Cloud resource management method and device, equipment and storage medium

Abstract

The invention relates to a cloud resource management method, apparatus and device, and a storage medium. The method comprises the steps of obtaining initial resource management data generated when a user manages cloud resources based on a resource management scheme; determining the resource management maturity of the user based on the initial resource management data; based on the resource management maturity, generating a resource management evaluation result corresponding to the resource management scheme, the resource management evaluation result including a cloud resource management suggestion corresponding to the resource management scheme; and updating a resource management scheme based on the cloud resource management suggestion, so that a user manages cloud resources according to the updated resource management scheme. Based on the method, the resource management maturity of the user can be accurately measured so as to accurately evaluate the treatment deficiency and potential risk of the user in the cloud resource management process, and then the cloud resource management effect of the user and the risk control capability of the cloud resource management are improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a cloud resource management method, apparatus, device and storage medium. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the present application as recited in the claims. No admission that the description herein is prior art is made by its inclusion in this section.

[0003] As a key technology of the digital economy, cloud computing is helping more and more companies build efficient and automated management mechanisms and infrastructure environments. However, the characteristics of cloud computing have also brought new management problems and potential risks to the Internet Technology (IT) management field of enterprises. Therefore, enterprises need to build management and management systems for cloud resources to ensure the rational use of resources. When conducting cloud resource management, related technologies determine cloud resource management solutions by combining the maturity of cloud resource management. However, when evaluating the maturity of cloud resource management, they cannot combine the characteristics of cloud computing, and cannot conduct timely and accurate evaluation of users' cloud management, and thus cannot accurately and timely discover the management deficiencies and potential risks of users in cloud management, resulting in poor cloud resource management effects for users. Summary of the invention

[0004] The cloud resource management method, apparatus, device and storage medium provided in the embodiments of the present application at least solve the problem in the related art that management deficiencies and potential risks of users in cloud management cannot be accurately and timely discovered, resulting in poor cloud resource management effects for users.

[0005] The above-mentioned object of the present application is achieved through the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a cloud resource management method, including:

[0007] Obtaining initial resource management data generated by users managing cloud resources based on resource management solutions;

[0008] Determining the resource management maturity of the user based on the initial resource management data;

[0009] Based on the resource management maturity, generating a resource management evaluation result corresponding to the resource management solution, wherein the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution;

[0010] The resource management scheme is updated based on the cloud resource management suggestion, so that the user can manage the cloud resources according to the updated resource management scheme.

[0011] In a second aspect, an embodiment of the present application provides a cloud resource management evaluation device, including:

[0012] An acquisition module is used to acquire initial resource management data generated by users managing cloud resources based on resource management solutions;

[0013] a determination module, configured to determine the resource management maturity of the user based on the initial resource management data;

[0014] A generating module, configured to generate a resource management evaluation result corresponding to the resource management solution based on the resource management maturity, wherein the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution;

[0015] An updating module is used to update the resource management scheme based on the cloud resource management suggestion, so that the user can manage the cloud resources according to the updated resource management scheme.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, and a memory storing a program, wherein the program comprises instructions, and when the instructions are executed by the processor, the processor executes the method according to the first aspect.

[0017] In a fourth aspect, an embodiment of the present application provides a non-transitory machine-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method described in the first aspect.

[0018] The solution provided in the embodiment of the present application provides a cloud resource management method, which can accurately and timely discover the management deficiencies and potential risks of users in cloud resource management, and improve the cloud resource management effect of users. Specifically, in actual applications, the initial resource management data generated by the user's management of cloud resources based on the resource management solution is first obtained, and then the user's resource management maturity is determined based on the initial resource management data. In this way, based on the resource management maturity, a resource management evaluation result including cloud resource management suggestions corresponding to the resource management solution can be generated, and finally the resource management solution can be updated according to the cloud resource management suggestions in the resource management evaluation result, so that the user can manage the cloud resources according to the updated resource management solution. Based on the above method, the user's resource management maturity can be accurately measured to achieve an accurate assessment of the governance deficiencies and potential risks that exist in the user's cloud resource management process, thereby improving the user's cloud resource management effect and risk control capabilities for cloud resource management.

[0019] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other embodiments can be obtained based on these drawings without creative work.

[0021] Figure 1 A flowchart of a cloud resource management method provided for an exemplary embodiment of the present application.

[0022] Figure 2 A schematic diagram of an application environment of a cloud resource management method provided for an exemplary embodiment of the present application.

[0023] Figure 3 A flowchart of a cloud resource management method provided for an exemplary embodiment of the present application.

[0024] Figure 4 An application diagram of a cloud resource management method provided for an exemplary embodiment of the present application.

[0025] Figure 5 A flowchart of a method for determining resource management maturity provided by an exemplary embodiment of the present application,

[0026] Figure 6 An application diagram of a cloud resource management method provided for an exemplary embodiment of the present application.

[0027] Figure 7 A schematic diagram of the structure of a cloud resource management device provided as an exemplary embodiment of the present application.

[0028] Figure 8 It is a structural schematic diagram of an electronic device provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0029] Embodiments of the present embodiment will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present embodiment are shown in the accompanying drawings, it should be understood that the present embodiment can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein, which are instead provided for a more thorough and complete understanding of the present embodiment. It should be understood that the drawings and embodiments of the present embodiment are only for exemplary purposes and are not intended to limit the scope of protection of the present embodiment.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Optionally, according to one aspect of the embodiments of the present application, a cloud resource management method is provided. As an optional implementation, the cloud resource management method can be applied to, but is not limited to, Figure 1 In the application environment shown. The application environment may include but is not limited to: a terminal device 102 for human-computer interaction with a user, a network 110, and a server 112. A cloud resource management application client is running in the terminal device 102. The terminal device 102 includes a display 108, a processor 106, and a memory 104. The display 108 is used to present the user's resource management evaluation results. In addition, the cloud platform 112 includes a database 114 and a processing engine 116, and the database is used to store initial resource management data, resource management maturity, and resource management evaluation results. The processing engine 116 is used to obtain the initial resource management data generated by the user's management of cloud resources based on the resource management solution; based on the initial resource management data, determine the user's resource management maturity; based on the resource management maturity, generate a resource management evaluation result corresponding to the resource management solution, and the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution; based on the cloud resource management suggestion, update the resource management solution so that the user can manage the cloud resources according to the updated resource management solution.

