Data processing method and device, electronic equipment and storage medium

Abstract

The invention discloses a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: in response to a data processing instruction of a target node, determining each to-be-monitored operation parameter and a corresponding time sliding window; in response to the fact that the current time belongs to the corresponding time sliding window, triggering a collection task of the operation parameters, and collecting parameter values of the operation parameters; determining an adjustment strategy of the target node based on the parameter value of each operation parameter to obtain and execute a capacity adjustment program associated with the adjustment strategy; and in response to successful execution of the capacity adjustment program, obtaining adjusted capacity information to call a preset deployment program so as to deploy the capacity information for the target node. According to the embodiment of the invention, the problems that the operation and maintenance personnel need to consume too much manpower and the stability of the service system is easily reduced when monitoring and maintaining the operation state of each server node can be solved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular, to a method, apparatus, electronic device, and storage medium for data processing. Background Art

[0002] In multiple fields, as the business volume and complexity of the business increase, the business system often requires multiple server nodes to support. Therefore, how to allocate traffic to each server node has become an important issue. In order to reasonably allocate traffic to each server node, in related technologies, it is usually necessary for operation and maintenance personnel to monitor and maintain the operating status of each server node. However, this method not only consumes too much manpower, but also easily fails to detect and maintain problems that occur in the server node in a timely manner, resulting in a decrease in the stability of the business system. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method, apparatus, electronic device, and storage medium for data processing, which can solve the problem that operation and maintenance personnel monitor and maintain the operating status of each server node, which not only consumes too much manpower, but also easily leads to a decrease in the stability of the business system.

[0004] To achieve the above object, according to one aspect of the embodiments of the present invention, a method for data processing is provided.

[0005] A method for data processing according to an embodiment of the present invention includes: in response to a data processing instruction of a target node, obtaining corresponding configuration information to determine each operating parameter to be monitored and a time sliding window corresponding to each operating parameter;

[0006] For each operating parameter, in response to the current time belonging to the corresponding time sliding window, triggering a collection task of the operating parameter to call a corresponding preset plug-in to collect the parameter value of the operating parameter;

[0007] Calling a preset operation and maintenance model, determining an adjustment strategy of the target node based on the parameter values of the operating parameters, and obtaining a capacity adjustment program associated with the adjustment strategy and executing it;

[0008] In response to the successful execution of the capacity adjustment program, obtaining the adjusted capacity information to call a preset deployment program to deploy the capacity information to the target node.

[0009] In one embodiment, the calling a preset operation and maintenance model, determining an adjustment strategy of the target node based on the parameter values of the operating parameters includes:

[0010] Invoke a preset operation and maintenance model to obtain the operation parameter decision tree corresponding to the target node, so as to match the parameter values of each operation parameter with the operation parameter decision tree and obtain a matching result;

[0011] Based on the matching result, determine the operation parameters to be adjusted and the corresponding adjustment directions to determine the adjustment strategy for the target node.

[0012] In another embodiment, determining the operation parameters to be adjusted and the corresponding adjustment directions based on the matching result to determine the adjustment strategy for the target node includes:

[0013] Based on the matching result, determine the operation parameters to be adjusted and the corresponding adjustment directions to generate an adjustment parameter array;

[0014] Calculate the similarity between the adjustment parameter array and the parameter data templates associated with each adjustment strategy to determine the adjustment strategy for the target node based on the similarity.

[0015] In another embodiment, determining the operation parameters to be adjusted and the corresponding adjustment directions based on the matching result to determine the adjustment strategy for the target node includes:

[0016] Based on the matching result, determine each operation parameter to be adjusted to obtain the adjustment level of each operation parameter to be adjusted;

[0017] In response to the adjustment levels of each operation parameter to be adjusted meeting a preset condition, obtain the adjustment directions corresponding to each operation parameter to be adjusted to determine the adjustment strategy for the target node.

[0018] In another embodiment, determining each operation parameter to be monitored and the corresponding time sliding window for each operation parameter includes:

[0019] Based on the configuration information, determine the monitoring frequency and sliding duration of each operation parameter to be monitored to calculate the set of time sliding windows corresponding to each operation parameter;

[0020] For each operation parameter, obtain the corresponding acquisition task template to establish the acquisition task corresponding to each time sliding window in the set of time sliding windows.

