Systems and methods for intelligent deployment of storage resources in a cloud environment

Abstract

This invention provides a system and method for intelligent deployment of storage resources in a cloud environment, comprising: a business resource application layer: providing basic cloud services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS); a business resource management layer: providing data display, load monitoring, data analysis, data computation, and automated auxiliary design parameter functions; and a business resource scheduling layer: responsible for performing resource creation and expansion operations at the basic resource layer according to the requirements of the management layer. This invention significantly improves the accuracy and speed of automatically creating storage resources in a cloud environment; implements an automatic expansion mechanism for monitoring virtual disks, improving the flexibility and convenience of storage resource usage; reduces the occurrence of alarm events, reduces the frequency of manual intervention, and improves the efficiency of enterprise operation and maintenance management.

Description

Technical Field

[0001] This invention relates to the field of cloud service technology, and more specifically, to a system and method for intelligent deployment of storage resources in a cloud environment. Background Technology

[0002] The rapid development of enterprise cloud computing has led to the encapsulation of IT resources such as networks, storage, and servers into cloud services. With the help of this emerging technology model, users can access infrastructure, platforms, and software resources on demand and in an easily scalable manner through the network, thereby obtaining the services they need.

[0003] Virtualized cloud storage technology is one of the core technologies of cloud computing. Its main purpose is to "pool" storage resources, so that administrators can simply retrieve them from the cloud storage resource pool for users who submit usage requests.

[0004] Compared to traditional storage, cloud storage needs to allocate resources requested by users on demand. Among these requirements, a smart deployment mechanism for storage resources that is diverse in scenarios and geared towards tenants is an important functional requirement.

[0005] In practical applications, cloud server application involves processes that require manual intervention to select or create storage resources and notify applicants of their use. These processes can lead to inefficiencies in resource application. By utilizing the intelligent allocation mechanism of the cloud management platform, we can quantitatively analyze the dynamic requests for cloud services and calculate a resource allocation method that takes into account both resource demand and service performance levels, thereby dynamically configuring storage resources for virtual machines.

[0006] The results show that the system and its method can effectively improve the efficiency of storage resource application in the cloud environment, which is of practical significance for improving the smoothness of user requests and the quality of cloud services.

[0007] Patent document CN117097611A discloses an SDN controller deployment method, apparatus, device, and storage medium. When deploying an SDN controller using a POD (Programmable Object) resource object model, it categorizes the controller's application components according to resource consumption and baselines the service capabilities of individual PODs running the controller's application components. A mapping table is established between network / service scale and the number of PODs. An SDN controller cluster is deployed based on this mapping table, and the mapping table is automatically adjusted by monitoring POD horizontal scaling records and preset adjustment rules, thereby ensuring a more accurate assessment of the required hardware resources when deploying the SDN controller. However, this patent cannot completely solve the existing technical problems, nor can it meet the needs of this invention. Summary of the Invention

[0008] To address the shortcomings of existing technologies, the purpose of this invention is to provide a system and method for intelligent deployment of storage resources in a cloud environment.

[0009] The system for intelligent deployment of storage resources in a cloud environment according to the present invention includes:

[0010] Business resource application layer: Provides basic cloud services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS);

[0011] Business resource management layer: Provides functions such as data display, load monitoring, data analysis, data calculation, and automated auxiliary design parameters;

[0012] Business resource scheduling layer: responsible for performing resource creation and expansion operations in the basic resource layer according to the requirements of management;

[0013] The business resource application layer processes user-initiated external cloud service usage requests, aggregates all business data to the business resource management layer, and after analysis and processing, encapsulates it into an automated job workflow. Then, it is forwarded to the automation engine of each data center through the workflow scheduler of the business resource scheduling layer for execution, and the latter performs automated resource deployment for the IT infrastructure resources of the region.

[0014] It also includes a resource load monitoring module, an automatic resource creation module, an automatic resource expansion module, and a resource data analysis module;

[0015] The resource data analysis module is responsible for receiving usage requests from external cloud service users, selecting and calculating the required storage resources for the cloud host, and triggering the operation of the automatic resource creation module.

