Method and device for optimizing cloud server resources, medium and equipment

Abstract

The application discloses a cloud server resource optimization method and device, medium and equipment, relates to the field of cloud servers, and mainly aims to improve the problem that the cloud server is difficult to optimize due to the chaotic occupation of the cloud server resources by various teams. The method comprises the following steps: determining a cloud server associated with a target occupation object based on a basic data table, wherein the basic data table is used for storing the mapping relationship between various occupation objects and a plurality of cloud servers; obtaining resource summary data and resource analysis data of the cloud server, wherein the resource summary data of the cloud server comprises use parameters of the cloud server, and the resource analysis data of the cloud server comprises parameters of the cloud server after optimization; generating a report according to the resource summary data and the resource analysis data of the cloud server, and sending the report to the target occupation object; obtaining a confirmation optimization instruction for the cloud server, calling an optimization system interface, and executing the optimization instruction on the cloud server resources.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cloud servers, and in particular to a cloud server resource optimization method and device, medium and equipment. BACKGROUND

[0002] As an important part of cloud computing services, a cloud server (Elastic Compute Service, ECS) is a simple, efficient, safe and reliable computing service with elastic processing capacity, and is a service platform providing comprehensive business capabilities for various Internet users. It integrates the three core elements of traditional Internet applications: computing, storage and network, and can provide users with public Internet infrastructure services. For large and medium-sized Internet users, cloud servers are an important part of the system carrier of various development departments, and the application running environment is on the cloud server. However, the maintenance and management of the cloud server is currently chaotic, and as time passes and business develops, more and more cloud server resources are applied by various department teams, which gradually increases the difficulty of cloud server resource management and control, and the resources of various teams are confused. Therefore, in order to better manage the cloud server, an optimization method for cloud server resources is urgently needed. SUMMARY

[0003] Therefore, the present application provides a cloud server resource optimization method and device, medium and equipment, which mainly aims to improve the technical problem that the cloud server is difficult to optimize due to the chaotic occupation of cloud server resources by various teams.

[0004] According to one aspect of the present application, a cloud server resource optimization method is provided, comprising:

[0005] determining a cloud server associated with a target occupation object based on a basic data table, the basic data table being used to store a mapping relationship between each occupation object and a plurality of cloud servers;

[0006] obtaining resource summary data and resource analysis data of the cloud server, the resource summary data of the cloud server including use parameters of the cloud server, and the resource analysis data of the cloud server including optimized parameters of the cloud server;

[0007] generating a report according to the resource summary data and the resource analysis data of the cloud server, and sending the report to the target occupation object;

[0008] obtaining a confirmation optimization instruction for the cloud server, calling an optimization system interface, and executing the optimization instruction for the cloud server resource.

[0009] Preferably, the basic data table includes the features: cloud server identifier and occupancy object identifier, and before determining the cloud server associated with the target occupancy object based on the basic data table, the method includes:

[0010] Taking the cloud server identifier as the key and the occupancy object identifier as the value, a mapping relationship between each occupancy object and different cloud servers is generated, and the mapping relationship is stored in the basic data table to establish the basic data table.

[0011] Preferably, the resource summary data of the cloud server is obtained, specifically including:

[0012] The resource data summary table and the resource data history table of the cloud server are established;

[0013] The cloud server resource data summary interface is periodically called according to a preset time interval, and the resource data of the cloud server is obtained to update the resource data summary table and the resource data history table of the cloud server.

[0014] Preferably, the report is generated according to the resource summary data and the resource analysis data of the cloud server, specifically including:

[0015] Based on the mapping relationship between the occupancy objects and different cloud servers stored in the basic data table, the number of cloud servers occupied by the target occupancy object is determined, and a cloud server resource utilization rate overview report is generated according to the resource utilization rate in the resource summary data of each cloud server occupied by the target occupancy object and the cloud server cost.

[0016] According to the number of cloud servers corresponding to each product type within a preset time interval, the cloud server cost, the cumulative optimization number, the cumulative saved cost, the number of cloud servers to be optimized, and the saved cost in the cloud server resource summary data, a cloud server optimization overview report is generated;

[0017] According to the number of cloud servers to be downgraded corresponding to each product type, the CPU usage rate and the memory usage rate in the resource summary data of the cloud server, a cloud server to be managed report is generated.

