Patent Publication Number: US-11640324-B2

Title: Intelligent cloud management based on profile

Description:
CLAIM OF PRIORITY 
     This application is a continuation of U.S. patent application Ser. No. 16/605,419 filed on Oct. 15, 2019, which is a U.S. National Stage Filing under 35 U.S.C. 371 of International Patent Application Serial No. PCT/US2018/028732, filed Apr. 21, 2018, and published as WO 2018/208472 A1 on Nov. 15, 2018, which claims priority to Chinese Application No. 201710335366.8, filed May 12, 2017, which applications and publication are incorporated herein by reference in their entirety. 
    
    
     BACKGROUND 
     As development of computer technique, cloud has been used in many fields. The term of “cloud” refers to a special IT resource, which may provide services including computation, data storage, information processing, and so on to remote cloud users based on network. The one who provides cloud resource may be a cloud provider, while the one who rents cloud resource may be a cloud tenant. In practical usage, the cloud tenant may be generally an institution, such as an enterprise or other organization, such as university, government, or the like. The cloud tenant may build its own business processing system with the rent cloud resource or do its own business processes based on a business system provided by a cloud provider, while the employees, i.e. the cloud users, of the institution may act as the cloud user of the cloud resource to process business of the institution, which includes business development based on cloud resources, business processing based on cloud resources, and maintenance of business system based on cloud resources, or the like. For example, a cloud tenant may be an e-business company and establish an internet sales platform with cloud resources rent from a cloud provider. The cloud resources supporting such internet sales platform may include a plurality of virtual servers, cloud databases, load balancer or other cloud resources. The employees of that e-business company may need to perform developing, maintenance and other business processing on the internet sales platform built on the cloud resource. 
     BRIEF SUMMARY 
     The embodiments of the present disclosure is provided to give a brief introduction to some concepts, which would be further explained in the following description. This Summary is not intended to identify essential technical features or important features of the subject as claimed nor to limit the scope of the subject as claimed. 
     A technical solution related to intelligent cloud management based profile is disclosed and applies Artificial Intelligence (AI) to cloud management and intelligently propose processing suggestions on cloud resource management. In daily work, behaviors for using cloud resources may show features of cloud users or cloud tenants themselves. The technical solution of intelligent cloud management of the present disclosure generates profile identifying cloud usage features by extracting cloud usage behavior data and intelligently proposes cloud management suggestions based on the profile. 
     The above description is merely a brief introduction of the technical solutions of the present disclosure, so that the technical means of the present disclosure may be clearly understood, and implemented according to the description of the specification, and the above and other technical objects, features and advantages of the present disclosure may be more obvious based on the embodiments of the present disclosure as follows. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    is a block diagram of cloud management system; 
         FIG.  2    is a schematic diagram showing generating of cloud-user profile of an embodiment of the present disclosure; 
         FIG.  3    is another schematic diagram showing another generating of cloud-tenant profile of an embodiment of the present disclosure; 
         FIG.  4    is still another schematic diagram showing still another generating of cloud-tenant profile of an embodiment of the present disclosure; 
         FIG.  5    is a schematic diagram showing generating of running status data of cloud resource of an embodiment of the present disclosure; 
         FIG.  6    is a block diagram of a module for generating cloud management suggestion of an embodiment of the present disclosure; 
         FIG.  7 A  is another block diagram of a module for generating cloud management suggestion of an embodiment of the present disclosure; 
         FIG.  7 B  is still another block diagram of a module for generating cloud management suggestion of an embodiment of the present disclosure; 
         FIG.  8    is still another block diagram of a module for generating cloud management suggestion of an embodiment of the present disclosure; 
         FIG.  9    is a block diagram showing cloud management templates of an embodiment of the present disclosure; 
         FIG.  10    is a scenario in which the embodiments of the present disclosure may be applied; 
         FIG.  11    is a schematic diagram showing processing of intelligent cloud management of an embodiment of the present disclosure; 
         FIG.  12    is a block diagram of an intelligent cloud management device of an embodiment of the present disclosure; and 
         FIG.  13    is a block diagram of an electric apparatus of an embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     In the following, description will be given in detail on the exemplary embodiments of the present disclosure, in connection with the accompanying drawing. Although drawings show the exemplary embodiments of the present disclosure, it should be appreciated that the present disclosure may be implemented in various ways without being limited by the embodiments set forth herein. On the contrary, these embodiments are provided for thorough understanding of the present disclosure, and completely conveying the scope of the present disclosure to the skills in the art. 
     Explanation for Terms 
     Cloud Provider: one providing cloud resources, e.g., Microsoft Axure, the cloud platform from Microsoft®, Ali Cloud from Alibaba®, and AWS cloud platform from Amazon. 
     Cloud Tenant: the cloud tenant is generally an institution, such as an enterprise or other organization, such as university, government, or the like. The cloud tenant may build its own business processing system with the rented cloud resource or do its own business processes based on a business system provided by a cloud provider. 
     Cloud User: people using cloud resources in cloud tenants. The usage of cloud resources by cloud users includes: developing and maintenance of business processing system based on cloud resources, processing business by using business processing system based on cloud resources, deployment and optimizing on the rented cloud resources and other usage. For example, when the cloud tenant is a company, the cloud users may be the employees of the company, i.e., engineers for developing and maintenance of systems, or salesmen for sales business of the company, or administrative staffs for human resource management in the company. 
     Cloud Resource: virtual computer resource provided to cloud tenants by cloud providers. In embodiments of the present disclosure, this term may be generally understood as including, for example, virtual machine resource, data storage resource, queue resource, data processing platform provided by a cloud provider, business processing system built by a cloud tenant based on rented resources such as virtual machines, databases, or the like, and so on. 
     In the present disclosure, term “technique” may refer to, for example, system(s), method(s), computer-readable instructions, module(s), algorithm, hardware logic (e.g., Field-Programmable Gate Array (FPGA)), Application Specific Integrated Circuit (ASIC), Application Specific Standard Parts (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), and/or other technique allowable in the above context and the present disclosure. 
     Cloud technique (also referred as cloud computing technique) has been widely used in various fields. The cloud resource provider may provide services including computing, data storage, information processing, or the like to cloud tenants and cloud users within cloud tenants based on internet. On the side of cloud tenant, to perform various business based on cloud normally and efficiently, the cloud tenant may perform various cloud management operations on cloud. In embodiments of the present disclosure, cloud management refers to operations of monitoring and analyzing usage of cloud resources, configuring, adjusting and maintenance with respect to cloud resources based analyzing results or the like. For example, such operations may include monitoring quantity of business of a cloud tenant, and adjusting amount of virtual machines or processing capability of virtual machines based on changes of business amount. As another example, such operations may include performing internet safety defense on business system built based on cloud, monitoring internet attack, virus or other cases, and performing processing such as virus killing or defensing. 
     Cloud management itself is a very professional and complex processing, and it is necessary to prepare specific management solutions after comprehensive analysis on usage of cloud and then perform the specific cloud management operations. This requires the person in charge of cloud management to have very rich professional acknowledge about cloud, fully understanding on the architecture and running status of cloud resources, and even rich developing experience on cloud. This is the only way to prepare reasonable management solutions based on usage of cloud and perform the same. Therefore, in current cloud management scheme, cloud management is performed by professional technicians. Although there is some auxiliary software on cloud management, such software is merely auxiliary tools and works passively. More particularly, such software performs management operations such as monitoring, inquiring, and configuring only based on instructions, configuration and even programming by cloud users. Therefore, such software is a kind of passive cloud management based on instructions from cloud users. 