[0016] The resource load monitoring module monitors the current load usage of all storage resources in the resource layer in real time. When the resource load exceeds the preset threshold, the resource load monitoring module generates a resource alarm event and triggers the dynamic expansion operation of the resource automatic expansion module.

[0017] Enterprise cloud environments use virtualization technology to allocate virtual machine hard disks from virtual disks in the storage resource pool to cloud hosts. When a user applies for a cloud host through the cloud management platform, the cloud service first automatically selects the computing resource pool according to a specific business method, then calculates the total amount of virtual machine hard disks required for this cloud host service application, determines whether to create disks and the number to be created according to the computing rules under different scenarios, then automatically assists in designing the technical parameters of storage resources, and finally logs into the storage array to automatically create disks.

[0018] Preferably, the resource load monitoring module includes: real-time monitoring of the load status of all storage resources in the resource layer; when a user creates basic storage resources through the cloud management platform, the user sets an upper limit threshold for the load of the resources used; when the resource load exceeds the threshold, the load monitoring module generates a resource alarm event and triggers dynamic expansion of the resources.

[0019] Preferably, the resource data analysis module includes:

[0020] The automated design-aided module is responsible for receiving usage requests from external users and finding and designing resource parameters for servers, networks, or storage for cloud hosts.

[0021] Resource Selection Submodule: Based on the resource parameters determined by the Automated Design Submodule, determine whether there are existing and usable storage resources for the cloud host service application;

[0022] Resource Computing Submodule: This module summarizes the application requirements for new virtual machine hard disks for cloud host services, and comprehensively judges whether new resources need to be created and their exact type and quantity requirements based on the available resources selected by the Resource Selection Submodule.

[0023] Preferably, the automatic resource creation module includes: once the cloud host application determines the virtual disks to be created and the number of virtual disks through the resource data analysis module, then calculates the technical parameters for creating storage resources through the cloud management platform, logs into the storage array of the basic resource environment through distributed access to create the disks, and mounts them on the physical server;

[0024] The default creation size for high-performance or standard virtual disks is 2000GB, while the default creation size for capacity virtual disks is 5000GB.

[0025] Preferably, the automatic resource expansion module includes:

[0026] When the virtual disk utilization reaches 80%, the resource load monitoring module responsible for real-time monitoring generates an alarm event and simultaneously notifies the automatic resource expansion module to perform an expansion operation. The latter calculates the expansion amount based on the remaining capacity of the resource pool within the storage array where the disk resides, as follows:

[0027] For high-performance or standard virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then exceeds 9000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then does not exceed 9000GB, an automatic expansion operation is performed.

[0028] Capacity-based virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator; if the current capacity of the disk is automatically expanded by 2000GB and then exceeds 16000GB, an alarm event is generated to notify the storage administrator to intervene; if the current capacity of the disk is automatically expanded by 2000GB and then does not exceed 16000GB, an automatic expansion operation is performed.

[0029] The method for intelligent deployment of storage resources in a cloud environment according to the present invention includes:

[0030] Resource data analysis steps: Responsible for receiving usage applications from external cloud service users, and selecting and computing the necessary storage resources for cloud hosts;

[0031] Automatic resource creation steps: Create basic storage resources based on the storage resources required for computation;

[0032] Resource load monitoring steps: Real-time monitoring of the current load usage of all storage resources in the resource layer; when the resource load exceeds a preset threshold, a resource alarm event is generated.

[0033] Automatic resource expansion steps: Perform dynamic expansion operations based on the results of resource load monitoring.

[0034] Preferably, the resource load monitoring step includes: real-time monitoring of the load status of all storage resources in the resource layer; when a user creates basic storage resources through the cloud management platform, the user sets an upper limit threshold for the load of the resources used; when the resource load exceeds the threshold, a resource alarm event is generated, triggering dynamic expansion of the resources.

[0035] Preferably, the resource data analysis step includes:

[0036] Automated design sub-step: Responsible for receiving usage requests from external users and finding and designing resource parameters for servers, networks, or storage for cloud hosts;

[0037] Resource selection sub-step: Based on the resource parameters determined in the automated design sub-step, determine whether there are existing usable storage resources for the cloud host service application;

[0038] Resource Calculation Sub-step: For cloud host services, summarize the application demand for new virtual machine hard disks, and combine the available resources selected in the resource selection sub-step to comprehensively determine whether new resources are needed and the exact type and quantity requirements.

