Recommendation method and device for cloud disk service change

Abstract

The invention provides a cloud disk service change recommendation method and device, and relates to the technical field of cloud computing, the method is applied to a cloud management platform, the cloud management platform is used for managing an infrastructure providing cloud services, the infrastructure comprises a storage pool formed by storage spaces of a plurality of cloud servers, and the storage pool comprises a plurality of cloud servers. The storage pool is virtually divided into a plurality of cloud disks, and the method comprises the steps that operation data of a first cloud disk in the plurality of cloud disks are acquired, and the operation data of the first cloud disk comprises a flow control parameter and a capacity utilization rate; determining a change strategy of the first cloud disk according to the operation data of the first cloud disk; and providing a recommendation interface for a tenant of the first cloud disk, wherein the recommendation interface comprises the change strategy. Based on the scheme, the change strategy of the cloud disk is determined according to the operation data of the cloud disk, and the change strategy is recommended to the tenant of the cloud disk. According to the cloud disk service change recommendation method provided by the embodiment of the invention, a proper change strategy can be recommended to the tenant, so that the service experience is improved.

Description

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on July 7, 2023, with application number 202310833309.8 and application name “Data-driven optimal cloud service recommendation system”, the entire contents of which are incorporated by reference in this application. Technical Field

[0002] The present application relates to the field of cloud computing technology, and more specifically, to a method and device for recommending cloud disk service changes. Background Art

[0003] A cloud disk can be a virtual disk combined with a cloud virtual machine in the form of block storage. Tenants can create and change file systems on cloud disks, as well as perform operations such as formatting. Tenants can read and write to cloud disks. The number of read and write operations per second on a cloud disk can be called input / output per second (IOPS), and the amount of data transmitted per second on a cloud disk can be called throughput. In a cloud disk, there are upper limits on IOPS and throughput, which are called IOPS upper limit and throughput upper limit, respectively. IOPS upper limit and throughput upper limit can describe the performance of a cloud disk.

[0004] When the performance of the cloud disk exceeds the performance parameters, the cloud disk will trigger flow control (referred to as "flow control"). For example, the flow control device will send a back pressure signal to the upstream of the cloud disk, which is used to instruct the upstream of the cloud disk to reduce or stop sending data to the cloud disk to ensure that the performance of the cloud disk does not exceed the upper limit.

[0005] Frequent triggering of flow control indicates that the current performance parameters of the cloud disk cannot meet the needs of tenants. Tenants can upgrade the cloud disk according to their own needs so that the upgraded cloud disk has appropriate performance and capacity. However, if tenants are expected to upgrade the cloud disk independently, they need to understand the real reason for flow control. However, most tenants do not have the ability to analyze the reasons for flow control and formulate appropriate change strategies, which makes the cost of tenants investing in cloud disk service changes high.

[0006] Therefore, how to enable tenants to adopt appropriate change strategies to improve the performance of cloud disks is an urgent problem to be solved. Summary of the invention

[0007] The present application provides a method and device for recommending cloud disk service changes, which can recommend appropriate change strategies to tenants, so that tenants can adopt appropriate change strategies to improve the performance of cloud disks.

[0008] In a first aspect, a method for recommending changes to a cloud disk service is provided, the method being applied to a cloud management platform, the cloud management platform being used to manage an infrastructure for providing cloud services, the infrastructure comprising a storage pool consisting of storage spaces of multiple cloud servers, the storage pool being virtually divided into multiple cloud disks, the method comprising: obtaining operating data of a first cloud disk among the multiple cloud disks, wherein the operating data of the first cloud disk comprises flow control parameters and capacity utilization; determining a change strategy for the first cloud disk based on the operating data of the first cloud disk; and providing a recommendation interface to tenants of the first cloud disk, the recommendation interface comprising the change strategy.

[0009] Based on the above scheme, the change strategy for the cloud disk is determined according to the operation data of the cloud disk, and the change strategy is recommended to the tenant of the cloud disk. The cloud disk service change recommendation method provided in the embodiment of the present application can recommend a suitable change strategy to the tenant, so that the tenant adopts a suitable change strategy to improve the performance of the cloud disk, thereby improving the service experience.