     Therefore, the embodiments of the present disclosure introduces a technical idea of AI into cloud management, and proposes a technical solution of cloud management, so as to offer a generating mechanism for pro-active and intelligent cloud management suggestions. 
     As shown in  FIG.  1   , which is a schematic block diagram of cloud management system  100  of an embodiment of the present disclosure. Cloud provider  101  provides cloud resources to a cloud tenant  102 . A cloud user  103  of the cloud tenant  102  performs daily business processing by using cloud resources. 
     Profile acquiring module  104  of the cloud provider  101  may obtain behavior data in using cloud of the cloud user  103 , perform analysis on the behavior data in using cloud of the cloud user  103 , and generate profile  107  identifying cloud using characteristic of the cloud user  103  and/or the cloud tenant  102 . On the other hand, a module  105  for acquiring running status data of cloud resource of the cloud provider  101  may acquire running status data of cloud resource  108  of cloud resources rented by the cloud tenant  102 . A module  106  for generating cloud management suggestion of the cloud provider  101  may generate cloud management suggestions  109  according to profile  107  and running status data of cloud resource  108  and push the same to the cloud user  103  of the cloud tenant  102  so as to help the cloud user  103  in cloud management. 
     In the above system  100 , the cloud provider  101  may include one or more cloud servers or cloud platforms for providing cloud resource services to cloud tenants  102 . Operation systems or business processing system for cloud resource management may be installed on the cloud server or cloud platform. The cloud user  103  may use one or more servers, computer terminals, mobile terminals, or other devices to use cloud resources, and client software for connecting with cloud servers or cloud platforms of the cloud provider  101  may be installed on such devices. 
     In the above, general description has been made on the system architecture for cloud management of embodiments of the present disclosure. In the following, detailed description would be made on each main parts in  FIG.  1    in connection with Figs. 
     Profile Acquiring Module 
     The profile acquiring module  104  is configured to generate profile  107 . Profile  107  may be generated by extracting features from the general behavior data in using cloud of the cloud tenant  102  or the behavior data in using cloud of a plurality of cloud users  103  of the cloud tenant  102 . Such profile  107  shows nonrepresentational appearance for the cloud tenant  102  and/or the cloud users  103  of the cloud tenant  102  on the cloud. Such nonrepresentational appearance is related to a cloud tenant  102  or a cloud user  103 , and is capable to show characteristic of the cloud tenant  102  or the cloud user  103  in cloud using behavior. As shown in  FIG.  2    to  FIG.  4   , in some examples, the profile  107  may further include cloud-user profile  201  and/or cloud-tenant profile  301 . The cloud user  102  rents cloud resources from the cloud provider  101 , and then the cloud user  101  of the cloud tenant  102  may use the cloud resources. The behavior in using cloud cited herein may include all kinds of processing behaviors or operations based on cloud resources, e.g., business processing of business processing system based on cloud resources, system development and maintenance based on cloud resources, cloud management or the like. The cloud user  103  of the cloud tenant  102  cited herein refers to people authorized to perform operations on the cloud resources rented by the cloud tenant  102 . For example, in a case the cloud tenant  102  is an enterprise, generally, the cloud user  103  may be an employee of the company. In some cases, the cloud user  103  may be someone outside of the company which has authorization. In general, the cloud user  103  cited herein refers to people who can access the cloud resources of the cloud tenant  102  and can perform operations on the cloud resources. 
     In some cases, the cloud resources rented by the cloud tenant  102  is actually used by the cloud user  103 , and thus, both the cloud-user profile  201  and the cloud-tenant profile  301  may be acquired by extracting features from the behavior data in using cloud  202  of the cloud user  103 . The profile  107  is kind of highly synoptically generated, and thus may be in a form of label. That is to say, the profile  107  may be specifically one or more labels showing cloud using characteristic. The profile  107  may identify the characteristic of the cloud tenant  102  and/or the cloud user  103  on the cloud in various feature aspects. 
     The cloud provider  101  may provide cloud resources to remote cloud tenants  102  via network. These cloud resources are not locally in the cloud tenant  102  or computers of the cloud users. All cloud using behaviors of the cloud user  103  of the cloud tenant  102  may be done by using the cloud resources on the side of cloud provider  101 . The cloud provider  101  may monitor and record all the behavior data in using cloud  202  of the cloud user  103 . Therefore, it is feasible to acquire the behavior data in using cloud  202  from a log file of a cloud operation system of the cloud provider  101 , or a special monitoring module for cloud using behavior may be provided in a cloud server of the cloud provider  101  to monitor the cloud using behavior specifically and acquire the behavior data in using cloud  202 . As an alternative embodiment, it is feasible to acquire the behavior data in using cloud  202  from a log file in a computer of the cloud user  103 , or provide a monitoring module for cloud using behavior in a computer of the cloud user  103  to perform monitoring and recording on the cloud using behavior. 
     A technique of big data analyzing and machine learning technique may be used to extract profile  107  based on the behavior data in using cloud  202 . Models of various labels may be preset and technique of data digging or semantic analyzing may be used to extract features, and then machine learning technique such as classifier may be used to classify labels so as to acquire the profile  107 . 
     In the following, explanation would be made on the exemplary generating procedure  200  of cloud-user profile  201  in connection with  FIG.  2   . As shown in  FIG.  2   , which is a schematic diagram of a generating procedure  200  of cloud-user profile  201  of embodiments of the present disclosure, the cloud-user profile  201  may include following kinds of labels and each kind of label may be regarded as one feature aspect. 
     (1) label identifying role  201   a  of the cloud user  103 : for example, position label in a company (high-level manager, middle-level, normal staff, or the like), job label in a company (salesman, administrative staff, engineer). In some examples, in a case that there is authorization obtained from the cloud tenant  102  and/or cloud user  103  for accessing its business data, position label may be extracted from approval authority  202   a  in a business processing procedure of the company, and job label may be extracted from business content  202   c  (including business documents, emails, working logs, or the like) processed by the cloud user. For example, main business documents processed by engineers may be technical documents (for example, design drawings, program codes, product developing files, or the like), while main business content of salesman may be business orders or various emails related to product sales, or the like. In other examples, the label of role  201   a  of cloud user may be acquired from role and/or authority function provided by the cloud platform. For example, the cloud platform of Azure of Microsoft may provide various account roles (e.g., administrator, service administrator, account administrator, cooperation administrator) and various using authority (e.g., r/w, read-only, contributor or the like). The cloud user  103  may self-define the role and/or authority, such as virtual machine administrator, storage read-only staff, or other roles, according to different needs of the company. 