[0039] Preferably, the automatic resource creation step includes: once the cloud host application determines the virtual disks to be created and the number of virtual disks through the resource data analysis step, the cloud management platform calculates the technical parameters for creating storage resources, logs into the storage array of the basic resource environment through distributed access to create the disks, and mounts them on the physical server;

[0040] The default creation size for high-performance or standard virtual disks is 2000GB, while the default creation size for capacity virtual disks is 5000GB.

[0041] Preferably, the automatic resource expansion step includes:

[0042] When the virtual disk utilization reaches 80%, an alarm event is generated, and an expansion operation is executed simultaneously. The latter calculates the expansion amount based on the remaining capacity of the resource pool within the storage array where the disk resides, as follows:

[0043] For high-performance or standard virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then exceeds 9000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then does not exceed 9000GB, an automatic expansion operation is performed.

[0044] Capacity-based virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator; if the current capacity of the disk is automatically expanded by 2000GB and then exceeds 16000GB, an alarm event is generated to notify the storage administrator to intervene; if the current capacity of the disk is automatically expanded by 2000GB and then does not exceed 16000GB, an automatic expansion operation is performed.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] (1) This invention greatly improves the accuracy and speed of automatically creating storage resource systems in the cloud environment; realizes the monitoring and automatic expansion mechanism of virtual disks, improves the flexibility and convenience of storage resource use; reduces the generation of alarm events, reduces the frequency of manual intervention, and improves the management efficiency of enterprise operation and maintenance.

[0047] (2) The software intelligent deployment system of the present invention was successfully implemented after design, coding and comprehensive testing. After the overall testing of the system, all test indicators met the industry standards and the design goals were fully achieved. The system was successful and received positive feedback from users. Attached Figure Description

[0048] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0049] Figure 1 Functional architecture diagram of an intelligent deployment solution for basic storage resources in enterprise cloud environments;

[0050] Figure 2 Functional module structure diagram of an intelligent deployment solution for basic storage resources in enterprise cloud environments;

[0051] Figure 3 Design diagram of the business process for applying for cloud servers;

[0052] Figure 4 Diagram showing the components of the resource data analysis module;

[0053] Figure 5 A flowchart for the resource computing submodule;

[0054] Figure 6 Functional collaboration diagram for intelligent deployment solutions of basic storage resources in enterprise cloud environments. Detailed Implementation

[0055] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0056] Example

[0057] The intelligent deployment solution relies on a cloud management platform, which is a virtualization resource management software system tailored for cloud computing data centers. The key to this solution lies in its integration of load monitoring functions for basic storage services, achieving automatic correlation between cloud host service requests and the resource supply levels of the existing storage system through an intelligent resource allocation mechanism.

[0058] By analyzing the total demand for virtual machine hard disks from cloud host services and automatically linking the basic storage environment to create or expand storage resources based on the actual load of the current storage system, the system achieves automatic mapping and resource scheduling of business needs for creating virtual machines in the cloud environment to the basic storage environment.

[0059] like Figure 1 As shown, the system adopts a distributed architecture, consisting of a business resource application layer, a business resource management layer, a business resource scheduling layer, and a basic resource layer from top to bottom. It runs across various operating system environments, enabling unified, efficient, and precise integrated management of cloud computing basic resources.

[0060] The business resource application layer provides basic cloud services, mainly including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).

[0061] The business resource management layer is the central control brain, which includes functions such as data display, load monitoring, data analysis, data calculation, and automated auxiliary design parameters.

[0062] The business resource scheduling layer is responsible for performing resource creation and expansion operations in the basic resource layer according to the requirements of the management.

[0063] The application layer, management layer, and scheduling layer of business resources together form the unified enterprise cloud computing management platform. The unified and centralized management platform and the independent and decentralized basic resource layer work together to achieve integrated resource management in the cloud environment.