[0018] Preferably, after the report is generated according to the resource summary data and the resource analysis data of the cloud server, the method further includes:

[0019] According to the resource summary data of the cloud server and the report, a summary report is generated according to a preset rule.

[0020] Preferably, the method further includes:

[0021] The cloud server resource data in the cloud server resource data summary table is compared and analyzed with the cloud server resource data in the cloud server resource data history table, and an analysis report is generated.

[0022] Preferably, the method further comprises:

[0023] If the summary thread of the cloud server resource data is abnormal, an abnormal warning message is sent to the corresponding occupying object based on the mapping relationship between the occupying object and different cloud servers stored in the basic data table.

[0024] According to another aspect of the present application, a cloud server resource optimization device is provided, comprising:

[0025] A determination module is configured to determine a cloud server associated with a target occupying object based on a basic data table, wherein the basic data table is configured to store a mapping relationship between each occupying object and multiple cloud servers.

[0026] An acquisition module is configured to acquire resource summary data and resource analysis data of the cloud server, wherein the resource summary data of the cloud server comprises usage parameters of the cloud server, and the resource analysis data of the cloud server comprises optimized parameters of the cloud server.

[0027] A generation module is configured to generate a report according to the resource summary data and the resource analysis data of the cloud server, and send the report to the target occupying object.

[0028] An optimization module is configured to acquire a confirmation optimization instruction for the cloud server, call an optimization system interface, and execute the optimization instruction for the cloud server resource.

[0029] Preferably, the basic data table comprises the features of cloud server identification and occupying object identification, and the device comprises, before the determination module:

[0030] An establishment module is configured to generate a mapping relationship between each occupying object and different cloud servers by taking the cloud server identification as a key and the occupying object identification as a value, and store the mapping relationship in the basic data table to establish the basic data table.

[0031] Preferably, the acquisition module specifically comprises:

[0032] An establishment unit is configured to establish a resource data summary table and a resource data history table of the cloud server.

[0033] An acquisition unit is configured to periodically call a cloud server resource data summary interface according to a preset time interval, and acquire resource data of the cloud server to update the resource data summary table and the resource data history table of the cloud server.

[0034] Preferably, the generating module is specifically used for:

[0035] determining the number of cloud servers occupied by the target occupied object based on the mapping relationship between the occupied objects and different cloud servers stored in the basic data table, and generating a cloud server resource rationality rate overview report according to the resource rationality rate of each cloud server occupied by the target occupied object and the cloud server cost in the resource summary data of the cloud server;

[0036] generating a cloud server optimization overview report according to the cloud server cost, the cumulative optimization number, the cumulative cost saving, the number of cloud servers to be optimized, and the cost saving of each product type corresponding to the cloud server in the cloud server resource summary data within a preset time interval;

[0037] generating a cloud server to be managed report according to the number of cloud servers to be downgraded corresponding to each product type, the CPU usage rate, and the memory usage rate in the cloud server resource summary data.

[0038] Preferably, the generating module is further used for:

[0039] generating a summary report according to the cloud server resource summary data and the report according to the preset rule.

[0040] Preferably, the generating module is further used for:

[0041] performing a comparative analysis operation on the cloud server resource data in the cloud server resource data summary table and the cloud server resource data in the cloud server resource data history table, and generating an analysis report.

[0042] Preferably, the device further comprises:

[0043] an alarm module, configured to: if an abnormal situation occurs in the cloud server resource data summary thread, send an abnormal warning information to the corresponding occupied object based on the mapping relationship between the occupied objects and different cloud servers stored in the basic data table.

[0044] According to another aspect of the present application, a storage medium is provided, and the storage medium stores at least one executable instruction, and the executable instruction causes a processor to perform operations corresponding to the cloud server resource optimization method described above.

[0045] According to another aspect of the present application, a computer device is provided, comprising a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface complete communication with each other through the communication bus.

[0046] The memory is used to store at least one executable instruction, and the executable instruction causes the processor to perform the operation corresponding to the optimization method of the cloud server resource.