     (2) label identifying business type  201   b  of business processed by the cloud user  103 : for example, the business type of the business being processed may be purchasing and sales order business, overseas trade business, technique developing project, legal service project, or the like. In some examples, in a case that there is authorization obtained from the cloud tenant  102  and/or cloud user  103  for accessing its business data, these labels may be extracted from related documents of business content  202   c . For example, the business type  201   b  of the business daily processed by a cloud user may be obtained by analyzing content of business documents or content of emails of the cloud user. In other examples, these labels may be extracted according to the business information provided when the cloud tenant  102  or the cloud user  103  signed order contract of cloud resources with the cloud provider  101 , e.g., the name of the company is identified as e-business company. 
     (3) label identifying cloud resource type  201   c  used by the cloud user  103 : for example, type of cloud service: cloud database service, virtual machine service, cloud storage service, mail service, and resource constitution mode of cloud resource: public cloud, private cloud and hybrid cloud. In some examples, such labels may be extracted from cloud resource configuring file  202   d  or cloud resource using log  202   e  of the cloud user  103 . 
     (4) label identifying cloud resource using habit  201   d  of the cloud user  103 : for example, system updating on off days, checking on health status of cloud resources upon starting work every day, using frequency of cloud resources. In some examples, such labels may be extracted from the cloud resource using log  202   e.    
     In the above, exemplary introduction has been made on several aspects of cloud-user profile  201 . It should be noted that, the cloud-user profile  201  shows characteristic in using cloud by a cloud user  103  (or in a perspective of cloud), and these characteristic are the ones appearing in a virtual environment of cloud rather than a real characteristic of the cloud user  103  in a physical environment. For example, some employee in a company offering legal consulting service (also is a cloud user  103 ) has a control authority of the highest level to cloud resources. From a view of cloud, the position label of this employee should be a high-level manager. However, in practical, in such company, the position label of this employee should be a system security maintenance staff. It can be seen that, the employee in a physical environment and the cloud user  103  in a cloud level may have totally different characters. However, in the embodiments of the present disclosure, the characteristic information showing in using cloud by a cloud user  103  is what should be concerned and a cloud management suggestion  109  of the specific cloud user  103  may be obtained by performing analyzing on these characteristic information. Such cloud management suggestion  109  may be pro-active and effective, and fully shows the conjunction application between AI and cloud management. 
     In the above, exemplary explanation has been made on content and obtaining of cloud-user profile  201 . In the following, explanation would be made on the generating  300  of cloud-tenant profile  301  in connection with  FIGS.  3  and  4   . 
     Cloud-tenant profile  301  is abstractive generalization of cloud using behaviors of a cloud tenant  102 . The cloud using behavior of the cloud tenant  102  is different from the cloud using behavior of the cloud user  103  as described above. More particularly, the cloud using behavior of the cloud user  103  may be a kind of individual behavior, while the cloud using behavior of the cloud tenant  102  may be a kind of using behavior in a view from the whole cloud tenant  102 . The cloud using behavior of the cloud tenant  102  may be regarded as being consist of the cloud using behaviors of a plurality of (all of or some of) cloud users  103  of the cloud tenant  102 . Therefore, the cloud using behavior of the cloud tenant  102  may be obtained by generalizing the cloud using behaviors of a plurality of cloud users  103  of the cloud tenant  102 . The cloud-tenant profile  301  is obtained by further generalizing the cloud using behavior of the cloud tenant  102 . Similarly with the cloud-user profile  201 , the cloud-tenant profile  301  may be in a form of label and different label may show characteristics showing on cloud by the cloud tenant  102  in different feature aspects. 
     The cloud-tenant profile  301  may be generated by at least two ways as follows. As shown in  FIG.  3   , which is a schematic diagram showing a generating  300   a  of a cloud-tenant profile  301  of an embodiment of the present disclosure, in the generating  300   a  shown in  FIG.  3   , in some examples, the behavior data in using cloud  202  of a plurality of cloud users  103  of a cloud tenant  102  may be collected, and then the features of a plurality of behavior data in using cloud  202  may be extracted so as to obtain the cloud-tenant profile  301  showing characteristic of the whole cloud using behavior of the cloud tenant  102 . As shown in  FIG.  4   , which is a schematic diagram showing another generating  300   b  of a cloud-tenant profile  301  of an embodiment of the present disclosure, in some examples, the features of the generated cloud-user profile  201  may be extracted so as to obtain the cloud-tenant profile  301 . 
     Furthermore, as shown in  FIG.  3    and  FIG.  4   , in some examples, the cloud-tenant profile  301  may include the following label, and each kind of label may be regarded as a feature aspect. 
     (1) industry label  301   a  identifying industry of cloud tenant  102 : for example, a company may be classified into e-commercial industry, production and manufacture industry, consulting service industry, finance industry, technique developing industry, IT industry, or the like, and different label may be set for different industries. 
     As shown in  FIG.  3   , in a case that authorization has been obtained from a cloud tenant  102  and/or a cloud user  103  to access its business data, the industry label may be extracted from business contents  202   c  (including business documents, e-mails, working logs, or the like) processed by a plurality of cloud users  103  of the company. For example, it may be determined that a company is in a e-commercial business by analyzing the business documents to find that the business documents processed by most cloud users  103  of the company are mostly related to shopping on internet, and thus a label of e-commercial industry may be set. For another example, it may be determined a company is in a finance industry by analyzing the e-mails and business documents processed by the cloud users of the company to find most of the business documents and e-mails of the company are related to stocks and investment information and thus a label of finance industry may be set. 
     In another examples, industry label of the industry  301   a  of a cloud tenant may be extracted from an order contract of cloud resources signed by the cloud tenant  102  or a cloud user  103  with a cloud supplier  101 . For example, the name of the company is identified as a finance company. 
     As shown in  FIG.  4   , as another way for generating the industry label of a cloud tenant  102 , the industry label may be extracted from the label in cloud-user profile  201  of a plurality of cloud users  103 . For example, in the description on the cloud-user profile  201 , the business-type label of the business processed by the cloud user  103  is described and the industry  301   a  of the company may be determined by analyzing the business type label  201   b  of most cloud users  103  of the company. For example, if the business type label  201   b  of most cloud users  103  of the company is technique development, it may be determined that the company is in a technique development industry and an industry label of technique development may be set. Furthermore, the industry label of the cloud tenant  102  may be extracted from the label identifying the cloud user role  201   a  as described above. For example, if the position label of most cloud users  103  of the company is financial analyst, it may be determined that the company is in a finance industry and an industry label of finance may be set. Furthermore, the label identifying cloud resource using habit  201   d  of a cloud user  103  may be used to determine the industry  301   a  of the cloud tenant  102 . For example, if most cloud users  103  of a company is set with a label of cloud resource using habit  201   d  of “updating system on off days”, it may be concluded that the company is possibly in IT industry. 
     (2) label identifying the organization structure  301   b  on cloud of a cloud tenant  102 , including, for example, label identifying whether the company has a vertical managing structure or horizontal managing structure, and which department is the core department among departments of the company and working relationship among departments, or the like. 
     Regarding such label on organization structure, in some examples, in a case that authorization has been obtained from a cloud tenant  102  and/or cloud user  103  to access its business data, such label may be extracted from an approval authority  202   a  of each cloud user  103 , behavior data in using cloud  202  on business procedures or the like by each cloud user  103 . The department information of each cloud user  103  may be obtained by analyzing different positions in business procedure  202   b  by each cloud user  103  and based on such department information, the organization structure  301   b  of the whole company may be extracted. 