[0064] The application layer processes user-initiated requests for external cloud services, aggregates all business data to the management layer, and after analysis and processing, encapsulates it into automated job workflows. These workflows are then forwarded by the scheduling layer's workflow scheduler to the automation engines in each data center for execution. The latter then performs automated resource deployment for the IT infrastructure resources of its respective region. Figure 6 As shown.

[0065] The software system for the intelligent deployment solution of storage resources mainly consists of the following four functional modules: resource load monitoring module, automatic resource creation module, automatic resource expansion module, and resource data analysis module, such as... Figure 2 As shown.

[0066] The resource data analysis module is responsible for receiving usage requests from external cloud service users, selecting and calculating the required storage resources for the cloud host, and triggering the operation of the automatic resource creation module.

[0067] The resource load monitoring module monitors the current load usage of all storage resources in the resource layer in real time. When the resource load exceeds a preset threshold, the load monitoring module generates a resource alarm event and triggers the dynamic expansion operation of the automatic resource expansion module. All modules cooperate with each other in the cloud service application process to jointly improve the efficiency and accuracy of basic resource utilization.

[0068] Enterprise cloud environments use virtualization technology to allocate virtual machine hard disks from virtual disks (hereinafter referred to as disks) within the storage resource pool for use by cloud hosts.

[0069] When a user applies for a cloud server through the cloud management platform, the cloud service first automatically selects a computing resource pool according to a specific business method, then calculates the total amount of virtual machine hard disks required for this cloud server service application, determines whether to create disks and the number to be created according to the computing rules under different scenarios, then automatically assists in designing the technical parameters of storage resources, and finally logs into the storage array to automatically create disks. The overall business flow steps are designed as follows: Figure 3 As shown.

[0070] Design of resource load monitoring module

[0071] This module monitors the load status of all storage resources in the resource layer in real time (such as "overall storage performance of virtual disks" and "virtual storage resource utilization"). When users create basic storage resources through the cloud management platform, they can set an upper limit threshold for the load of the resources used. When the resource load exceeds the threshold, the load monitoring module will generate a resource alarm event, triggering dynamic expansion of the resources.

[0072] Design of resource data analysis module

[0073] Resource data analysis is the core module for realizing intelligent deployment of storage resources, and it is also the foundation for enabling rapid delivery of cloud host services and processing of storage resources.

[0074] like Figure 4 As shown, the resource data analysis software system consists of three functional sub-modules: an automated assisted design sub-module, a resource selection sub-module, and a resource calculation sub-module.

[0075] The automated design-aided module is responsible for receiving usage requests from external users and finding and designing resource parameters for servers, networks, or storage for cloud hosts.

[0076] The resource selection submodule determines whether there are available storage resources for the cloud host service application based on the resource parameters determined by the automated assisted design submodule.

[0077] The resource computing submodule summarizes the application requirements for new virtual machine hard disks for cloud host services, and combines the available resources selected by the resource selection submodule to comprehensively determine whether new resources need to be created and the exact type and quantity requirements.

[0078] Automated Design Submodule

[0079] The automated design submodule allows for the selection of computing, storage, and network resources for cloud servers requested in batches by external users. The mechanism for sequentially searching, verifying, and determining the computing resource pool to which each cloud server belongs is a key step in ensuring the accurate and efficient implementation of the cloud server request service.

[0080] First, the scope of the computing resource pool to which the cloud service belongs is searched using the following seven rules. There is no order among the rules, and the result can have a maximum of two computing resource pools.

[0081] (1) The same cloud service belongs to the same operating node region value, such as "Shanghai 01";

[0082] (2) The same type of resource usage, such as "operating environment";

[0083] (3) The attribute of the computing resource pool is "general";

[0084] (4) Whether the newly created resource attribute is "Yes";

[0085] (5) The same cloud service resource level, such as "Gold";

[0086] (6) The same associated virtual machine template name, such as "CentOS79";

[0087] (7) The virtualization type of the physical server hosting the computing resource pool, such as "VMware";

[0088] Secondly, the first cloud server requested in a batch will undergo a special verification of the defined computing resource pool, according to the following rules:

[0089] (1) If there are two computing resource pools, determine whether they belong to the same virtualization controller;

[0090] (2) If there are two computing resource pools, determine whether the number and name of the virtual disks in the pool are consistent.