[0021] In another embodiment, after collecting the parameter values of the operation parameters, it further includes:

[0022] Update the parameter values of the operation parameters to the sample set for model training, and perform model training on the operation and maintenance model based on the updated sample set to update the operation and maintenance model.

[0023] To achieve the above object, according to another aspect of the embodiments of the present invention, a data processing device is provided.

[0024] A data processing device according to an embodiment of the present invention includes: a determination unit, configured to obtain corresponding configuration information in response to a data processing instruction of a target node, so as to determine each operating parameter to be monitored and a time sliding window corresponding to each operating parameter;

[0025] An acquisition unit, configured to, for each operating parameter, trigger an acquisition task of the operating parameter in response to the current time belonging to the corresponding time sliding window, so as to call a corresponding preset plugin to acquire the parameter value of the operating parameter;

[0026] An adjustment unit, configured to call a preset operation and maintenance model, determine an adjustment strategy of the target node based on the parameter values of each operating parameter, so as to obtain a capacity adjustment program associated with the adjustment strategy and execute it;

[0027] A deployment unit, configured to, in response to successful execution of the capacity adjustment program, obtain adjusted capacity information, so as to call a preset deployment program to deploy the capacity information to the target node.

[0028] In one embodiment, the adjustment unit is specifically configured to:

[0029] Call a preset operation and maintenance model, obtain an operating parameter decision tree corresponding to the target node, so as to match the parameter values of each operating parameter with the operating parameter decision tree to obtain a matching result;

[0030] Determine the operating parameter to be adjusted and the corresponding adjustment direction based on the matching result, so as to determine the adjustment strategy of the target node.

[0031] In another embodiment, the adjustment unit is specifically configured to:

[0032] Determining the operating parameter to be adjusted and the corresponding adjustment direction based on the matching result to determine the adjustment strategy of the target node includes:

[0033] Determine the operating parameter to be adjusted and the corresponding adjustment direction based on the matching result to generate an adjustment parameter array;

[0034] Calculate the similarity between the adjustment parameter array and the parameter data templates associated with each adjustment strategy, so as to determine the adjustment strategy of the target node based on the similarity.

[0035] In another embodiment, the adjustment unit is specifically configured to:

[0036] Determine each operating parameter to be adjusted based on the matching result, so as to obtain the adjustment level of each operating parameter to be adjusted;

[0037] In response to the adjustment level meeting a preset condition for each of the operating parameters to be adjusted, obtain the adjustment direction corresponding to each operating parameter to be adjusted, so as to determine the adjustment strategy of the target node.

[0038] In yet another embodiment, the determining unit is specifically configured to:

[0039] Based on the configuration information, determine the monitoring frequency and sliding duration of each operating parameter to be monitored, so as to calculate the set of time sliding windows corresponding to each operating parameter;

[0040] For each of the operating parameters, obtain the corresponding acquisition task template, so as to establish the acquisition task corresponding to each time sliding window in the set of time sliding windows.

[0041] In yet another embodiment, the device further includes:

[0042] An updating unit, configured to update the parameter value of the operating parameter to the sample set for model training, and perform model training on the operation and maintenance model based on the updated sample set, so as to update the operation and maintenance model.

[0043] To achieve the above object, according to yet another aspect of the embodiments of the present invention, an electronic device is provided.

[0044] An electronic device according to an embodiment of the present invention includes: one or more processors; a storage device, configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the data processing method provided by the embodiments of the present invention.

[0045] To achieve the above object, according to yet another aspect of the embodiments of the present invention, a computer-readable medium is provided.

[0046] A computer-readable medium according to an embodiment of the present invention has a computer program stored thereon, and when the program is executed by a processor, the data processing method provided by the embodiments of the present invention is implemented.

[0047] To achieve the above object, according to yet another aspect of the embodiments of the present invention, a computer program product is provided.

[0048] A computer program product according to an embodiment of the present invention includes a computer program, and when the program is executed by a processor, the data processing method provided by the embodiments of the present invention is implemented.

