System resource processing method and device, electronic equipment and storage medium

Abstract

The invention provides a system resource processing method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: determining current resource information, obtaining first access data of each system service, and determining a first data volume and access time corresponding to each first access data, an access data sequence is generated according to the multiple pieces of first access data and the first data volume and access time corresponding to each piece of first access data, system resource information conforming to a first time range is determined according to the access data sequence and artificial intelligence AI, and the access time is earlier than the time included in the first time range; the resource adjustment information is determined according to the current resource information and the system resource information, and the current system resource is adjusted according to the resource adjustment information to obtain the target system resource, so that the system resource can be adjusted in time according to the resource demand of the system service, and the system resource waste caused by excessive system resources is avoided; and the stability of the system can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a system resource processing method, device, electronic device and storage medium. Background Art

[0002] Configuring system resources is a key step in ensuring that the system provides stable system services. When fewer resources are configured for the system and the system has a large amount of business to be executed, the system's business will be interrupted due to insufficient system resources. When more resources are configured for the system and the system has a small amount of business to be executed, a large amount of resources will be wasted.

[0003] Therefore, how to adjust system resources in a timely manner so that system resources can adapt to the resource requirements of system business has become a key research direction. Summary of the invention

[0004] The present disclosure proposes a system resource processing method, device, electronic device, storage medium and computer program product, aiming to solve the technical problems in the related technologies at least to a certain extent.

[0005] The first aspect of the present disclosure proposes a system resource processing method, including: determining current resource information, wherein the current resource information is used to describe the current system resources; obtaining first access data of each system service, and determining a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources; generating an access data sequence according to multiple first access data and a first data volume and an access time corresponding to each first access data; determining system resource information that meets a first time range according to the access data sequence and artificial intelligence AI, wherein the access time is earlier than the time included in the first time range; determining resource adjustment information according to the current resource information and the system resource information; and adjusting the current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources.

[0006] The second aspect of the present disclosure proposes a system resource processing device, including: a first determination module, used to determine current resource information, wherein the current resource information is used to describe the current system resources; an acquisition module, used to obtain first access data of each system service, and determine the first data volume and access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources; a generation module, used to generate an access data sequence according to multiple first access data and the first data volume and access time corresponding to each first access data; a second determination module, used to determine system resource information that meets the first time range according to the access data sequence and artificial intelligence AI, and the access time is earlier than the time included in the first time range; a third determination module, used to determine resource adjustment information according to the current resource information and the system resource information; and an adjustment module, used to adjust the current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources.

[0007] An embodiment of the third aspect of the present disclosure proposes an electronic device, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement a system resource processing method.

[0008] The fourth aspect of the present disclosure provides a computer-readable storage medium. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute a system resource processing method.

[0009] The fifth aspect embodiment of the present disclosure proposes a computer program product, including a computer program, characterized in that the computer program is executed by a processor to process system resources.

[0010] The system resource processing method, device, electronic device, storage medium and computer program product proposed in this embodiment have at least the following beneficial effects: by determining current resource information, wherein the current resource information is used to describe the current system resources, obtaining first access data of each system service, and determining the first data volume and access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources, generating an access data sequence according to multiple first access data and the first data volume and access time corresponding to each first access data, determining system resource information that meets the first time range according to the access data sequence and artificial intelligence AI, the access time is earlier than the time included in the first time range, determining resource adjustment information according to the current resource information and the system resource information, and adjusting the current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources, thereby being able to timely adjust the system resources according to the resource requirements of the system services, so that the adjusted target system resources can adapt to the resource requirements of the system services provided by the system within the first time position, avoiding waste of system resources caused by excessive system resources, thereby improving the stability of the system.

[0011] Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and / or additional aspects and advantages of the present disclosure will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0013] Figure 1 is a flowchart of a method for processing system resources according to the first embodiment of the present disclosure;

[0014] Figure 2 is a flowchart of a method for processing system resources according to a second embodiment of the present disclosure;

[0015] Figure 3 is a flowchart of a system resource processing method according to the third embodiment of the present disclosure;

[0016] Figure 4 is a block diagram of a system resource processing device according to the present disclosure;

[0017] Figure 5 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0018] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0019] It should be noted that the executor of the system resource processing method of this embodiment may be a system resource processing device, which may be implemented by software and / or hardware, and which may be configured in an electronic device, which may include but is not limited to a terminal, a server, etc.