[0010] In combination with the first aspect, in certain implementations of the first aspect, the change strategy includes one or more of not upgrading, expanding the cloud disk capacity, switching to a second cloud disk, or automatically increasing performance during flow control, wherein the performance of the second cloud disk is greater than the performance of the first cloud disk.

[0011] Based on the above scheme, the cloud disk service change recommendation method provided in the embodiment of the present application can recommend at least four different change strategies based on the operating data of the tenant's cloud disk. For example, when the tenant does not need to upgrade, it can be recommended not to upgrade, so as to avoid the tenant from over-upgrading the cloud disk and paying a higher cost. For another example, when the tenant's performance is low due to insufficient cloud disk capacity, it can be recommended to expand the cloud disk capacity to effectively improve the performance of the tenant's cloud disk. For another example, when the tenant occasionally has high-performance requirements, it can be recommended to automatically increase the performance during flow control, thereby improving the tenant's usage experience without excessively increasing the tenant's expenditure. For another example, when the tenant really needs to switch to a higher-performance cloud disk, it is recommended to switch to a new cloud disk. Therefore, the cloud disk service change recommendation method provided in the embodiment of the present application can flexibly provide tenants with change strategies, save tenants' usage costs, and improve tenants' usage experience.

[0012] In combination with the first aspect, in certain implementations of the first aspect, a change strategy for the first cloud disk is determined based on the operating data of the first cloud disk, including: when the flow control parameter is greater than or equal to a first threshold, determining the change strategy based on the capacity utilization rate.

[0013] Based on the above solution, when the flow control parameters are high, the change strategy can be determined according to the capacity utilization rate. For example, if the flow control is caused by insufficient capacity, the cloud disk capacity can be expanded. For another example, if the problem of insufficient capacity is eliminated, it may be necessary to switch to a new cloud disk or use other methods to improve the performance of the cloud disk. In this way, the cause of flow control can be analyzed by capacity utilization, so as to recommend appropriate change strategies to tenants, save tenants' usage costs, and improve tenants' usage experience.

[0014] In combination with the first aspect, in certain implementations of the first aspect, the change strategy is determined based on the capacity utilization rate, including: when the capacity utilization rate is greater than a second threshold, determining the change strategy to expand the cloud disk capacity; when the capacity utilization rate is less than or equal to the second threshold, determining the change strategy based on the flow control parameter.

[0015] Based on the above solution, when the capacity utilization rate is high, the reason for flow control may be insufficient capacity, so the change strategy is determined to expand the cloud disk capacity, effectively improving the performance of the tenant cloud disk and improving the tenant's user experience. When the capacity utilization rate is low, the reason for flow control is not insufficient capacity, so the change strategy is further determined based on the flow control parameters to avoid excessive expansion and save tenants' usage costs.

[0016] In combination with the first aspect, in certain implementations of the first aspect, the operating data of the first cloud disk also includes the current capacity of the first cloud disk, wherein determining that the change strategy is to expand the cloud disk capacity includes: determining the target capacity based on the current capacity of the first cloud disk; and determining that the change strategy is to expand the cloud disk capacity to the target capacity.

[0017] Based on the above solution, when the cloud disk capacity needs to be expanded, the target capacity can also be calculated, and the tenants can be recommended to upgrade the cloud disk to expand the cloud disk capacity to the target capacity, thereby effectively improving the performance of the tenant's cloud disk, avoiding frequent triggering of flow control, and improving the tenant's user experience.

[0018] In combination with the first aspect, in certain implementations of the first aspect, the change strategy is determined based on the flow control parameter, including: when the flow control parameter is less than a third threshold, determining that the change strategy is to automatically increase performance during flow control, wherein the third threshold is greater than the first threshold; when the flow control parameter is greater than or equal to the third threshold, determining that the change strategy is to switch to a second cloud disk.

[0019] Based on the above solution, when the flow control is triggered very frequently, the change strategy can be determined to replace the new cloud disk with higher performance to meet the tenant's long-term high-performance needs and improve the tenant's user experience. When the flow control is triggered between not too frequent and very frequent, the change strategy can be determined to automatically increase performance during flow control, so that when high-performance needs arise, the performance can be temporarily increased to improve the tenant's user experience. When the high-performance needs disappear, the previous cloud disk can be used to save the tenant's usage costs.