[0032] The specific process is as follows: Assume that Figure 1The terminal device 102 shown runs a cloud resource management client, and the cloud platform 112 executes step S101 to send the initial resource management data generated by the user managing the cloud resources based on the resource management solution to the terminal device 102. The terminal device 102 executes steps S102 to S105 to obtain the initial resource management data generated by the user managing the cloud resources based on the resource management solution; based on the initial resource management data, determine the user's resource management maturity; based on the resource management maturity, generate a resource management evaluation result corresponding to the resource management solution, and the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution; based on the cloud resource management suggestion, update the resource management solution so that the user can manage the cloud resources according to the updated resource management solution.

[0033] In one or more embodiments, the above-mentioned dialogue processing method of the present application can be applied to Figure 2 In the application environment shown. Figure 2 As shown, human-computer interaction can be performed between user 202 and user equipment 204. User equipment 204 includes memory 206 and processor 208. In this embodiment, user equipment 204 can refer to but is not limited to executing the operations executed by the above terminal equipment 102 to generate resource management evaluation results.

[0034] Optionally, the terminal device 102 and the user device 204 include but are not limited to mobile phones, laptops, tablet computers, PDAs, MIDs (Mobile Internet Devices), desktop computers, smart TVs, etc. The cloud resource management client in the embodiment of the present application includes but is not limited to providing cloud resource management functions for video clients, instant messaging clients, browser clients, etc., using the cloud resource management method of the present application to interact with users, and receive user input information, etc. The above network may include but is not limited to: wired network, wireless network, wherein the wired network includes: local area network, metropolitan area network and wide area network, and the wireless network includes: Bluetooth, WIFI and other networks that realize wireless communication. The above cloud platform 112 includes a cloud server, which includes but is not limited to a private cloud server or a public cloud server. The above is only an example, and no limitation is made to this in this embodiment.

[0035] In the process of digital transformation, enterprises usually use cloud services to meet office and production needs. However, the technical characteristics of cloud services such as "elasticity, real-time delivery, and decentralization" have also brought new management problems and potential risks to the information technology governance field of enterprises. For example, after enterprises deploy cloud services, the user identity system on the cloud becomes more complicated. In addition to the operation and maintenance team, the development team, security and compliance team, and financial management team must also participate in the management and use of cloud services. Therefore, it is necessary to implement refined permission management strategies for the complex identity system on cloud services. At the same time, since the creation or deletion of resources in cloud services no longer relies solely on the operation and maintenance team, the frequency of operation behaviors of various personnel roles on the cloud has also greatly increased, and the security risks of data information in cloud services are relatively large. When conducting cloud resource management, the relevant technology determines the cloud resource management solution by combining the maturity of cloud resource management. However, when evaluating the maturity of cloud resource management, it cannot combine the characteristics of cloud computing, and cannot timely and accurately evaluate the user's cloud management, and thus cannot accurately and timely discover the management deficiencies and potential risks of users in cloud management, resulting in poor cloud resource management effects for users.

[0036] In order to solve the above technical problems, as an optional implementation method, an embodiment of the present application provides a cloud resource management method.

[0037] Figure 3 A flowchart of a cloud resource management method provided by an exemplary embodiment of the present application. Figure 3 As shown, the method comprises the following steps:

[0038] Step S301: Acquire initial resource management data generated by a user managing cloud resources based on a resource management solution.

[0039] Step S302: determining the resource management maturity of the user based on the initial resource management data.

[0040] Step S303: Generate a resource management evaluation result corresponding to the resource management solution based on the resource management maturity, wherein the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution.

[0041] Step S304: updating the resource management solution based on the cloud resource management suggestion, so that the user can manage the cloud resources according to the updated resource management solution.

[0042] The cloud resource management method provided in the embodiments of the present application can be applied to various application fields that require cloud resource management, such as industrial manufacturing, construction engineering, and urban planning. For example, taking an enterprise in the field of industrial manufacturing as an example, through the above-mentioned cloud resource management method, the user's resource management maturity can be determined based on the initial resource management data generated by the enterprise's management of cloud resources, and finally the user's resource management evaluation result including cloud resource management suggestions is generated, and the resource management plan of the enterprise is updated according to the resource management evaluation result, so that the enterprise can accurately and timely discover the management deficiencies and potential risks in cloud management.

[0043] To achieve cloud resource management, firstly, the initial resource management data generated by the user managing the cloud resources based on the resource management solution is obtained.

[0044] As described in the embodiments above, the cloud resource management method of the embodiments of the present application can be applied to terminal devices and user devices. Before obtaining the initial resource management data generated by the user managing the cloud resources based on the resource management solution, the user can send a cloud resource management request to the terminal device or the user device. After obtaining the above-mentioned cloud resource management request, the terminal device or the user device will obtain the initial resource management data generated by the user managing the cloud resources based on the resource management solution. Among them, the user can generate a cloud resource management request by clicking or sliding on the terminal device or the user device. It should be noted that the description of the terminal device and the user device can refer to the above-mentioned embodiments, and this application will not repeat them here.

[0045] The initial resource management data may include data generated by the user's management of cloud resources. For example, data generated by the user's classification of cloud resources, data generated by the user's stratification of cloud resources, or data generated by the user's quota of cloud resources, etc. Correspondingly, the resource management scheme may include the scheme adopted by the user to manage cloud resources. For example, the classification scheme adopted by the user to classify cloud resources, the stratification scheme adopted by the user to stratify cloud resources, or the quota scheme adopted by the user to allocate quotas to cloud resources, etc.

[0046] In an optional embodiment, users can manage cloud resources based on the various service modules provided in the cloud platform. For example, the service modules provided by the cloud platform may include a resource management module, an identity authority management module, a resource management module, a behavior audit module, an automation management module, and other modules. Among them, different service modules each correspond to different resource governance schemes and initial resource governance data. In the above embodiment, the resource management scheme includes one of a plurality of resource governance schemes, and the initial resource management data includes one of a plurality of initial resource governance data. In other words, taking the resource management module as an example, the resource governance scheme corresponding to the resource management module may include the above resource management scheme, and the corresponding initial resource governance data may include the above initial resource management data.

