Cloud resource management platform, cloud resource management method, equipment and storage medium

Abstract

The invention discloses a cloud resource management platform, a cloud resource management method, equipment and a storage medium, and relates to the technical field of resource management, the cloud resource management platform comprises a user demand application module used for obtaining a cloud resource application request of a target user; the user demand management module is used for carrying out application limit query and order grading on the cloud resource application request to obtain a request approval type; the user demand approval module is used for performing demand approval on the cloud resource application request according to the request approval type to obtain an application approval result; and the cloud resource delivery management module is used for performing resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, and creating a cloud resource instance corresponding to the cloud resource application request so as to perform resource delivery management.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of resource management, and particularly relates to a cloud resource management platform, a cloud resource management method, equipment and a storage medium. BACKGROUND

[0002] With the rapid development and wide application of cloud computing technology, as an important part of enterprise informatization construction, private cloud has become an important means for many organizations to realize flexible resource allocation and improve IT service efficiency. As a key link in private cloud construction, private cloud resource management is directly related to the rational allocation of resources, use efficiency and operating cost. Especially in the case of limited resources, how to efficiently manage private cloud resources has become an important issue that enterprise IT departments must solve. SUMMARY

[0003] The main purpose of the present application is to provide a cloud resource management platform, a cloud resource management method, equipment and a storage medium, which aims to efficiently manage private cloud resources in the case of limited resources.

[0004] To achieve the above purpose, the present application provides a cloud resource management platform, which comprises:

[0005] A user demand application module is configured to obtain a cloud resource application request of a target user.

[0006] A user demand management module is configured to perform application restriction query and order classification on the cloud resource application request, and obtain a request approval type.

[0007] A user demand approval module is configured to perform demand approval on the cloud resource application request according to the request approval type, and obtain an application approval result.

[0008] A cloud resource delivery management module is configured to perform resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, create a cloud resource instance corresponding to the cloud resource application request, and perform resource delivery management.

[0009] In an embodiment, the cloud resource service access module is further configured to build a front-end form component corresponding to a cloud resource service provided by a cloud service provider, and configure the cloud resource service through the front-end form component to realize quick access of the cloud resource service.

[0010] In an embodiment, the component package management module is further configured to locally store the front-end form component built by the cloud resource service access module, and find a component package in the local storage according to component package information corresponding to the cloud resource application request, so as to enable the target user to perform request configuration.

[0011] In an embodiment, a resource planning management module is further included, configured to perform resource planning analysis according to the cloud resource application request of the target user and the resource planning configuration rule corresponding to the target user, and detect whether the target user meets the resource application authorization condition.

[0012] In an embodiment, a data storage module is further included, configured to integrate and store resource management process information corresponding to the cloud resource instance through a quota data field, an approval data field, a delivery data field and an extension data field.

[0013] To achieve the above object, the present application provides a cloud resource management method, which comprises:

[0014] obtaining a cloud resource application request of a target user;

[0015] performing application restriction query and order classification on the cloud resource application request to obtain a request approval type;

[0016] performing demand approval on the cloud resource application request according to the request approval type to obtain an application approval result;

[0017] performing resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, creating a cloud resource instance corresponding to the cloud resource application request, and performing resource delivery management.

[0018] In an embodiment, after obtaining the cloud resource application request of the target user, the following steps are included:

[0019] obtaining a resource planning configuration rule corresponding to the target user;

[0020] determining a resource application restriction condition corresponding to the target user according to the resource planning configuration rule, and performing matching analysis on the resource application restriction condition and the cloud resource application request;

[0021] If the resource application restriction condition and the cloud resource application request match successfully, it is determined that the target user meets the resource application authorization condition, and the steps of performing application restriction query and order classification on the cloud resource application request to obtain a request approval type are executed.

[0022] In an embodiment, the step of performing application restriction query and order classification on the cloud resource application request to obtain a request approval type comprises:

[0023] determining that the target user is not in a preset blacklist according to user information in the cloud resource application request;

[0024] determine the resource amount in the cloud resource application request, the order belonging organization, and the index data, perform order grading on the cloud resource application request, and determine the order level corresponding to the cloud resource application request;

[0025] According to the order level, a request approval type corresponding to the cloud resource application request is configured. In addition, to achieve the above-mentioned purpose, the present application also proposes a cloud resource management device, which comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the cloud resource management method as described above.

[0026] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and the storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the cloud resource management method as described above.

[0027] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the steps of the cloud resource management method as described above.

[0028] The present application provides a cloud resource management platform and a cloud resource management method, device and storage medium, the cloud resource management platform comprises: a user demand application module for obtaining a cloud resource application request of a target user; a user demand management module for performing application restriction query and order grading on the cloud resource application request to obtain a request approval type; a user demand approval module for performing demand approval on the cloud resource application request according to the request approval type to obtain an application approval result; and a cloud resource delivery management module for performing resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, creating a cloud resource instance corresponding to the cloud resource application request, and performing resource delivery management, so that the user only needs to submit once, and the system automatically completes the restriction verification, grading and approval, significantly reducing manual intervention. At the same time, the approval type is determined by the rule engine in real time, avoiding human error, improving the approval speed and consistency, and triggering resource scheduling and instance creation immediately after the approval is passed, shortening the delivery cycle and improving the user experience. Among them, the whole process data is connected, the approval result directly drives the resource delivery, eliminates the information gap, reduces the communication cost, at the same time, the interface and data structure are unified, the subsequent new cloud services do not need to change the approval logic, and can be put into operation only by configuration, with strong expansibility. BRIEF DESCRIPTION OF DRAWINGS

[0029] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the application.

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, for those skilled in the art, the other drawings can be obtained based on these drawings without any creative effort.

[0031] Figure 1 One of the system module architecture diagrams provided by the cloud resource management platform of the present application;

[0032] Figure 2 The scenario implementation example diagram provided by the cloud resource management method of the present application regarding demand application;

[0033] Figure 3 The scenario implementation example diagram provided by the cloud resource management method of the present application regarding shopping cart;

[0034] Figure 4 The private cloud resource management system architecture diagram provided by the cloud resource management method of the present application;

[0035] Figure 5 The scenario implementation example diagram provided by the cloud resource management method of the present application regarding service access management;

[0036] Figure 6 The scenario implementation example diagram provided by the cloud resource management method of the present application regarding componentized architecture;

[0037] Figure 7 The flowchart provided by the cloud resource management method of the present application embodiment one;

[0038] Figure 8 The brief flowchart example diagram provided by the cloud resource management method of the present application;

[0039] Figure 9 The second system module architecture diagram provided by the cloud resource management platform of the present application;

[0040] Figure 10 The scenario implementation example diagram provided by the cloud resource management method of the present application regarding user map;

[0041] Figure 11 The device structure schematic diagram of the hardware running environment involved in the cloud resource management method in the embodiments of the present application.