[0091] If the verification fails, the cloud host will not be initialized again, will exit, and the administrator will be notified for manual processing; if the verification succeeds, the cloud host will directly use the defined range of computing resources.

[0092] Finally, all cloud servers will select one from the computing resource pool that has been determined and verified by the automated design, according to the following rules.

[0093] (1) Based on the user’s specific requirements for the number of CPUs (greater than 16) and memory (greater than 32GB) designed for each cloud host, the high-performance computing resource pool should be selected first, and the ordinary computing resource pool should be selected if there is none.

[0094] (2) In other cases, select the first computing resource pool.

[0095] After each cloud host is assigned to a computing resource pool, the resource selection submodule is notified.

[0096] Resource Selection Submodule

[0097] This module is used to determine whether there are existing and usable storage resources for each cloud host that has been applied for.

[0098] First, after each cloud server is assigned to a computing resource pool, its storage resource pool can be determined. The following six rules are used to search for all virtual disks within the storage resource pool, categorized by performance level. The result may show one, multiple, or no virtual disks.

[0099] (1) The same cloud service belongs to the same operating node region value, such as "Shanghai 01";

[0100] (2) The same type of resource usage, such as "operating environment";

[0101] (3) Whether the newly created resource attribute is "Yes";

[0102] (4) Tenant code number, such as "OT";

[0103] (5) The same virtual disk performance level type, such as "high performance";

[0104] (6) The same virtual disk is used for the same purpose, such as "OS";

[0105] Secondly, combining the real-time data collected by the resource load monitoring module, the multiple virtual disks of each performance level that have been identified are sorted from smallest to largest according to their current resource utilization, and then verified according to the following rules:

[0106] (1) If the difference in utilization between the two virtual disks with the lowest resource utilization is greater than 20%, select the one with the lowest resource utilization; otherwise, randomly select one of the two disks.

[0107] (2) In other cases, select the virtual disk with the lowest resource utilization.

[0108] Finally, the maximum capacity of the selected disk is checked according to the performance level type, as follows:

[0109] The maximum capacity of each high-performance or standard virtual disk is 7000GB, and the maximum capacity of a capacity virtual disk is 8000GB. If the capacity exceeds this limit, it cannot be selected for use.

[0110] Resource Computing Submodule

[0111] This module calculates the total number of new virtual machine hard disks requested for each cloud host service based on three performance levels: high-performance, standard, and capacity. It also considers various scenarios where available virtual disks of the same performance level exist to comprehensively determine whether new disks need to be created, and the exact type and quantity of new resources required. The calculation process is as follows: Figure 5 As shown.

[0112] Design of the automatic resource creation module

[0113] Once the cloud server application determines the required virtual disks and their quantity through the resource data analysis module, the technical parameters for creating storage resources can be calculated through the cloud management platform. Then, the disks are created by logging into the storage array of the basic resource environment through distributed access and mounted on the physical server.

[0114] The default creation size for high-performance or standard virtual disks is 2000GB, while the default creation size for capacity virtual disks is 5000GB.

[0115] Design of an automatic resource expansion module

[0116] When the virtual disk utilization reaches 80%, the resource load monitoring module responsible for real-time monitoring generates an alarm event and simultaneously notifies the automatic resource expansion module to perform an expansion operation. The latter calculates the expansion amount based on the remaining capacity of the resource pool within the storage array where the disk resides, as follows:

[0117] High-performance or standard virtual disks

[0118] (1) When the remaining capacity of the internal resource pool of the storage array where the disk is located is less than 3000GB, an alarm event is generated to notify the storage administrator to intervene and handle it.

[0119] (2) If the disk capacity is automatically expanded by 1000GB and then exceeds 9000GB, an alarm event will be generated to notify the storage administrator to intervene and handle the situation.

[0120] (3) The current disk capacity can be automatically expanded by 1000GB, and the capacity will not exceed 9000GB. Automatic expansion operation can be performed.

[0121] Capacity-based virtual disks

[0122] (1) When the remaining capacity of the internal resource pool of the storage array where the disk is located is less than 3000GB, an alarm event is generated to notify the storage administrator;

[0123] (2) If the disk capacity is automatically expanded by 2000GB and then exceeds 16000GB, an alarm event will be generated to notify the storage administrator to intervene.