[0047] By means of the technical solution, the embodiment of the application has at least the following advantages:

[0048] The application provides an optimization method and device for cloud server resources. First, a cloud server associated with a target occupancy object is determined based on a basic data table, and the basic data table is used to store a mapping relationship between each occupancy object and multiple cloud servers. Second, resource summary data and resource analysis data of the cloud server are obtained, the resource summary data of the cloud server includes a use parameter of the cloud server, and the resource analysis data of the cloud server includes an optimized parameter of the cloud server. Third, a report is generated according to the resource summary data and the resource analysis data of the cloud server, and the report is sent to the target occupancy object. Finally, a confirmation optimization instruction for the cloud server is obtained, an optimization system interface is called, and the optimization instruction for the cloud server resource is executed. Compared with the prior art, the embodiment of the application establishes a connection between the occupancy object and the cloud server, and the resource data of the cloud server occupied by each occupancy object is summarized to generate a report and sent to the corresponding occupancy object, thereby improving the overall control of the cloud server resource. Further, the cloud server is optimized according to the optimization instruction, and precise optimization of the cloud server is realized.

[0049] The above description is only a summary of the technical solutions of the application. In order to enable the technical means of the application to be more clearly understood, the following detailed description of the preferred embodiments can be implemented according to the content of the description, and in order to enable the above and other purposes, features and advantages of the application to be more obvious and easy to understand, the following detailed description of the preferred embodiments of the application is provided. BRIEF DESCRIPTION OF DRAWINGS

[0050] By reading the detailed description of the preferred embodiments below, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of illustrating the preferred embodiments and are not considered as limiting the application. Moreover, the same reference numerals are used to represent the same components throughout the drawings. In the drawings:

[0051] Figure 1 A flowchart of an optimization method for cloud server resources provided by the embodiment of the application is shown;

[0052] Figure 2 A flowchart of the overall process in the actual application scenario provided by the embodiment of the application is shown;

[0053] Figure 3 A block diagram of an optimization device for cloud server resources provided by the embodiment of the application is shown;

[0054] Figure 4 A structural schematic diagram of a computer device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0055] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0056] Embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) is the use of digital computers or computer-controlled machines to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0057] Artificial intelligence basic technologies generally include technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. Artificial intelligence software technology mainly includes computer vision technology, robot technology, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning, etc.

[0058] Based on this, in one embodiment, as shown in Figure 1 a cloud server resource optimization method is provided, which is applied to a computer device such as a server, for example. The server can be a standalone server, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms, etc. basic cloud computing services such as intelligent medical systems, digital medical platforms, etc. The above method includes the following steps:

[0059] 101. Determine the cloud server associated with the target occupancy object based on the basic data table.

[0060] The basic data table is used for storing the mapping relationship between each occupancy object and the plurality of cloud servers. In the embodiment of the application, the target occupancy object is used for representing a user using the cloud server, which can be an individual or a team, such as a health insurance team, a car insurance team, and the like. The basic data table can include the following fields: team, group, leader, English abbreviation, Chinese name, online state, production and operation leader, production and operation backup, test and operation leader, development leader, test leader, mail group, and PO leader. The English abbreviation and the Chinese name are the cloud server name occupied by the current target occupancy object, so as to clearly show the relationship between the cloud server and the occupancy object, that is, to determine the occupancy target of the cloud server.

[0061] 102. Obtain resource summary data and resource analysis data of the cloud server.

[0062] The resource summary data of the cloud server includes the use parameter of the cloud server, and the resource analysis data of the cloud server includes the optimized parameter of the cloud server. In the embodiment of the application, the resource summary data of the cloud server includes the current information of the cloud server and the current resource information of the cloud server, that is, the current use condition of the cloud server, such as cloud server information, resource running information of the cloud server, P95 index of CPU and memory, monthly maximum value, monthly average value, optimization suggestion, and the like. The resource analysis data of the cloud server is used for representing the statistical data of the related dimensions of the cloud server, including trend analysis chart data, system overview information, host resource optimization condition, and the like.

[0063] It should be noted that, based on the resource analysis data of the cloud server, the cost fluctuation of the cloud server after resource optimization can be viewed, so as to perform visual management.

[0064] 103. Generate a report according to the resource summary data and the resource analysis data of the cloud server, and send the report to the target occupancy object.