[0020] It should be noted that the process of obtaining, storing, using, and processing information in the disclosed technical solution complies with the relevant provisions of national laws and regulations and does not violate public order and good morals.

[0021] It should be noted that in the embodiments of the present application, there may be existing solutions in the industry such as certain software, components, models, etc., which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the relevant content of the solution.

[0022] Figure 1 is a flowchart of a system resource processing method according to the first embodiment of the present disclosure, such as Figure 1 As shown, the method includes:

[0023] S101: Determine current resource information, where the current resource information is used to describe current system resources.

[0024] Among them, the current resource information is used to describe the current system resources, which can be the current remaining resources of the system, or the resources pre-allocated to a certain system service, and the system resources can be system hardware resources, such as memory, processor performance, or network resources, such as network bandwidth, number of servers, etc., without any restrictions.

[0025] In the disclosed embodiments, the current resource information may be determined by obtaining the system's log information and parsing the log information to determine the system's current resource information. Alternatively, the system's resource usage may be monitored based on a system monitoring tool (e.g., Zabbix, Nagios, Prometheus, etc.) to determine the system's current resource information.

[0026] S102: Acquire first access data of each system service, and determine a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on current system resources.

[0027] The system provides at least one system service based on current system resources, that is, the system can use current system resources to execute system services, and the system services may be, for example, data processing services, session services, etc., without limitation.

[0028] The first access data of each system service refers to data used to record, monitor and analyze the user's use of the system service. The first access data may be, for example, an access type, an access parameter, and the like.

[0029] The amount of data occupied by each first access data is the first data amount, and the first access data has a corresponding access time.

[0030] In the disclosed embodiment, the log data of the system service may be collected in real time through a log collection tool, and the log data may be parsed to obtain the first access data of each system service, and determine the first data volume and access time corresponding to each first access data.

[0031] S103: Generate an access data sequence according to a plurality of first access data and a first data volume and an access time corresponding to each first access data.

[0032] In the embodiment of the present disclosure, after obtaining the first access data of each system service and determining the first data volume and access time corresponding to each first access data, an access data sequence can be generated based on multiple first access data and the first data volume and access time corresponding to each first access data.

[0033] In some embodiments, an access data sequence is generated based on multiple first access data and the first data volume and access time corresponding to each first access data. The access time corresponding to the first access data may be unified in time format, and all first access data and the first data volume corresponding to each first access data are sorted according to the access time to obtain a sorted access data sequence.

[0034] In other embodiments, an access data sequence is generated based on multiple first access data and the first data volume and access time corresponding to each first access data. This may be by creating an empty data structure (such as a list, array, or database table), and adding the multiple first access data and the first data volume and access time corresponding to each first access data to the aforementioned created empty data structure to obtain the access data sequence. There is no limitation to this.

[0035] S104: Determine system resource information that matches the first time range based on the access data sequence and artificial intelligence AI, where the access time is earlier than the time included in the first time range.

[0036] The access time is earlier than the time included in the first time range.

[0037] The system resource information that complies with the first time range is used to describe the system resources required by the system to provide system services within the first time range.

[0038] In the disclosed embodiment, after generating an access data sequence based on multiple first access data and the first data volume and access time corresponding to each first access data, system resource information that meets the first time range can be determined based on the access data sequence and artificial intelligence (AI).

[0039] In some embodiments, system resource information that meets the first time range is determined based on the access data sequence and artificial intelligence AI. This can be based on a mapping relationship between a good sample access data sequence and sample system resource information, pre-training an artificial intelligence model until the model converges, and then inputting the access data sequence into the trained artificial intelligence model to obtain system resource information that meets the first time range output by the model.

[0040] Alternatively, system resource information that fits the first time range may be determined based on the access data sequence and artificial intelligence AI. Alternatively, AI technology (such as a machine learning algorithm) may be used to construct a time screening model that can automatically identify and screen out data records that fall within the first time range. After screening out data records that are earlier than the first time range, AI technology (such as natural language processing, data mining, etc.) may be used to extract the required system resource information from the screened data records.

[0041] S105: Determine resource adjustment information according to current resource information and system resource information.

[0042] The resource adjustment information is used to adjust the system resources to match the resource requirements of the system services, to avoid the inability of system services to run due to insufficient system resources, or to avoid wasting system resources due to a large amount of system resources.

[0043] The resource adjustment information may refer to a strategy for adjusting system resources, such as expanding or reducing system resources, or may refer to an adjustment amount for system resources, which is not limited.