[0124] (3) The current disk capacity can be automatically expanded by 2000GB, which will not exceed 16000GB. Automatic expansion operation can be performed.

[0125] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0126] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A system for intelligent deployment of storage resources in a cloud environment, characterized in that, include: Business resource application layer: Provides basic cloud services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS); Business resource management layer: Provides functions such as data display, load monitoring, data analysis, data calculation, and automated auxiliary design parameters; Business resource scheduling layer: responsible for performing resource creation and expansion operations in the basic resource layer according to the requirements of management; The business resource application layer processes user-initiated external cloud service usage requests, aggregates all business data to the business resource management layer, and after analysis and processing, encapsulates it into an automated job workflow. Then, it is forwarded to the automation engine of each data center through the workflow scheduler of the business resource scheduling layer for execution, and the latter performs automated resource deployment for the IT infrastructure resources of the region. It also includes a resource load monitoring module, an automatic resource creation module, an automatic resource expansion module, and a resource data analysis module; The resource data analysis module is responsible for receiving usage requests from external cloud service users, selecting and calculating the required storage resources for the cloud host, and triggering the operation of the automatic resource creation module. The resource load monitoring module monitors the current load usage of all storage resources in the resource layer in real time. When the resource load exceeds the preset threshold, the resource load monitoring module generates a resource alarm event and triggers the dynamic expansion operation of the resource automatic expansion module. Enterprise cloud environments use virtualization technology to allocate virtual machine hard disks from virtual disks in the storage resource pool to cloud hosts. When a user applies for a cloud host through the cloud management platform, the cloud service first automatically selects the computing resource pool according to a specific business method, then calculates the total amount of virtual machine hard disks required for this cloud host service application, determines whether to create disks and the number to be created according to the computing rules under different scenarios, then automatically assists in designing the technical parameters of storage resources, and finally logs into the storage array to automatically create disks. Cloud services automatically select computing resource pools based on specific business methods, including: First, the scope of the computing resource pool to which the cloud service belongs is searched by a preset first rule. The preset first rule includes multiple rules, and there is no order among the multiple rules. The result is at most two computing resource pools. Secondly, the first cloud server requested in a batch will undergo a special verification of the defined computing resource pool, according to the following rules: If there are two compute resource pools, determine whether they belong to the same virtualization controller; if there are two compute resource pools, determine whether the number and name of the virtual disks in the pool are the same. If the verification fails, the cloud server will not be initialized again, will exit, and the administrator will be notified for manual handling. If the verification is successful, the cloud host will then directly use the defined range of computing resources. Finally, all cloud servers select one from the computing resource pool range that has been determined and verified by the automated assisted design, according to the preset second rule.

2. The system for intelligent deployment of storage resources in a cloud environment according to claim 1, characterized in that, The resource load monitoring module includes: real-time monitoring of the load status of all storage resources in the resource layer; when a user creates basic storage resources through the cloud management platform, they set an upper limit threshold for the load of the resources used; when the resource load exceeds the threshold, the load monitoring module generates a resource alarm event, triggering dynamic expansion of the resources.

3. The system for intelligent deployment of storage resources in a cloud environment according to claim 1, characterized in that, The resource data analysis module includes: The automated design-aided module is responsible for receiving usage requests from external users and finding and designing resource parameters for servers, networks, or storage for cloud hosts. Resource Selection Submodule: Based on the resource parameters determined by the Automated Design Submodule, determine whether there are existing and usable storage resources for the cloud host service application; Resource Computing Submodule: This module summarizes the application requirements for new virtual machine hard disks for cloud host services, and comprehensively judges whether new resources need to be created and their exact type and quantity requirements based on the available resources selected by the Resource Selection Submodule.

4. The system for intelligent deployment of storage resources in a cloud environment according to claim 1, characterized in that, The automatic resource creation module includes: once the cloud host application determines the virtual disks to be created and the number of virtual disks through the resource data analysis module, the cloud management platform calculates the technical parameters for creating storage resources, logs into the storage array of the basic resource environment through distributed access to create the disks, and mounts them on the physical server; The default creation size for high-performance or standard virtual disks is 2000GB, while the default creation size for capacity virtual disks is 5000GB.