[0065] In the embodiments of the present application, the report includes a target occupancy object report (i.e., a target team report) and a comprehensive report. The target occupancy object report is a report sent to the target team and the target team members, including resource rationalization rate overview, cloud server optimization overview, cloud server to be managed details, and detailed resources to be optimized attachments. Specifically, the target team information is obtained by obtaining the correspondence between the cloud server and the target team, and all cloud server resource conditions under the current target team are summarized and sent to the target team and the target team members. In addition, the comprehensive report is a summary report of the cloud server usage of all teams, which can be sent to the management layer for viewing the resource usage and optimization of each team. The comprehensive report includes resource rationalization rate overview, cloud server optimization overview, team dimension optimization overview, and top 10 subsystems to be managed. Specifically, the information of each target team is obtained by obtaining the correspondence between the cloud server and each target team, and the generated comprehensive report is sent to the management layer to form a comparison, so as to stimulate the enthusiasm of each team optimization, thereby increasing the efficiency and cooperation of resource optimization.

[0066] It should be noted that while the report is sent to each team, a resource optimization prompt is output to prompt the team and the team members to automatically optimize.

[0067] 104, obtaining a confirmation optimization instruction for the cloud server, calling an optimization system interface, and executing the optimization instruction for the cloud server resource.

[0068] In the embodiments of the present application, when the confirmation optimization instruction of the target team is obtained, the interface of the optimization system is called to automatically optimize the resources of the cloud server.

[0069] Compared with the prior art, the embodiments of the present application establish the correspondence between the occupancy object and the cloud server, and summarize the resource data of the cloud server occupied by each occupancy object to generate a report and send it to the corresponding occupancy object, thereby improving the overall control of the cloud server resources. Further, the cloud server is optimized according to the optimization instruction, and the precise optimization of the cloud server is realized.

[0070] In order to further illustrate and limit, in the embodiments of the present application, the basic data table includes the features of cloud server identifier and occupancy object identifier. Before determining the cloud server associated with the target occupancy object based on the basic data table, the embodiment method includes: taking the cloud server identifier as the key and the occupancy object identifier as the value to generate the mapping relationship between each occupancy object and different cloud servers, and storing the mapping relationship in the basic data table to establish the basic data table.

[0071] The cloud server identifier can be an English abbreviation of the cloud server system, and is specifically used to represent the identity ID of the cloud server system, i.e., a unique identity identifier. The occupying object identifier is the identity identifier of the user occupying the current cloud server system, for example, the ID account of a team and a responsible person. The cloud server system English abbreviation is associated with the team or the responsible person or both, which is not limited in the present application. Specifically, the cloud server system English abbreviation is used as a key, the user occupying the current cloud server system is used as a value, and a mapping relationship between the occupying object and the cloud server is generated by association, so that the occupying party user of each cloud server can be quickly determined based on the mapping relationship.

[0072] It should be noted that, since the cloud server system English abbreviation is the unique identity identifier of the cloud server system, the association with the occupying party can accurately obtain the occupying party of each cloud server system.

[0073] To further illustrate and limit, in the embodiment of the present application, the resource summary data of the cloud server is obtained, specifically including: establishing a cloud server resource data summary table and a resource data history table; periodically calling a cloud server resource data summary interface according to a preset time interval, and obtaining cloud server resource data to update the cloud server resource data summary table and the resource data history table.

[0074] The cloud server resource summary table is used to store the current usage of the cloud server, including the basic data of the cloud server, including but not limited to CPU usage, memory usage, etc.; and the cloud server processing data obtained by processing the basic data of the cloud server, including but not limited to downgrading suggestions, downgrading cost savings, etc. Preferably, the current resource data of the cloud server can be stored in the cloud server resource summary table in an overlay form to update the cloud server resource summary table. The cloud server resource data history table is used to store the history record of the usage of the cloud server, which is similar to a collection of cloud server resource summary tables at different time points. For example, a record update time field can be added to the cloud server resource data summary table at the current update time point, and the cloud server resource summary table with the update time can be added to the cloud server resource data history table to update the cloud server resource data history table. In addition, the preset time interval can be specifically set according to the actual usage of the cloud server. If the cloud server is frequently occupied, the preset time interval can be set relatively short, for example, one day, one week, etc. If the cloud server is relatively idle, the preset time interval can be set relatively long, for example, one month, one quarter, etc., to save the update cost, which is not limited in the present application.