[0049] One embodiment of the above invention has the following advantages or beneficial effects: In the embodiment of the present invention, for a target node, after a data processing instruction is triggered, each operation parameter to be monitored and the corresponding time sliding window can be determined through configuration information, so that when the current time belongs to the corresponding time sliding window, the parameter values of each operation parameter can be collected through a collection task and a preset plug-in, and then input into an operation and maintenance model to determine an adjustment strategy for the target node and perform capacity adjustment and deployment. Thus, in the embodiment of the present invention, the operation parameters to be monitored in the target node can be monitored and collected to determine how to adjust the capacity of the target node, and the capacity adjustment and deployment can be completed in a timely manner, realizing the monitoring of the running state of the target node and enabling the target node to reasonably allocate traffic through capacity adjustment and deployment in a timely manner, avoiding the problems that when operation and maintenance personnel monitor and maintain the running state, not only excessive manpower is consumed, but also the stability of the business system is easily reduced.

[0050] The further effects of the above non-conventional optional manner will be described below in combination with specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings are used to better understand the present invention and do not constitute an improper limitation to the present invention. Among them:

[0052] Figure 1 is a schematic diagram of a main process of a data processing method according to an embodiment of the present invention;

[0053] Figure 2 is a schematic diagram of another main process of a data processing method according to an embodiment of the present invention;

[0054] Figure 3 is a schematic diagram of the main units of a data processing device according to an embodiment of the present invention;

[0055] Figure 4 is an exemplary system architecture diagram to which an embodiment of the present invention can be applied;

[0056] Figure 5 is a schematic diagram of the structure of a computer system suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following describes exemplary embodiments of the present invention with reference to the drawings, including various details of the embodiments of the present invention to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for the sake of clarity and conciseness, the description below omits the description of well-known functions and structures.

[0058] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. All aspects of data acquisition, storage, use, processing, etc. in the technical solution of this application comply with the relevant regulations of national laws and regulations.

[0059] An embodiment of the present invention provides a data processing system, which can be used in scenarios for monitoring and operation and maintenance of each server node in a business system.

[0060] In an embodiment of the present invention, each business system may include multiple server nodes, and each server node can monitor and perform operation and maintenance on its running status. Specifically, the data processing system can be integrated with the business system, or can be separately set up and establish a data connection to achieve monitoring and operation and maintenance of each server node.

[0061] An embodiment of the present invention provides a data processing method, which can be executed by the data processing system, as Figure 1 shown, this method includes:

[0062] S101: In response to a data processing instruction of a target node, obtain corresponding configuration information to determine each running parameter to be monitored and the time sliding window corresponding to each running parameter.

[0063] Among them, the target node can represent a server node that needs to be monitored and maintained, and the data processing instruction represents an instruction for monitoring and maintaining the target node.

[0064] In an embodiment of the present invention, each node (server node) that needs to be monitored and maintained can be pre-configured. The configuration information may include the running parameters to be monitored, as well as the monitoring information of each running parameter to be monitored, so as to facilitate determining the monitoring implementation method of each running parameter. Therefore, when responding to the data processing instruction of the target node in this step, the corresponding configuration information can be obtained to determine each running parameter to be monitored therefrom.

[0065] In an embodiment of the present invention, the way to monitor the running parameter is to collect the data value of the running parameter. In order to avoid excessive calculation due to excessive data collection, the sliding window technology can be used to implement data collection. After determining each running parameter to be monitored, the monitoring frequency and sliding duration of each running parameter to be monitored can be determined based on the configuration information. The monitoring frequency represents the time point of data collection, and then the data collection time period can be determined through the sliding duration, and data collection is performed during this time period.

[0066] It should be noted that the operating parameters to be monitored in the embodiments of the present invention can be set based on requirements, and specifically can include application information, configuration parameters of nodes, usage parameters of resources, performance parameters of request responses, etc. For example, it can include: GC (Garbage Collection) duration, number of threads, memory usage rate, disk usage rate, CPU usage rate, load rate, bandwidth usage rate, number of database connections, number of GCs, and so on.