     In some other examples, as mentioned above, the cloud platform may provide the cloud user  103  with different roles and/or authorization functions. For example, the cloud platform of Azure of Microsoft may provide different roles of account (e.g., administrator, service administrator, account administrator, cooperation administrator) and different using authorization (e.g., read/write, read-only, donator, or the like). The cloud user  103  may self-define roles and/or authorization according to needs of the company, e.g., administrator of virtual machine, memory read-only person and different roles. The organization structure  301   b  of a cloud tenant  102  may be obtained by performing analysis based on the roles and/or authorization of the cloud users  103 . 
     Furthermore, in some examples, the label of organization structure  301   b  may be directly extracted based on label of each cloud user  103 . As described above, each cloud user  103  is identified with role label  201   a , based on which each department information may be obtained and the organization structure  301  of departments may be further generated. 
     (3) label identifying cloud resource using mode  301   c  of cloud tenant  102 . In some examples, the cloud resource using mode  301   c  may include service types of the cloud services used by a cloud tenant  102  including cloud database service, virtual machine service, cloud storage service and the like, and resource constitution mode of cloud resource: public cloud, private cloud and hybrid cloud. 
     The label of cloud resource using mode  301   c  may be extracted from cloud resource configuring file  202   d  or cloud resource using log  202   e  of a plurality of cloud users  103 . The label of cloud resource using mode  301   c  may be also directly extracted based on label of cloud resource using mode  301   c  of each cloud user  103 . 
     Exemplary description is made on some aspects of cloud-tenant profile  301  in the above. It should be noted that, the cloud-tenant profile  301  mainly shows characteristic of a cloud tenant  102  reflected on cloud (or in a perspective of cloud), and these characteristic are features shown in a virtual environment of cloud and not the real characteristic of cloud tenant  102  in a physical environment. For example, a company is a commercial company in a physical environment, but the company is a company in IT industry not commercial industry from a perspective of cloud, since the company has rented a lot of cloud resources as a cloud tenant  102  for development of commercial platform system. 
     The above various label is merely an exemplary example based on technical idea of the present disclosure. In practice, various label may be defined flexibly according to feature of cloud resources of cloud tenant  102 , cloud user  103  and cloud supplier  101  so as to generate abstract information identifying features in cloud using by cloud users  103  and cloud tenants  102  more effectively. 
     In the above, description has been made on exemplary content and generating ways for cloud-user profile  201  and cloud-tenant profile  301 . 
     Therefore, in the embodiments of the present disclosure, the above cloud-user profile  201  and cloud-tenant profile  301  are both generalized based on behavior data in using cloud  202 , and intelligent and pro-active cloud management suggestion  108  may be provided for cloud tenant  102  and cloud user  101  only based on profile  107  from a perspective of cloud (which adequately shows information on cloud using characteristic). 
     Module for Obtaining Running Status Data of Cloud Resource 
     The module  105  for obtaining running status data of cloud resource may be configured to monitor the running status of cloud resources and generate running status data of cloud resource  108 . As shown in  FIG.  5   , which is a schematic diagram showing generating  500  of running status data of cloud resource  108  of an embodiment of the present disclosure, the running status data of cloud resource  108  refers to the running status data of a cloud resource  501  rented by a cloud tenant  102  during business processing. In some examples, the running status data of cloud resource  108  may include: cloud health status  108   a , safety shielding status  108   b  of a business processing system built on cloud resources, cloud resource load status  108   c , and the like. The cloud resources  502  monitored by the module  105  for obtaining running status data of cloud resource may include: virtual machine  501   a , cloud storage  501   b , business processing system  501   c , and the like. 
     The cloud resources  501  may be located on the side of a cloud supplier  101 , and thus the cloud supplier  101  may perform monitoring on the running status of cloud resources  501 . More particularly, a cloud server of the cloud supplier  101  may monitor the cloud resources  501  and generate running status data of cloud resource  108 . 
     Furthermore, in some examples, as an alternative embodiment, the running status of cloud resources  501  may be monitored on the side of the cloud tenant  102 . Accordingly, the running status data of cloud resource  108  may be generated on the side of the cloud tenant  102 . More particularly, a local computer of a cloud tenant  102  may monitor the cloud resources  501  used by the cloud tenant  102  and generate running status data of cloud resource  108 . 
     Module for Generating Cloud Management Suggestion 
     The module  106  for generating cloud management suggestion may be configured to generate cloud management suggestion  109  according to profile  107  and running status data of cloud resource  108 .  FIG.  6    is a block diagram  600  of a module  106  for generating cloud management suggestion of an embodiment of the present disclosure. 
     In some examples, the module for generating cloud management suggestion may be configured to generate cloud management suggestion  109  by using a Bot (robot) module  601 . In embodiments of the present disclosure, the Bot module  601  may refer to an artificial intelligent (AI) module built on an AI data platform. In some cases, the Bot may be in a form of Chatbot, which may talk with user in a way of conversation by imitating humans, answer questions from users based on the support from a strong AI data platform  602  on the background, and propose various suggestions to users according to conversation with users. 
     The Bot module  601  may access the AI data platform to obtain proposing cloud management suggestion after acquiring the profile  107  and running status data of cloud resource  108 . That is to say, the profile  107  and running status data of cloud resource  108  are input information of the Bot module  601 , and the processing suggestion  108  on cloud management is output information of Bot module  601 . 
     In some examples, to acquire more professional cloud management suggestion  109 , a third-party Bot module  702  may be used to generate cloud management suggestion  109 .  FIG.  7 A  is another block diagram  700 A of a module  106  for generating cloud management suggestion of an embodiment of the present disclosure. 
     In the block diagram  700 A, a primary Bot module  701  may be provided and connected to a plurality of third-party Bot modules  702 . The plurality of third-party Bot modules  702  may have different functions, and each third-party Bot module  702  may be corresponding to a third-party AI platform, respectively. In some examples, the third-party Bot module  702  may include a Bot for monitoring and analyzing virtual-machine, a Bot for scanning and analyzing bugs, and a Bot for providing industry solutions. 
     The primary Bot module  701  may send the acquired profile  107  and running status data of cloud resource  108  to the third-party Bot module  702 , and the third-party Bot module  702  may perform analysis on the profile  107  and running status data of cloud resource  108  to extract information as needed, and then generate processing suggestion  109  on cloud management by means of related third-party AI data platform  703  and send the same to the primary Bot module  701 . The primary Bot module  701  may provide the processing suggestion  109  on cloud management to the cloud users  103  in a pro-active way, after the primary Bot module  701  receives the processing suggestion  109  on cloud management from the third-party Bot module  702 . The above primary Bot module  701  and each third-party Bot module  702  may be provided in a server of cloud supplier  101  in a way of Plug-able Bot module, or provided in a server of a cloud tenant  102  or a computer of a cloud user  103 . It should be noted that, each third-party Bot module  702  may be supported by AI data platform  703  of third-parties, so that the third-party Bot modules  702  may use resources of third-parties to provide intelligent cloud management suggestion  109  according to the profile  107  and running status data of cloud resource  108  sent by the primary Bot module  701 . 