[0044] In some embodiments, resource adjustment information is determined based on current resource information and system resource information. The current resource information and system resource information are compared to obtain a comparison result, and when the comparison result indicates that the current resources of the system are less than the resources required to execute system services within a first time range, the resource adjustment strategy is determined to be to expand the system's resources; when the comparison result indicates that the current resources are greater than the resources required to execute system services within the first time range, the resource adjustment strategy is determined to be to reduce the system's resources.

[0045] In other embodiments, resource adjustment information is determined based on current resource information and system resource information. The difference between current resource quantity information (current remaining resource quantity) and system resource information (required resource quantity) may be determined, and the difference between current resource quantity information (current remaining resource quantity) and system resource information (required resource quantity) may be used as resource adjustment information.

[0046] S106: Adjust the current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources.

[0047] In the disclosed embodiment, after determining resource adjustment information according to current resource information and system resource information, the current system resources may be adjusted according to the resource adjustment information to obtain target system resources.

[0048] That is to say, in the embodiments of the present disclosure, the current system resources can be expanded or reduced in capacity based on the resource adjustment information. Thus, by adjusting the resources, the system's processing capabilities can be optimized to better meet service requirements. By ensuring that critical services obtain sufficient resources, the stable operation of the system can be maintained. By allocating resources to the system services that need them most, more efficient resource utilization can be achieved. By optimizing resource usage, energy consumption and operation and maintenance costs can be reduced. In the event of a failure, these redundant resources can quickly take over services to reduce downtime.

[0049] In an embodiment of the present disclosure, by determining current resource information, wherein the current resource information is used to describe current system resources, obtaining first access data of each system service, and determining a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources, generating an access data sequence according to a plurality of first access data and a first data volume and an access time corresponding to each first access data, determining system resource information that conforms to a first time range according to the access data sequence and artificial intelligence AI, wherein the access time is earlier than a time included in the first time range, determining resource adjustment information according to the current resource information and the system resource information, and adjusting the current system resources according to the resource adjustment information, to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources, thereby being able to timely adjust the system resources according to the resource requirements of the system services, so that the adjusted target system resources can be adapted to the resource requirements of the system services provided by the system within the first time position, thereby avoiding waste of system resources caused by excessive system resources, thereby being able to improve the stability of the system.

[0050] Figure 2 is a flow chart of a system resource processing method according to a second embodiment of the present disclosure, such as Figure 2 As shown, the method includes:

[0051] S201: Determine current resource information, where the current resource information is used to describe current system resources.

[0052] The specific description of S201 can be found in the above embodiment, which will not be repeated here.

[0053] S202: Establishing a communication connection between a data detection service and each system service through a first service, wherein the data detection service includes: an interface of a first method, and the first method is used to obtain first access data.

[0054] In the disclosed embodiment, a data detection service may be pre-configured for the system. The data detection service can automatically collect current resource information of the system and can adjust current system resources according to the current resource information and system resource information.

[0055] The first service may be, for example, an open source secure shell protocol service (OpenSSH), which is not limited.

[0056] The data detection service includes: an interface of a first method, and the first method is used to obtain first access data.

[0057] That is to say, in the embodiment of the present disclosure, the data detection service may be deployed on a separate service, a python3 environment may be installed on the server, and a communication connection may be established between the data detection service and each system service through the first service.

[0058] S203: In response to receiving the trigger instruction, call the interface of the first method according to the trigger instruction to obtain first access data of each system service.

[0059] In the embodiment of the present disclosure, after establishing a communication connection between the data detection service and each system service through the first service, in response to receiving a trigger instruction, the data detection service can call the interface of the first method according to the trigger instruction to obtain the first access data of each system service, and store the first access data of each system service in a database.

[0060] S204: Generate an access data sequence according to a plurality of first access data and a first data volume and an access time corresponding to each first access data.

[0061] The specific description of S204 can be found in the above embodiment, which will not be repeated here.

[0062] S205: Provide at least one candidate time range in an interface of an electronic device, wherein the electronic device is at least used to deploy a data detection service.

[0063] The candidate time range may be a plurality of pre-set time ranges later than the access time.

[0064] That is to say, in the embodiments of the present disclosure, multiple candidate time ranges can be pre-set based on service requirements in actual business scenarios or service execution conditions in historical time periods, and the multiple candidate time ranges can be provided for display in the interface of the electronic device for users to select based on service requirements.