[0067] In the embodiments of the present invention, the data system can develop a client for data collection to access the business system and realize data collection of the operating parameters to be monitored in the business system. Specifically, the client can be implemented through scripting languages, shell (a programming language), python (a programming development language), nodojs (a JavaScript runtime environment based on the Chrome V8 engine), etc. The access method between the client and the business system can be not limited. For example, it can be implemented by generating middleware through cloud compilation. The business system can access the cloud compilation middleware. In the source code compilation link of the business system, the source code is passed into the cloud compilation middleware to enhance the compilation result through the cloud compilation middleware. In the cloud compilation of the business system, the feature attribute extraction client mirror can be automatically placed. It starts with the deployment of the business system and can play the role of data extraction. For another example, through the cloud installation method, the client is uploaded to the cloud, and then the script plugin technology, such as shell, python, etc., is deployed. The plugin is introduced into the deployment script of the business system and can start with the startup of the project in the business system to perform data extraction; for another example, the client can be directly installed on the service node and starts with the startup of the server node.

[0068] S102: For each operating parameter, in response to the current time belonging to the corresponding time sliding window, trigger the collection task of the operating parameter to call the corresponding preset plugin to collect the parameter value of the operating parameter.

[0069] Among them, after determining the time window of each operating parameter, the collection task template corresponding to the operating parameter can be obtained, and then the collection task corresponding to the time sliding window can be established. In the embodiments of the present invention, usually, the data of the operating parameter needs to be collected multiple times. Therefore, in step S101, the corresponding time sliding window set can be determined, and then the collection task corresponding to each time sliding window in the time sliding window set can be determined.

[0070] After determining the time sliding window, it is possible to determine in real time whether the time sliding window is reached, that is, whether the current time belongs to the corresponding time sliding window. When the current time belongs to the corresponding time sliding window, the corresponding acquisition task can be triggered. The acquisition task represents the acquisition of the parameter values of the operation parameters. Therefore, the data acquisition of the operation parameters can be performed within the time sliding window.

[0071] Specifically, in the embodiments of the present invention, there may be a preset plug-in for data acquisition to acquire the parameter values of the operation parameters through the preset plug-in.

[0072] It should be noted that in the embodiments of the present invention, a daemon process can be implanted in the business system to implement the acquisition of the parameter values of the operation parameters.

[0073] S103: Invoke a preset operation and maintenance model, determine the adjustment strategy of the target node based on the parameter values of each operation parameter, and obtain and execute the capacity adjustment program associated with the adjustment strategy.

[0074] Among them, the operation and maintenance model is pre-configured and trained. After collecting the parameter values of each operation parameter in step S102, they can be input into the operation and maintenance model to determine how to adjust the target node through the calculation of the operation and maintenance model.

[0075] In the embodiments of the present invention, the operation and maintenance of the target node is realized by adjusting the capacity of the target node, so that the target node can be maintained in a reasonable state. Therefore, the adjustment strategy represents the strategy for adjusting the capacity of the target node. After obtaining the adjustment strategy, the capacity adjustment program associated with the adjustment strategy can be obtained and executed.

[0076] Specifically, in the embodiments of the present invention, the capacity adjustment may include the methods of expansion or contraction, that is, the capacity is expanded or reduced, such as the methods of horizontal scaling and vertical scaling.

[0077] For example, horizontal and vertical scaling can adjust the adaptation configuration (such as CPU, memory, disk, etc.), or can adjust the pool resource information, such as the thread pool, connection pool, etc., or can adjust the virtual machine jvm (Java virtual machine) information to prevent improper jvm settings, frequent GC or long GC pause time.

[0078] The capacity adjustment program is pre-configured, and corresponding capacity adjustment programs can be set for different adjustment methods, so as to realize the capacity adjustment. In the implementation of the capacity scaling method, if the business system uses the private cloud cluster deployment method, a container orchestration tool can be used, for example: Kubernetes (K8s, an open-source tool for managing containerized applications on multiple hosts in a cloud platform) to realize the capacity scaling; if the business system uses a non-private cloud cluster deployment method, it can be realized by adopting an automatic service application service.