     In the block diagram  700 A, uniform interface standard may be designed and each third-party Bot module  702  may follow that interface standard so as to identify the information formats of the profile  107  and running status data of cloud resource  108  acquired by the primary Bot module  701  and return cloud management suggestion  109  recognizable by the primary Bot module  701  and then the primary Bot module  701  may push the cloud management suggestion  109  to the cloud users  103  in a form of conversation. 
     In view that there are various kinds of third-party Bot modules  702 , in some examples, it may be unnecessary to require the third-party Bot module  702  to follow uniform interface standard. In such case, the primary Bot module  701  may perform the conversion of the interface standards. More particularly, the primary Bot module  701  may convert profile  107  and running status data of cloud resource  108  to a data format which is recognizable to a selected third-party Bot module  702  according to the third-party Bot module  702  after the primary Bot module  701  acquires the profile  107  and running status data of cloud resource  108 , and the primary Bot module  701  may send the profile  107  and running status data of cloud resource  108  in converted data format to the third-party Bot module  702 . The primary Bot module  701  may perform recognition on the cloud management suggestion  109  returned by the third Bot module  702  upon receiving it, and generate a processing suggestion conforming to the format of information of the primary Bot module  701  and push to cloud users  103  in a manner of conversation. 
     In some examples, the primary Bot module  701  may select a suitable third-party Bot module  702  according to the profile  107  and running status data of cloud resource  108  to provide cloud management suggestion  109 . For example, the profile  107  required by a primary Bot module  701  may involve a cloud tenant  102  in IT industry and the cloud resources mainly used by the cloud tenant  102  may be of virtual-machine service. According to the running status data of cloud resource  108 , the business processing system built by this company based on virtual machine has been hacked frequently. Based on such information, the primary Bot module  701  may preferably select a third Bot module  702  providing analysis on network safety to provide cloud management suggestion  109 . 
     Furthermore, in some examples, the primary Bot module  701  may acquire feedback information via conversation with cloud users  103  so as to rank respective third-party Bot module  702 , which may be used as critical for selecting third-party Bot module  702 . 
     In some examples, the structure of the block diagram  700 B in  FIG.  7 B  may be adopted. In block diagram  700 B, a primary Bot module  701  and a third-party Bot module  702  are in a parallel structure, in which the primary Bot module  701  may first receive profile  107  and running status data of cloud resource  108 , and then perform analysis on the profile  107  and the running status data of cloud resource  108  so as to determine whether or not the primary Bot module  701  may be able to generate cloud management suggestion  109 . If so, the primary Bot module  701  may directly access an AI data platform  704  of a cloud supplier corresponding thereto to obtain cloud management suggestion  109 , and push the same to a cloud user  103  in a way of conversation. If it is determined that the primary Bot module  701  cannot generate or is unsuitable for generating cloud management suggestion  109  upon analysis on the profile  107  and running status data of cloud resource  108 , the profile  107  and running status data of cloud resource  108  may be sent to other third-party Bot module  702  capable to generate cloud management suggestion  109 , and the third-party Bot module  702  may acquire cloud management suggestion  109  from the third-party AI data platform  703  corresponding thereto and push the same to a cloud user  103  in a way of conversation. In the above, description has been made on a technical solution for generating cloud management suggestion  109  with Bot module  601 . Based on the above technical solution, the cloud user  103  may preset cloud management templates  801  in advance and the content of cloud management suggestion  109  may be customized or guided through these cloud management templates. As shown in  FIG.  8   , which is still another block diagram  800  of a module  106  for generating cloud management suggestion of an embodiment of the present disclosure, compared with diagram  600 , in the diagram  800 , a cloud management templates  801  may be added and may recite preset management matters and/or related parameters of management matters therein. 
     As shown in  FIG.  9   , which is a block diagram  900  showing content of cloud management templates  801  of an embodiment of the present disclosure, in the block diagram  900 , the cloud management templates  801  may make pre-settings on DDoS shielding  802 , cloud health detection  803  and maintenance schedule  804  and the like. For example, regarding DDoS shielding  802 , the settings may include: confidence parameter is 0.8, which means the alert should be triggered upon an event has reached the confidence parameter; target range is all cloud tenants, which means DDoS shielding should be monitored with respect to cloud resources of cloud tenants; type of target resources is any type, which means DDoS shielding should be monitored with respect to all types of resources. 
     In a case that cloud management templates  801  are preset, cloud management suggestion  109  may be generated according to profile  107 , running status data of cloud resource  108 , and cloud management templates  801 . In some examples, the cloud management templates  801  may be parameter settings for Bot module  601  (e.g., confidence parameter against predicted threatens, and alert processing suggestion would be made only when the confidence parameter is passed), or managing terms requiring attention of Bot module  601  (e.g., cloud health should be paid more attention to). 
     In some examples, cloud management templates  801  may be in a form of program script, or set in association with primary Bot module  701  or third-party Bot module  702 , so as to make adjustment to the running of programs of the primary Bot module  701  or other third-party Bot module  702 . 
     The module  106  for generating cloud management suggestion may provide cloud management suggestion  109  to cloud users  103 , after generating the same, so as to guide the cloud users on cloud managing operations. In some examples, cloud management suggestion  109  may be provided to cloud users  103  in a pro-active way. For example, conversation window would be popped up on the computer or mobile terminal of a cloud user  103  so as to enter a conversation-interactive mode with the cloud users. The conversation may be initiated by the Bot module  601  in the block diagram  600  or the primary Bot module  701  in the block diagram  700 A or  700 B. The conversation cited herein may refer to a conversation, which is actively initiated according to the monitoring on cloud resource running status, instead of passively waiting for instructions input by cloud users  103  or acquiring cloud management suggestions in other ways. Such mechanism of providing cloud management suggestion  109  to cloud users  103  in a pro-active way significantly shows the technical idea of combining cloud management with AI. 
     In some examples, cloud management suggestion  109  may include: one or more information among alert processing suggestion with respect to cloud management, optimizing processing suggestion, predicted processing suggestion and the like. 
     Alert processing suggestion: to find problems or risks in using of cloud resources based on running status data of cloud resource  108  and profile  107 , and therefore this information may provide processing suggestion for solving such problems or risks. 
     Optimizing processing suggestion: to find optimizable parts in using cloud resources based on running status data of cloud resource  108  and profile  107 , so that the cloud resources may be used more efficiently, and therefore, this information may provide processing suggestion on optimizing using of cloud resources. 
     Predicted processing suggestion: to predict possible problems in the future based on running status data of cloud resource  108  and profile  107 , so as to provide processing suggestion on states possibly occurring in the future, e.g., how to adjust the using of cloud resources. 
     In some examples, the conversation initiated by the primary Bot module  701  may be dynamically adjusted according to information input by cloud users  103 . After the primary Bot module  701  provides cloud management suggestion  109  to cloud users in a way of conversation, the primary Bot module may further acquire information input by cloud users  103  during subsequent conversation, and acquire new cloud management suggestion  109  according to profile  107 , running status data of cloud resource  108  and input information during conversation. During obtaining new cloud management suggestion  109 , the primary Bot module  701  may adjust the selected third-party Bot module  702  according to information input by cloud users  103 , so as to provide further processing suggestion more conforming needs of cloud users  103 . 