[0065] S206: Receive a time setting instruction, where the time setting instruction is used to select a candidate time range from at least one candidate time range.

[0066] The time setting instruction is an instruction made by the user terminal and is used to select a candidate time range from at least one candidate time range.

[0067] That is to say, in the embodiment of the present disclosure, at least one candidate time range may be provided in the interface of the electronic device, and the electronic device may accept a time setting instruction from the user to determine the first time range according to the time setting instruction.

[0068] S207: Using the candidate time range selected by the time setting instruction as the first time range.

[0069] In the embodiment of the present disclosure, the electronic device may receive a time setting instruction made by a user terminal, and based on the time setting instruction, use the candidate time range selected by the time setting instruction as the first time range.

[0070] In an embodiment of the present disclosure, at least one candidate time range is provided in an interface of an electronic device, wherein the electronic device is at least used to deploy a data detection service and receive a time setting instruction, wherein the time setting instruction is used to select a candidate time range from at least one candidate time range, and the candidate time range selected by the time setting instruction is used as the first time range, so that it is more convenient for users to set the time without manually entering a specific time point or time period. Users can easily switch between different time ranges according to different scenarios or task requirements. The setting method of the candidate time range reduces the problem of inaccurate time setting caused by manual input errors of users, has good scalability and adaptability, and can meet the time range setting requirements of different users.

[0071] S208: Determine system resource information that matches the first time range based on the access data sequence and artificial intelligence AI, where the access time is earlier than the time included in the first time range.

[0072] S209: Determine resource adjustment information according to current resource information and system resource information.

[0073] S210: Adjust current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources.

[0074] The specific description of S208 - S210 can be found in the above embodiment, which will not be repeated here.

[0075] In the embodiment of the present disclosure, by determining the current resource information, a communication connection is established between the data detection service and each system service through the first service, wherein the data detection service includes: an interface of the first method, the first method is used to obtain first access data, in response to receiving a trigger instruction, the interface of the first method is called according to the trigger instruction to obtain the first access data of each system service, an access data sequence is generated according to multiple first access data and the first data volume and access time corresponding to each first access data, and at least one candidate time range is provided in the interface of the electronic device, wherein the electronic device is at least used to deploy the data detection service, receive a time setting instruction, and use the candidate time range selected by the time setting instruction as the first time range, so that it is more convenient for users to set time without manually entering a specific time point or time period. Users can set the time according to different scenarios or any Service needs, easily switch between different time ranges, the setting method of candidate time ranges reduces the problem of inaccurate time setting caused by manual input errors by users, has good scalability and adaptability, and can meet the time range setting needs of different users, and determines the system resource information that meets the first time range according to the access data sequence and artificial intelligence AI, and the access time is earlier than the time included in the first time range. The resource adjustment information is determined according to the current resource information and the system resource information, and the current system resources are adjusted according to the resource adjustment information to obtain the target system resources. As a result, the system resources can be adjusted in time according to the resource needs of the system services, so that the adjusted target system resources can be adapted to the resource needs of the system services provided by the system in the first time position, thereby avoiding the waste of system resources caused by excessive system resources, thereby improving the stability of the system.

[0076] Figure 3 is a flow chart of a system resource processing method according to the third embodiment of the present disclosure, such as Figure 3 As shown, the method includes:

[0077] S301: Determine current resource information, where the current resource information is used to describe current system resources.

[0078] S302: Acquire first access data of each system service, and determine a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on current system resources.

[0079] S303: Generate an access data sequence according to a plurality of first access data and a first data volume and an access time corresponding to each first access data.

[0080] The specific description of S301 - S303 can be found in the above embodiment, which will not be repeated here.

[0081] S304: Determine a data volume sequence corresponding to the first time range according to the access data sequence and the AI, wherein the data volume sequence at least includes a second data volume corresponding to each second access data.

[0082] The data volume sequence at least includes the second data volume corresponding to each second access data.

[0083] The second access data refers to data used to record, monitor and analyze the user's use of system services. The second access data may be, for example, access type, access parameter, etc., which is not limited.

[0084] The amount of data occupied by each second access data is the second data amount, and there is no restriction on this.