[0079] In one implementation, the operation and maintenance model can be implemented through a running parameter decision tree. Each leaf node of the decision tree can include the value range corresponding to each running parameter. For example, each leaf node can correspond to the value range of a running parameter. Then, by comparing the parameter value of the running parameter with the value range, it can be determined whether the running parameter needs to be adjusted and the adjustment direction can be determined. The adjustment direction can include upward adjustment or downward adjustment. Upward adjustment can indicate that the parameter value of the running parameter is lower than the minimum value of the corresponding value range, and downward adjustment can indicate that the parameter value of the running parameter is higher than the maximum value of the corresponding value range. The adjustment strategy determined in this step can be: call the preset operation and maintenance model, obtain the running parameter decision tree corresponding to the target node, so as to match the parameter values of each running parameter with the running parameter decision tree and obtain the matching result; determine the running parameter to be adjusted and the corresponding adjustment direction based on the matching result, so as to determine the adjustment strategy of the target node.

[0080] Specifically, in this step, an associated parameter array template can be set for different adjustment strategies of each running parameter. Among them, the parameter array template can correspond to multiple arrays, and each array represents a combination of a running parameter adjustment method. Each element of the array corresponds to a running parameter one by one, and the positive and negative of the element value can represent the adjustment direction of the corresponding running parameter. The value of the element can include 1 or 0, where 1 indicates that the running parameter needs to be adjusted, and 0 indicates that the running parameter does not need to be adjusted. In this way, after determining the running parameter to be adjusted and the corresponding adjustment direction, the corresponding adjustment parameter array can be generated in the same way, and then the similarity between the adjustment parameter array and the parameter array template associated with each adjustment strategy can be calculated to determine the adjustment strategy of the target node based on the similarity. For example, the adjustment strategy with the highest similarity can be determined as the adjustment strategy of the target node.

[0081] It should be noted that since the situation where some running parameters are out of the value range in special scenarios can be temporarily ignored, in the embodiments of the present invention, an adjustment level can be set for some running parameters. When a parameter with a lower adjustment level is determined as the running parameter to be adjusted, capacity adjustment may not be performed. Therefore, after determining each running parameter to be adjusted based on the matching result, the adjustment level of each running parameter to be adjusted can be obtained, and then it can be judged whether the preset conditions are met; in response to the adjustment levels of each running parameter to be adjusted meeting the preset conditions, obtain the adjustment direction corresponding to each running parameter to be adjusted, so as to determine the adjustment strategy of the target node; in response to the adjustment levels of each running parameter to be adjusted not meeting the preset conditions, determine the non-adjustment strategy. The preset conditions can be set based on requirements. For example, it can be set that the adjustment levels of the running parameters to be adjusted are all the lowest levels.

[0082] S104: In response to the successful execution of the capacity adjustment program, obtain the adjusted capacity information to call a preset deployment program to deploy the capacity information to the target node.

[0083] Among them, the successful execution of the capacity adjustment program indicates that the capacity has been successfully adjusted. Therefore, the adjusted capacity information can be obtained and deployed, that is, call a preset deployment program to deploy the capacity information to the target node.

[0084] The deployment program can adopt smooth deployment means. If the target node is deployed using containers, rolling deployment technology can be used, such as Mesos (an open-source distributed resource management framework), Docker Swarm (a cluster of open-source application container engines), and Kubernetes; if the target node is deployed using servers, automated scripting technology can be used. The principle is: upgrade one or more services at a time, and after the upgrade is completed, add them to the production environment, and continuously execute this process until the deployment of the target node is completed.

[0085] In the embodiment of the present invention, the operation and maintenance model is pre-trained, and the parameter values of the operation parameters collected during the execution of the embodiment of the present invention can also be used as training sample data, so that the operation and maintenance model can be trained and updated in real time. Therefore, after collecting the parameter values of the operation parameters in the embodiment of the invention, the parameter values of the operation parameters can also be updated to the sample set for model training, and model training is performed on the operation and maintenance model based on the updated sample set to update the operation and maintenance model.

[0086] It should be noted that a data warehouse can also be set up in the embodiment of the present invention to store the parameter values of the collected operation parameters and can perform data cleaning on them to generate sample data for model training.

[0087] In the embodiment of the present invention, in the embodiment of the present invention, the operation parameters to be monitored in the target node can be monitored and collected to determine how to adjust the capacity of the target node, and the capacity adjustment and deployment can be completed in a timely manner, realizing the monitoring of the running state of the target node and enabling the target node to reasonably allocate traffic through capacity adjustment and deployment in a timely manner, avoiding the problems that the operation and maintenance personnel need to consume too much manpower to monitor and maintain the running state and are likely to cause the reduction of the stability of the business system.