[0047] Therefore, when obtaining the initial resource management data generated by the user managing the cloud resources based on the resource management solution, the initial resource management data generated by the user managing the cloud resources based on the resource management module can be obtained from the cloud platform. In this embodiment, the resource management module can be mainly responsible for managing and recording various types of resources on the user's cloud.

[0048] In actual applications, when users manage cloud resources based on cloud management tools, initial resource management data will be generated through the resource management module on the cloud platform. In this embodiment, the management tool may include a console, a command console, a command line tool, OpenAPI (Open Application Programming Interface), etc. When a user needs to manage cloud resources, the user can send a cloud resource management request to the cloud platform through a client, etc. After the cloud platform receives the request, it obtains the above initial resource management data based on the resource management module.

[0049] After the initial resource management data is acquired, the resource management maturity of the user may be determined based on the initial resource management data.

[0050] Resource management maturity is the maturity of cloud resource management. Cloud resource management maturity refers to the maturity of enterprises and other users in managing cloud resources when using cloud services. Cloud resource management maturity includes the user's ability to purchase, deploy, use, and optimize cloud services. The level of cloud resource management maturity directly affects the user's performance in terms of security, reliability, scalability, and cost-effectiveness in cloud services. Therefore, cloud resource management maturity can directly reflect the management deficiencies and potential risks that exist in the user's cloud resource management. In order to enable users to better manage cloud resources, before users further manage cloud resources, the cloud resource management maturity of users managing cloud resources based on resource management solutions can be determined.

[0051] In an optional embodiment, the resource management maturity of the user can be determined by calculating the resource management maturity score of the user, that is, the resource management maturity score of the user is used as the resource management maturity. For example, the initial resource management data can be classified, and the resource management score of each category of the initial resource management data can be calculated respectively. Finally, based on the resource management scores of each category, the resource management maturity score of the user is obtained.

[0052] For example, the resource management maturity score is divided into three intervals: greater than 80 points, greater than 60 points and less than 80 points, and less than 60 points. The maturity levels corresponding to the above intervals are security level, risk level and high risk level. Assuming that the user's resource management maturity score is 70 points, the user's resource management maturity is in the risk level.

[0053] After determining the resource management maturity of the user, a resource management evaluation result corresponding to the resource management solution can be generated based on the resource management maturity. In this embodiment, the resource management evaluation result may include cloud resource management suggestions corresponding to the resource management solution. It should be noted that the resource management evaluation result may also include information such as the level and score of the user's resource management maturity.

[0054] In this embodiment, cloud resource management suggestions can be determined based on the resource management score of each category of initial resource management data in the above embodiment. Specifically, it is assumed that the initial resource management data is divided into three categories: A data, B data, and C data, wherein the resource management score of A data is calculated to be 50 points, and the resource management scores of B data and C data are both 90 points. If 60 points is used as the passing line for the resource management score, it means that the user has major defects in the management of A data. At this time, corresponding cloud resource management suggestions can be generated for A data. Taking A data as the data generated by the user's classification of cloud resources as an example, cloud resource management suggestions may include suggestions on how to classify cloud resources, etc.

[0055] Finally, the resource management scheme can be updated based on the cloud resource management suggestion, so that users can manage cloud resources according to the updated resource management scheme.

[0056] After obtaining the resource management assessment results, users can identify the deficiencies and defects of the current resource management plan. At this time, they can update the resource management plan according to the cloud resource management recommendations and manage the cloud according to the updated resource management plan.

[0057] For example, still taking the above embodiment as an example, assuming that the cloud resource management suggestion includes suggestions on how to classify cloud resources, it means that there are deficiencies in the current resource management solution for classifying cloud resources, and the part of the resource management solution for classifying cloud resources can be updated based on the cloud resource management suggestion.

[0058] In an embodiment of the present application, the user's resource management maturity is determined by obtaining the initial resource management data generated by the user's management of cloud resources based on the resource management solution. Based on the resource management maturity, a resource management assessment result including cloud resource management suggestions is generated. In this way, the resource management solution can be updated based on the cloud resource management suggestions in the resource management assessment result to enable the user to better manage cloud resources. Through this method, the user's resource management maturity can be accurately measured, the governance deficiencies and potential risks of the user in the cloud resource management process can be assessed, and the user's cloud resource management effect and risk control capabilities can be improved.

[0059] As mentioned above, let's take a cloud resource management scenario of an enterprise as an example. Figure 4 The cloud resource management method in this application scenario is illustrated by way of example.

[0060] like Figure 4 As shown, assuming that the enterprise's users need to manage cloud resources, they can generate a resource management request on the terminal device (assuming it is a tablet computer) by clicking, and based on the above resource management request, obtain from the cloud platform the initial resource management data generated by the user's management of cloud resources based on the resource management module.

[0061] Afterwards, the tablet computer determines the user's resource management maturity based on the initial resource management data. Specifically, the initial resource management data is first classified to obtain multiple categories of initial resource management data. Assume that the initial resource management data of the enterprise includes three categories: A data, B data, and C data, wherein the resource management score of Class A data is calculated to be 50 points, and the resource management scores of Class B data and Class C data are both 90 points. Accordingly, the calculated resource management maturity score is 70 points. It should be noted that the resource management score and the resource management maturity score can be calculated by weighted summation or by a preset calculation model, which is not limited in the embodiments of the present application.

[0062] Assuming that 60 points is the passing score for resource management, it means that the user has major defects in the management of Class A data. In this case, corresponding cloud resource management suggestions can be generated for Class A data. At the same time, assuming that the resource management maturity score is divided into three intervals: greater than 80 points, greater than 60 points and less than 80 points, and less than 60 points. The maturity levels corresponding to the above intervals are security level, risk level, and high risk level. The resource management maturity of the enterprise is in the risk level category.

[0063] In this way, the resource management assessment result corresponding to the enterprise can be generated based on the above data. The resource management assessment result includes the resource management maturity of the enterprise as a risk category, and the cloud resource management suggestions corresponding to the A-type data.

[0064] The tablet computer displays the resource management assessment results to the enterprise's users, who can update the current resource management plan based on the cloud resource management suggestions in the resource management assessment results and manage cloud resources according to the updated resource management plan.