[0085] That is to say, in the embodiments of the present disclosure, the access data sequence may be cleaned to remove duplicate, invalid or abnormal data, and ensure that the timestamps in the access data sequence are aligned with the first time range. Then, according to the needs, the access data sequence may be aggregated according to time intervals (such as hours, days, weeks, etc.) to obtain a summary of the access data within each time interval. Then, according to the characteristics of the access data sequence and the analysis needs, a suitable AI model may be selected, such as a recurrent neural network, a long short-term memory network, a time series analysis model, etc., and the AI ​​model may be trained using the historical access data sequence. After the model training is completed, the model may be used to predict or generate the access data within the first time range to obtain a second data volume corresponding to each second access data. Then, the second data volume of each second access data corresponding to the first time range may be extracted from the prediction results of the AI ​​model, and the extracted second data volumes may be arranged in chronological order to construct a data volume sequence corresponding to the access data sequence.

[0086] Optionally, in some embodiments, determining the data volume sequence corresponding to the first time range based on the access data sequence and AI can be done by inputting the access data sequence into a prediction model and obtaining the data volume sequence corresponding to the first time range output by the prediction model, wherein the prediction model has modeled and learned the mapping relationship between the access data sequence and the data volume sequence corresponding to the first time range.

[0087] Among them, the prediction model has modeled and learned the mapping relationship between the access data sequence and the data volume sequence corresponding to the first time range, that is, the initial prediction model can be trained according to the mapping relationship between the access data sequence and the data volume sequence corresponding to the first time range until the initial prediction model converges. The initial prediction model can be an artificial intelligence model, and the artificial intelligence model can be, for example, a deep learning model, or a neural network model, etc., without limitation.

[0088] That is to say, in the embodiments of the present disclosure, the access data sequence can be input into a pre-trained prediction model, and the data volume sequence corresponding to the first time range output by the prediction model can be obtained. As a result, the data volume in the future time period can be more accurately predicted, thereby improving the accuracy of the prediction, optimizing resource utilization, reducing risks, and promoting the automation and intelligence of business processing.

[0089] In the disclosed embodiment, the prediction model includes: an autoregressive sub-model, a differential sub-model and a moving average sub-model.

[0090] In the disclosed embodiment, the prediction model may be an autoregressive integrated moving average model (ARIMA). The ARIMA model is composed of three parts, including an autoregressive sub-model, a differential sub-model, and a moving average sub-model.

[0091] The basic idea of ​​the ARIMA model is to use the historical information of the data itself to predict the future. The ARIMA model attempts to extract the time series patterns hidden behind the data through the autocorrelation and difference of the data, and then use these patterns to predict future data.

[0092] Among them, the autoregressive model part is used to process the autoregressive part of the time series, which takes into account the impact of observations in the historical period on the current value. The difference submodel part is used to make the non-stationary time series stable. Through first-order or second-order difference processing, the trend and seasonal factors in the time series are eliminated. The moving average submodel part is used to process the moving average part of the time series, which takes into account the impact of the prediction error in the historical event segment on the current value. Combining the above three models, the ARIMA model can not only capture the trend changes of the data, but also process data with temporary, sudden changes or large noise.

[0093] In the embodiment of the present disclosure, the mathematical expression of the prediction model can be expressed as:

[0094] Y t =φ1Y t -1+φ2Y t -2+Kφ p Y t-p +θ1ε t -2+Kθ q ε t-q +ε t ;

[0095] Among them, Y t To access the data sequence, φ1 to φ pare the parameters of the AR model, which are used to describe the relationship between the current value and the values ​​at p time points in the past. q are the parameters of the MA model, which are used to describe the relationship between the current value and the error at the past q time points, ε t is the error term at time point t, and c is a constant term.

[0096] Optionally, in some embodiments, the access data sequence is input into the prediction model, and a data volume sequence corresponding to the first time range is obtained by the prediction model output. The first impact information corresponding to each first access data in the access data sequence can be extracted through an autoregressive sub-model, wherein the first impact information is used to describe the impact of the first access data on the second data volume; the second impact information is obtained by performing differential processing on multiple first impact information through a differential sub-model; the third impact information is obtained through a moving average sub-model, and a data volume sequence corresponding to the first time range is generated based on the second impact information and the third impact information, wherein the third impact information is used to describe the impact of the prediction error on the second data volume.

[0097] The first impact information is used to describe the impact of the first access data on the second data volume, that is, the impact of the observation value in the historical time period on the current value.

[0098] The second impact information is used to describe the trend and seasonal factors in the time series.

[0099] The third impact information is used to describe the impact of the prediction error on the second data volume, that is, the impact of the prediction error in the historical event segment on the current value.