[0075] To further illustrate and define, in the embodiments of the application, a report is generated according to the resource summary data and the resource analysis data of the cloud servers, specifically including: determining the number of cloud servers occupied by a target occupying object based on the mapping relationship between the occupying object and different cloud servers stored in the basic data table, and generating a cloud server resource rationality overview report according to the resource rationality rate in the resource summary data of each cloud server occupied by the target occupying object and the cloud server cost; generating a cloud server optimization overview report according to the number of cloud servers corresponding to each product type within a preset time interval, the cloud server cost, the cumulative optimization number, the cumulative saved cost, the number of cloud servers to be optimized, and the saved cost in the cloud server resource summary data; and generating a cloud server to be managed report according to the number of cloud servers to be downgraded corresponding to each product type, the CPU usage rate, and the memory usage rate in the resource summary data of the cloud servers.

[0076] The cloud server resource rationality overview report can be used to show the overall rationality rate of all cloud servers associated with each team or responsible person and the use of cloud server resources, and further compare it with a preset rationality range to determine whether the use of each cloud server is reasonable, thereby realizing an overview of the utilization rate of all cloud servers. The cloud server optimization overview report can be used to view the number of cloud servers optimized in the current period, the resources (such as the amount of money) saved after optimization, and further determine the optimization progress and effect of the current cloud servers. The cloud server to be managed report can be used to show the detailed information of the cloud servers to be managed in the cloud servers associated with each team and the resources that can be saved after optimization. In addition, in order to save resources, when determining the cloud servers to be managed, all cloud servers can be arranged in descending order according to the use, and a preset number of cloud servers are selected as the cloud servers to be managed.

[0077] Optionally, in the embodiments of the application, after generating the report according to the resource summary data and the resource analysis data of the cloud servers, the embodiment method further includes: generating a summary report according to the resource summary data of the cloud servers and the report according to a preset rule.

[0078] For example, a Python jinja2 template engine can be used to generate the report content in html format, and the generation rule can be: (1) the title of the report body: xxx team resource rationality report (2) divided into three paragraphs: a. cloud server resource rationality overview b. cloud server optimization overview c. cloud server to be managed details a, b, and c correspond to the three reports generated in the previous step (3) optimization rule description: set a hyperlink, and triggering the click can open a front-end page to view the specific optimization rules of each product (4) contact information.

[0079] Optionally, in the embodiment of the present application, the example method further comprises: comparing and analyzing the cloud server resource data in the cloud server resource data summary table with the cloud server resource data in the cloud server resource data history table to generate an analysis report.

[0080] For example, the analysis report can include a resource utilization rate line chart generated according to the CPU utilization rate and the memory utilization rate of the cloud server; a column chart of the number of optimized cloud servers and the number of cloud servers to be optimized in a team; a combination chart of a stacked chart and a table chart of the optimization cost in a team and a period, and the like.

[0081] Optionally, in the embodiment of the present application, the example method further comprises: if the summary thread of the cloud server resource data is in an abnormal condition, sending an abnormal warning message to the corresponding occupying object based on the mapping relationship between the occupying object and the different cloud servers stored in the basic data table.

[0082] In a specific application scenario, as shown in Figure 2 The resource utilization and cost saving information of the cloud server are associated to the specific process of a team as shown in the "resource fine management and control" part in the figure; the process of team report pushing based on the resource optimization result of the cloud server is as shown in the "monthly report pushing" part in the figure; and the process of department comprehensive report pushing based on the resource information of the cloud server is as shown in the "monthly report pushing" part in the figure.

[0083] The present application provides a cloud server resource optimization method, which first determines the cloud server associated with a target occupying object based on a basic data table, the basic data table being used to store the mapping relationship between each occupying object and multiple cloud servers; secondly, resource summary data and resource analysis data of the cloud server are obtained, the resource summary data of the cloud server including the use parameters of the cloud server, and the resource analysis data of the cloud server including the optimized parameters of the cloud server; thirdly, a report is generated according to the resource summary data and the resource analysis data of the cloud server, and the report is sent to the target occupying object; and finally, a confirmation optimization instruction for the cloud server is obtained, an optimization system interface is called, and the optimization instruction for the cloud server resource is executed. Compared with the prior art, the embodiment of the present application establishes the contact between the occupying object and the cloud server, and the resource data of the cloud server occupied by each occupying object is summarized to generate a report and sent to the corresponding occupying object, thereby improving the overall control of the cloud server resource. Further, the cloud server is optimized according to the optimization instruction, and the precise optimization of the cloud server is realized.