[0065] Figure 5 A flowchart of a method for determining resource management maturity provided by an exemplary embodiment of the present application is shown in FIG. Figure 5 As shown, the method comprises the following steps:

[0066] Step S501: classify initial resource management data based on a first preset classification rule to obtain first classification information, wherein the first classification information includes at least one first data category and at least one resource management data corresponding to each of the first data categories.

[0067] Step S502: Calculate the resource management score corresponding to at least one first data category respectively.

[0068] Step S503: determining the resource management maturity of the user based on the resource management score corresponding to each of the at least one first data categories.

[0069] To determine the resource management maturity of the user, first, the initial resource management data is classified based on a first preset classification rule to obtain first classification information. In this embodiment, the first classification information includes at least one first data category and at least one resource management data corresponding to each of the first data categories.

[0070] In this embodiment, the first preset classification rule may be a rule for classifying the initial resource management data according to information such as the purpose, dimension, or function provided by the resource management module in the cloud platform. For example, the first preset classification rule is to classify the initial resource management data according to the function provided by the resource management module in the cloud platform. Assuming that the resource management module in the cloud platform can provide resource classification function, resource stratification function, and resource quota function, the initial resource management data can be divided into resource classification data, resource stratification data, and resource quota data. It should be noted that the first preset classification rule can be personalized according to the user's cloud resource management needs, and the embodiment of the present application does not impose specific restrictions on the specific content of the first preset classification rule.

[0071] After the first classification information is obtained, the resource management score corresponding to at least one first data category may be calculated respectively.

[0072] In this embodiment, in order to calculate the resource management scores corresponding to each of the first data categories, optionally, for any target first data category in at least one first data category, the resource management data corresponding to the target first data category can be classified based on a second preset classification rule to obtain second classification information. In this embodiment, the second classification information includes at least one second data category and at least one sub-resource management data corresponding to each of the second data categories.

[0073] Afterwards, the resource management score corresponding to the target first data category may be calculated based on the first preset weight corresponding to each of the at least one second data categories and the parameters of the sub-resource management data corresponding to each of the at least one second data categories.

[0074] In actual applications, the resource management data corresponding to each of the first data categories can be further classified. Specifically, the resource management data corresponding to each of the first data categories can be classified based on the second preset classification rule. In this embodiment, the second preset classification rule is similar to the first preset classification rule. Specifically, the second preset classification rule can be a rule for classifying the resource management data corresponding to the first data category according to the user, dimension and other information of the resource management data corresponding to the first data category. For example, taking the first data category as resource classification data as an example, the first data category can be divided into resource grouping data, resource label data, grouping strategy data and label strategy data, etc. according to the second preset classification rule. Correspondingly, the sub-resource management data corresponding to the above-mentioned second data category may include resource grouping rate, resource labeling rate, grouping strategy coverage rate and label strategy coverage rate, etc. It should be noted that the second preset classification rule can be personalized according to the user's cloud resource management needs, and the embodiment of the present application does not specifically limit the specific content of the second preset classification rule.

[0075] After determining the second data categories and the sub-resource management data corresponding to each of the second data categories, the first preset weights corresponding to each of the second data categories and the parameters of at least one sub-resource management data corresponding to each of the second data categories can be obtained to calculate the resource management score corresponding to the corresponding target first data category.

[0076] In the embodiment of the present application, the sub-resource management score corresponding to each second data category may be calculated first, and then the resource management score corresponding to the final target first data category may be calculated.

[0077] The sub-resource management score corresponding to the second data category can be calculated based on the following formula (1):

[0078] O i =ω i (k j |1≤j≤m)(1)

[0079] Wherein, O is the set of the second data category, O i Score the sub-resource management of the second data category of the i-th item, k j is the parameter of the sub-resource management data of the second data category of the i-th item, there are m parameters in total, ω i A calculation function for managing the score of the sub-resource of the second data category of the i-th item.

[0080] The resource management score corresponding to the target first data category can be calculated based on the following formula (2):

[0081]

[0082] Where S is the resource management score corresponding to the target first data category, n is the number of second data categories corresponding to the target first data category, O i Score the sub-resource management of the second data category of the i-th item, λ i A first preset weight for scoring the management of the sub-resource of the i-th second data category.

[0083] For example, the first target data category is resource classification data, and the resource classification data includes resource grouping data and resource tag data. Assume that the current user enterprise A currently has 100 member users on the cloud, that is, the total number of users is 100; among them, there are 50 users who perform resource grouping and 60 users with resource tags. Then the resource grouping rate of the enterprise user is 0.5, and the resource tagging rate is 0.6.

[0084] Based on the above formula (1), assuming that the calculation functions corresponding to the resource grouping data and the resource tag data are both 1, the sub-resource management score corresponding to the resource grouping data is 0.5, and the sub-resource management score corresponding to the resource tag data is 0.6. Based on the above formula (2), assuming that the first preset weight corresponding to the resource grouping data is 6, and the first preset weight corresponding to the resource tag data is 4, the calculated resource management score corresponding to the resource classification data is 5.4.

[0085] When determining the resource management maturity of a user, the second preset weight corresponding to each of the at least one first data categories can be obtained respectively; then, based on the second preset weight corresponding to each of the at least one first data categories and the resource management score corresponding to each of the at least one first data categories, the resource management maturity of the user in managing cloud resources is obtained by weighted sum calculation.

[0086] In this embodiment, the second preset weights corresponding to the first data categories can be preset according to the actual usage requirements of the user. The resource management maturity can be calculated based on the following formula (3):

[0087]

[0088] Among them, Q is the resource management maturity, S t is the resource management score corresponding to the t-th first data category, T is the number of first data categories, and p t is the second preset weight corresponding to the t-th first data category.

[0089] For example, taking the first data category including resource classification data, resource stratification data and resource quota data as an example, assuming that the second preset weights of the above three first data categories are 4, 2 and 6 respectively. Among them, the resource management score corresponding to the resource classification data is 6, the resource management score corresponding to the resource stratification data is 8, and the resource management score corresponding to the resource quota data is 6. Based on the above formula (3), it can be obtained that the resource management maturity of the user is 76.

[0090] In an optional embodiment, to generate a resource management assessment result, a target resource management maturity level corresponding to the resource management maturity can be determined from multiple resource management maturity levels, and then a resource management assessment result corresponding to the user is generated based on the target resource management maturity level and the resource management maturity.

