Intelligent operation and maintenance method, device and equipment for downtime, medium and program product

Abstract

The invention discloses an intelligent operation and maintenance method, device and equipment for downtime, a medium and a program product. The method comprises the steps that operation information of a service process is monitored, when the operation information of the service process exceeds a corresponding parameter configuration preset threshold value, a warning prompt is given out, whether the service process exists or not is monitored, and when the service process does not exist, a service is restarted immediately; detecting abnormal stack information in the service operation process, and storing the abnormal stack information of the whole link; and extracting the downtime file and the abnormal stack information log file, combining the downtime file and the abnormal stack information log file, quickly positioning a downtime reason, and generating a downtime result analysis report. Through the real-time monitoring function, not only can a warning prompt be given out, but also the service can be restarted at the first time, so that the system availability is guaranteed; in addition, the downtime reason can be quickly and accurately positioned in the shortest time, manual intervention is not needed, the system maintenance pressure of operation and maintenance personnel and developers is reduced, the user experience is improved, and user group loss caused by the downtime reason is prevented.

Description

Technical Field

[0001] The present invention relates to the field of operation and maintenance technology of software operating systems, and in particular to an intelligent operation and maintenance method, device, equipment, medium and program product for downtime. Background Art

[0002] With the continuous progress of society, software systems have been widely used in various fields, playing a pivotal role in modern society and playing an important role. For example, Java is the most popular programming language in the current software development market, and is widely used in enterprise applications, mobile applications, Web development, game development and other fields. Java's cross-platform nature and open source policy make it the first choice for many developers and enterprises, and it has a huge community support and rich ecosystem, allowing developers to easily find various tools, frameworks and libraries to help them quickly develop high-quality applications.

[0003] As software systems continue to develop, people have higher and higher requirements for software reliability, security, and performance, resulting in the continuous increase in software scale and complexity. For any system running in a production environment, downtime is a serious problem. This situation may cause business interruptions, data loss, and a significant decline in user experience. Downtime can have a negative impact on a company's reputation and financial situation, so it is crucial to find the cause of downtime and prevent it.

[0004] Downtime is usually a manifestation of system performance problems. By studying downtime, we can find performance bottlenecks, such as a thread consuming a lot of CPU resources or excessive memory resource usage. By optimizing these problems, the performance of the system can be improved. Therefore, it is also very important for system administrators and developers to understand how to solve downtime problems. By studying the causes of system downtime, we can gain insight into the key factors that cause system instability. For example, downtime may be caused by hardware failure, software defects, network problems, or human errors. By identifying these factors, we can take appropriate measures to improve the stability of the system. For example, when the system crashes, the first thing to do is to carefully analyze the cause of the downtime. This may involve viewing system logs, monitoring system resource usage, checking application error messages, etc. Once the problem is found, appropriate measures can be taken to repair and optimize it.

[0005] Currently, the software market uses the following analysis tools for JVM downtime files:

[0006] Visual VM: is an open source Java virtual machine monitoring and troubleshooting tool, such as viewing thread status, heap memory snapshots, GC behavior, etc.

[0007] Eclepse MAT: is a tool for analyzing Java heap dump files. It can load heap dump files and provide detailed memory analysis reports, including object reference relationships, memory leak analysis, object size and other information to help find memory problems.

[0008] IBM HeapAnalyzer: is a tool for analyzing IBM JVM heap dump files. It can load heap dump files and provide detailed memory analysis reports, including object reference relationships, memory leak analysis, object size and other information.

[0009] At present, all these downtime files are manually analyzed by operation and maintenance technicians. However, for ordinary operation and maintenance staff with limited knowledge and technical levels, the analysis is difficult and the analysis cost is high. It is urgent to develop an intelligent operation and maintenance method for downtime problems. Existing intelligent operation and maintenance technologies, such as CN201811252827.6, the name of the invention: monitoring and early warning method, device and storage medium based on JVM. This prior art discloses a monitoring and early warning method, electronic device and storage medium based on JVM, but there is no downtime analysis function in the technical solution, and the cause of the downtime cannot be quickly obtained. Prior art CN201910653532.8, the name of the invention is a downtime positioning and repair method and system, which discloses a downtime positioning and repair method and system, which only analyzes the downtime problem caused by third-party software, and does not have the function of monitoring and early warning.