[0100] That is to say, in the embodiments of the present disclosure, the autoregressive part of the access data sequence can be processed based on the autoregressive sub-model to obtain the first influence information corresponding to each first access data in the access data sequence, and the first-order or second-order equal difference processing can be performed on the multiple first influence information through the differential sub-model to obtain the second influence information, and then the moving average part of the second influence information is processed by the moving average sub-model, and the data volume sequence corresponding to the first time range is generated according to the second influence information and the third influence information. Thus, the three sub-models of the joint prediction model can be used to process the access data sequence in an orderly manner, and the data volume sequence corresponding to the first time range can be accurately predicted, thereby improving the determination effect of the data volume sequence.

[0101] S305: Determine system resource information that meets the first time range according to the data volume sequence.

[0102] In the embodiment of the present disclosure, after determining the data volume sequence corresponding to the first time range according to the access data sequence and AI, the system resource information that conforms to the first time range can be determined according to the data volume sequence.

[0103] In some embodiments, system resource information that conforms to a first time range is determined based on a data volume sequence. The data volume sequence and the first time range may be input into a large model, and the large model processes the data volume sequence to determine the system resource information that conforms to the first time range.

[0104] In some other embodiments, system resource information that meets the first time range is determined based on the data volume sequence. Alternatively, a reference data volume sequence and different reference system resource information corresponding to each reference data volume sequence may be obtained, and each reference system resource information has a corresponding reference time range. Then, the data volume sequence may be determined from multiple reference data volume sequences, and a reference time range that is the same as the first time range may be determined from the reference time range corresponding to the data volume sequence. The reference system resource information corresponding to the reference time range may be used as the system resource information that meets the first time range. There is no limitation on this.

[0105] Optionally, in some embodiments, determining system resource information that conforms to the first time range based on the data volume sequence may be performed by determining distribution characteristics of multiple second data volumes in the data volume sequence, and determining system resource information that conforms to the first time range based on the distribution characteristics.

[0106] Among them, in the data volume sequence, the distribution characteristics of the "multiple second data volumes" can be described from a statistical perspective, mainly involving characteristic information such as the central tendency, degree of dispersion, skewness and peak state of the data.

[0107] That is to say, in the embodiments of the present disclosure, the peak time period, the trough time period and the changing trend of the data volume can be identified based on the distribution characteristics of the data volume sequence, and a reasonable resource demand threshold can be determined in combination with the actual situation of the system resources, and then the system resource information that meets the first time range can be determined based on the resource demand pattern and the threshold. Thus, the distribution characteristics of the data volume sequence can be analyzed, and the resource demand of the system in different time periods can be accurately identified. This helps to achieve accurate resource allocation and avoid excessive or insufficient allocation of resources. The resource allocation strategy formulated according to the resource demand pattern and threshold can ensure that resources are fully utilized during peak periods and reasonably released during trough periods, which helps to improve the overall utilization efficiency of resources.

[0108] S306: Determine resource adjustment information according to current resource information and system resource information.

[0109] S307: Adjust the current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources.

[0110] The specific description of S306-S307 can be found in the above embodiment, which will not be repeated here.

[0111] In the embodiment of the present disclosure, by determining the current resource information, wherein the current resource information is used to describe the current system resources, and then obtaining the first access data of each system service, and determining the first data volume and access time corresponding to each first access data, and generating an access data sequence according to the plurality of first access data and the first data volume and access time corresponding to each first access data, and then determining the data volume sequence corresponding to the first time range according to the access data sequence and AI, wherein the data volume sequence at least includes the second data volume corresponding to each second access data, and then determining the system resource information that meets the first time range according to the data volume sequence, and determining the resource adjustment information according to the current resource information and the system resource information, and adjusting the current system resources according to the resource adjustment information to obtain the target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources, thereby, through accurate prediction and flexible adjustment, it is possible to avoid system performance degradation or crash caused by resource shortage, and at the same time, dynamically adjusting system resources can ensure that resources are fully utilized when needed and released when not needed, thereby helping to improve the overall resource utilization efficiency of the system and thus improve system performance.