[0042] The object implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0043] It should be understood that the specific embodiments described herein are merely intended to explain the technical solutions of the present application, and are not intended to limit the present application.

[0044] In order to better understand the technical solutions of the present application, the following will be described in detail in combination with the drawings of the specification and specific embodiments.

[0045] It should be noted that the execution subject of the present embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a big data service platform, a cloud resource management system, etc. capable of realizing the above functions. The present embodiment and the following embodiments will be described below taking the cloud resource management system as an example.

[0046] Based on this, the present embodiment provides a cloud resource management platform, which is described in detail with reference to Figure 1 , Figure 1 One of the system module architectures provided by the cloud resource management platform of the present application.

[0047] In the present embodiment, the cloud resource management platform comprises a user demand application module, a user demand management module, a user demand approval module and a cloud resource delivery management module, wherein,

[0048] The user demand application module is configured to obtain a cloud resource application request of a target user.

[0049] It should be noted that the cloud resource application request refers to a complete application record submitted by the target user through a front-end form on a tenant portal or a demand application home page, which at least contains the applied cloud resource service type, resource specification, quantity, expected use duration, belonging environment identifier, business use description and target user identity identifier.

[0050] It should be further noted that the purpose of this module is to integrate the information scattered in multiple systems and repeatedly filled in the past into one-time interaction, so as to reduce the user operation cost and ensure that the subsequent process can obtain structured raw data.

[0051] In addition, the user demand application module is a functional module provided by the resource management platform for user application. The user can view the applied demand order on the demand application home page, and he can also apply for new demand or perform some operations on the applied order, such as order storage, quota return and export, etc. Among them, the user can apply for different types of resources according to his own scene in the demand application module, such as monthly demand, large demand and temporary demand. However, whether the user can apply for large demand and temporary demand for specific cloud service resources is determined by service access configuration.

[0052] For example, the user clicks the monthly demand application button to enter the monthly demand application form, the left side displays all cloud services accessed by the current resource management platform, and the right side form is the application form included in the front-end component developed by each cloud service provider. The user confirms the required resources, fills out the form, and then adds the demand order to the shopping cart. In the shopping cart, the user can view the newly submitted demand, and by selecting one or more orders in the shopping cart, the selected orders can be submitted for approval. The order status and information can be viewed on the home page list, which can be referred to Figure 2 and Figure 3 .

[0053] Specifically, in an embodiment, cloud resource application requests can be submitted through three scenario entrances of monthly demand, temporary demand, or large demand. Then, the system automatically adds corresponding verification rules according to the selected scenario and temporarily stores multiple orders in the "shopping cart" block before submitting them collectively.

[0054] For example, a team developer logs in to the tenant portal and selects the "monthly demand" entrance. The system displays the "domestic virtual machine service" front-end component that has been accessed. The developer fills in "4 cores, 8 GB, 50 GB storage, 3 months of usage" and clicks "add to cart". Then, the developer selects the "domestic object storage" component and fills in 500 GB capacity. Finally, two cloud resource application requests are generated and submitted together.

[0055] Additionally, reference can be made to Figure 4 , Figure 4 The private cloud resource management system architecture diagram provided by the cloud resource management method of the present application. The platform provides three types of users. The first type is ordinary users who submit cloud service resource demands through the tenant portal, form orders, and after the orders are approved and the resources are allocated, quickly jump to the corresponding resource delivery page to create cloud service instances. The second type is cloud service provider users who develop front-end components for specific services based on the basic components provided by the resource management platform, upload them to the resource management platform, and then access the resource management system through configuration. After completing the corresponding configuration, the users can develop and use the application. The third type of user is the operation and management personnel and the resource administrators of each organization and team. The resource administrators can manage the resource demands of their organization and team through the resource management platform, plan and apply for resources, and perform other operations. The operation personnel perform scenario-based operation on different resource demands through the configuration capability of the resource management platform, and on the other hand, review and allocate the resources applied by the users.

[0056] In addition, since the resource requirements can involve different environments, such as the resources of the development environment, the resources of the test environment, and the resources of the production environment, the resource management platform needs to obtain the resource base information of different environments for user selection. For this scenario, the resource management platform adopts separate front-end and back-end deployment. When the user selects the environment to which the resource belongs in the application requirement, the system obtains the data by forwarding the corresponding request to the specified environment through the environment identifier in the gateway service.

[0057] The user requirement management module is configured to perform application restriction query and order grading on the cloud resource application request to obtain a request approval type.

[0058] It should be noted that the application restriction query refers to real-time checking by the system according to preset rules whether the target user is on the blacklist, whether the applied resource exceeds the team quota, whether the filled specification is disabled, and the like. The order grading refers to dividing the request into three levels of standard, high standard, and non-standard by using a rule engine according to the resource quantity, the organization to which the order belongs, index data, and the like.

[0059] It should be further noted that the request approval type refers to a specific approval process identifier mapped according to the order level and the current operation strategy, such as “team monthly review”, “non-standard requirement review”, or “automatic pass”.

[0060] More specifically, since the operation scenario of the private cloud service resource has the characteristics of high complexity and frequent changes, in order to adapt to such characteristics, the resource requirement management platform develops a set of dynamic configuration management functions based on a rule engine, so that the operation can modify the rules in a timely manner and switch to a new operation scenario. The rule engine is a component embedded in an application program, which aims to separate business decisions from the code. It makes decisions by accepting data input, interpreting business rules, and making decisions according to these rules, thereby realizing centralized management and dynamic modification of business logic. For example, by using the easyrule rule engine and configuring rules using the mvel syntax, the corresponding rules are configured for frequently changing businesses. When the system runs and executes the corresponding business, the current configured rules of the business are queried, the rule engine outputs the business path, and different business branches are executed. The main scenarios include:

[0061] 1. Order grading: By configuring rules, the order is divided into three levels of standard, high standard, and non-standard according to the resource quantity of the order application, the organization to which the order belongs, index data, and the like, so as to adapt to different approval processes.