[0084] Further, as an implementation of the method shown in Figure 1 The present application provides a cloud server resource optimization device, as shown inFigure 3 The apparatus comprises:

[0085] The apparatus comprises:

[0086] The determining module 21 is configured to determine a cloud server associated with a target occupancy object based on a basic data table, wherein the basic data table is used to store mapping relationships between occupancy objects and a plurality of cloud servers.

[0087] The obtaining module 22 is configured to obtain resource summary data and resource analysis data of the cloud server, wherein the resource summary data of the cloud server comprises usage parameters of the cloud server, and the resource analysis data of the cloud server comprises parameters of the cloud server after optimization.

[0088] The generating module 23 is configured to generate a report according to the resource summary data and the resource analysis data of the cloud server, and send the report to the target occupancy object.

[0089] The optimization module 24 is configured to obtain a confirmation optimization instruction for the cloud server, call an optimization system interface, and execute the optimization instruction for the cloud server resource.

[0090] In a specific application scenario, the basic data table comprises features of a cloud server identifier and an occupancy object identifier, and before the determining module, the apparatus comprises:

[0091] The establishing module is configured to generate mapping relationships between occupancy objects and different cloud servers by taking the cloud server identifier as a key and taking the occupancy object identifier as a value, store the mapping relationships in the basic data table, and establish the basic data table.

[0092] In a specific application scenario, the obtaining module specifically comprises:

[0093] The establishing unit is configured to establish a resource data summary table and a resource data history table of the cloud server.

[0094] The obtaining unit is configured to periodically call a cloud server resource data summary interface according to a preset time interval, and obtain resource data of the cloud server to update the resource data summary table and the resource data history table of the cloud server.

[0095] In a specific application scenario, the generating module is specifically configured to:

[0096] determine the number of cloud servers occupied by the target occupancy object based on the mapping relationship between occupancy objects and different cloud servers stored in the basic data table, and generate a cloud server resource rationality rate overview report according to the resource rationality rate in the resource summary data of each cloud server occupied by the target occupancy object and the cloud server cost;

[0097] generate a cloud server optimization overview report according to the cloud server cost, the cumulative optimization number, the cumulative cost saving, the number of cloud servers to be optimized, and the cost saving of the cloud server resource summary data corresponding to each product type within a preset time interval;

[0098] generate a cloud server to be managed report according to the number of cloud servers to be downgraded corresponding to each product type, the CPU usage rate, and the memory usage rate in the resource summary data of the cloud server.

[0099] In a specific application scenario, the generating module is further configured to:

[0100] generate a summary report according to the cloud server resource summary data and the report according to a preset rule.

[0101] In a specific application scenario, the generating module is further configured to:

[0102] perform a comparative analysis operation on the cloud server resource data in the cloud server resource data summary table and the cloud server resource data in the cloud server resource data history table, and generate an analysis report.

[0103] In a specific application scenario, the device further comprises:

[0104] An alarm module is configured to, if an abnormal situation occurs in the cloud server resource data summary thread, send an abnormal warning message to the corresponding occupancy object based on the mapping relationship between occupancy objects and different cloud servers stored in the basic data table.

[0105] This application provides a cloud server resource optimization device. First, it determines the cloud servers associated with a target occupying object based on a basic data table, which stores the mapping relationships between each occupying object and multiple cloud servers. Second, it acquires the resource summary data and resource analysis data of the cloud servers. The resource summary data includes the usage parameters of the cloud servers, and the resource analysis data includes the optimized parameters of the cloud servers. Third, it generates a report based on the resource summary data and resource analysis data of the cloud servers and sends the report to the target occupying object. Finally, it obtains a confirmation optimization instruction for the cloud server, calls the optimization system interface, and executes the optimization instruction for the cloud server resources. Compared with existing technologies, this application improves the comprehensiveness of cloud server resource control by establishing a connection between the occupying object and the cloud server, summarizing the resource data of the cloud servers occupied by each occupying object to generate a report and sending it to the corresponding occupying object; furthermore, it optimizes the cloud server according to the optimization instruction, achieving precise optimization of the cloud server.