     More particularly, during above conversation, input information during conversation may include one or more of context information of conversation, voice information of cloud user  103 , emotion information of cloud user  103 , environment information of cloud user  103 , time information. That is to say, during conversation, not only context information input in a form of characters may be acquired, but information which is available via terminal of cloud user  103  or other sensors may be also acquired, so that determination may be made more efficiently on needs of cloud users  103  so as to provide more effective cloud management suggestion  109 . 
     Embodiments of Applications 
     In the above, description is made on functions and implementation of each part of intelligent cloud management. In the following, further explanation would be made on technical solution of intelligent cloud management with embodiments of specific applications. 
     In the following, description would be made on technical solution of embodiments of the present disclosure with an embodiment.  FIG.  10    is an application scenario  1000  of an embodiment of the present disclosure. With an employee  1070  named “John” (cloud user  103 ) as an example, John is hired by an e-commercial company located in Shenzhen (cloud tenant  102 ), and his job is mainly development and maintenance with virtual machine as cloud resource, and thus performance of virtual machine is highly required. With respect to cloud user  103  such as John, cloud management suggestion  109  may be generated in the following four aspects. 
     (1) Profile  107   
     As Shown in the Drawings, Behavior Data in Using Cloud of John May be Generalized as six pieces of label of cloud-user profile  201 : “e-commerce”  1071  (label identifying industry type), “Shenzhen”  1072  (label identifying working location), “development and maintenance”  1073  (label identifying job type), “virtual machine”  1074  (label identifying specific cloud resource being used), “SQL Azure”  1075  (label identifying type of cloud service), “Performance”  1076  (label identifying requirement on cloud resources). More particularly, SQL Azure is relation database service running cloud computation built on Windows Azure cloud operation system. In the above label as profile  107 , there is part of label is also as label of cloud-tenant profile  401  of the company (as cloud tenant) where John is located, e.g., “e-commerce”  1071  and “Shenzhen”  1072 . In the present embodiment, it may be also regarded that the cloud management suggestion  109  is made based on cloud-user profile  201  and cloud-tenant profile  301 . 
     (2) Bot Module  601   
     According to profile of John (e.g., “e-commerce”  1071 , “development and maintenance”  1073 , “performance”  1076 , and “SQL Azure”  1075 ), the primary Bot module  701  may select and use the following kinds of third-party Bot module  702 . 
     Monitoring virtual machine and measure SQL database  702   a : for monitoring virtual machine and measuring performance index of SQL database according to running status data of cloud resource (such as loading status of virtual machine, read/write speed of SQL database, or the like), and providing configuration management suggestion on virtual machine and SQL database in connection with profile (e.g., attention has been paid to “performance”  1076  and the job type is “development and maintenance”  1073 ); 
     DDos (Distributed Denial of Service) analysis  702   b : for performing analysis on DDoS attacking according to running status data of cloud resource (records of attacks blocked by firewall), and providing suggestions on protection strategy for e-commerce in connection with profile  107  of John (e.g., industry label of “e-commerce”  1071 ); 
     Machine learning based on cloud using  702   c : for performing machine learning on running status data of cloud resource (running status data of cloud resource during each period in the past one year) and profile  107  of John (e.g., industry label of “e-commerce”  1071  and label of used cloud service of “SQL Azure”  1075 ) to generate prediction data on cloud resource running status for a period in the future, and generate management suggestion for making adjustment on cloud resources based on such prediction data. On the other hand, a third-party Bot module  702  having rich knowledge on some industry may be generated by big data analysis on behavior data in using cloud  202  of such industry. 
     (3) Cloud Management Templates  801   
     John may customize cloud management templates  801  according to his needs, which may include templates of the following two types: 
     DDos shielding  802 , which may define shielding level, programs to be monitored preferably, or the like; 
     Cloud health detection  803 , which may define time and frequency and regions, which need more attention to be paid to, for performing cloud health detection. 
     (4) Running Status Data of Cloud Resource  108  Acquired by Monitoring 
     Running status data of cloud resource  108  may include various kinds of logs such as virtual machine loading ratio  1081 , measuring data of SOL Azure  1082 , blocking records by firewall  1083 . These running status data of cloud resource  108  may be used as basis for the Bot module  601  to generate cloud management suggestion in combination with profile  107  and cloud management templates  801 . 
     Cloud management suggestion  109  in the following aspects may be generated based on the technical contents in the above four aspects and be pushed to John in a way of pro-active conversation: 
     (1) alert suggestion  1091 : a third-party Bot module  702  may extract measuring data of SQL Azure by analysis on running status data of cloud resource, and with analysis on such measuring data, it is found that, there are several request blocked by the firewall in the past few hours. Therefore, a conversation may be actively initiated to suggest John checking whether or not the requests blocked by the firewall is incorrect operations or invasion threats. 
     (2) optimizing suggestion  1092 : a third-party Bot module  702  may perform analysis on data of loading status of virtual machine and find that the CPU of the virtual machine is in a high loading ratio of 70%-80% on weekend. Therefore, a conversation may be actively initiated to suggest John creating a script program to automatically increase loading capacity of virtual machine on weekend and automatically decrease loading capacity of virtual machine after weekend. 
     (3) prediction suggestion  1093 : a third-party Bot module  702  may perform analysis and find that the company where John is in is labeled with an industry label of “e-commerce”  1071 , and predict that there would be an order rush from November to December based on big data analysis on industry of “e-commerce”  1071  by the third-party Bot module  702 . Therefore, John may be suggested maintaining current loading capacity of virtual machine and increasing performance level of SQL Azure so as to deal with the potential bottleneck of performance. 
     Upon obtaining suggestions in the above three-aspects, John may make effective management on cloud resources being used and solve problems and risks in cloud resources more effectively, optimize configuration of cloud resources, and make deployment of cloud resources against possible circumstances in the future in advance. 
     These processing suggestion may be pro-actively proposed to John without deep understanding of John on running of cloud resources. It may be only necessary for John to perform operations according to cloud management suggestions provided in conversation and greatly decrease difficulty of cloud management. 
     Exemplary Embodiments 
     In the above, detailed description has been made on technical solution of intelligent cloud management with application  1000 . In the following further explanation would be made on processing  1100  of intelligent cloud management of embodiments of the present disclosure. As shown in  FIG.  11   , which is a schematic diagram showing processing  1100  of intelligent cloud management of an embodiment of the present disclosure, the processing  1100  may include: 
     S 101 : acquiring profile  107  based on behavior data in using cloud  202 . As mentioned above, the profile  107  may be cloud-user profile  201  of cloud tenant, cloud-tenant profile  301 , or combination thereof. 
     In some examples, the cloud-user profile  201  may be generated as follows: acquiring behavior data in using cloud  202  of a cloud user  103 , generating the cloud-user profile  201  according to the behavior data in using cloud  202  of the cloud user  103 . 
     In some examples, cloud-tenant profile  301  may be generated as follows: acquiring behavior data in using cloud  202  of a plurality of cloud users  103 , generating cloud-tenant profile  301  according to behavior data in using cloud  202  of a plurality of cloud users  103 . 
     In some examples, cloud-tenant profile  301  may be also generated as follows: acquiring cloud-user profile  201  of a plurality of cloud users  103 , and generating cloud-tenant profile  301  according to cloud-user profile  201  of a plurality of cloud users  103 . 
