real-time intelligent operation and maintenance method and the intelligent operation and maintenance system include:

[0015] First, improve the efficiency of fault diagnosis and prevention: Through the analysis and reasoning capabilities of LLM, the root cause of the problem can be quickly located and repair suggestions can be provided; combined with the analysis of historical data, early warning of problems that may arise in the future can be issued.

[0016] Second, enhance cross-system and cross-team collaboration capabilities: The RCA-Agent unit is responsible for collecting and integrating the abnormal information and link configuration data detected by each Agent intelligent body; coordinating the analysis tasks between different Agent intelligent bodies to achieve a better collaboration mechanism.

[0017] Third, realize automated operation and maintenance: through real-time processing and analysis of massive log information, automated fault detection and repair can be realized, reducing the burden of manual operation and maintenance and improving operation and maintenance efficiency.

[0018] Fourth, improve system reliability and availability: quickly locate and fix problems to reduce service interruption time; provide early warning and prevent possible future problems to enhance system reliability.

[0019] Fifth, reduce operation and maintenance costs: Automated operation and maintenance greatly reduces labor costs; through the analysis and optimization of historical data, resource utilization efficiency can be further optimized.

[0020] Therefore, the present invention can process massive log information in real time and automatically through the big data technology framework and the coordinated work of multiple Agent intelligent bodies; based on the emergence and reasoning capabilities of LLM, it can not only quickly locate the current defects, but also provide repair suggestions for the current defects, and warn of possible problems in the future; in addition, the present invention accurately collects the abnormal information, links, and configuration information detected by other Agent intelligent bodies through the RCA-Agent unit to locate the root cause; at the same time, it is responsible for converging the collaboration rounds, and determines the direction of the next step of analysis and drilling down according to the feedback from other Agent intelligent bodies, thereby realizing a cross-system and cross-team collaboration mechanism.

[0021] In their daily work, the operation and maintenance personnel of the data team will query the logs to find abnormal information in the logs and locate the root cause of the abnormality. However, in the face of massive logs, the existing technology can only solve superficial problems and current problems, and cannot prevent potential risks, nor can it make predictions based on the overall architecture of the operation and maintenance system; based on this, the real-time intelligent operation and maintenance method and intelligent operation and maintenance system described in this application have the following beneficial effects: on the one hand, it can prevent potential risks on the basis of solving superficial problems, and on the other hand, it can make predictions based on the overall architecture of the operation and maintenance system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 A flowchart of a real-time intelligent operation and maintenance method provided by an embodiment of the present invention.

[0025] Figure 2 Another flowchart of the real-time intelligent operation and maintenance method provided by an embodiment of the present invention.

[0026] Figure 3 A schematic diagram of a framework of an intelligent operation and maintenance system provided in an embodiment of the present invention.

[0027] Figure 4Another schematic diagram of the framework of the intelligent operation and maintenance system provided by an embodiment of the present invention.

[0028] Figure 5 A block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0030] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or other features, integers, steps, operations, elements, components and / or combinations thereof.

[0031] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0032] It should be further understood that the term "and / or" used in the present specification and the appended claims refers to one or any combination and all possible combinations of the associated listed items, and includes these combinations.

[0033] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0034] Example 1

[0035] See also Figure 1 to Figure 2 , which is a flow chart of a real-time intelligent operation and maintenance method provided by an embodiment of the present invention. An embodiment of the present invention proposes a real-time intelligent operation and maintenance method, which is used in an intelligent operation and maintenance system. The intelligent operation and maintenance system includes a Kafka unit, an intelligent agent collection unit, and an RCA-Agent unit connected in sequence; the real-time intelligent operation and maintenance method includes:

[0036] S1, actively reports the batch logs so that the Kafka unit contains the batch logs.

[0037] S2, consumes the batch logs of Kafka units and extracts the key content of the text.

[0038] S3, based on the key content of the text, the agent collection unit generates unified context information and sends the unified context information to the RCA-Agent unit.

[0039] S4, generating a solution according to the unified context information, and storing the solution in a local knowledge base.

[0040] In one embodiment, the RCA-Agent unit of the intelligent operation and maintenance system is connected to the information auxiliary unit; the real-time intelligent operation and maintenance method also includes: S5, based on the information auxiliary unit receiving abnormal dynamic problems input from the outside, obtaining abnormal feedback information, and then generating an operation and maintenance analysis report.

[0041] In one embodiment, the step S1, actively reporting the batch logs so that the Kafka unit includes the batch logs, includes: S101, actively reporting the batch logs of the first number of Serve service units to the Kafka unit so that the Kafka unit includes the batch logs.

[0042] In one embodiment, the step S2, consuming the batch logs of the Kafka unit and extracting the key text content, includes: S102, using the fling framework to actively consume the batch logs of the Kafka unit in a stream form, based on regular matching, real-time cleaning of the information content of the batch logs, and extracting the key text content.