[0020] In combination with the first aspect, in certain implementations of the first aspect, the operating data of the first cloud disk also includes performance parameters, wherein determining that the change strategy is to switch to the second cloud disk includes: determining the target performance based on the performance parameters of the first cloud disk; and determining that the change strategy is to switch to a second cloud disk that meets the target performance.

[0021] Based on the above solution, when performance needs to be improved, the target performance can also be calculated, and tenants can be recommended to upgrade the cloud disk to a new cloud disk that meets the target performance, thereby effectively avoiding frequent triggering of flow control and improving the tenant's user experience.

[0022] In combination with the first aspect, in certain implementations of the first aspect, a change strategy for the first cloud disk is determined based on the operating data of the first cloud disk, including: when the flow control parameter is less than a first threshold, determining that the change strategy is not to upgrade.

[0023] Based on the above solution, when the flow control parameters are low, it means that the tenant's current cloud disk performance can meet the operation requirements and there is no need to change the cloud disk service. Therefore, the change strategy can be not to upgrade, thereby saving the tenant's usage costs.

[0024] In combination with the first aspect, in some implementations of the first aspect, the recommendation interface also includes operating data of the first cloud disk.

[0025] Based on the above solution, the recommendation interface also includes the operation data of the cloud disk, so that the tenants can clearly know the operation status of the cloud disk, which helps the tenants make decisions and improves the tenants' usage experience.

[0026] In combination with the first aspect, in certain implementations of the first aspect, the method also includes: obtaining operating data of the storage pool; determining the upgrade time corresponding to the change strategy based on the operating data of the storage pool; wherein, providing a recommendation interface to the tenants of the first cloud disk includes: providing a recommendation interface to the tenants of the first cloud disk, the recommendation interface also including the upgrade time.

[0027] Based on the above scheme, the cloud disk service change recommendation method provided in the embodiment of the present application can determine the upgrade time according to the storage pool operation data, and provide the upgrade time to the tenant, which helps the tenant make a decision on whether to upgrade and improves the tenant's user experience.

[0028] In a second aspect, an embodiment of the present application provides a cloud disk service change recommendation device, which includes a module for implementing the first aspect or any possible implementation method of the first aspect.

[0029] In a third aspect, a computing device cluster is provided, comprising at least one computing device, each computing device comprising a processor and a memory; the processor of the at least one computing device is used to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the recommended method for changing the cloud disk service of the first aspect or any possible implementation of the first aspect.

[0030] In a fourth aspect, a computer program product comprising instructions is provided. When the instructions are executed by a computing device cluster, the computing device cluster executes the recommended method for changing the cloud disk service of the first aspect or any possible implementation of the first aspect.

[0031] In a fifth aspect, a computer-readable storage medium is provided, comprising computer program instructions. When the computer program instructions are executed by a computing device cluster, the computing device cluster executes the method for recommending cloud disk service changes of the first aspect or any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a system diagram based on a cloud server system according to an embodiment of the present application.

[0033] Figure 2 It is a schematic flowchart of a recommended method for changing a cloud disk service provided in an embodiment of the present application.

[0034] Figure 3 It is a schematic flowchart of determining a change strategy provided in an embodiment of the present application.

[0035] Figure 4 It is a schematic diagram of a recommendation interface provided in an embodiment of the present application.

[0036] Figure 5 It is a schematic block diagram of a cloud disk service change recommendation device provided in an embodiment of the present application.

[0037] Figure 6 It is a schematic block diagram of a computing device provided in an embodiment of the present application.

[0038] Figure 7It is a schematic block diagram of a computing device cluster provided in an embodiment of the present application.

[0039] Figure 8 It is a schematic block diagram of another computing device cluster provided in an embodiment of the present application.

[0040] Fig. 9 It is a schematic block diagram of a cloud disk service change recommendation system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0042] The present application will present various aspects, embodiments or features around a system that may include multiple devices, components, modules, etc. It should be understood and appreciated that each system may include additional devices, components, modules, etc., and / or may not include all of the devices, components, modules, etc. discussed in conjunction with the figures. In addition, combinations of these schemes may also be used.

[0043] In addition, in the embodiments of the present application, words such as "exemplary" and "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present concepts in a concrete way.