[0088] The following Figure 1 illustrated embodiments are used to specifically describe the method for data processing in the embodiment of the present invention, as Figure 2 shown, the method includes:

[0089] S201: In response to the data processing instruction of the target node, obtain the corresponding configuration information.

[0090] S202: Determine the monitoring frequency and sliding duration of each operating parameter to be monitored based on the configuration information, so as to calculate the set of time sliding windows corresponding to each operating parameter.

[0091] S203: For each operating parameter, obtain the corresponding acquisition task template to establish the acquisition task corresponding to each time sliding window in the set of time sliding windows.

[0092] S204: In response to the current time belonging to the corresponding time sliding window, trigger the acquisition task of the operating parameter to call the corresponding preset plugin to acquire the parameter value of the operating parameter.

[0093] S205: Call the preset operation and maintenance model to obtain the operating parameter decision tree corresponding to the target node, so as to match the parameter values of each operating parameter with the operating parameter decision tree to obtain the matching result.

[0094] S206: Determine the operating parameter to be adjusted and the corresponding adjustment direction based on the matching result to determine the adjustment strategy of the target node.

[0095] S207: Obtain the capacity adjustment program associated with the adjustment strategy and execute it.

[0096] S208: In response to the successful execution of the capacity adjustment program, obtain the adjusted capacity information to call the preset deployment program to deploy the capacity information to the target node.

[0097] It should be noted that the data processing principle in the embodiments of the present invention is the same as that in Figure 1 the embodiments shown and will not be elaborated here.

[0098] To solve the problems existing in the prior art, an embodiment of the present invention provides a data processing device 300, as Figure 3 shown. The device 300 includes:

[0099] A determination unit 301, configured to obtain the corresponding configuration information in response to the data processing instruction of the target node, so as to determine each operating parameter to be monitored and the time sliding window corresponding to each operating parameter;

[0100] An acquisition unit 302, configured to, for each operating parameter, in response to the current time belonging to the corresponding time sliding window, trigger the acquisition task of the operating parameter to call the corresponding preset plugin to acquire the parameter value of the operating parameter;

[0101] An adjustment unit 303, configured to call the preset operation and maintenance model, determine the adjustment strategy of the target node based on the parameter values of each operating parameter, so as to obtain the capacity adjustment program associated with the adjustment strategy and execute it;

[0102] The deployment unit 304 is configured to obtain the adjusted capacity information in response to the successful execution of the capacity adjustment program, so as to call a preset deployment program to deploy the capacity information to the target node.

[0103] It should be understood that the implementation manner of the embodiments of the present invention is the same as that of the embodiments Figure 1 shown, and will not be elaborated herein.

[0104] In one embodiment, the adjustment unit 303 is specifically configured to:

[0105] Call a preset operation and maintenance model to obtain the operation parameter decision tree corresponding to the target node, and match the parameter values of each operation parameter with the operation parameter decision tree to obtain a matching result;

[0106] Based on the matching result, determine the operation parameters to be adjusted and the corresponding adjustment directions, so as to determine the adjustment strategy of the target node.

[0107] In another embodiment, the adjustment unit 303 is specifically configured to:

[0108] Determine the operation parameters to be adjusted and the corresponding adjustment directions based on the matching result to determine the adjustment strategy of the target node, including:

[0109] Determine the operation parameters to be adjusted and the corresponding adjustment directions based on the matching result to generate an adjustment parameter array;

[0110] Calculate the similarity between the adjustment parameter array and the parameter data templates associated with each adjustment strategy, and determine the adjustment strategy of the target node based on the similarity.

[0111] In another embodiment, the adjustment unit 303 is specifically configured to:

[0112] Determine each operation parameter to be adjusted based on the matching result to obtain the adjustment level of each operation parameter to be adjusted;

[0113] In response to the adjustment levels of each operation parameter to be adjusted meeting a preset condition, obtain the adjustment directions corresponding to each operation parameter to be adjusted, so as to determine the adjustment strategy of the target node.