[0062] 2. Application restriction: By configuring rules, the conditions for applying for resources are controlled, such as not allowing the black list to apply, not allowing some systems to apply, and the like.

[0063] 3. Operation parameter configuration: By configuring rules, the operation can easily control the platform functions, such as automatic resource allocation, visibility of some dependent resources, and whether to start the verification logic, etc.

[0064] Therefore, the user demand management module based on the rule engine gives the operation great flexibility, which can adjust the business logic at any time without developing or modifying the application configuration for the business scenario, and at the same time, determines in advance whether to apply and how to approve, avoids manual checking one by one, ensures that high-risk orders enter a more stringent approval channel, and low-risk orders are quickly released.

[0065] Specifically, in an embodiment, the rule engine uses EasyRules and describes the blacklist, quota threshold, and grading strategy in MVEL syntax. The operation personnel only need to modify the rule text on the configuration page to take effect in real time without restarting the application. Continuing the above example, after the system receives the two cloud resource application requests, it finds that the object storage order capacity > 200GB, the rule engine marks it as "non-standard" (i.e. non-standard request), and returns the request approval type "non-standard demand review"; while the virtual machine order is marked as "standard" because of the small capacity and sufficient team quota, and returns the request approval type "automatic pass".

[0066] The user demand approval module is configured to perform demand approval on the cloud resource application request according to the request approval type, and obtain an application approval result.

[0067] It should be noted that the demand approval refers to the decision of "pass", "return to modify", or "reject" made by the corresponding approval role (team leader, resource administrator, or automated script) after viewing the approval elements (quota data field, approval data field information) pushed by the system in the approval workbench. The application approval result refers to structured data containing approval conclusion, approval opinion, adjusted resource quota, and effective time.

[0068] It should be further noted that this module decouples the approver and system rules through the process engine, which can interface with third-party approval systems without modifying the code, realizing the pluggable extension of the approval process.

[0069] Specifically, according to the request approval type, the demand approval is performed on the cloud resource application request, and an application approval result is obtained. In an embodiment, the non-standard demand review adopts an online meeting + electronic signature mode, and the system synchronizes the meeting minutes in real time and locks the order state; the standard process is completely automated, and the approval result is returned in milliseconds. For example, after the object storage order enters "non-standard demand review", the review committee checks the historical usage rate and budget balance in the system and decides to reduce the capacity by 20% and pass the review; the system generates the application approval result "pass, quota 400GB", and writes it into the approval data field for subsequent audit.

[0070] The cloud resource delivery management module is configured to perform resource scheduling on the target cloud resource according to the application approval result and the cloud resource application request, create a cloud resource instance corresponding to the cloud resource application request, and perform resource delivery management.

[0071] It should be noted that the resource scheduling refers to automatically selecting an optimal physical host, a storage cluster and a network segment according to the approved quota, an environment identifier and a resource pool real-time load; the cloud resource instance creation refers to calling a bottom cloud platform API to automatically fill in parameters and start a virtual machine, a container, an object storage bucket and the like according to delivery data fields; and the resource delivery management refers to writing back an instance ID, access credentials and monitoring tags to an order after the instance is created, and updating a quota ledger to form a complete traceable link from “procurement – warehousing – application – delivery”.

[0072] It should be further noted that the module realizes zero repeated entry of a user by associating the delivery data field with the cloud resource application request, and all delivery actions are completed through an idempotent interface to prevent dirty data from being generated when retrying. In addition, the module also has a quick channel from resource application to delivery, and after the user applies for a resource through the system, the module supports quick jumping to a resource delivery page and automatically pre-filling delivery information, thereby reducing the repeated workload of the user and increasing convenience.

[0073] Specifically, according to the application approval result and the cloud resource application request, resource scheduling is performed on the target cloud resource, a cloud resource instance corresponding to the cloud resource application request is created, and resource delivery management is performed. For a cloud resource that needs to be deployed in multiple environments, the system routes the scheduling request to the corresponding private cloud area at the gateway layer according to the environment identifier, to ensure that the production, test and development environments are strictly isolated. For example, a virtual machine order that passes the approval is scheduled to a “production – availability zone A” host by the cloud resource delivery management module, and the instance creation is completed within 2 minutes; the system automatically writes the instance ID, login key and monitoring tag to the delivery data field, sends a delivery notification email to the user, and at the same time, lights up the “delivered” node on the resource link diagram, to complete the resource delivery management.

[0074] The embodiment obtains a cloud resource application request of a target user through a user demand application module; a user demand management module is configured to query application restrictions and order classification of the cloud resource application request to obtain a request approval type; a user demand approval module is configured to perform demand approval on the cloud resource application request according to the request approval type to obtain an application approval result; and a cloud resource delivery management module is configured to perform resource scheduling on target cloud resources according to the application approval result and the cloud resource application request, create a cloud resource instance corresponding to the cloud resource application request, and perform resource delivery management, so that the user only needs to submit once, the system automatically completes restriction verification, classification and approval, significantly reduces manual intervention, the approval type is determined in real time by a rule engine, human error is avoided, the approval speed and consistency are improved, resource scheduling and instance creation are triggered immediately after the approval is passed, the delivery cycle is shortened, and the user experience is improved. In the whole process, the data is connected, the approval result directly drives the resource delivery, the information gap is eliminated, the communication cost is reduced, and the interface and data structure are unified. Subsequent addition of cloud services does not require changes to the approval logic, and can be put online through configuration, with strong scalability.

[0075] In a feasible implementation, a cloud resource service access module is further included, configured to build a front-end form component corresponding to a cloud resource service provided by a cloud service provider, and configure the cloud resource service through the front-end form component to realize quick access of the cloud resource service.

[0076] It should be noted that the cloud service provider refers to a resource provider inside or outside an organization, responsible for delivering allocable resources such as computing, storage, network, and platform services to the cloud resource management platform; the cloud resource service refers to a specific cloud computing capability provided by the cloud service provider, such as a virtual machine instance, an object storage bucket, a database cluster, and a load balancing instance.