[0010] This application is based on the existing technology and creates an intelligent operation and maintenance method, device, equipment, medium and program product for downtime, which can monitor the service process, issue warning prompts, immediately restart the service, and automatically start the analysis of the cause of the downtime, quickly locate the cause of the downtime, reduce the pressure on operation and maintenance personnel and developers to maintain the system, and ensure the rapid recovery of the software system. Summary of the invention

[0011] The technical problem to be solved by the present invention is to provide an intelligent operation and maintenance method for downtime, so that it can monitor the service process, issue warning prompts, immediately restart the service, and automatically start downtime cause analysis, quickly locate the cause of the downtime, reduce the pressure on operation and maintenance personnel and developers to maintain the system, and ensure the rapid recovery of the software system, thereby overcoming the shortcomings caused by the downtime of the existing software system.

[0012] In order to solve the above technical problems, in a first aspect, the present invention provides an intelligent operation and maintenance method for downtime, which specifically includes the following steps:

[0013] Monitor the running information of the service process. When the running information of the service process exceeds the preset threshold of the corresponding parameter configuration, a warning prompt is issued, and the service process is monitored to see if it exists. If the service process does not exist, the service is restarted immediately.

[0014] Detect abnormal stack information during service operation and store abnormal stack information of the entire link;

[0015] Extract the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link, combine the downtime file and the abnormal stack information log file, quickly locate the cause of the downtime, and generate a corresponding downtime result analysis report.

[0016] According to a specific implementation manner of an embodiment of the present invention, the parameter configuration preset threshold includes at least one of a CPU usage threshold, a memory usage threshold, and a thread and method response threshold.

[0017] According to a specific implementation method of an embodiment of the present invention, the step of detecting abnormal stack information during service operation and storing the abnormal stack information of the entire link also includes: a filtering step for screening out irrelevant log information, and supports cluster real-time full-text retrieval of massive log data, supports the input and output of multiple logs, and supports the storage of data in multiple formats.

[0018] According to a specific implementation of an embodiment of the present invention, the step of extracting the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link is automatically triggered when the monitoring service process does not exist;

[0019] After the downtime result analysis report is generated, it is automatically forwarded to the subscribed staff.

[0020] According to a specific implementation of an embodiment of the present invention, the step of combining the downtime file with the abnormal stack information log file to quickly locate the cause of the downtime specifically includes:

[0021] Perform data preprocessing on the downtime file and the abnormal stack information log file and generate corresponding feature vectors:

[0022] For the crash file, convert the HeapDump binary file of the crash file into structured data, and extract the heap memory usage, thread status, system information, stack information, and memory overflow error information, and use this information to generate the corresponding feature vector of the crash file;

[0023] For the exception stack information log file, filter out irrelevant log information, and extract variables in the log file, including IP address, operator ID, time, thread ID, text information, SQL information, and generate a feature vector of the exception stack information log file;

[0024] After the feature vector is extracted, a fault detection model is constructed based on the feature vector of the abnormal stack information log file. The fault detection model can combine the structured data of the downtime file with the abnormal stack information log of the application system to perform matching detection:

[0025] If the structured data of the downtime file can match the corresponding link abnormality log information, it indicates that the downtime is caused by the application system code. If the structured data of the downtime file does not match the corresponding link abnormality log information, it indicates that the downtime is caused by reasons other than the application system. The cause of the downtime can be quickly located.

[0026] In a second aspect, an embodiment of the present invention further provides an intelligent operation and maintenance device for downtime, the device comprising:

[0027] The service process monitoring module is configured to monitor the running information of the service process. When the running information of the service process exceeds the preset threshold of the corresponding parameter configuration, a warning prompt is issued, and the service process is monitored to determine whether it exists. When the service process does not exist, the service is restarted immediately.

[0028] The abnormal log detection module is configured to detect abnormal stack information during the service operation process and store the abnormal stack information of the entire link;

[0029] The downtime file analysis module is configured to extract the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link, combine the downtime file and the abnormal stack information log file, quickly locate the cause of the downtime, and generate a corresponding downtime result analysis report.

[0030] According to a specific implementation of an embodiment of the present invention, the service process monitoring module further includes a parameter configuration threshold preset module, which is configured to set at least one of a CPU usage threshold, a memory usage threshold, and a thread and method response threshold;

[0031] The downtime file analysis module also includes:

[0032] An extraction module is configured to automatically extract a downtime file automatically generated before a service downtime and an exception stack information log file of the entire link;

[0033] A data preprocessing module is configured to perform data preprocessing on the extracted downtime file and abnormal stack information log file, and generate corresponding feature vectors;

[0034] The fault detection module is configured to build a fault detection model based on the feature vector of the abnormal stack information log file, and combine the downtime file structured data with the abnormal stack information log of the application system through the fault detection model to complete data matching and result analysis, and generate a downtime result analysis report.