[0114] In another embodiment, the determination unit 301 is specifically configured to:

[0115] Based on the configuration information, determine the monitoring frequency and sliding duration of each operation parameter to be monitored, and calculate the time sliding window sets corresponding to each operation parameter;

[0116] For each of the operating parameters, obtain the corresponding acquisition task template to establish the acquisition tasks corresponding to each time sliding window in the time sliding window set.

[0117] In yet another embodiment, the apparatus 300 further includes:

[0118] An update unit, configured to update the parameter value of the operating parameter to the sample set for model training, and perform model training on the operation and maintenance model based on the updated sample set to update the operation and maintenance model.

[0119] It should be understood that the implementation manner of the embodiments of the present invention is the same as that of the embodiments shown in Figure 1 、 2 and will not be described in detail here.

[0120] In the embodiments of the present invention, the operating parameters to be monitored in the target node can be monitored and acquired to determine how to adjust the capacity of the target node, and the capacity adjustment and deployment can be completed in a timely manner, realizing the monitoring of the operating state of the target node and enabling the target node to reasonably allocate traffic through capacity adjustment and deployment in a timely manner, avoiding the problems that the operation and maintenance personnel need to consume too much manpower for monitoring and maintaining the operating state and easily lead to the reduction of the stability of the business system.

[0121] According to an embodiment of the present invention, the embodiments of the present invention further provide an electronic device and a readable storage medium.

[0122] The electronic device according to the embodiment of the present invention includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the data processing method provided by the embodiments of the present invention.

[0123] Figure 4 An exemplary system architecture 400 to which the data processing method or data processing apparatus according to the embodiments of the present invention can be applied is shown.

[0124] As Figure 4 shown, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405. The network 404 is used to provide a medium for communication links between the terminal devices 401, 402, 403 and the server 405. The network 404 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0125] Users can use terminal devices 401, 402, and 403 to interact with server 405 via network 404 to receive or send messages, etc. Various client applications can be installed on terminal devices 401, 402, and 403.

[0126] Terminal devices 401, 402, and 403 can be, but are not limited to, smart phones, tablet computers, laptop portable computers, desktop computers, and so on.

[0127] Server 405 can be a server that provides various services. The server can analyze and process data such as product information query requests received, and feedback the processing results (such as product information - only for example) to the terminal device.

[0128] It should be noted that the data processing method provided by the embodiments of the present invention is generally executed by server 405. Correspondingly, the data processing device is generally set in server 405.

[0129] It should be understood that Figure 4 the numbers of the terminal devices, networks, and servers in

[0130] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, networks, and servers. Figure 5 Shown below is a schematic structural diagram of a computer system 500 suitable for implementing the embodiments of the present invention with reference to Figure 5 The shown computer system is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0131] As Figure 5 shown, computer system 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to the program stored in read-only memory (ROM) 502 or the program loaded from storage section 508 into random access memory (RAM) 503. In RAM 503, various programs and data required for the operation of system 500 are also stored. CPU 501, ROM 502, and RAM 503 are connected to each other via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0132] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as required. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc. is mounted on the drive 510 as required so that a computer program read therefrom is installed into the storage section 508 as required.

[0133] Specifically, according to an embodiment disclosed by the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment disclosed by the present invention includes a computer program product which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 509, and / or installed from the removable medium 511. When the computer program is executed by a central processing unit (CPU) 501, the above functions defined in the system of the present invention are performed.

[0134] It should be noted that the computer-readable medium shown in the present invention can be a computer-readable signal medium, 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, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium 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, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which the computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable medium can 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 can be transmitted by any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0135] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram can represent a unit, a program segment, or a part of code, and the above unit, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0136] The units involved in the embodiments of the present invention can be implemented in software or in hardware. The described units can also be provided in a processor. For example, it can be described as: a processor includes a determination unit, a collection unit, an adjustment unit, and a deployment unit. Among them, the names of these units do not constitute a limitation on the unit itself in some cases. For example, the determination unit can also be described as "the unit for determining the function of the determination unit".

[0137] As another aspect, the present invention also provides a computer-readable medium, which can be included in the device described in the above embodiments; or can exist alone without being assembled into the device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by the device, the device is caused to execute the data processing method provided by the present invention.

[0138] As another aspect, the present invention also provides a computer program product, including a computer program, and when the program is executed by a processor, it implements the data processing method provided by the embodiments of the present invention.