[0044] The business scenarios described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Ordinary technicians in this field can know that with the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0045] References to "one embodiment" or "some embodiments" etc. described in this specification mean that a particular feature, structure or characteristic described in conjunction with the embodiment is included in one or more embodiments of the present application. Thus, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0046] Figure 1 It is a system diagram based on a cloud server system according to an embodiment of the present application.

[0047] like Figure 1As shown, the cloud management platform 110 is used to manage the infrastructure that provides multiple cloud services, the infrastructure includes multiple cloud data centers, each cloud data center includes multiple cloud servers, each cloud server includes cloud service resources, and provides corresponding cloud services for tenants. For example, multiple microservices can run in a cloud server.

[0048] The cloud management platform 110 provides an access interface (such as an application program interface (API)). The tenant can operate the client remote access access interface to register a cloud account and password on the cloud management platform and log in to the cloud management platform. After the cloud management platform successfully authenticates the cloud account and password, the tenant can further pay to select and purchase a virtual machine with specific specifications (processor, memory, disk) on the cloud management platform. After the payment is successful, the cloud management platform provides the remote login account and password of the purchased virtual machine. The client can remotely log in to the virtual machine and install and run the tenant's application in the virtual machine. Tenants of cloud services can be individuals, enterprises, schools, hospitals, administrative agencies, etc.

[0049] The functions of the cloud management platform 110 include, but are not limited to, user console, computing management service, network management service, storage management service, authentication service, and image management service. The user console provides an API to interact with tenants, the computing management service is used to manage servers running virtual machines and containers and bare metal servers, the network management service is used to manage network services (such as gateways, firewalls, etc.), the storage management service is used to manage storage services (such as data bucket services), the authentication service is used to manage tenant accounts and passwords, and the image management service is used to manage virtual machine images. Tenants can use the client 130 to log in to the cloud management platform 110 through the Internet 120 to manage the rented cloud services.

[0050] For example, multiple cloud servers can form a storage pool, and multiple cloud disks of the same or different specifications can be divided according to the performance (such as read and write bandwidth, input and output frequency) and total capacity of the storage pool. Tenants can rent one or more of these cloud disks. It should be noted that the multiple cloud disks rented by a tenant can come from one storage pool or from multiple storage pools.

[0051] A cloud disk can be a virtual disk combined with a cloud virtual machine in the form of block storage. Tenants can create and change file systems on the cloud disk, as well as perform operations such as formatting. Tenants can read and write to the cloud disk through the cloud management platform 110. The number of read and write operations performed by the cloud disk per second can be called input / output per second (IOPS), and the amount of data transmitted by the cloud disk per second can be called throughput. In a cloud disk, there are upper limits on IOPS and throughput, which are respectively called IOPS upper limit and throughput upper limit. The IOPS upper limit and throughput upper limit can describe the performance of the cloud disk.

[0052] The following lists the performance and capacity of some cloud disks.

[0053] Enhanced solid-state drive (ESSD): The API is ESSD, the IOPS limit is 128,000, and the throughput limit is 1,000 MB / s.

[0054] Ultra-high IO cloud hard disk (solid-state drive, SSD): API is SSD, IOPS upper limit is 50,000; throughput upper limit is 350MB / s.

[0055] General SSD V2: API is GPSSD2, IOPS upper limit is 128,000, and throughput upper limit is 1,000 MB / s.

[0056] General-purpose SSD: API is GPSSD, IOPS upper limit is 20,000, and throughput upper limit is 250 MB / s.

[0057] High IO: The API is SAS, the IOPS limit is 5000, and the throughput limit is 150 MB / s.

[0058] Normal IO: API is SATA, IOPS upper limit is 2200, and throughput upper limit is 50 MB / s.

[0059] IOPS is the number of read and write operations performed by the cloud disk per second. Throughput is the amount of data transmitted by the cloud disk per second, that is, the amount of data read and written.

[0060] When the performance of a cloud disk exceeds the upper limit of the performance (such as the IOPS upper limit or the throughput upper limit), the cloud disk will trigger flow control (referred to as "flow control"). For example, the flow control device will send a back pressure signal to the upstream of the cloud disk. The back pressure signal is used to instruct the upstream of the cloud disk to reduce or stop sending data to the cloud disk to ensure that the performance of the cloud disk does not exceed the upper limit. Therefore, flow control will increase the delay in sending data, reduce business processing efficiency, and reduce tenant experience.