[0043] In one embodiment, the agent collection unit includes a second number of Agent agents; the step S3, based on the text key content, the agent collection unit generates unified context information and sends the unified context information to the RCA-Agent unit, including: S103, first taking the log information containing the text key content as valid log information, and then aggregating the valid log information output by the second number of Agent agents within a preset time interval and generating unified context information, and sending the unified context information to the RCA-Agent unit.

[0044] In one embodiment, the step S4 generates a solution based on the unified context information and stores the solution in the local knowledge base, including: S104, summarizing and analyzing all the unified context information through the RCA-Agent unit, and obtaining the solution corresponding to the unified context information through the root cause location module, and storing the solution in the local knowledge base in the form of key-value.

[0045] In one embodiment, the RCA-Agent unit includes an analysis and warning module, a root cause location module, and a local knowledge base, and the analysis and warning module and the root cause location module are both connected to the local knowledge base; the step S5, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, obtains abnormal feedback information, and then generates an operation and maintenance analysis report, including: S105, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, the abnormal dynamic problem is transmitted to the root cause location module of the RCA-Agent unit for divergence, and then the abnormal dynamic problem is distributed and drilled down to the second number of Agent intelligent agents through the root cause location module; S106, according to the corresponding relationship between the second number of Agent intelligent agents and the abnormal dynamic problem, a third number of Agent intelligent agents with a corresponding relationship are screened out from the second number of Agent intelligent agents, and the abnormal dynamic problem is converted into abnormal feedback information; S107, the RCA-Agent unit receives the abnormal feedback information sent by the third number of Agent intelligent agents, and then the analysis and warning module in the RCA-Agent unit analyzes the abnormal feedback information to generate an operation and maintenance analysis report.

[0046] The present invention also proposes an intelligent operation and maintenance system, see Figure 3 as well as Figure 4 The intelligent operation and maintenance system is used to execute the real-time intelligent operation and maintenance method as described in any of the above embodiments. In one embodiment, the real-time intelligent operation and maintenance method specifically includes the following steps S101 to S107:

[0047] S101, actively report the batch logs of the first number of Serve service units to the Kafka unit, so that the Kafka unit contains the batch logs.

[0048] S102, use the Flink framework to actively consume the batch logs of the Kafka unit in the form of streams, clean the information content of the batch logs in real time based on regular matching, and extract the key text content.

[0049] S103, firstly taking the log information containing the key content of the text as the valid log information, then aggregating the valid log information output by the second number of Agent intelligent bodies within a preset time interval and generating unified context information, and sending the unified context information to the RCA-Agent unit.

[0050] S104, summarizing and analyzing all unified context information through the RCA-Agent unit, obtaining solutions corresponding to the unified context information through the root cause location module, and storing the solutions in the local knowledge base in a key-value form.

[0051] S105, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, the abnormal dynamic problem is transmitted to the root cause location module of the RCA-Agent unit for divergence, and then the abnormal dynamic problem is distributed and drilled down to a second number of Agent intelligent bodies through the root cause location module.

[0052] S106, according to the correspondence between the second number of Agent intelligent agents and the abnormal dynamic problems, a third number of Agent intelligent agents with corresponding relationships are selected from the second number of Agent intelligent agents, and the abnormal dynamic problems are converted into abnormal feedback information.

[0053] S107, the RCA-Agent unit receives the abnormal feedback information sent by the third number of Agent intelligent bodies, and then the analysis and warning module in the RCA-Agent unit analyzes the abnormal feedback information and generates an operation and maintenance analysis report.

[0054] Those skilled in the art can understand the related terms of the above embodiments. The related terms of the intelligent seal recognition method and seal recognition system include:

[0055] Embedding: An important concept in the field of machine learning and natural language processing. It refers to converting discrete, high-dimensional data (such as text, images, etc.) into continuous, low-dimensional data representation.

[0056] LLM: Large Language Model.

[0057] KNN: A classic machine learning algorithm, namely K-Nearest Neighbors, can be used for nearest neighbor search in vector databases.

[0058] To sum up, with the development of the digital economy industry, more and more services need to be maintained on the platform. The operation and maintenance personnel of the data team mainly face the following challenges: First, insufficient automation: some operation and maintenance work still relies on manual operation and expert experience, lacks sufficient automation and intelligence, and is prone to human errors; Second, the operation and maintenance data analysis capabilities are not strong: the existing operation and maintenance system cannot effectively collect and analyze a large amount of operation and maintenance data, and cannot timely discover and prevent potential risks; Third, lack of foresight and globality: the existing operation and maintenance solutions only focus on fixing current problems, and lack predictions of the entire system architecture and future development trends; Fourth, lack of cross-team and cross-system collaboration: operation and maintenance collaboration between different teams or systems is generally difficult, and there is a lack of effective collaboration mechanisms.

[0059] In their daily work, the operation and maintenance personnel of the data team will query the logs to find abnormal information in the logs and locate the root cause of the abnormality. However, in the face of massive logs, the existing technology can only solve superficial problems and current problems, and cannot prevent potential risks, nor can it make predictions based on the overall architecture of the operation and maintenance system; based on this, the real-time intelligent operation and maintenance method and intelligent operation and maintenance system described in this application have the following beneficial effects: on the one hand, it can prevent potential risks on the basis of solving superficial problems, and on the other hand, it can make predictions based on the overall architecture of the operation and maintenance system.