[0077] Further, the front-end form component refers to an independent front-end code package developed based on the Vue framework and dynamically loaded by the resource management platform, containing input controls, verification rules, default values, and help prompts required to collect user application information, wherein the cloud resource service configuration refers to an operation set of filling in service metadata, associating front-end form component paths, setting approval rules, and limiting strategies in the resource management platform, so that new services can be visible to users in the tenant portal and can be applied without changing the platform core code.

[0078] Further, the module aims to compress the traditional "new service online" process of several weeks or even months to minutes, reduce development coupling and operation complexity; by componentization and configuration separation of "display logic" and "business logic", cloud service providers only need to focus on the differentiation fields of their own services, while the platform focuses on general capabilities, forming a win-win situation.

[0079] Specifically, the cloud resource management platform provides unified basic components for general information, such as region components, availability zone components, system components, etc., so that cloud service providers can develop front-end components for specific services based on the basic components, and then upload them to the demand platform through the component package management function of the resource platform. After adding service configuration and filling in component path, the cloud resource management platform can load the corresponding component package, that is, build the front-end form component corresponding to the cloud resource service provided by the cloud service provider, so that users can use it when applying for corresponding resources on the resource management platform, and fill in the necessary information when applying for specific resources.

[0080] Further, the cloud resource service access module is divided into two parts, one part is component package upload, and the other part is service access configuration. A service access configuration is added in the service access configuration menu. When adding a configuration, information such as service type, supported environment, classification, and responsible person needs to be filled in, among which the key is the component of the related page. The front-end user can load the corresponding page according to the path configuration, which can be referred to Figure 5 In addition to basic configuration, cloud service providers can also configure business scenarios such as demand classification, temporary limit, and applicable specifications to adapt to different resource demand scenarios, which are not limited here.

[0081] In an embodiment, the cloud service provider uses Vue CLI to package the application form into a UMD format component package, and submits it through the component package upload interface provided by the platform and fills in the version number; the platform automatically decompresses, verifies and stores the component in the object storage or local file system, and at the same time generates a service access configuration record in the database containing service type, supported environment, classification, responsible person, component path, and approval rule reference; when the target user applies for the service, the resource management platform loads the corresponding component and renders the page according to the configuration record, realizing the real "zero backend change" access.

[0082] In a feasible implementation, it further includes a component package management module, which is used for local storage of the front-end form component built by the cloud resource service access module, and according to the component package information corresponding to the cloud resource application request, searches the component package in the local storage for the target user to request configuration.

[0083] It should be noted that the local storage refers to a persistent storage area deployed in the resource management platform server disk or object storage, used to store the compressed package of the front-end form component, the decompressed file directory and version metadata; the component package information refers to a metadata set that can uniquely identify a certain front-end form component, including but not limited to service type, version number, component path, verification hash value and creation timestamp.

[0084] Further, the component package lookup refers to the index service provided by the component package management module, which quickly locates and returns the physical path or CDN address of the corresponding component package according to the service type and environment identifier carried by the cloud resource application request; the request configuration refers to that the target user fills in the cloud resource application, and the system dynamically loads the matched front-end form component to render the input interface related to the cloud resource service, thereby completing the configuration process of resource specifications, quantity, purpose and other parameters.

[0085] Further, the component package management module can prevent compatibility problems caused by component upgrade or rollback through version management and cache strategy, and significantly reduce the front-end loading delay; when the cloud service provider uploads a new version of the component package, the module automatically retains the historical version, and the operator can switch the default version as needed to realize gray release and rapid rollback.

[0086] Specifically, in a possible implementation, the component package management module adopts a hierarchical directory structure: the first-level directory is named by service type, the second-level directory is named by version number, and the third-level directory stores the decompressed static resources; the system maintains a component package index table, which records the current effective default version and the switchable historical version list of each service.

[0087] Further, when the target user initiates a cloud resource application request, the user demand application module obtains the corresponding component package information through the component package management module according to the service type and environment identifier carried in the request; the component package management module will find the default version of the locally saved component package according to the component package requested by the user, and then splice the local file path or object storage URL, and immediately issue the corresponding component package to the front-end page rendering, which can be referred to as Figure 6 .

[0088] In a possible implementation, the resource planning management module is further included, which is configured to perform resource planning analysis according to the cloud resource application request of the target user and the resource planning configuration rule corresponding to the target user, and detect whether the target user meets the resource application authorization condition.

[0089] It should be noted that, in view of the strong management and control characteristics of the domestic cloud service resources in the resource-limited scene, the resource demand management adds a resource planning management module, which can plan the cloud resources in three levels, i.e., resource domain resource planning, center / branch resource planning, and team resource planning. Through the resource planning management module, the resource use plan within the organization can be made in advance, and the resources can be planned to each team. When a team member formally applies for resource demand, the amount of resources that can be applied is limited by the amount of team planning resources, and if the amount of resources that can be applied exceeds the amount of team planning resources, the application is not allowed. In addition to planning resources, the resource planning management module also provides functions such as quota allocation, storage, and over-quota plan to meet the different needs of resource administrators, which are not limited here.

[0090] It should be further noted that the resource planning configuration rule refers to a set of pre-set quota upper limit, use period, resource type white list, and reservation strategy with organization level, resource domain, center / branch, and team as dimensions; the resource planning analysis refers to real-time comparison of the rule with the currently allocated, applied, and to-be-issued quota, calculation of the remaining available amount, and generation of an allowed or rejected judgment result; and the resource application authorization condition refers to whether the remaining quota of the target user's team in the specified resource domain, center, and team three-level planning is greater than or equal to the current application amount, and whether the restrictions such as blacklist, disabled period, and over-quota plan are triggered.

[0091] Specifically, in an embodiment, the resource planning management module uses a rule engine to calculate in real time: first, read the remaining quota of the team dimension, then add the center-level reserved pool, and finally check the total upper limit of the resource domain; if any level does not meet the requirement, return a rejection with a suggested adjustment, so as to lock the resources in advance through three-level planning (resource domain-center / branch-team) to avoid resource contention caused by "first come, first served"; when the team quota is insufficient, the module supports quota allocation, storage, and over-quota plan application to ensure business flexibility while keeping the whole process controllable.

[0092] For example, a team applies for 100-core CPU, the system finds that the team-level remaining quota is only 60 cores, the center-level reserved pool has 50 cores available, and the resource planning configuration rule allows cross-level allocation, so the quota allocation is automatically completed and it is determined that the resource application authorization condition is met, and the next step of approval is allowed.