[0091] Specifically, when determining the target resource management maturity, the target resource management maturity interval to which the resource management maturity belongs can be determined from multiple resource management maturity intervals, and each of the multiple resource management maturity intervals corresponds to a different resource management maturity level; then, the resource management maturity level corresponding to the target resource management maturity interval is determined as the target resource management maturity level.

[0092] For example, assuming that the resource management maturity interval includes three intervals: greater than 80 points, greater than 60 points and less than 80 points, and less than 60 points, if the resource management maturity of an enterprise user is 90 points, then the resource management maturity interval greater than 80 points is the target resource management maturity interval corresponding to the enterprise user.

[0093] Assuming that the maturity levels corresponding to the above-mentioned resource management maturity intervals are security level, risk level and high-risk level, the target resource management maturity level corresponding to the enterprise user is the security level.

[0094] In an optional embodiment, each of the multiple resource management maturity levels corresponds to a different cloud resource management recommendation.

[0095] When generating a resource management assessment result corresponding to a user based on the target resource management maturity level and the resource management maturity, it is possible to first determine whether the target resource management maturity level meets the preset level conditions and output the determination result. If the determination result indicates that the target resource management maturity level does not meet the preset level conditions, obtain a cloud resource management suggestion corresponding to the target resource management maturity level. Finally, a resource management assessment result is generated based on the cloud resource management suggestion corresponding to the target resource management maturity level and the resource management maturity. In this embodiment, the resource management assessment result includes resource management maturity, the target resource management maturity level, and the cloud resource management suggestion corresponding to the target resource management maturity level.

[0096] In this embodiment, the preset level condition may include whether the target resource management maturity level meets the preset level. For example, the resource management maturity level includes the safety level, risk level and high risk level. In this case, the preset level condition may include whether the target resource management maturity level is the safety level.

[0097] First, determine whether the target resource management maturity level meets the preset level conditions. If the target resource management maturity level meets the preset level conditions, it means that the current resource management plan has no management defects and does not need to be updated. On the contrary, if the target resource management maturity level does not meet the preset level conditions, it means that the current resource management plan has management defects and needs to be updated.

[0098] When obtaining cloud resource management recommendations corresponding to the target resource management maturity level, the corresponding cloud resource management recommendations can be determined based on the resource management score corresponding to the first data category. For example, taking the first data category including resource classification data and resource stratification data as an example, the resource management scores corresponding to the resource classification data and the resource stratification data are 4.0 and 7.0, respectively. If the passing line for the resource management score is 6.0, that is, the resource management score corresponding to the resource classification data fails, while the resource management score corresponding to the resource stratification data passes. At this point, the corresponding cloud resource management recommendations can be determined for the resource classification data, for example, the cloud resources need to be further classified, and so on.

[0099] In an optional embodiment, in order to generate a resource management assessment result, a target resource management maturity level corresponding to the resource management maturity can be determined among multiple resource management maturity levels; a target parameter level corresponding to the sub-resource management data of each second data category can be determined among multiple parameter levels; finally, a resource management assessment result corresponding to the user is generated based on the target resource management maturity level, the target parameter level and the resource management maturity.

[0100] In this embodiment, the resource management maturity level is the same as the resource management maturity level in the above embodiment, and this situation will not be repeated here.

[0101] The target parameter level is similar to the resource management maturity level. First, the target parameter interval to which the parameters of each sub-resource management data belong can be determined in multiple parameter intervals, and then the parameter level corresponding to the target parameter interval is determined as the target parameter level of the corresponding second data category.

[0102] In this embodiment, each of the multiple resource management maturity levels corresponds to a different first cloud resource management suggestion, and each of the multiple parameter levels corresponds to a different second cloud resource management suggestion.

[0103] When generating a resource management assessment result corresponding to a user based on the target resource management maturity level, the target parameter level, and the resource management maturity, first, it is possible to determine whether the target resource management maturity level meets the first preset level condition and output the determination result; if the determination result shows that the target resource management maturity level does not meet the first preset level condition, obtain a cloud resource management suggestion corresponding to the target resource management maturity level and a second cloud resource management suggestion corresponding to each second data category, the second cloud resource management suggestion being determined based on the target parameter level corresponding to the second data category, and the target parameter level being determined based on the parameters of the sub-resource management data corresponding to the second data category. Finally, a resource management assessment result corresponding to a user can be generated based on the target resource management maturity level, the target parameter level, and the resource management maturity, the resource management assessment result including resource management maturity, the target resource management maturity level, the first cloud resource management suggestion corresponding to the target resource management maturity level, and the second cloud resource management suggestion corresponding to each second data category.

[0104] In this embodiment, when obtaining the second cloud resource management suggestions corresponding to each second data category, it is possible to first determine whether the parameter level corresponding to the second data category meets the second preset level condition. If it meets the second preset level condition, there is no need to obtain the corresponding second cloud resource management suggestion; if it does not meet the second preset level condition, then obtain the corresponding second cloud resource management suggestion. It should be noted that the first preset level condition and the second preset level condition in this embodiment are similar to the preset level conditions corresponding to the resource management maturity level in the above embodiment. For details, please refer to the description of the preset level conditions corresponding to the resource management maturity level in the above embodiment, and the embodiments of this application will not be repeated here.

[0105] In this embodiment, the corresponding second cloud resource management suggestion can be determined based on the sub-resource management score corresponding to the second data category. For example, taking resource classification data as an example, assuming that the second data categories included in the resource classification data are resource grouping data and resource tag data, respectively, wherein the sub-resource management score corresponding to the resource grouping data is 0.5, and the sub-resource management score corresponding to the resource tag data is 0.7. If the passing line of the self-resource management score is 0.6, that is, the sub-resource management score corresponding to the resource grouping data fails, and the sub-resource management score corresponding to the resource tag data passes. At this point, the corresponding cloud resource management suggestion can be determined for the resource grouping data, for example, the cloud resources need to be further grouped, and so on.

[0106] When generating resource management assessment results, the target resource management maturity level, the first cloud resource management suggestion corresponding to the target resource management maturity level, the resource management maturity, the target parameter level and the second cloud resource management suggestion corresponding to the target parameter level can be added to the resource management assessment results.