[0035] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0036] at least one processor; and,

[0037] a memory communicatively connected to the at least one processor; wherein,

[0038] The memory stores instructions that can be executed by the at least one processor. When the instructions are executed by the at least one processor, the at least one processor implements the intelligent operation and maintenance method for downtime as described in any one of the first aspect or any one of the implementations of the first aspect.

[0039] In a fourth aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, which stores computer instructions, and when the computer instructions are executed by at least one processor, the at least one processor executes the intelligent operation and maintenance method for downtime in the aforementioned first aspect or any implementation method of the first aspect.

[0040] In the fifth aspect, an embodiment of the present invention further provides a computer program product, comprising a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises program instructions, and when the program instructions are executed by a computer, the computer executes the intelligent operation and maintenance method for downtime in the aforementioned first aspect or any implementation of the first aspect.

[0041] After adopting such a design, the present invention has at least the following advantages:

[0042] The intelligent operation and maintenance method for downtime of the present invention can generate warning information corresponding to the operation information and issue a warning prompt when the service operation information exceeds the corresponding preset alarm threshold through the real-time monitoring function; it can also try to restart the application system when it is found that the JVM process does not exist, and build a fault detection model based on the generated downtime file and the link abnormal stack information log of the application system, use a machine learning algorithm, quickly analyze the cause of the downtime, and automatically forward the technical operation and maintenance personnel. The method can not only restart the application service in the first time, ensure the rapid recovery of the system, improve the system availability, reduce the problems of business interruption, data loss and significant decline in user experience caused by downtime; it can also quickly and accurately locate the cause of downtime in the shortest time, without manual intervention, reduce the pressure of operation and maintenance personnel and developers to maintain the system, overcome the various disadvantages of manual analysis, greatly improve the user experience, and prevent the loss of user groups caused by downtime. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0044] Figure 1 It is a process logic diagram of the intelligent operation and maintenance method according to an embodiment of the present invention.

[0045] Figure 2 It is a flow logic diagram of the service process monitoring step in the intelligent operation and maintenance method according to an embodiment of the present invention.

[0046] Figure 3 It is a process logic diagram of the abnormal log detection step in the intelligent operation and maintenance method of an embodiment of the present invention.

[0047] Figure 4 It is a process logic diagram of the downtime file analysis step in the intelligent operation and maintenance method of an embodiment of the present invention.

[0048] Figure 5 It is a process logic diagram of the message service step in the intelligent operation and maintenance method according to an embodiment of the present invention.

[0049] Figure 6 It is a structural block diagram of the intelligent operation and maintenance device according to an embodiment of the present invention.

[0050] Figure 7 A schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0052] In order to quickly help users solve the downtime problem, the present invention provides an intelligent operation and maintenance method for downtime. Taking the operation of a user-side application service system as an example, the present invention is described in detail.

[0053] See attached Figure 1 As shown, the intelligent operation and maintenance method of this embodiment specifically includes the following steps:

[0054] S1.Service process monitoring steps: see the attached Figure 2 As shown, the running information of the service process is monitored. When the running information of the service process exceeds the preset threshold of the corresponding parameter configuration, a warning prompt is issued, and the service process is monitored. When the service process does not exist, an attempt is made to restart the service immediately to ensure that the service resumes operation quickly. Among them, the preset threshold of the parameter configuration belongs to at least one of the CPU usage threshold, the memory usage threshold, the thread and method response threshold.

[0055] S2. Abnormal log detection steps: see the attached Figure 3 As shown, the abnormal stack information during the service operation is detected, and the abnormal stack information of the entire link is stored. Among them, the abnormal stack information includes the running SQL information. In addition, the abnormal log detection step also includes a filtering step for filtering out irrelevant log information, and supports the cluster to perform full-text retrieval of massive log data in real time, supports the input and output of multiple logs, and also supports the storage of data in multiple formats.

[0056] S3. Downtime file analysis step: This is the core step in the intelligent operation and maintenance method. Specifically, the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link are extracted, the downtime file and the abnormal stack information log file are combined, the cause of the downtime is quickly located, and the corresponding downtime result analysis report is generated.

[0057] The step of extracting the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link is automatically triggered when the monitoring service process does not exist.