     S 102 : acquiring running status data of cloud resource  108 . More particularly, cloud resource running status may be monitored so that running status data of cloud resource  108  may be obtained. 
     It should be noted that flow chart is shown in drawings for illustration, but there is no limit on sequence of the above S 101  and S 102 , and these two steps may be performed in parallel or sequentially. 
     S 103 : generating cloud management suggestion  109  according to profile  107  and running status data of cloud resource  108 . In some examples, cloud management suggestion  109  may include one or more of alert cloud management suggestion, optimizing cloud management suggestion, prediction cloud management suggestion. 
     In some examples, this step may be performed by a third-party Bot module  702 . More particularly, such step may include: sending profile  107  and running status data of cloud resource  108  to the third-party Bot module  702  and obtaining cloud management suggestion  109  returned by the third-party Bot module  702 . 
     Furthermore, in some examples, during generating cloud management suggestion  109  by a third-party Bot module  702 , the following steps may be further included: selecting a matched third-party Bot module  702  according to profile  107  and running status data of cloud resource  108  and sending the profile  107  and running status data of cloud resource  108  to that third-party Bot module  702 . 
     Furthermore, the processing  1100  may further include: receiving feedback information of a cloud user  103 , and performing ranking on the plurality of third-party Bot modules  702  according to the feedback information. 
     In some examples, the above processing  1100  may further include: acquiring preset cloud management template  801 , which may be preset by a cloud user  103 . Accordingly, the above step S 103  may further include: generating cloud management information  109  according to the profile  107 , running status data of cloud resource  108  and the preset cloud management suggestion  109 . 
     More particularly, in some examples, preset management matters and/or related parameters of management matters may be recorded in the preset cloud management template  801 . 
     S 104 : pushing cloud management suggestion to a cloud user  103  in a way of conversation. 
     In some examples, during conversation, input information of the cloud user  103  may be obtained, and new cloud management suggestion  109  may be obtained according to profile  107 , running status data of cloud resource  108  and input information of cloud user  103 , and then the new cloud management suggestion  109  may be pushed to the cloud user  103 . 
     More particularly, the input information of cloud user  103  may include one or more of character information input by a cloud user  103 , voice information input by a cloud user  103 , and emotion information of cloud user  103 , environment information where a cloud user  103  is located, time information for responding conversation by a cloud user  103 . 
     Implementation of each processing operation in the above steps has been detailed descripted in the above and may be similarly applied to the above steps. 
     Examples of Implementation 
     As shown in  FIG.  12   , which is a block diagram  1200  of an intelligent cloud management device of an embodiment of the present disclosure, the intelligent cloud management device may include: module  104  for acquiring profile, module  105  for acquiring running status data of cloud resource, and module  106  for generating cloud management suggestion. 
     More particularly, the module  104  for acquiring profile may be configured to acquire profile based on behavior data in using cloud; the module  105  for acquiring running status data of cloud resource may be configured to acquire running status data of cloud resource  108 ; the module  106  for generating cloud management suggestion may be configured to generate cloud management suggestion  109  at least according to profile  107  and running status data of cloud resource  108 . 
     The above intelligent cloud management device may be provided in a server of cloud supplier  101 , or in a server of cloud tenant or in a computer of a cloud user  103 . 
     Furthermore, in some examples, each component or module related in the above  FIG.  1    to  FIG.  10    and  FIG.  12   , such as module  104  for acquiring profile, module  105  for acquiring running status data of cloud resource, module  106  for generating cloud management suggestion, Bot module  601 , primary Bot module  701 , third-party Bot module  702 , and the like, and one or more steps in the flow chart shown in  FIG.  11    may be implemented by software, hardware, or in combination of software and hardware. For example, the above component or module and one or more steps may be implemented in system on chip (SoC). Soc may include: integrated circuit chip, including one or more of processing unit (such as center processing unit (CPU), micro controller, micro processing unit, digital signal processing unit (DSP) or the like), memory, one or more communication interface, and/or other circuit for performing its function and alternative embedded firmware. 
     As shown in  FIG.  13   , which is a block diagram of an electric apparatus  1300  of an embodiment of the present disclosure, the electric apparatus  1300  may include: a memory  1301  and a processor  1302 . 
     The memory  1301  may be configured to store programs. In addition to the above programs, the memory  1301  may be configured to store other data to support operations on the electric apparatus  1300 . The examples of these data may include instructions of any applications or methods operated on the electric apparatus  1300 , contact data, phone book data, messages, pictures, videos, and the like. 
     The memory  1301  may be implemented by any kind of volatile or nonvolatile storage device or their combinations, such as static random access memory (SRAM), electronically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk memory, or optical disk. 
     The memory  1301  may be coupled to the processor  1302  and contain instructions stored thereon. The instructions may cause the electric apparatus to perform operations upon being executed, the operations may include: acquiring profile  107  based on behavior data in using cloud  202 ; acquiring running status data of cloud resource  108 ; generating cloud management suggestion  109  at least according to profile  107  and running status data of cloud resource  108 . Furthermore, the above operations may include pushing cloud management suggestion  109  to a cloud user  103  in a way of conversation. Furthermore, during conversation, the following steps may be included: acquiring input information of a cloud user  103 ; acquiring new cloud management suggestion  109  according to profile  107 , running status data of cloud resource  108  and input information of the cloud user  103 ; and providing the new cloud management suggestion  109  to the cloud user  103 . 
     In some examples, the above profile  107  may include cloud-user profile  201 . Then, the acquiring profile based on behavior data in using cloud  202  may include: acquiring behavior data in using cloud  202  of a cloud user  103 ; generating cloud-user profile  201  according to behavior data in using cloud  202  of the cloud user  103 . 
     In some other examples, the above profile  107  may include cloud-tenant profile  301 . Then the acquiring profile  107  based on behavior data in using cloud  202  may include: acquiring cloud-user profile  201  of a plurality of cloud users  103 ; generating cloud-tenant profile  301  according to cloud-user profile  201  of a plurality of cloud users  103 . 
     Furthermore, in some examples, the generating cloud management suggestion  109  according to profile  107  and running status data of cloud resource  108  may include: sending profile  107  and running status data of cloud resource  108  to a third-party Bot module  702 , and acquiring cloud management suggestion  109  returned by the third-party Bot module  702 . 
     The above operations have been detailed descripted in the above in the embodiments of the above methods and apparatus, and may be similarly applied to electric apparatus  1300 . That is, the operations mentioned in the above embodiments may be recorded in memory  1301  in program and be performed by processor  1302 . 
     Furthermore, as shown in  FIG.  13   , the electric apparatus  1300  may further include: a communication unit  1303 , a power supply unit  1304 , an audio unit  1305 , a display unit  1306 , chipset  1307 , and other units. Only part units are exemplarily shown in  FIG.  13    and it is obvious to one skilled in the art that the electric apparatus  1300  only includes the units shown in  FIG.  13   . 
     The communication unit  1303  may be configured to facilitate wireless or wired communication between the electric apparatus  1300  and other apparatuses. The electric apparatus may be connected to wireless network based on communication standard, such as WiFi, 2G, 3G, or their combination. In an exemplary example, the communication unit  1303  may receive radio signal or radio related information from external radio management system via radio channel. In an exemplary example, the communication unit  1303  may further include near field communication (NFC) module for facilitating short-range communication. For example, the NFC module may be implemented with radio frequency identification (RFID) technology, Infrared data association (IrDA) technology, ultra wideband (UWB) technology, Bluetooth (BT) technology and other technologies. 