[0093] In a possible implementation, a data storage module is further included, which is configured to integrate and store resource management process information corresponding to a cloud resource instance through a quota data field, an approval data field, a delivery data field, and an extension data field.

[0094] It should be noted that the quota data field refers to a structured field set recording the required resources of this application, such as CPU core number, memory size, storage capacity, used to record the corresponding dimension quota value of the resource required to be issued by the user's current application, for example, the user applies for a virtual machine, and needs to issue how much CPU and how much memory quota. The approval data field refers to the approval person, approval opinion, approval timestamp and adjusted quota value generated in the approval process, used to record the order of the user's current application, which information needs to be displayed to the approval personnel as the basis for approval, to help the approval personnel better approve the resource application.

[0095] Further, the delivery data field refers to parameters that need to be automatically backfilled in the resource instance creation stage, such as image ID, network subnet, instance name prefix, used to record the order of the user's current application, which information is the mandatory information when creating the corresponding instance of resource delivery, used for automatic pre-filling when creating the resource instance, reducing the user's repeated entry work. The extension data field refers to the metadata specific to the cloud resource service, such as database version number, cache specification, backup strategy, used to record the unique information of the specific cloud service associated with the order of the user's current application.

[0096] Further, the data storage module serializes the four-domain information using a unified JSON Schema and stores it in a wide table or a document database of a relational database, ensuring traceability throughout the process; when the resource instance life cycle changes (scaling, recycling, migration), the module appends version records to realize auditing and rollback.

[0097] Specifically, in an embodiment, the data storage module generates a globally unique TraceID for each cloud resource instance, and the four-domain data are all taken as the primary key of the TraceID, supporting cross-module association query. For example, after a certain object storage instance is created, the data storage module writes: quota data field "500GB", approval data field "approver A, pass", delivery data field "bucket-name-001, East-1 region", extension data field "version control enabled, lifecycle policy 30 days", and displays the complete path from application to delivery on the resource link diagram through the TraceID, so as to provide differentiated information entry for different cloud service resources through front-end component combination technology, and the back-end integrates differentiated information through special data structure, separates the common information and unique information of cloud services, and reduces the overall complexity of the system.

[0098] Based on this, the embodiment of the present application provides a cloud resource management method, which refers to Figure 7 , Figure 7 The flowchart provided by the cloud resource management method embodiment one of the present application.

[0099] Step S61, obtain a cloud resource application request of a target user;

[0100] It should be noted that the cloud resource application request refers to a structured data package filled in by the target user in the front-end form for applying for private cloud resources, which at least includes: cloud resource service type, resource specification, quantity, expected use duration, belonging environment identifier, business use description, target user identity identifier, and team affiliation information, thereby providing unified, complete and structured input data for all subsequent processes, avoiding repeated communication caused by information missing, and through front-end component rendering, the user only needs to fill in once to generate a standardized request, significantly reducing the operation complexity.

[0101] Specifically, the cloud resource application request of the target user is obtained. In one possible implementation, the target user submits multiple cloud resource application requests at a time through a shopping cart, the system assigns a unique TraceID to each request, and writes the request in JSON format to a message queue. For example, developer Xiao Zhang selects the "monthly demand" entry in the tenant portal, fills in "apply for 4-core 8GB localized virtual machine trial for 3 months" and submits, the system generates a cloud resource application request with TraceID VM-20250714-001 and pushes it to the backend.

[0102] Step S62, order classification and application restriction query are performed on the cloud resource application request to obtain a request approval type;

[0103] Specifically, according to the user information in the cloud resource application request, it is determined that the target user is not in the preset blacklist, and then the resource quantity in the cloud resource application request, the order belonging organization, and the index data are determined. The cloud resource application request is classified by order to determine the order level corresponding to the cloud resource application request, so as to configure the request approval type corresponding to the cloud resource application request according to the order level, and then realize the integration of "interception-classification" through centralized management of rules, which not only prevents illegal applications from occupying resources, but also ensures that requests of different risk levels enter the matching approval channel, thereby improving the overall efficiency.

[0104] For example, in a specific embodiment, the system finds that the team has sufficient quota and is not in the blacklist, but the total CPU quantity exceeds the threshold, so the order classification is "non-standard", and the request approval type is set to "non-standard demand review".

[0105] Step S63, according to the request approval type, demand review is performed on the cloud resource application request to obtain an application approval result;

[0106] It should be noted that the demand approval refers to that the approver or authorized script gives a decision of "pass", "return for modification" or "reject" after viewing the quota data field and the approval data field information of the script in the approval workbench; the application approval result refers to a structured record containing the approval conclusion, the approval opinion, the adjusted quota and the effective time.

[0107] Specifically, according to the request approval type, the cloud resource application request is subjected to demand approval, and an application approval result is obtained, so as to realize decoupling of the approver and the system rule through a process engine, support multiple modes such as manual, countersignature and automatic script, and guarantee compliance and flexibility.

[0108] For example, the review committee views the approval data field of VM-20250714-001 in the system, decides to adjust the CPU to 2 cores and "pass", and the system generates an application approval result, wherein the application approval result is: conclusion "pass"; adjusted quota "2 cores 8 GB"; effective time "2025-07-1500:00:00".

[0109] In step S64, according to the application approval result and the cloud resource application request, resource scheduling is performed on the target cloud resource, and a cloud resource instance corresponding to the cloud resource application request is created to perform resource delivery management.

[0110] Specifically, according to the application approval result and the cloud resource application request, resource scheduling is performed on the target cloud resource, and a cloud resource instance corresponding to the cloud resource application request is created to perform resource delivery management. In one possible implementation, if the target environment is a multi-active scene, the scheduler preferentially selects an available zone with a delay <5 ms, and automatically configures cross-zone replicas.

[0111] Continuing the above example, the system schedules the cloud resource of TraceID VM-20250714-001 to "East-1 production available zone A" according to the application approval result, and completes virtual machine creation within 2 minutes; instance ID i-abc123, login key and monitoring tag are written into the delivery data field, the user receives an email notification and can directly log in and use, and resource delivery management is completed, so as to guarantee retry safety through idempotent scheduling interface and versioned delivery data field, and when the instance creation is successful, the user can one-click jump to the delivery page in the tenant portal, realizing "zero repetitive input".