[0060] Example 2

[0061] See also Figure 5 , Figure 5 This is a block diagram of an electronic device provided by the present invention. The electronic device can be a terminal or a server, wherein the terminal can be an electronic device with communication functions such as a smart phone, a tablet computer, a laptop computer, a desktop computer, a personal digital assistant, and a wearable device. The server can be an independent server or a server cluster composed of servers.

[0062] It includes a processor 111 , a communication interface 112 , a memory 113 , and a communication bus 114 , wherein the processor 111 , the communication interface 112 , and the memory 113 communicate with each other via the communication bus 114 .

[0063] The memory 113 is used to store computer programs.

[0064] In one embodiment of the present invention, the processor 111 is used to implement the method provided by any one of the aforementioned method embodiments when executing the program stored in the memory 113 .

[0065] It should be understood that in the embodiment of the present application, the processor 111 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0066] It is understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0067] Therefore, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method provided in any one of the aforementioned method embodiments are implemented.

[0068] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which can store program codes. The computer-readable storage medium can be non-volatile or volatile.

[0069] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions, but such implementation should not be considered to be beyond the scope of the present invention.

[0070] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0071] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0072] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0073] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0074] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0075] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A real-time intelligent operation and maintenance method, characterized in that: The method is used for an intelligent operation and maintenance system, which includes a Kafka unit, an intelligent agent collection unit, and an RCA-Agent unit connected in sequence; the real-time intelligent operation and maintenance method includes: S1, actively report the batch logs so that the Kafka unit contains the batch logs; S2, consumes the batch logs of Kafka units and extracts the key text content; S3, based on the key content of the text, the agent collection unit generates unified context information and sends the unified context information to the RCA-Agent unit; S4, generating a solution according to the unified context information, and storing the solution in a local knowledge base.

2. The real-time intelligent operation and maintenance method according to claim 1, characterized in that: The RCA-Agent unit of the intelligent operation and maintenance system is connected to the information auxiliary unit; the real-time intelligent operation and maintenance method also includes: S5, based on the abnormal dynamic problem received from the external input by the information auxiliary unit, obtains abnormal feedback information, and then generates an operation and maintenance analysis report.

3. The real-time intelligent operation and maintenance method according to claim 2, characterized in that: The step S1 actively reports the batch logs so that the Kafka unit contains the batch logs, including: S101, actively report the batch logs of the first number of Serve service units to the Kafka unit, so that the Kafka unit contains the batch logs.

4. The real-time intelligent operation and maintenance method according to claim 3, characterized in that: The step S2 consumes the batch logs of the Kafka unit and extracts the key text content, including: S102 uses the flink framework to actively consume the batch logs of the Kafka unit in the form of streams, cleans the information content of the batch logs in real time based on regular matching, and extracts the key text content.

5. The real-time intelligent operation and maintenance method according to claim 4, characterized in that: The agent collection unit includes a second number of Agent agents; the step S3, based on the key content of the text, the agent collection unit generates unified context information and sends the unified context information to the RCA-Agent unit, includes: S103, firstly taking the log information containing the key content of the text as the valid log information, then aggregating the valid log information output by the second number of Agent intelligent bodies within a preset time interval and generating unified context information, and sending the unified context information to the RCA-Agent unit.

6. The real-time intelligent operation and maintenance method according to claim 5, characterized in that: The step S4, generating a solution according to the unified context information and storing the solution in a local knowledge base, includes: S104, summarizing and analyzing all unified context information through the RCA-Agent unit, obtaining solutions corresponding to the unified context information through the root cause location module, and storing the solutions in the local knowledge base in the form of key-value.

7. The real-time intelligent operation and maintenance method according to claim 6, characterized in that: The RCA-Agent unit includes an analysis and warning module, a root cause location module, and a local knowledge base, wherein the analysis and warning module and the root cause location module are both connected to the local knowledge base; The step S5, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, obtains abnormal feedback information, and then generates an operation and maintenance analysis report, includes: S105, based on the abnormal dynamic problem received by the information auxiliary unit from the outside, the abnormal dynamic problem is transmitted to the root cause location module of the RCA-Agent unit for divergence, and then the abnormal dynamic problem is distributed and drilled down to a second number of Agent intelligent bodies through the root cause location module; S106, according to the correspondence between the second number of Agent intelligent agents and the abnormal dynamic problems, selecting a third number of Agent intelligent agents having the corresponding relationship from the second number of Agent intelligent agents, and converting the abnormal dynamic problems into abnormal feedback information; S107, the RCA-Agent unit receives the abnormal feedback information sent by the third number of Agent intelligent bodies, and then the analysis and warning module in the RCA-Agent unit analyzes the abnormal feedback information and generates an operation and maintenance analysis report.

8. An intelligent operation and maintenance system, characterized in that: The intelligent operation and maintenance system is used to execute the real-time intelligent operation and maintenance method as described in any one of claims 1 to 7.

Images