[0107] Based on the above embodiment, as an optional implementation method, Figure 6 The present application also provides a cloud resource management method, including the following contents:

[0108] First, users with cloud resource management needs obtain initial resource management data generated based on the resource management solution from the resource management module in the cloud platform. It should be noted that before obtaining the initial resource management data of different dimensions from the cloud platform, when users manage resources on the cloud through various cloud management tools, including but not limited to consoles, command line tools, OpenAPI and other tools, some initial resource management data will be generated through the resource management module on the cloud.

[0109] Second, based on the initial resource management data, determine the user's resource management maturity.

[0110] After the initial resource management data is acquired, the initial resource management data is classified according to a first preset classification rule to obtain a plurality of first data categories and resource management data corresponding to each first data category.

[0111] In this embodiment, it is assumed that the first preset classification rule is to classify the initial resource management data based on the functions provided by the resource management module, wherein the resource management module includes a resource classification function and a resource stratification function, and accordingly, the first data category includes resource classification data and resource stratification data.

[0112] The resource management scores corresponding to the resource classification data and resource stratification data are calculated respectively through the resource classification calculation model and the resource stratification calculation model.

[0113] In this embodiment, resource classification data and resource layered data are classified respectively to obtain second classification information. In this embodiment, it is assumed that the second data category included in the resource classification data is resource grouping data and resource tag data; the second data category included in the resource layered data is resource organizational structure information.

[0114] Taking resource classification data as an example, in this embodiment, it is assumed that the current user enterprise A currently has 100 member users on the cloud, that is, the total number of users is 100; among them, there are 50 users who perform resource grouping and 60 users with resource tags. Then the resource grouping rate corresponding to the enterprise user resource grouping data is 0.5, and the resource labeling rate corresponding to the resource label data is 0.6.

[0115] Based on the above formula (1), assuming that the calculation functions corresponding to the resource grouping data and the resource tag data are both 1, the sub-resource management score corresponding to the resource grouping data is 0.5, and the sub-resource management score corresponding to the resource tag data is 0.6. Based on the above formula (2), assuming that the first preset weight corresponding to the resource grouping data is 6, and the first preset weight corresponding to the resource tag data is 4, the calculated resource management score corresponding to the resource classification data is 5.4. In this embodiment, the resource management score corresponding to the resource stratification data is calculated in the same way as the resource management score corresponding to the resource classification data, and the embodiments of this application are not repeated here. In this embodiment, it is assumed that the resource management score corresponding to the resource stratification data is 8.0. In this embodiment, the higher the resource management score, the better the cloud resource management capability of the corresponding data category.

[0116] Based on the resource management score corresponding to the resource classification data and the resource management score corresponding to the resource stratification data, the resource management maturity of the user is determined through the resource management maturity calculation model.

[0117] Specifically, it is assumed that the second preset weight corresponding to the resource classification data is 6, and the second preset weight corresponding to the resource layering data is 4. Based on the above formula (3), it can be calculated that the user's resource management maturity is 64.4.

[0118] Third, based on the user's resource management maturity, a resource management evaluation result corresponding to the resource management solution is generated. The resource management evaluation result includes cloud resource management recommendations corresponding to the resource management solution.

[0119] First, a target resource management maturity level corresponding to the resource management maturity is determined among a plurality of resource management maturity levels.

[0120] Specifically, a target resource management maturity interval to which the resource management maturity belongs is determined among multiple resource management maturity intervals, each of which corresponds to a different resource management maturity level; and the resource management maturity level corresponding to the target resource management maturity interval is determined as the target resource management maturity level.

[0121] Assuming that the resource management maturity interval includes three intervals: greater than 80 points, greater than 60 points and less than 80 points, and less than 60 points, if the resource management maturity of an enterprise user is 90 points, then the resource management maturity interval of greater than 60 points and less than 80 points is the target resource management maturity interval corresponding to the enterprise user.

[0122] Assuming that the maturity levels corresponding to the above-mentioned resource management maturity intervals are security level, risk level and high-risk level, the target resource management maturity level corresponding to the enterprise user is risk level.

[0123] Then, a resource management assessment result corresponding to the user is generated based on the target resource management maturity level and the resource management maturity.

[0124] Specifically, each resource management maturity level corresponds to a different cloud resource management suggestion. First, determine whether the target resource management maturity level meets the preset level conditions, and output the judgment result. If the judgment result shows that the target resource management maturity level does not meet the preset level conditions, obtain the cloud resource management suggestion corresponding to the target resource management maturity level; generate a resource management assessment result based on the cloud resource management suggestion corresponding to the target resource management maturity level and the resource management maturity, and the resource management assessment result includes resource management maturity, target resource management maturity level, and cloud resource management suggestion corresponding to the target resource management maturity level.

[0125] In this embodiment, it is assumed that the preset level condition is that the resource management maturity level is the security level. Obviously, the target resource management maturity level in this embodiment is the risk level, which does not meet the preset level condition. Therefore, it is necessary to add the cloud resource management corresponding to the risk level to the resource management evaluation result. Therefore, the resource management evaluation result of the embodiment of the present application includes a resource management maturity of 64.4, a target resource management maturity level of a risk level, and a cloud resource management recommendation of further grouping cloud resources.

[0126] Fourth, based on the cloud resource management suggestion, the resource management scheme is updated so that users can manage cloud resources according to the updated resource management scheme.

[0127] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0128] According to another aspect of the embodiments of the present application, a cloud resource management method device for implementing the above cloud resource management method is also provided. Figure 7 As shown, the device includes: an acquisition module 701, a determination module 702, a generation module 703 and an update module 704.

[0129] The acquisition module 701 is used to acquire initial resource management data generated by the user managing the cloud resources based on the resource management solution.

[0130] The determination module 702 is used to determine the resource management maturity of the user based on the initial resource management data.

[0131] The generation module 703 is used to generate a resource management evaluation result corresponding to the resource management solution based on the resource management maturity, and the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution.

[0132] The updating module 704 is used to update the resource management scheme based on the cloud resource management suggestion, so that the user can manage the cloud resources according to the updated resource management scheme.