[0106] According to one embodiment of this application, a storage medium is provided, the storage medium storing at least one executable instruction, which can execute the cloud server resource optimization method in any of the above method embodiments.

[0107] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0108] Figure 4 The diagram shows a structural schematic of a computer device according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the computer device.

[0109] like Figure 4 As shown, the computer device may include: a processor 302, a communications interface 304, a memory 306, and a communications bus 308.

[0110] The processor 302, communication interface 304, and memory 306 communicate with each other via communication bus 308.

[0111] Communication interface 304 is used to communicate with other network elements such as clients or other servers.

[0112] The processor 302 is configured to execute the program 310, and specifically, execute the related steps in the method embodiments of optimizing the cloud server resources.

[0113] Specifically, the program 310 can include program codes including computer operation instructions.

[0114] The processor 302 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the computer device can be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0115] The memory 306 is configured to store the program 310. The memory 306 can include a high-speed RAM memory, and can also include a non-volatile memory, such as at least one disk memory.

[0116] The program 310 can be specifically configured to cause the processor 302 to perform the following operations:

[0117] determine a cloud server associated with a target occupancy object based on a basic data table, the basic data table being configured to store mapping relationships between each occupancy object and a plurality of cloud servers;

[0118] obtain resource summary data and resource analysis data of the cloud server, the resource summary data of the cloud server including usage parameters of the cloud server, and the resource analysis data of the cloud server including optimized parameters of the cloud server;

[0119] generate a report according to the resource summary data and the resource analysis data of the cloud server, and send the report to the target occupancy object;

[0120] obtain a confirmation optimization instruction for the cloud server, call an optimization system interface, and execute the optimization instruction for the cloud server resources.

[0121] The storage medium can also include an operating system and a network communication module. The operating system is a program for managing the physical resources of the entity device and the software resources of the cloud server resource optimization, and supports the running of the information processing program and other software and / or programs. The network communication module is configured to realize the communication between the components in the storage medium, and the communication between the other hardware and software in the information processing entity device.

[0122] The various embodiments described in this specification are intended to be illustrative only and in no way limit the scope of the application. One skilled in the art will readily recognize from the disclosure herein, that alternative embodiments of the methods and systems of the present application can be constructed from a wide variety of different components and configurations of components. The methods and systems of the present application are therefore not limited to the specific embodiments described herein, but rather, the scope of the present application is to be determined entirely by the following claims, which are to be interpreted in accordance with the principles of patent law.

[0123] The methods and systems of the present application can be implemented in a number of ways. For example, the methods and systems of the present application can be implemented using software, hardware, firmware, or any combination of these methods. Any features described as modules, components or steps can be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. Any features described as a process or method can be implemented as a whole in one device or circuit, or as parts in two or more devices or circuits. The order of any steps described is not limited to the order described, unless otherwise specifically stated.

[0124] It should be apparent to those skilled in the art that the modules and steps of the application described above can be implemented with a general computing device, which can be centralized on a single computing device or distributed across multiple computing devices in a network, and optionally implemented with program code executable by a computing device, which can be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described can be performed in an order different from that shown or described, or made into individual integrated circuit modules, or made into a single integrated circuit module, or a plurality of modules or steps. Thus, the present application is not limited to any particular hardware and software combination.

[0125] The preferred embodiments of the application described above are intended to be illustrative only and not limiting. Numerous modifications and adaptations thereof will be apparent to those skilled in the art without departing from the spirit and scope of the present application. All such and similar modifications of the methods and systems of the present application as set forth above, and all such and similar equivalents thereof, are intended to fall within the scope of the present application.