     The power supply unit  1304  may be configured to supply power to various units of the electric apparatus. The power supply unit  1304  may include a power supply management system, one or more power supplies, and other units related to power generation, management, and allocation. 
     The audio unit  1305  may be configured to output and/or input audio signals. For example, the audio unit  1305  may include a microphone (MIC). When the electric apparatus in an operation mode, such as calling mode, recording mode, and voice recognition mode, the MIC may be configured to receive external audio signals. The received audio signals may be further stored in the memory  1301  or sent via the communication unit  1303 . In some examples, the audio unit  1305  may further include a speaker configured to output audio signals. 
     The display unit  1306  may include a screen, which may include liquid crystal display (LCD) and touch panel (TP). If the screen includes a touch panel, the screen may be implemented as touch screen so as to receive input signal from users. The touch panel may include a plurality of touch sensors to sense touching, sliding, and gestures on the touch panel. The touch sensor may not only sense edges of touching or sliding actions, but also sense period and pressure related to the touching or sliding operations. 
     The above memory  1301 , processor  1302 , communication unit  1303 , power supply unit  1304 , audio unit  1305  and display unit  1306  may be connected with the chip set  1307 . The chip set  1307  may provide interface between the processor  1302  and other units of the electric apparatus  1300 . Furthermore, the chip set  1307  may provide interface for each unit of the electric apparatus  1300  to access the memory  1301  and communication interface for accessing among units. 
     Example Clauses 
     A. A method, including: acquiring profile based on behavior data in using cloud; acquiring running status data of cloud resource; and generating cloud management suggestion at least according to the profile and the running status data of cloud resource. 
     B. The method according to paragraph A, wherein the profile may include cloud-tenant profile, and the acquiring profile based on behavior data in using cloud may include: acquiring behavior data in using cloud of a plurality of cloud users; and generating the cloud-tenant profile according to the behavior data in using cloud of the plurality of cloud users. 
     C. The method according to paragraph A, wherein the profile may include cloud-user profile, and the acquiring profile based on the behavior data in using cloud may include: acquiring behavior data in using cloud of a cloud user; and generating the cloud-user profile according to the behavior data in using cloud of the cloud user. 
     D. The method according to paragraph A, wherein the profile may include cloud-tenant profile, and the acquiring profile based on the behavior data in using cloud may include: acquiring cloud-user profile of a plurality of cloud users; and generating the cloud-tenant profile according to the cloud-user profile of the plurality of cloud users. 
     E. The method according to paragraph A, wherein the generating cloud management suggestion at least according to the profile and the running status data of cloud resource may include: sending the profile and the running status data of cloud resource to a third-party Bot module, and acquiring the cloud management suggestion returned by the third-party Bot module. 
     F. The method according to paragraph E, wherein the sending the profile and the running status data of cloud resource to a third-party Bot module may include: selecting a third-party Bot module from a plurality of third-party Bot modules according to the profile and the running status data of cloud resource, and sending the profile and the running status data of cloud resource to the selected third-party Bot module. 
     G. The method according to paragraph F, further including: receiving feedback information from a cloud user, and performing ranking on the plurality of third-party Bot modules according to the feedback information. 
     H. The method according to paragraph A, further including: pushing the cloud management suggestion to a cloud user in conversation. 
     I. The method according to paragraph H, further including: acquiring input information of the cloud user during conversation; acquiring another cloud management suggestion according to the profile, the running status data of cloud resource, and the input information of the cloud user; and 
     pushing the another cloud management suggestion to the cloud user. 
     J. The method according to paragraph I, wherein the input information of the cloud user may include one or more of: word information input by the cloud user, voice information input by the cloud user, emotion information of the cloud user, environment information of environment where the cloud user is in, time information on period for the cloud user to response to the conversation. 
     K. The method according to paragraph A, further including: acquiring a preset cloud management template; the generating cloud management suggestion at least according to the profile and the running status data of cloud resource may include: generating cloud management suggestion according to the profile, the running status data of cloud resource and the preset cloud management template. 
     L. The method according to paragraph K, wherein preset management matters and/or related parameters of management matters are recorded in the preset cloud management template. 
     M. The method according to paragraph A, wherein the cloud management suggestion may include: one or more of alert cloud management suggestion, optimizing cloud management suggestion, and prediction cloud management suggestion. 
     N. An electric apparatus, including: a processing unit; and a memory, coupled to the processing unit and containing instructions stored thereon, the instructions cause the electric apparatus to perform operations upon being executed by the processing unit, the operations may include: acquiring profile based on behavior data in using cloud; acquiring running status data of cloud resource; and generating cloud management suggestion at least according to the profile and the running status data of cloud resource. 
     O. The electric apparatus according to paragraph N, wherein the profile may include a cloud-user profile, and the acquiring profile based on behavior data in using cloud may include: acquiring behavior data in using cloud of a cloud user; and generating the cloud-user profile according to the behavior data in using cloud of the cloud user. 
     P. The electric apparatus according to paragraph N, wherein the profile may include cloud-tenant profile, and the acquiring profile based on the behavior data in using cloud may include: acquiring cloud-user profile of a plurality of cloud users; and generating the cloud-tenant profile according to the cloud-user profile of the plurality of cloud users. 
     Q. The electric apparatus according to paragraph N, wherein the generating cloud management suggestion at least according to the profile and the running status data of cloud resource may include: sending the profile and the running status data of cloud resource to a third-party Bot module, and acquiring the cloud management suggestion returned by the third-party Bot module. 
     R. The electric apparatus according to paragraph N, wherein the operations further include: pushing the cloud management suggestion to a cloud user in conversation. 
     S. The electric apparatus according to paragraph R, wherein the operations further include: acquiring input information of the cloud user during conversation; acquiring another cloud management suggestion according to the profile, the running status data of cloud resource, and the input information of the cloud user; and providing the another cloud management suggestion to the cloud user. 
     T. A device, including: a module for acquiring profile configured to acquire profile based on behavior data in using cloud; a module for acquiring running status data of cloud resource configured to acquire running status data of cloud resource; and a module for generating cloud management suggestion configured to generate cloud management suggestion at least according to the profile and the running status data of cloud resource. 
     It would be obvious to one skilled in the art that, all or part of steps for implementing the above embodiments may be accomplished by hardware related to programs or instructions. The above program may be stored in a computer readable storing medium. Such program may perform the steps of the above embodiments upon being executed. The above storing medium may include: ROM, RAM, magnetic disk, or optic disk or other medium capable of storing program codes. 
     It should be noted that the foregoing embodiments are merely used to illustrate the technical solution of the present disclosure, and not to limit the present disclosure. Although the present disclosure has been described in detail with reference to the foregoing embodiments, one skilled in the art would understand that the technical solutions recited in the foregoing embodiments may be modified or all or a part of the technical features may be replaced equally. These modifications and replacements are not intended to make corresponding technical solution depart from the scope of the technical solution of embodiments of the present disclosure.