[0061] Frequent triggering of flow control indicates that the current performance limit of the cloud disk cannot meet the needs of tenants. Tenants can upgrade the cloud disk through the cloud management platform 110, for example, by selecting operations such as expanding the capacity of the cloud disk and changing the type of the cloud disk. In other words, tenants can upgrade the cloud disk according to their own needs so that the upgraded cloud disk has appropriate performance and capacity.

[0062] Generally speaking, the performance and capacity of cloud disks are coupled. Taking SSD cloud disks as an example, the throughput can be calculated by the following formula:

[0063] Throughput = min(350,120+0.5×capacity)

[0064] According to the above formula, if you create a 100GB SSD cloud disk, the upper limit of the throughput is 170MB / s; if you create a 200GB SSD cloud disk, the upper limit of the throughput is 220MB / s; if you create a 500GB SSD cloud disk, the upper limit of the throughput is 350MB / s. That is to say, in an SSD cloud disk, when the capacity is below 460GB, increasing the capacity can increase the upper limit of the throughput. When the capacity exceeds 460GB, increasing the capacity cannot increase the upper limit of the throughput. IOPS and capacity can also be coupled, that is, for a certain cloud disk, there is a value. When the capacity of the cloud disk is above this value, increasing the capacity cannot increase the upper limit of IOPS. When the capacity of the cloud disk is below this value, increasing the capacity can increase the upper limit of IOPS. In addition, IOPS and throughput will also affect each other.

[0065] During the use of the cloud disk, since part of the capacity will be used, the upper limit of performance such as throughput may be affected by the capacity utilization rate. When the capacity utilization rate is high, the performance of the cloud disk will be affected by insufficient capacity, and increasing the capacity can improve performance. For example, the total capacity of the tenant's cloud disk is 200GB, the capacity utilization rate is 99%, and the remaining capacity is 2GB. If the tenant wants to write 3GB of new data at this time, due to the insufficient remaining cloud disk capacity, the cloud disk needs to release part of the capacity (such as cached data such as snapshots) so that the tenant can write 3GB of data. However, it takes a certain amount of time to release the capacity, and flow control will be triggered during this period. Tenants can only feel the results of this flow control, but are not clear about the reasons for the flow control.

[0066] Performance and capacity can also be partially decoupled. For example, the baseline value of the IOPS upper limit provided by the general-purpose SSD V2 cloud disk with API GPSSD2 is 3000, and the baseline value of the throughput upper limit is 125MiB / s. While keeping the capacity size unchanged, the IOPS upper limit and throughput upper limit of the cloud disk can be flexibly configured. The throughput upper limit and IOPS upper limit can be set freely, among which the IOPS upper limit can be pre-configured by the tenant, ranging from 3000 to 128000. The throughput upper limit can also be configured by the tenant, ranging from 125 to 1000MiB / s.

[0067] However, if you want tenants to upgrade the cloud disk on their own, you need to understand the real reason for the flow control. For example, tenants need to clarify whether the flow control occurs because the cloud disk itself has insufficient performance or simply because the cloud disk has a high capacity utilization rate. If it is because the cloud disk itself has insufficient performance, you need to replace it with a new cloud disk with higher performance. Expanding the capacity of the original cloud disk will not significantly improve performance and cannot solve the problem. If it is because the cloud disk has a high capacity utilization rate, expanding the cloud disk can significantly improve performance, and replacing it with a new cloud disk with higher performance will bring additional costs to the tenant. However, most tenants do not have the ability to analyze the cause of flow control and formulate appropriate change strategies, which results in tenants being unable to solve the problem of insufficient performance, thus frequently triggering flow control, affecting the tenant's user experience, or causing tenants to upgrade excessively and invest too much cost in changing cloud disk services.

[0068] Therefore, how to enable tenants to adopt appropriate change strategies to improve the performance of cloud disks is an urgent problem to be solved.