[0058] The steps of combining the downtime file with the abnormal stack information log file to quickly locate the cause of the downtime are shown in the attached Figure 4 As shown, the specific execution steps include:

[0059] The downtime file and the abnormal stack information log file are preprocessed and corresponding feature vectors are generated: for the downtime file, the HeapDump binary file of the downtime file is converted into structured data, and the heap memory usage, thread status, system information, stack information, and memory overflow error information are extracted, and the feature vector of the corresponding downtime file is generated from these information; for the abnormal stack information log file, some irrelevant log information is filtered out again, and variables in the log file are extracted, including IP address, operator ID, time, thread ID, text information, and SQL information, to generate a feature vector of the abnormal stack information log file;

[0060] After the feature vector is extracted, a fault detection model is constructed based on the feature vector of the abnormal stack information log file. The fault detection model can combine the structured data of the downtime file with the abnormal stack information log of the application system to perform matching detection: if the structured data of the downtime file can match the corresponding link abnormality log information, it indicates that the downtime is caused by the code of the application system; if the structured data of the downtime file does not match the corresponding link abnormality log information, it indicates that the downtime is caused by reasons other than the application system, and the cause of the downtime is quickly located to help users quickly solve the problem.

[0061] Specifically, the fault detection model uses the association rule mining FP Tree algorithm as an unsupervised anomaly detection method. The unsupervised method does not require data annotation and locates the data information of related anomalies by distinguishing the feature distance between the anomaly instance and other instances.

[0062] S4. Message service steps: see attached Figure 5 As shown, after receiving the downtime result analysis report, it is stored and automatically forwarded to the subscribed staff to quickly resolve the error source of the downtime.

[0063] Figure 6 The intelligent operation and maintenance device 30 for downtime of the present invention is shown, including a service process monitoring module 301, an abnormal log detection module 302, a downtime file analysis module 303, and a message service module 304.

[0064] The service process monitoring module 301 is used to monitor the running information of the service process. When the running information of the service process exceeds the corresponding parameter configuration preset threshold, a warning prompt is issued, and the service process is monitored to see whether it exists. When the service process does not exist, the service is immediately restarted. Among them, the service process monitoring module includes a parameter configuration threshold preset module 3011, which is used to set at least one of the CPU usage threshold, memory usage threshold, thread and method response threshold.

[0065] The abnormal log detection module 302 is used to detect abnormal stack information during the service operation process and store the abnormal stack information of the entire link.

[0066] The downtime file analysis module 303 is used to extract the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link, combine the downtime file and the abnormal stack information log file, quickly locate the cause of the downtime, and generate a corresponding downtime result analysis report. The downtime file analysis module 303 includes an extraction module 3031, a data preprocessing module 3032, and a fault detection module 3033.

[0067] The extraction module 3031 is used to automatically extract the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link.

[0068] The data preprocessing module 3032 is used to perform data preprocessing on the extracted downtime file and abnormal stack information log file, and generate corresponding feature vectors.

[0069] The fault detection module 3033 is used to build a fault detection model based on the feature vector of the abnormal stack information log file, and combine the downtime file structured data with the abnormal stack information log of the application system through the fault detection model to complete data matching and result analysis, and generate a downtime result analysis report.

[0070] The message service module 304 is used to receive and store the downtime result analysis report, and can also automatically forward it to the subscribed staff.

[0071] See also Figure 7 The embodiment of the present invention further provides an electronic device 40, the electronic device 40 comprising:

[0072] at least one processor; and,

[0073] a memory communicatively connected to the at least one processor; wherein,

[0074] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent operation and maintenance method for downtime in the aforementioned method embodiment.

[0075] An embodiment of the present invention further provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the intelligent operation and maintenance method for downtime in the aforementioned method embodiment.

[0076] An embodiment of the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the intelligent operation and maintenance method for downtime in the aforementioned method embodiment.

[0077] Reference below Figure 7 , which shows a schematic diagram of the structure of an electronic device 40 suitable for implementing an embodiment of the present invention. The electronic device in the embodiment of the present invention may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 7 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0078] like Figure 7 As shown, the electronic device 40 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 40 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0079] Typically, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 may allow the electronic device 40 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 7 4 shows an electronic device 40 having various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0080] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present invention are executed.

[0081] It should be noted that the computer-readable medium of the present invention can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0082] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0083] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: obtains at least two Internet Protocol addresses; sends a node evaluation request including the at least two Internet Protocol addresses to a node evaluation device, wherein the node evaluation device selects an Internet Protocol address from the at least two Internet Protocol addresses and returns it; receives the Internet Protocol address returned by the node evaluation device; wherein the obtained Internet Protocol address indicates an edge node in a content distribution network.

[0084] Alternatively, the computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device: receives a node evaluation request including at least two Internet Protocol addresses; selects an Internet Protocol address from the at least two Internet Protocol addresses; and returns the selected Internet Protocol address; wherein the received Internet Protocol address indicates an edge node in a content distribution network.