[0133] As an optional embodiment, acquisition module 701 is specifically used to obtain from the cloud platform the initial resource management data generated by the user managing the cloud resources based on the resource management module. The resource management module includes one of the multiple service modules provided by the cloud platform. The multiple service modules each correspond to a different resource governance plan and initial resource governance data. The resource management plan includes one of the multiple resource governance plans, and the initial resource management data includes one of the multiple initial resource governance data.

[0134] As an optional embodiment, the determination module 702 is specifically used to classify the initial resource management data based on a first preset classification rule to obtain first classification information, the first classification information including at least one first data category and at least one resource management data corresponding to each of the first data categories; respectively calculate the resource management score corresponding to each of the at least one first data category; and determine the resource management maturity of the user based on the resource management score corresponding to each of the at least one first data category.

[0135] As an optional embodiment, the determination module 702 is specifically used to classify the resource management data corresponding to any target first data category in at least one first data category based on a second preset classification rule to obtain second classification information, wherein the second classification information includes at least one second data category and at least one sub-resource management data corresponding to each second data category; based on the first preset weight corresponding to each at least one second data category and the parameters of the sub-resource management data corresponding to each at least one second data category, calculate the resource management score corresponding to the target first data category.

[0136] As an optional embodiment, the determination module 702 is specifically used to obtain the second preset weight corresponding to each of the at least one first data categories; based on the second preset weight corresponding to each of the at least one first data categories and the resource management score corresponding to each of the at least one first data categories, the resource management maturity of the user's management of cloud resources is obtained by weighted sum calculation.

[0137] As an optional embodiment, the generation module 703 is specifically used to determine a target resource management maturity level corresponding to a resource management maturity level among multiple resource management maturity levels; and generate a resource management assessment result corresponding to the user based on the target resource management maturity level and the resource management maturity.

[0138] As an optional embodiment, the generation module 703 is specifically used to determine the target resource management maturity interval to which the resource management maturity belongs among multiple resource management maturity intervals, each of the multiple resource management maturity intervals corresponding to a different resource management maturity level; and determine the resource management maturity level corresponding to the target resource management maturity interval as the target resource management maturity level.

[0139] As an optional embodiment, each of the multiple resource management maturity levels corresponds to a different cloud resource management suggestion;

[0140] Correspondingly, generation module 703 is specifically used to determine whether the target resource management maturity level meets the preset level conditions and output the judgment result; when the judgment result shows that the target resource management maturity level does not meet the preset level conditions, obtain the cloud resource management suggestions corresponding to the target resource management maturity level; generate a resource management evaluation result based on the cloud resource management suggestions corresponding to the target resource management maturity level and the resource management maturity, and the resource management evaluation result includes resource management maturity, target resource management maturity level and cloud resource management suggestions corresponding to the target resource management maturity level.

[0141] As an optional embodiment, generation module 703 is further specifically used to determine a target resource management maturity level corresponding to a resource management maturity among multiple resource management maturity levels; and determine a target parameter level corresponding to sub-resource management data of each second data category among multiple parameter levels; and generate a resource management assessment result corresponding to the user based on the target resource management maturity level, the target parameter level and the resource management maturity.

[0142] As an optional embodiment, each of the multiple resource management maturity levels corresponds to a different first cloud resource management suggestion, and each of the multiple parameter levels corresponds to a different second cloud resource management suggestion.

[0143] Correspondingly, generation module 703 is specifically used to determine whether the target resource management maturity level meets the first preset level conditions and output the judgment result; when the judgment result shows that the target resource management maturity level does not meet the first preset level conditions, obtain the cloud resource management suggestions corresponding to the target resource management maturity level and the second cloud resource management suggestions corresponding to each second data category, the second cloud resource management suggestions are determined based on the target parameter level corresponding to the second data category, and the target parameter level is determined based on the parameters of the sub-resource management data corresponding to the second data category; based on the target resource management maturity level, the target parameter level and the resource management maturity, generate the corresponding resource management evaluation result for the user, the resource management evaluation result includes the resource management maturity, the target resource management maturity level, the first cloud resource management suggestions corresponding to the target resource management maturity level and the second cloud resource management suggestions corresponding to each second data category.

[0144] The embodiment of the present application also provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication. The memory stores a computer program executable by the at least one processor, and the computer program is used to enable the electronic device to perform the method of the embodiment of the present application when executed by the at least one processor.

[0145] An embodiment of the present application also provides a non-transitory machine-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to enable the computer to execute the method of the embodiment of the present application.

[0146] The embodiment of the present application also provides a computer program product, including a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute the method of the embodiment of the present application.

[0147] refer to Figure 8 , the structural block diagram of the electronic device that can be used as the server or client of the embodiment of the present application will be described, which is an example of the hardware device that can be applied to various aspects of the present application. The electronic device is intended to represent various forms of digital electronic computer equipment, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples, and are not intended to limit the implementation of the present application described and / or required herein.

[0148] As shown in the figure, the electronic device includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. In RAM 803, various programs and data required for the operation of the electronic device can also be stored. The computing unit 801, ROM 802 and RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0149] Multiple components in the electronic device are connected to the I / O interface 805, including: an input unit 806, an output unit 807, a storage unit 808, and a communication unit 809. The input unit 806 can be any type of device that can input information to the electronic device, and the input unit 806 can receive input digital or character information, and generate key signal input related to user settings and / or function control of the electronic device. The output unit 807 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 808 can include but is not limited to a disk, an optical disk. The communication unit 809 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0150] The computing unit 801 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a CPU, a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above. For example, in some embodiments, the method embodiments of the present application may be implemented as a computer program, which is tangibly contained in a machine-readable storage medium, such as a storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via ROM 802 and / or a communication unit 809. In some embodiments, the computing unit 801 may be configured to perform the above method in any other appropriate manner (e.g., by means of firmware).

[0151] The computer program for implementing the method of the embodiment of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0152] In the context of the present application embodiment, the machine-readable storage medium can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. The machine-readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. The machine-readable signal medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0153] It should be noted that the term "including" and its variations used in the embodiments of the present application are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". The modifications of "one" and "multiple" mentioned in the embodiments of the present application are illustrative and not restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0154] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0155] The various steps described in the method implementation methods provided in the embodiments of the present application can be performed in different orders and / or in parallel. In addition, the method implementation methods may include additional steps and / or omit the steps shown. The scope of protection of the present application is not limited in this respect.