[0069] Figure 2 1 is a schematic flow chart of a method 200 for recommending a change in a cloud disk service provided in an embodiment of the present application. The method 200 can recommend a suitable change strategy to a tenant, thereby improving the performance of the cloud disk. The method 200 can be executed by any device with computing functions, such as a cloud management platform 110. The method 200 can be applied to a cloud management platform 110, which is used to manage an infrastructure for providing cloud services, the infrastructure including a storage pool consisting of storage spaces of multiple cloud servers, which is virtually divided into multiple cloud disks.

[0070] S210, obtaining operation data of a first cloud disk among multiple cloud disks, wherein the operation data of the first cloud disk includes flow control parameters and capacity utilization rate.

[0071] The first cloud disk may be any cloud disk of the tenant, and the operation data of the first cloud disk may be the operation data of the first cloud disk in the past period of time. This application does not limit the specific time, for example, it may be the operation data in the past few hours, the past few days, or the past few months. It is understandable that the operation data also includes the current operation data.

[0072] This application does not limit the specific form of the flow control parameter. The flow control parameter can be understood as the flow control situation. The flow control parameter can include the number of flow control times or the flow control frequency, etc. For example, the first cloud disk has triggered a total of 90 flow controls in the past 30 days. The flow control parameter can be 90, which means that 90 flow controls have been triggered in the past 30 days. In this case, the flow control parameter can be understood as the number of flow controls. The flow control parameter can also be 3, which means that in the past 30 days, an average of 3 flow controls were triggered per day. In this case, the flow control parameter can be understood as the flow control frequency.

[0073] This application does not limit the specific form of capacity utilization rate, and capacity utilization rate can also be understood as capacity usage. For example, if the total capacity of the first cloud disk is 100GB and the used capacity is 80GB, then the capacity utilization rate is 80%. The capacity utilization rate can also be expressed in absolute values, that is, it is understood as the capacity usage. For example, if the total capacity of the first cloud disk is 100GB and the used capacity is 80GB, then the capacity utilization rate is also 80.

[0074] It should be noted that the operation data is not limited to flow control parameters and capacity utilization. For example, the operation data may also include the performance of the first cloud disk, such as IOPS, throughput, etc.

[0075] S220: Determine a change strategy for the first cloud disk according to the operating data of the first cloud disk.

[0076] The embodiments of S220 can be found in the following text and will not be described in detail here.

[0077] S230: Provide a recommendation interface to the tenant of the first cloud disk, where the recommendation interface includes the change strategy.

[0078] Based on the above scheme, the change strategy for the cloud disk is determined according to the operation data of the cloud disk, and the change strategy is recommended to the tenant of the cloud disk. The cloud disk service change recommendation method provided in the embodiment of the present application can recommend a suitable change strategy to the tenant, so that the tenant adopts the suitable change strategy to improve the performance of the cloud disk.

[0079] In some embodiments, the change strategy includes one or more of not upgrading, expanding the cloud disk capacity, switching to a second cloud disk, or automatically increasing performance during flow control, wherein the performance of the second cloud disk is greater than the performance of the first cloud disk.

[0080] Among them, not upgrading can mean informing the tenant that the first cloud disk is in good operating condition and does not need to be upgraded. Not upgrading can also mean not providing the recommendation interface to the tenant. Expanding the capacity of the cloud disk can mean expanding the current capacity of the first cloud disk to a capacity larger than the current capacity. Switching to the second cloud disk can mean that the tenant no longer rents the first cloud disk and rents the second cloud disk at the same time. In the case where the tenant determines that the change strategy is to automatically increase performance during flow control, the capacity and performance of the first cloud disk when there is no flow control are consistent with those before the change strategy is determined. The performance of the first cloud disk is improved during the duration of flow control, and it is still restored to the same level as before the change strategy is determined when the flow control ends. It can be understood that the change strategy of automatically increasing performance during flow control may not change the capacity of the cloud disk.

[0081] Based on the above scheme, the method for recommending cloud disk service changes provided in the embodiment of the present application can recommend at least four different change strategies based on the operating data of the tenant's cloud disk. For example, when the tenant does not need to upgrade, it can be recommended not to upgrade, so as to avoid the tenant from over-upgrading the cloud disk and paying a higher cost. For another example, when the tenant's performance is low due to insufficient cloud disk capacity, it can be recommended to expand the cloud disk capacity to effectively improve the performance of the tenant's cloud disk. For another example, when the tenant occasionally has high-performance requirements, it can be recommended to automatically increase the performance during flow control, thereby improving the tenant's usage experience without excessively increasing the tenant's expenditure. For another example, when the tenant really needs to switch to a higher-performance cloud disk, it is recommended to switch to a new cloud disk. Therefore, the method for recommending cloud disk service changes provided in the embodiment of the present application can flexibly provide tenants with change strategies, save tenants' usage costs, and improve tenants' usage experience.