[0112] Figure 4 is a block diagram of a system resource processing device according to the present disclosure, such as Figure 4 As shown, the system resource processing device 40 includes:

[0113] A first determining module 401 is used to determine current resource information, wherein the current resource information is used to describe current system resources;

[0114] an acquisition module 402, configured to acquire first access data of each system service and determine a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on current system resources;

[0115] A generating module 403, configured to generate an access data sequence according to a plurality of first access data and a first data volume and an access time corresponding to each first access data;

[0116] A second determination module 404 is used to determine, based on the access data sequence and the artificial intelligence AI, system resource information that matches the first time range, and the access time is earlier than the time included in the first time range;

[0117] A third determining module 405 is used to determine resource adjustment information according to current resource information and system resource information; and

[0118] The adjustment module 406 is used to adjust the current system resources according to the resource adjustment information to obtain the target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources.

[0119] In some embodiments of the present disclosure, the acquisition module 402 is further configured to:

[0120] Establishing a communication connection between the data detection service and each system service through the first service, wherein the data detection service includes: an interface of a first method, the first method is used to obtain first access data;

[0121] In response to receiving the trigger instruction, the interface of the first method is called according to the trigger instruction to obtain the first access data of each system service.

[0122] In some embodiments of the present disclosure, the system resource processing device 40 is further configured to:

[0123] Providing at least one candidate time range in an interface of an electronic device, wherein the electronic device is at least used to deploy a data detection service;

[0124] receiving a time setting instruction, wherein the time setting instruction is used to select a candidate time range from at least one candidate time range;

[0125] The candidate time range selected by the time setting instruction is used as the first time range.

[0126] In some embodiments of the present disclosure, the second determining module 404 is further configured to:

[0127] Determine, according to the access data sequence and the AI, a data volume sequence corresponding to the first time range, wherein the data volume sequence at least includes a second data volume corresponding to each second access data;

[0128] System resource information that complies with the first time range is determined according to the data volume sequence.

[0129] In some embodiments of the present disclosure, the second determining module 404 is further configured to:

[0130] The access data sequence is input into the prediction model, and the data volume sequence corresponding to the first time range output by the prediction model is obtained, wherein the prediction model has modeled and learned the mapping relationship between the access data sequence and the data volume sequence corresponding to the first time range.

[0131] In some embodiments of the present disclosure, the prediction model includes: an autoregressive sub-model, a differential sub-model, and a moving average sub-model;

[0132] The second determining module 404 is further configured to:

[0133] Extracting first impact information corresponding to each first access data in the access data sequence through an autoregressive sub-model, wherein the first impact information is used to describe the impact of the first access data on the second data volume;

[0134] Performing differential processing on the plurality of first impact information through a differential sub-model to obtain second impact information;

[0135] The third impact information is obtained through the moving average sub-model, and a data volume sequence corresponding to the first time range is generated according to the second impact information and the third impact information, wherein the third impact information is used to describe the impact of the prediction error on the second data volume.

[0136] In some embodiments of the present disclosure, the second determining module 404 is further configured to:

[0137] determining distribution characteristics of a plurality of second data volumes in the data volume sequence;

[0138] System resource information that matches the first time range is determined according to the distribution characteristics.

[0139] In an embodiment of the present disclosure, by determining current resource information, wherein the current resource information is used to describe current system resources, obtaining first access data of each system service, and determining a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources, generating an access data sequence according to a plurality of first access data and a first data volume and an access time corresponding to each first access data, determining system resource information that conforms to a first time range according to the access data sequence and artificial intelligence AI, wherein the access time is earlier than a time included in the first time range, determining resource adjustment information according to the current resource information and the system resource information, and adjusting the current system resources according to the resource adjustment information, to obtain target system resources, wherein after the adjustment, the system provides at least one system service based on the target system resources, thereby being able to timely adjust the system resources according to the resource requirements of the system services, so that the adjusted target system resources can be adapted to the resource requirements of the system services provided by the system within the first time position, thereby avoiding waste of system resources caused by excessive system resources, thereby being able to improve the stability of the system.

[0140] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a computer-readable storage medium, and a computer program product.

[0141] Figure 5 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present disclosure is shown.

[0142] Figure 5 The electronic device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0143] like Figure 5 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 that connects various system components (including the memory 28 and the processing unit 16).

[0144] The bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor or a local bus using any of a variety of bus structures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Peripheral Component Interconnection (PCI) bus.

[0145] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0146] The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 Not shown, often called a "hard drive").