[0112] The embodiment obtains a cloud resource application request of a target user, then performs application restriction query and order classification on the cloud resource application request to obtain a request approval type, and then performs demand approval on the cloud resource application request according to the request approval type to obtain an application approval result, and then performs resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, and creates a cloud resource instance corresponding to the cloud resource application request to perform resource delivery management, so as to provide a general and configurable private cloud service resource management solution, ensure that a cloud service provider can access a unified private cloud resource management system in a configurable and fast manner, and reduce the development cost of cloud services; meanwhile, an end-to-end resource link traceable solution is provided, which ensures that an operator can trace the destination and use scene of resources, and effectively solves the problems that resource utilization is difficult to evaluate and resource use is difficult to quantify.

[0113] In a feasible implementation, after obtaining the cloud resource application request of the target user, the following steps are included:

[0114] In step S71, a resource planning configuration rule corresponding to the target user is obtained.

[0115] It should be noted that the resource planning configuration rule refers to a set of pre-set quota upper limit, use period, resource type white list and reservation strategy in the dimensions of organization level, resource domain, center / branch, and team; the target user refers to an individual or team representative who submits a cloud resource application request in a tenant portal, and the identity information thereof is used to be associated to the above-mentioned level dimensions, thereby providing the most authoritative, real-time and dynamically adjustable authorization baseline for subsequent matching analysis, ensuring that any application has a clear rule basis before entering the approval, thereby avoiding the passive situation of "applying while discovering quota shortage".

[0116] Specifically, the resource planning configuration rule corresponding to the target user is obtained, and in a possible implementation, the resource planning configuration rule is stored in a configuration center in the form of JSON Schema, supports real-time hot update by an operator through a page, and the system pushes changes to a rule engine through a long connection to realize second-level effect.

[0117] For example, an operator administrator adds a rule in the configuration center: "the monthly CPU quota upper limit of team A in the East China-1 resource domain is 500 cores", and the system immediately synchronizes the rule to the rule engine cache for calling by the target user in subsequent application.

[0118] In step S72, the resource planning configuration rule is used to determine a resource application restriction situation corresponding to the target user, and the resource application restriction situation is matched and analyzed with the cloud resource application request.

[0119] It should be noted that the resource application restriction condition refers to a comprehensive description of the current available remaining quota, disabled period, disabled resource type list and special constraint conditions calculated according to the rules; the matching analysis refers to comparing the specifications, quantity, use environment in the cloud resource application request with the above-mentioned restriction conditions item by item, outputting the matching success or failure result and failure reason details, so as to complete the three-level (resource domain-center-team) quota deduction pre-play at one time, avoid the complex transaction of traditional deduction and rollback, and improve the concurrent processing efficiency; at the same time, the failure reason is returned to the front end in a structured field, and the user can self-adjust the application parameters and retry.

[0120] Specifically, according to the resource planning configuration rule, the resource application restriction condition corresponding to the target user is determined, and the resource application restriction condition is matched with the cloud resource application request, in an embodiment, the matching analysis adopts the MVEL expression embedded in the rule engine, and takes "remaining quota ≥ application quantity AND resource type ∈ whitelist AND current period ∈ allowed period" as a Boolean expression for instant calculation. For example, after the target user "team-a-dev" submits "apply for 100 core CPU", the rule engine reads that the remaining quota of team A in the East-1 resource domain is 450 cores, which satisfies "≥ 100 cores", and the CPU is in the whitelist and the current period is allowed, so the matching analysis result is "success"; if the remaining quota is only 80 cores, the result is "failure: CPU quota is insufficient by 20 cores".

[0121] In step S73, if the resource application restriction condition matches the cloud resource application request successfully, it is determined that the target user meets the resource application authorization condition, so as to perform the steps of applying for the resource application restriction query and order classification of the cloud resource application request, and obtaining the request approval type.

[0122] It should be noted that the resource application authorization condition refers to the Boolean result of the system determining that the target user meets all the constraints such as quota, period and type in the current resource domain, center and team three-level dimensions; "performing the resource application restriction query and order classification of the cloud resource application request" refers to further performing fine-grained restriction verification and risk classification by using the blacklist, business rules, historical indicators and the like on the premise that the resource planning authorization has been passed, so as to output the final request approval type, so that the system forms a "double-layer access control" mechanism by completing macro quota authorization by the resource planning management module and micro rule verification and classification by the user demand management module, which prevents macro over-allocation and avoids micro rule violation, and the whole process can be automatically transferred without manual intervention.

[0123] Specifically, in one possible implementation, if the matching is successful, the system labels the cloud resource application request as "authorized" and directly sends it to the rule engine for order grading; if the matching fails, the front end immediately prompts the failure reason and guides the user to lower the specification or initiate a quota allocation application.

[0124] For example, due to the successful matching analysis result, the system marks the request of TraceID "VM-20250714-002" as "authorized", and then enters the order grading logic; according to the application amount of 100 cores and the historical CPU utilization rate of the team of 90%, the rule engine divides it into "high mark", and finally the request approval type is set to "team monthly review".

[0125] The embodiment determines the resource application restriction condition corresponding to the target user according to the resource planning and configuration rule corresponding to the target user, and matches the resource application restriction condition with the cloud resource application request, so that if the resource application restriction condition matches the cloud resource application request successfully, it is determined that the target user meets the resource application authorization condition, to perform the steps of application restriction query and order grading on the cloud resource application request to obtain the request approval type, and then lock the quota in advance to avoid the application being rejected due to insufficient macro resources after entering the approval, reduce invalid approval link and time waste, and realize double-layer verification (macro planning + micro rule), that is, "zero false negatives and zero missed audits", which prevents over-provisioning and does not excessively limit reasonable demand, so as to realize rule centralized configuration, hot update, and effective operation, and the operation personnel can adjust the resource strategy at any time without modifying the code, the operation and maintenance cost tends to be zero, the failure reason is returned in a structured field in real time, the user can self-adjust the parameters or initiate a quota allocation, reduce communication costs, improve experience, and support precise control in concurrent scenarios through real-time deduction of the quota account book, and eliminate the risk of dirty data caused by traditional "first deduction and then rollback".

[0126] In one possible implementation, the application restriction query and order grading on the cloud resource application request to obtain the request approval type comprises:

[0127] In step S81, the user information in the cloud resource application request is used to determine that the target user is not in a preset blacklist.