[0139] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for data processing, characterized in that, including: In response to a data processing instruction of a target node, obtaining corresponding configuration information to determine each operating parameter to be monitored and a time sliding window corresponding to each said operating parameter; For each said operating parameter, in response to the current time belonging to the corresponding time sliding window, triggering a collection task of the operating parameter to call a corresponding preset plugin to collect the parameter value of the operating parameter; Calling a preset operation and maintenance model, determining an adjustment strategy of the target node based on the parameter values of each said operating parameter, to obtain a capacity adjustment program associated with the adjustment strategy and execute it; In response to successful execution of the capacity adjustment program, obtaining adjusted capacity information to call a preset deployment program to deploy the capacity information to the target node.

2. The method according to claim 1, characterized in that, The calling a preset operation and maintenance model, determining an adjustment strategy of the target node based on the parameter values of each said operating parameter, includes: Calling a preset operation and maintenance model, obtaining an operating parameter decision tree corresponding to the target node, to match the parameter values of each said operating parameter with the operating parameter decision tree to obtain a matching result; Determining an operating parameter to be adjusted and a corresponding adjustment direction based on the matching result to determine the adjustment strategy of the target node.

3. The method according to claim 2, characterized in that, Determining an operating parameter to be adjusted and a corresponding adjustment direction based on the matching result to determine the adjustment strategy of the target node, includes: Determining an operating parameter to be adjusted and a corresponding adjustment direction based on the matching result to generate an adjustment parameter array; Calculating the similarity between the adjustment parameter array and a parameter data template associated with each adjustment strategy to determine the adjustment strategy of the target node based on the similarity.

4. The method according to claim 2, characterized in that, Determining an operating parameter to be adjusted and a corresponding adjustment direction based on the matching result to determine the adjustment strategy of the target node, includes: Determining each operating parameter to be adjusted based on the matching result to obtain an adjustment level of each said operating parameter to be adjusted; In response to the adjustment levels of each said operating parameter to be adjusted meeting a preset condition, obtaining an adjustment direction corresponding to each operating parameter to be adjusted to determine the adjustment strategy of the target node.

5. The method according to claim 1, characterized in that, The determining each operating parameter to be monitored and a time sliding window corresponding to each said operating parameter, includes: Based on the configuration information, determining the monitoring frequency and sliding duration of each operating parameter to be monitored to calculate a set of time sliding windows corresponding to each said operating parameter; For each said operating parameter, obtaining a corresponding collection task template to establish a collection task corresponding to each time sliding window in the set of time sliding windows.

6. The method according to claim 1, characterized in that, After collecting the parameter value of the operating parameter, further includes: Updating the parameter value of the operating parameter to a sample set for model training, performing model training on the operation and maintenance model based on the updated sample set to update the operation and maintenance model.

7. An apparatus for data processing, characterized in that, including: A determining unit, configured to, in response to a data processing instruction of a target node, obtain corresponding configuration information to determine each operating parameter to be monitored and a time sliding window corresponding to each said operating parameter; The acquisition unit is configured to, for each of the operating parameters, trigger an acquisition task of the operating parameter in response to the current time belonging to the corresponding time sliding window, so as to call a corresponding preset plugin to acquire the parameter value of the operating parameter; The adjustment unit is configured to call a preset operation and maintenance model, determine an adjustment strategy for the target node based on the parameter values of the operating parameters, so as to obtain a capacity adjustment program associated with the adjustment strategy and execute it; The deployment unit is configured to, in response to the successful execution of the capacity adjustment program, obtain the adjusted capacity information, so as to call a preset deployment program to deploy the capacity information to the target node.

8. The apparatus according to claim 7, characterized in that, Specifically, the adjustment unit is configured to: Call a preset operation and maintenance model, obtain the operating parameter decision tree corresponding to the target node, so as to match the parameter values of the operating parameters with the operating parameter decision tree to obtain a matching result; Determine the operating parameter to be adjusted and the corresponding adjustment direction based on the matching result, so as to determine the adjustment strategy for the target node.

9. An electronic device, characterized in that, It includes: One or more processors; A storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1-6.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the method according to any one of claims 1-6 is implemented.

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