Claims

1. A method for optimizing cloud server resources, the method comprising: The method comprises the following steps: ​ determining a cloud server associated with a target occupancy object based on a basic data table, wherein the basic data table is used to store a mapping relationship between each occupancy object and a plurality of cloud servers; obtaining resource summary data and resource analysis data of the cloud server, wherein the resource summary data of the cloud server comprises a use parameter of the cloud server, and the resource analysis data of the cloud server comprises an optimized parameter of the cloud server; generating a report based on the resource summary data and the resource analysis data of the cloud server, and sending the report to the target occupancy object; obtaining a confirmation optimization instruction for the cloud server, calling an optimization system interface, and executing the optimization instruction for the cloud server resource; the step of generating the report based on the resource summary data and the resource analysis data of the cloud server comprises the following steps: determining the number of cloud servers occupied by the target occupancy object based on the mapping relationship between the occupancy objects and different cloud servers stored in the basic data table, and generating a cloud server resource rationality overview report based on the resource rationality and the cloud server cost in the resource summary data of each cloud server occupied by the target occupancy object; generating a cloud server optimization overview report based on the number of cloud servers corresponding to each product type within a preset time interval, the cloud server cost, the cumulative optimization number, the cumulative saved cost, the number of cloud servers to be optimized, and the saved cost in the cloud server resource summary data; generating a cloud server to be managed report based on the number of cloud servers to be downgraded corresponding to each product type, the CPU usage rate, and the memory usage rate in the resource summary data of the cloud server.

2. The method of claim 1, wherein, The basic data table comprises the following features: cloud server identifier and occupancy object identifier, and before the step of determining the cloud server associated with the target occupancy object based on the basic data table, the method comprises the following steps: generating a mapping relationship between each occupancy object and different cloud servers by taking the cloud server identifier as a key and the occupancy object identifier as a value, and storing the mapping relationship in the basic data table to establish the basic data table.

3. The method of claim 1, wherein, The step of obtaining the resource summary data of the cloud server comprises the following steps: establishing a resource data summary table and a resource data history table of the cloud server; periodically calling a cloud server resource data summary interface according to a preset time interval, and obtaining resource data of the cloud server to update the resource data summary table and the resource data history table of the cloud server.

4. The method of claim 1, wherein, After the step of generating the report based on the resource summary data and the resource analysis data of the cloud server, the method further comprises the following steps: generating a summary report according to a preset rule based on the resource summary data of the cloud server and the report.

5. The method of claim 4, wherein, The method further comprises the following steps: performing a comparative analysis operation on the cloud server resource data in the cloud server resource data summary table and the cloud server resource data in the cloud server resource data history table to generate an analysis report.

6. The method according to any one of claims 1 to 5, characterized in that, The method further comprises the following steps: If the cloud server resource data aggregation thread is abnormal, an abnormal warning message is sent to the corresponding occupying object based on the mapping relationship between the occupying object and different cloud servers stored in the basic data table.

7. A cloud server resource optimization device, characterized in that, The method comprises the following steps: A determination module is configured to determine a cloud server associated with a target occupying object based on a basic data table, wherein the basic data table is used to store a mapping relationship between each occupying object and a plurality of cloud servers. An acquisition module is configured to acquire resource aggregation data and resource analysis data of the cloud server, wherein the resource aggregation data of the cloud server comprises usage parameters of the cloud server, and the resource analysis data of the cloud server comprises optimized parameters of the cloud server. A generation module is configured to generate a report based on the resource aggregation data and the resource analysis data of the cloud server, and send the report to the target occupying object. An optimization module is configured to acquire a confirmation optimization instruction for the cloud server, call an optimization system interface, and execute the optimization instruction for the cloud server resource. The generation module is specifically configured to: determine the number of cloud servers occupied by the target occupying object based on the mapping relationship between the occupying object and different cloud servers stored in the basic data table, and generate a cloud server resource rationality overview report according to the resource rationality rate and the cloud server cost of each cloud server occupied by the target occupying object in the resource aggregation data of the cloud server; generate a cloud server optimization overview report according to the number of cloud servers corresponding to each product type within a preset time interval, the cloud server cost, the cumulative optimization number, the cumulative saved cost, the number of cloud servers to be optimized, and the saved cost in the cloud server resource aggregation data; generate a cloud server to be managed report according to the number of cloud servers to be downgraded corresponding to each product type, the CPU usage rate, and the memory usage rate in the resource aggregation data of the cloud server.

8. A storage medium having at least one executable instruction stored therein, wherein the executable instruction causes a processor to perform operations corresponding to the cloud server resource optimization method of any one of claims 1-6.

9. A computer device comprising: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface complete communication with each other through the communication bus. The memory is used to store at least one executable instruction, and the executable instruction causes the processor to perform operations corresponding to the cloud server resource optimization method of any one of claims 1-6.

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