[0085] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0086] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0087] The units involved in the embodiments of the present invention may be implemented by software or hardware, wherein the name of a unit does not limit the unit itself in some cases.

[0088] It should be noted that the above embodiments and features therein may be combined with each other if there is no conflict.

[0089] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An intelligent operation and maintenance method for downtime, characterized in that: The specific steps include: Monitor the running information of the service process. When the running information of the service process exceeds the preset threshold of the corresponding parameter configuration, a warning prompt is issued, and the service process is monitored to see if it exists. If the service process does not exist, the service is restarted immediately. Detect abnormal stack information during service operation and store abnormal stack information of the entire link; Extract the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link, combine the downtime file and the abnormal stack information log file, quickly locate the cause of the downtime, and generate a corresponding downtime result analysis report.

2. The intelligent operation and maintenance method for downtime according to claim 1, characterized in that: The parameter configuration preset threshold includes at least one of a CPU usage threshold, a memory usage threshold, a thread and a method response threshold.

3. The intelligent operation and maintenance method for downtime according to claim 1, characterized in that: The steps of detecting abnormal stack information during service operation and storing abnormal stack information of the entire link also include: a filtering step for screening out irrelevant log information, supporting clusters to perform full-text retrieval of massive log data in real time, supporting the input and output of multiple logs, and supporting the storage of data in multiple formats.

4. The intelligent operation and maintenance method for downtime according to claim 1, characterized in that: The step of extracting the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link is automatically triggered when the monitoring service process does not exist; After the downtime result analysis report is generated, it is automatically forwarded to the subscribed staff.

5. The intelligent operation and maintenance method for downtime according to claim 1, characterized in that: The step of combining the downtime file with the abnormal stack information log file to quickly locate the cause of the downtime specifically includes: Perform data preprocessing on the downtime file and the abnormal stack information log file and generate corresponding feature vectors: For the crash file, convert the HeapDump binary file of the crash file into structured data, and extract the heap memory usage, thread status, system information, stack information, and memory overflow error information, and use this information to generate the corresponding feature vector of the crash file; For the exception stack information log file, filter out irrelevant log information, and extract variables in the log file, including IP address, operator ID, time, thread ID, text information, SQL information, and generate a feature vector of the exception stack information log file; After the feature vector is extracted, a fault detection model is constructed based on the feature vector of the abnormal stack information log file. The fault detection model can combine the structured data of the downtime file with the abnormal stack information log of the application system to perform matching detection: If the structured data of the downtime file can match the corresponding link abnormality log information, it indicates that the downtime is caused by the application system code. If the structured data of the downtime file does not match the corresponding link abnormality log information, it indicates that the downtime is caused by reasons other than the application system. The cause of the downtime can be quickly located.

6. An intelligent operation and maintenance device for downtime, characterized in that: The device comprises: The service process monitoring module is configured to monitor the running information of the service process. When the running information of the service process exceeds the preset threshold of the corresponding parameter configuration, a warning prompt is issued, and the service process is monitored to determine whether it exists. When the service process does not exist, the service is restarted immediately. The abnormal log detection module is configured to detect abnormal stack information during the service operation process and store the abnormal stack information of the entire link; The downtime file analysis module is configured to extract the downtime file automatically generated before the service downtime and the abnormal stack information log file of the entire link, combine the downtime file and the abnormal stack information log file, quickly locate the cause of the downtime, and generate a corresponding downtime result analysis report.

7. The intelligent operation and maintenance device for downtime according to claim 6, characterized in that: The service process monitoring module also includes a parameter configuration threshold preset module, which is configured to set at least one of a CPU usage threshold, a memory usage threshold, and a thread and method response threshold; The downtime file analysis module also includes: An extraction module is configured to automatically extract a downtime file automatically generated before a service downtime and an exception stack information log file of the entire link; A data preprocessing module is configured to perform data preprocessing on the extracted downtime file and abnormal stack information log file, and generate corresponding feature vectors; The fault detection module is configured to build a fault detection model based on the feature vector of the abnormal stack information log file, and combine the downtime file structured data with the abnormal stack information log of the application system through the fault detection model to complete data matching and result analysis, and generate a downtime result analysis report.

8. An electronic device, characterized in that: The electronic device includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor executes the intelligent operation and maintenance method for downtime as described in any one of claims 1 to 5.

9. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which, when executed by at least one processor, cause the at least one processor to execute the intelligent operation and maintenance method for downtime as described in any one of claims 1 to 5.

10. A computer program product, characterized in that The computer program product includes a computer program / instruction, which, when executed by a processor, implements the intelligent operation and maintenance method for downtime as described in any one of claims 1 to 5.

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