[0128] It should be noted that the user information refers to a set of identity fields capable of uniquely identifying the target user, including but not limited to username, employee number, organization path, mailbox, role label and historical behavior label; the preset blacklist refers to a list of subjects prohibited from applying for resources statically or dynamically maintained by an operator in a rule engine, which can be derived from audit punishment records, security event associated accounts or compliance risk control lists, so that high-risk users can be intercepted in milliseconds through one-time blacklist hit detection, avoiding waste of subsequent quota calculation and approval resources, in addition, the blacklist supports real-time hot update, and the rule engine takes effect immediately after the operator adds or deletes records through the page.

[0129] Specifically, according to the user information in the cloud resource application request, it is determined that the target user is not in the preset blacklist, wherein the blacklist data can be cached in the memory in the form of BloomFilter, the system first performs hash comparison on the username, and if it is hit, it is confirmed again in the source database, which ensures performance and avoids false positives.

[0130] For example, the user information carried by the cloud resource application request is "user = zhangsan@team-a", the system queries the blacklist and finds that the user is marked because of the violation of the expansion last month, and returns "reject: user is in the blacklist" immediately after hitting the rule, and the process is terminated.

[0131] Step S82, determining the resource amount, order belonging organization and index data in the cloud resource application request, classifying the order of the cloud resource application request, and determining the order level corresponding to the cloud resource application request;

[0132] It should be noted that the resource amount refers to the numerical sum of CPU core number, memory GB, storage GB or instance quantity requested in the application; the order belonging organization refers to the center, branch, team and other hierarchical information where the target user is located, which is used to associate the quota baseline and historical usage level of the organization; the index data includes but is not limited to resource utilization rate, budget execution rate, SLA violation times, carbon emission index and other operation metrics of the organization in the past 30 days; the order level refers to the discrete level divided by the system according to the comprehensive score of the above three elements, such as "standard", "high standard" and "non-standard", so as to map complex multi-dimensional information to a single level through a quantitative scoring model, which simplifies the subsequent routing logic and provides observable risk stratification for operation, wherein the scoring threshold can be dynamically adjusted to support quarterly strategy smooth transition.

[0133] Specifically, the resource quantity in the cloud resource application request, the order belonging organization, and the index data are determined, the cloud resource application request is order graded, and the order grade corresponding to the cloud resource application request is determined. For example, in a specific embodiment, the requested resource quantity is 200 cores of CPU, the risk coefficient of the belonging organization "East China Center - Financial Team" is 1.2, the comprehensive score of the index data is 70, the model calculates a total score of 78, and the system determines that the order grade is "high mark".

[0134] In step S83, the request approval type corresponding to the cloud resource application request is configured according to the order grade.

[0135] It should be noted that the request approval type refers to a specific approval process identifier bound to the order grade, which is used to determine the subsequent approval path, the approval person role, the parallel or serial node, and the SLA time limit. The configuration process is completed by the rule engine in milliseconds, and the result is written into the metadata field of the cloud resource application request.

[0136] Specifically, the request approval type corresponding to the cloud resource application request is configured according to the order grade. For example, the request with the order grade of "high mark" is mapped to the "team monthly review" process, the system immediately pushes the request to the team leader's workbench and sets the SLA to complete the approval within 24 hours, thereby realizing "grading and routing", avoiding the delay and error caused by manual judgment, and supporting gray adjustment, that is, the operation personnel only need to modify the grade-process mapping table to temporarily change part of the "high mark" order to take the "quick channel", without modifying the code.

[0137] In this embodiment, the target user is determined not to be in the preset blacklist according to the user information in the cloud resource application request, and then the resource quantity in the cloud resource application request, the order belonging organization, and the index data are determined, the cloud resource application request is order graded, the order grade corresponding to the cloud resource application request is determined, the request approval type corresponding to the cloud resource application request is configured according to the order grade, and then high-risk users are rejected in milliseconds through pre-interception of the blacklist, to avoid waste of resources in subsequent calculation and approval, and to map multi-dimensional indexes into a single grade through a unified quantitative model, realize clear decision path, zero manual intervention, shorten the delivery cycle of low-risk requests, concentrate firepower to review high-risk, and online hot adjustment of threshold and weight, so that the operation strategy takes effect in seconds with business changes, without the need for version release. In addition, structured logs are generated throughout the process to provide traceable and quantifiable data foundation for subsequent audit, risk control, and capacity prediction.

[0138] For the purpose of understanding the implementation process of the cloud resource management method, please refer to Figure 8 , Figure 8A brief flowchart example provided by the cloud resource management method of the present application.

[0139] Specifically, the overall function implementation process of the cloud resource management platform can be summarized as a "six-step closed loop": service access → operation configuration → user application → demand approval → resource allocation → instance creation, and the module architecture diagram of the process implementation is as shown in Figure 9 .

[0140] Firstly, the cloud service provider uploads the front-end form component and fills in the service metadata (such as virtual machine specifications, database version) through the "service access" entrance, and the platform automatically completes the component registration and version management; the operation personnel sets the blacklist, quota threshold and approval rules for each service in "operation configuration", for example, marks the request of "more than 100 cores" as "non-standard"; then, the user selects the required service and fills in the parameters on the "apply for resources" page, for example, applies for "4-core 8GB virtual machine for 3 months" at a time, and the system immediately sends the order to the "demand approval" channel; if the user is not in the blacklist and the application amount is lower than the remaining quota of the team, the order is automatically classified as "standard" and directly passed, otherwise it is pushed to "non-standard demand review". After the approval, the "resource allocation" module deducts the quota in real time according to the approval result and calls the underlying API; the "instance creation" pulls up the virtual machine within 2 minutes in the specified availability zone, the platform writes back the instance ID and login key to the delivery data field, and sends a notification email to the user, completing the full-link closed loop from demand to delivery. In addition, the platform also has other functions, which can be referred to Figure 10 .

[0141] It should be noted that the examples in the figure are only used to understand the present application and do not constitute a limitation on the cloud resource management method of the present application. Based on this technical concept, more forms of simple changes are within the protection scope of the present application.

[0142] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0143] The present application provides a cloud resource management device, which comprises at least one processor and a memory in communication connection with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the cloud resource management method in the above embodiment one.