5. The system for intelligent deployment of storage resources in a cloud environment according to claim 1, characterized in that, The automatic resource expansion module includes: When the virtual disk utilization reaches 80%, the resource load monitoring module responsible for real-time monitoring generates an alarm event and simultaneously notifies the automatic resource expansion module to perform an expansion operation. The latter calculates the expansion amount based on the remaining capacity of the resource pool within the storage array where the disk resides, as follows: For high-performance or standard virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then exceeds 9000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then does not exceed 9000GB, an automatic expansion operation is performed. Capacity-based virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator; if the current capacity of the disk is automatically expanded by 2000GB and then exceeds 16000GB, an alarm event is generated to notify the storage administrator to intervene; if the current capacity of the disk is automatically expanded by 2000GB and then does not exceed 16000GB, an automatic expansion operation is performed.

6. A method for intelligent deployment of storage resources in a cloud environment, employing the system for intelligent deployment of storage resources in a cloud environment as described in claim 1, characterized in that, include: Resource data analysis steps: Responsible for receiving usage applications from external cloud service users, and selecting and computing the necessary storage resources for cloud hosts; Automatic resource creation steps: Create basic storage resources based on the storage resources required for computation; Resource load monitoring steps: Real-time monitoring of the current load usage of all storage resources in the resource layer; when the resource load exceeds a preset threshold, a resource alarm event is generated. Automatic resource expansion steps: Perform dynamic expansion operations based on the results of resource load monitoring.

7. The method for intelligent deployment of storage resources in a cloud environment according to claim 6, characterized in that, The resource load monitoring steps include: real-time monitoring of the load status of all storage resources in the resource layer; when users create basic storage resources through the cloud management platform, they set an upper limit threshold for the load of the resources used; when the resource load exceeds the threshold, a resource alarm event is generated, triggering dynamic expansion of the resources.

8. The method for intelligent deployment of storage resources in a cloud environment according to claim 6, characterized in that, The resource data analysis steps include: Automated design sub-step: Responsible for receiving usage requests from external users and finding and designing resource parameters for servers, networks, or storage for cloud hosts; Resource selection sub-step: Based on the resource parameters determined in the automated design sub-step, determine whether there are existing usable storage resources for the cloud host service application; Resource Calculation Sub-step: For cloud host services, summarize the application demand for new virtual machine hard disks, and combine the available resources selected in the resource selection sub-step to comprehensively determine whether new resources are needed and the exact type and quantity requirements.

9. The method for intelligent deployment of storage resources in a cloud environment according to claim 6, characterized in that, The automatic resource creation steps include: once the cloud host application determines the virtual disks to be created and the number of disks through the resource data analysis steps, the cloud management platform calculates the technical parameters for creating storage resources, logs into the storage array of the basic resource environment through distributed access to create disks, and mounts them on the physical server; The default creation size for high-performance or standard virtual disks is 2000GB, while the default creation size for capacity virtual disks is 5000GB.

10. The method for intelligent deployment of storage resources in a cloud environment according to claim 6, characterized in that, The automatic resource expansion step includes: When the virtual disk utilization reaches 80%, an alarm event is generated, and an expansion operation is performed simultaneously. The latter calculates the expansion amount based on the remaining capacity of the resource pool within the storage array where the disk resides, as follows: For high-performance or standard virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then exceeds 9000GB, an alarm event is generated to notify the storage administrator to intervene; if the disk's current capacity is automatically expanded by 1000GB and then does not exceed 9000GB, an automatic expansion operation is performed. Capacity-based virtual disks: When the remaining capacity of the internal resource pool of the storage array where the disk resides is less than 3000GB, an alarm event is generated to notify the storage administrator; if the current capacity of the disk is automatically expanded by 2000GB and then exceeds 16000GB, an alarm event is generated to notify the storage administrator to intervene; if the current capacity of the disk is automatically expanded by 2000GB and then does not exceed 16000GB, an automatic expansion operation is performed.

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