[0156] The term "embodiment" in this specification refers to specific features, structures or characteristics described in conjunction with the embodiment that can be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. The various embodiments in this specification are described in a related manner, and the same or similar parts between the various embodiments refer to each other. In particular, for the device, equipment, and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts refer to the partial description of the method embodiment.

[0157] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the attached claims.

Claims

1. A cloud resource management method, comprising: Obtaining initial resource management data generated by users managing cloud resources based on resource management solutions; Determining the resource management maturity of the user based on the initial resource management data; Based on the resource management maturity, generating a resource management evaluation result corresponding to the resource management solution, wherein the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution; The resource management scheme is updated based on the cloud resource management suggestion, so that the user can manage the cloud resources according to the updated resource management scheme.

2. The method according to claim 1, wherein: The obtaining of initial resource management data generated by the user managing cloud resources based on the resource management solution includes: The initial resource management data generated by the user managing the cloud resources based on the resource management module is obtained from the cloud platform, the resource management module includes one of the multiple service modules provided by the cloud platform, the multiple service modules respectively correspond to different resource governance schemes and initial resource governance data, the resource management scheme includes one of the multiple resource governance schemes, and the initial resource management data includes one of the multiple initial resource governance data.

3. The method according to claim 1, wherein: The determining the resource management maturity of the user based on the initial resource management data includes: Classifying the initial resource management data based on a first preset classification rule to obtain first classification information, wherein the first classification information includes at least one first data category and resource management data corresponding to each of the at least one first data category; respectively calculating a resource management score corresponding to each of the at least one first data category; The resource management maturity of the user is determined based on the resource management score corresponding to each of the at least one first data categories.

4. The method according to claim 3, wherein: The respectively calculating the resource management score corresponding to each of the at least one first data category comprises: For any target first data category in the at least one first data category, classify the resource management data corresponding to the target first data category based on a second preset classification rule to obtain second classification information, wherein the second classification information includes at least one second data category and sub-resource management data corresponding to each of the at least one second data category; The resource management score corresponding to the target first data category is calculated based on the first preset weight corresponding to each of the at least one second data categories and the parameters of the sub-resource management data corresponding to each of the at least one second data categories.

5. The method according to claim 3, wherein: The determining the resource management maturity of the user based on the resource management score corresponding to each of the at least one first data category comprises: Respectively obtaining a second preset weight corresponding to each of the at least one first data category; Based on the second preset weight corresponding to each of the at least one first data categories and the resource management score corresponding to each of the at least one first data categories, the resource management maturity of the user managing the cloud resources is obtained by weighted sum calculation.

6. The method according to claim 1, wherein: The generating, based on the resource management maturity, a resource management evaluation result corresponding to the resource management solution includes: Determining a target resource management maturity level corresponding to the resource management maturity level among a plurality of resource management maturity levels; The resource management assessment result corresponding to the user is generated based on the target resource management maturity level and the resource management maturity.

7. The method according to claim 6, wherein: The determining a target resource management maturity level corresponding to the resource management maturity level among a plurality of resource management maturity levels includes: Determining a target resource management maturity interval to which the resource management maturity belongs from a plurality of resource management maturity intervals, wherein the plurality of resource management maturity intervals respectively correspond to a different resource management maturity level; The resource management maturity level corresponding to the target resource management maturity interval is determined as the target resource management maturity level.

8. The method according to claim 6, wherein: The multiple resource management maturity levels each correspond to a different cloud resource management suggestion; The generating the resource management assessment result corresponding to the user based on the target resource management maturity level and the resource management maturity includes: Determine whether the target resource management maturity level meets the preset level conditions, and output the determination result; If the judgment result indicates that the target resource management maturity level does not meet the preset level condition, obtaining cloud resource management suggestions corresponding to the target resource management maturity level; The resource management assessment result is generated based on the cloud resource management suggestions corresponding to the target resource management maturity level and the resource management maturity, and the resource management assessment result includes the resource management maturity, the target resource management maturity level and the cloud resource management suggestions corresponding to the target resource management maturity level.

9. The method according to claim 4, wherein: The generating, based on the resource management maturity, a resource management evaluation result corresponding to the resource management solution includes: determining a target resource management maturity level corresponding to the resource management maturity level among a plurality of resource management maturity levels; and Determining a target parameter level corresponding to each sub-resource management data of the second data category among a plurality of parameter levels; The resource management assessment result corresponding to the user is generated based on the target resource management maturity level, the target parameter level and the resource management maturity.

10. The method according to claim 9, wherein: The multiple resource management maturity levels each correspond to a different first cloud resource management suggestion, and the multiple parameter levels each correspond to a different second cloud resource management suggestion; The generating the resource management assessment result corresponding to the user based on the target resource management maturity level, the target parameter level and the resource management maturity includes: Determine whether the target resource management maturity level meets the first preset level condition, and output the determination result; If the judgment result shows that the target resource management maturity level does not meet the first preset level condition, obtaining a cloud resource management suggestion corresponding to the target resource management maturity level and a second cloud resource management suggestion corresponding to each second data category, wherein the second cloud resource management suggestion is determined based on a target parameter level corresponding to the second data category, and the target parameter level is determined based on a parameter of the sub-resource management data corresponding to the second data category; The resource management assessment result corresponding to the user is generated based on the target resource management maturity level, the target parameter level and the resource management maturity, and the resource management assessment result includes the resource management maturity, the target resource management maturity level, the first cloud resource management recommendation corresponding to the target resource management maturity level, and the second cloud resource management recommendation corresponding to each second data category.

11. A cloud resource management evaluation device, comprising: An acquisition module is used to acquire initial resource management data generated by users managing cloud resources based on resource management solutions; a determination module, configured to determine the resource management maturity of the user based on the initial resource management data; A generating module, configured to generate a resource management evaluation result corresponding to the resource management solution based on the resource management maturity, wherein the resource management evaluation result includes a cloud resource management suggestion corresponding to the resource management solution; An updating module is used to update the resource management scheme based on the cloud resource management suggestion, so that the user can manage the cloud resources according to the updated resource management scheme.

12. An electronic device comprising: A processor, and a memory storing a program, wherein the program comprises instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 10.

13. A non-transitory machine-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 10.

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