[0144] The following will be described with reference to Figure 11This document illustrates a structural diagram of a cloud resource management device suitable for implementing embodiments of this application. The cloud resource management device in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 11 The cloud resource management device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0145] like Figure 11 As shown, the cloud resource management device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in the read-only memory 1002 or a program loaded from the storage device 1003 into the random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the cloud resource management device. The processing unit 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the cloud resource management device to communicate wirelessly or wiredly with other devices to exchange data. While the figure shows cloud resource management devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0146] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are performed.

[0147] The cloud resource management device provided by the present application adopts the cloud resource management method in the above-mentioned embodiments, and can solve the technical problems in the background art. Compared with the prior art, the cloud resource management device provided by the present application has the same beneficial effects as the cloud resource management method provided by the above-mentioned embodiments, and other technical features in the cloud resource management device are the same as the features disclosed in the previous embodiment method, which will not be repeated here.

[0148] It should be understood that parts of the present disclosure can be realized by hardware, software, firmware or a combination thereof. In the description of the above-mentioned embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0149] The above is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0150] The present application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e. computer program) for performing the cloud resource management method in the above-mentioned embodiments.

[0151] The computer readable storage medium provided in the application may be, for example, a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system or device, or any combination of the above. More specific examples of the computer readable storage medium may include, but are not limited to, an electric connection with one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the embodiment, the computer readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electric wire, an optical cable, an RF (Radio Frequency), and the like, or any suitable combination of the above.

[0152] The computer readable storage medium described above may be contained in the cloud resource management device, or may exist separately without being assembled into the cloud resource management device.

[0153] The computer readable storage medium described above carries one or more programs, which, when executed by the cloud resource management device, cause the cloud resource management device to:

[0154] obtain a cloud resource application request of a target user;

[0155] perform application restriction query and order classification on the cloud resource application request to obtain a request approval type;

[0156] perform demand approval on the cloud resource application request according to the request approval type to obtain an application approval result;

[0157] perform resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, create a cloud resource instance corresponding to the cloud resource application request, and perform resource delivery management.

[0158] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0159] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0160] The modules involved in the embodiments of the present application can be implemented in software or hardware. In some cases, the name of the module does not constitute a limitation on the module itself.

[0161] The readable storage medium provided by the present application is a computer readable storage medium, which stores computer readable program instructions (i.e. computer programs) for executing the cloud resource management method described above, and can solve the technical problems in the background art. Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the cloud resource management method provided by the above embodiments, which will not be described here.

[0162] The embodiment of the present application provides a computer program product, comprising a computer program, which realizes the steps of the cloud resource management method when executed by a processor.

[0163] The computer program product provided by the present application can solve the technical problems in the background art. Compared with the prior art, the beneficial effects of the computer program product provided by the embodiment of the present application are the same as those of the cloud resource management method provided by the above-mentioned embodiment, and are not described here.

[0164] The above-mentioned is only part of the embodiments of the present application, and does not limit the patent scope of the present application. Any equivalent structural transformation, direct / indirect application in other related technical fields made by using the content of the present application specification and drawings within the technical concept of the present application are included in the patent protection scope of the present application.

Claims

1. A cloud resource management platform, comprising a user demand application module, a user demand management module, a user demand approval module, and a cloud resource delivery management module, characterized in that, the user demand application module is configured to obtain a cloud resource application request of a target user; the user demand management module is configured to perform application restriction query and order classification on the cloud resource application request to obtain a request approval type; the user demand approval module is configured to perform demand approval on the cloud resource application request according to the request approval type to obtain an application approval result; the cloud resource delivery management module is configured to perform resource scheduling on target cloud resources according to the application approval result and the cloud resource application request, create a cloud resource instance corresponding to the cloud resource application request, and perform resource delivery management.

2. The cloud resource management platform of claim 1, wherein, Further comprising a cloud resource service access module, which is configured to build a front-end form component corresponding to a cloud resource service provided by a cloud service provider, and configure the cloud resource service through the front-end form component to realize quick access of the cloud resource service.

3. The cloud resource management platform of claim 2, wherein, Further comprising a component package management module, which is configured to locally store the front-end form component built by the cloud resource service access module, and according to component package information corresponding to the cloud resource application request, find the component package in the local storage for request configuration by the target user.

4. The cloud resource management platform of claim 1, wherein, Further comprising a resource planning management module, which is configured to perform resource planning analysis according to the cloud resource application request of the target user and the resource planning configuration rules corresponding to the target user, and detect whether the target user meets the resource application authorization conditions.

5. The cloud resource management platform of claim 1, wherein, Further comprising a data storage module, which is configured to integrate and store resource management process information corresponding to a cloud resource instance through a quota data domain, an approval data domain, a delivery data domain, and an extension data domain.

6. A cloud resource management method characterized by, It comprises: obtaining a cloud resource application request of a target user; performing application restriction query and order classification on the cloud resource application request to obtain a request approval type; performing demand approval on the cloud resource application request according to the request approval type to obtain an application approval result; performing resource scheduling on target cloud resources according to the application approval result and the cloud resource application request, creating a cloud resource instance corresponding to the cloud resource application request, and performing resource delivery management.

7. The cloud resource management method of claim 6, wherein, After obtaining the cloud resource application request of the target user, it comprises: obtaining resource planning configuration rules corresponding to the target user; determining resource application restriction conditions corresponding to the target user according to the resource planning configuration rules, and performing matching analysis on the resource application restriction conditions and the cloud resource application request; if the resource application restriction conditions and the cloud resource application request match successfully, it is determined that the target user meets the resource application authorization conditions, and the step of performing application restriction query and order classification on the cloud resource application request to obtain a request approval type is executed.

8. The cloud resource management method of claim 6, wherein, the step of performing application restriction query and order classification on the cloud resource application request to obtain a request approval type comprises: According to the user information in the cloud resource application request, it is determined that the target user is not in a preset black list; Determine the resource amount, order belonging organization, and index data in the cloud resource application request, order grade the cloud resource application request, and determine the order grade corresponding to the cloud resource application request; According to the order grade, the request approval type corresponding to the cloud resource application request is configured.

9. A cloud resource management device, characterized by, The cloud resource management device comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the cloud resource management method according to any one of claims 6 to 8.

10. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program. When the computer program is executed by the processor, the steps of the cloud resource management method according to any one of claims 6 to 8 are implemented.

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