[0147] although Figure 5Not shown in the figure, a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a compact disc read only memory (hereinafter referred to as: CD-ROM), a digital versatile disc read only memory (hereinafter referred to as: DVD-ROM) or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0148] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0149] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), may also communicate with one or more devices that enable the human body to interact with the electronic device 12, and / or communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. In addition, the electronic device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 through a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0150] The processing unit 16 executes various functional applications and parameter information determination by running the program stored in the memory 28, such as implementing the business data storage method mentioned in the above embodiment, or implementing the business data acquisition method mentioned in the above embodiment.

[0151] It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present disclosure, unless otherwise specified, the meaning of "plurality" is two or more.

[0152] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present disclosure includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0153] It should be understood that the various parts of the present disclosure can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0154] A person of ordinary skill in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0155] In addition, each functional unit in each embodiment of the present disclosure may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0156] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0157] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0158] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A system resource processing method, characterized in that: The following steps are involved: Determining current resource information, wherein the current resource information is used to describe current system resources; Acquire first access data of each system service, and determine a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources; generating an access data sequence according to a plurality of the first access data and a first data volume and an access time corresponding to each of the first access data; Determine, based on the access data sequence and the artificial intelligence AI, system resource information that matches a first time range, wherein the access time is earlier than a time included in the first time range; Determining resource adjustment information according to the current resource information and the system resource information; and The current system resources are adjusted according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides the at least one system service based on the target system resources.

2. The method according to claim 1, characterized in that The obtaining of the first access data of each system service includes: Establishing a communication connection between a data detection service and each of the system services through a first service, wherein the data detection service comprises: an interface of a first method, the first method being used to obtain the first access data; In response to receiving a trigger instruction, the interface of the first method is called according to the trigger instruction to obtain first access data of each system service.

3. The method according to claim 1, characterized in that The method further comprises: providing at least one candidate time range in an interface of an electronic device, wherein the electronic device is at least used to deploy the data detection service; receiving a time setting instruction, wherein the time setting instruction is used to select a candidate time range from the at least one candidate time range; The candidate time range selected by the time setting instruction is used as the first time range.

4. The method according to claim 1, characterized in that The determining, according to the access data sequence and the artificial intelligence AI, system resource information that matches the first time range includes: Determine, according to the access data sequence and the AI, a data volume sequence corresponding to the first time range, wherein the data volume sequence at least includes a second data volume corresponding to each second access data; The system resource information that complies with the first time range is determined according to the data volume sequence.

5. The method according to claim 4, characterized in that The step of determining a data volume sequence corresponding to the first time range according to the access data sequence and the AI ​​includes: The access data sequence is input into a prediction model, and a data volume sequence corresponding to the first time range output by the prediction model is obtained, wherein the prediction model has modeled and learned a mapping relationship between the access data sequence and the data volume sequence corresponding to the first time range.

6. The method according to claim 5, characterized in that The prediction model includes: an autoregressive sub-model, a differential sub-model and a moving average sub-model; The step of inputting the access data sequence into a prediction model and obtaining a data volume sequence output by the prediction model and corresponding to the first time range includes: Extracting first impact information corresponding to each first access data in the access data sequence by using the autoregressive sub-model, wherein the first impact information is used to describe the impact of the first access data on the second data amount; Performing differential processing on the plurality of first impact information by using the differential sub-model to obtain second impact information; The third impact information is obtained through the moving average sub-model, and a data volume sequence corresponding to the first time range is generated according to the second impact information and the third impact information, wherein the third impact information is used to describe the impact of the prediction error on the second data volume.

7. The method according to claim 4, characterized in that The determining, according to the data volume sequence, system resource information that conforms to the first time range includes: determining distribution characteristics of a plurality of the second data amounts in the data amount sequence; System resource information that matches a first time range is determined according to the distribution characteristics.

8. A system resource processing device, characterized in that: The device comprises: A first determination module, used to determine current resource information, wherein the current resource information is used to describe current system resources; an acquisition module, configured to acquire first access data of each system service, and determine a first data volume and an access time corresponding to each first access data, wherein the system provides at least one system service based on the current system resources; A generating module, configured to generate an access data sequence according to a plurality of the first access data and a first data volume and an access time corresponding to each of the first access data; A second determination module is used to determine system resource information that meets a first time range according to the access data sequence and artificial intelligence AI, wherein the access time is earlier than a time included in the first time range; A third determining module, configured to determine resource adjustment information according to the current resource information and the system resource information; and An adjustment module is used to adjust the current system resources according to the resource adjustment information to obtain target system resources, wherein after the adjustment, the system provides the at least one system service based on the target system resources.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, when instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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