[0082] Combine the following Figure 3 Some embodiments of S220 are described in detail.

[0083] Figure 3 It is a schematic flowchart of determining a change strategy provided in an embodiment of the present application. Figure 3 Can be combined with S220, Figure 3 The illustrated process may be executed by any device having computing capabilities, such as the cloud management platform 110 .

[0084] See also Figure 3 In some embodiments, S220 includes: when the flow control parameter is greater than or equal to a first threshold, determining the change strategy according to the capacity utilization rate.

[0085] The first threshold can be preset, for example, the first threshold can be set to flow control 5 times a day. If the flow control parameter is greater than or equal to the first threshold, it means that the tenant's first cloud disk has been subjected to flow control for a large number of times, and the performance of the first cloud disk may not meet the performance required by the tenant to run the application.

[0086] Based on the above solution, when the flow control parameters are high, the change strategy can be determined according to the capacity utilization rate. For example, if the flow control is caused by insufficient capacity, the cloud disk capacity can be expanded. For another example, if the problem of insufficient capacity is eliminated, it may be necessary to switch to a new cloud disk or use other methods to improve the performance of the cloud disk. In this way, the cause of flow control can be analyzed by capacity utilization, so as to recommend appropriate change strategies to tenants, save tenants' usage costs, and improve tenants' usage experience.

[0087] See also Figure 3 In some embodiments, S220 includes: when the flow control parameter is less than a first threshold, determining that the change strategy is not to upgrade.

[0088] Based on the above solution, when the flow control parameters are low, it means that the tenant's current cloud disk performance can meet the operation requirements and there is no need to change the cloud disk service. Therefore, the change strategy can be not to upgrade, thereby saving the tenant's usage costs.

[0089] See also Figure 3 In some embodiments, the change strategy is determined according to the capacity utilization rate, including: when the capacity utilization rate is greater than a second threshold, determining the change strategy to expand the cloud disk capacity; when the capacity utilization rate is less than or equal to the second threshold, determining the change strategy according to the flow control parameter.

[0090] The second threshold may be preset, for example, the second threshold may be set to 90%.

[0091] If the capacity utilization rate is greater than the second threshold, it means that the capacity utilization rate of the tenant's first cloud disk is high, and the reasons for excessive flow control and insufficient performance may be insufficient capacity. Therefore, it can be determined that the change strategy is to expand the cloud disk capacity. If the capacity utilization rate is less than or equal to the second threshold, it means that the capacity utilization rate of the tenant's first cloud disk is not high. Even if the cloud disk capacity is increased, the performance of the first cloud disk cannot be significantly improved. Therefore, the change strategy can be further determined based on the frequency of high-performance requirements. For example, when high-performance requirements occur more frequently, a new high-performance cloud disk can be used to continuously provide higher performance. For another example, when high-performance requirements do not occur frequently, high performance can be provided when high performance is needed to save tenants' usage costs.

[0092] Based on the above solution, when the capacity utilization rate is high, the reason for flow control may be insufficient capacity, so the change strategy is determined to expand the cloud disk capacity, effectively improving the performance of the tenant cloud disk and improving the tenant's user experience. When the capacity utilization rate is low, the reason for flow control is not insufficient capacity, so the change strategy is further determined based on the flow control parameters to avoid excessive expansion and save tenants' usage costs.

[0093] In some embodiments, the operating data of the first cloud disk also includes the current capacity of the first cloud disk, wherein determining that the change strategy is to expand the cloud disk capacity includes: determining the target capacity based on the current capacity of the first cloud disk; and determining that the change strategy is to expand the cloud disk capacity to the target capacity.

[0094] The current capacity may be the current total capacity of the first cloud disk. In other words, the current capacity may be the capacity of the first cloud disk before the change strategy is determined.

[0095] For example, assuming that the current capacity of an SSD cloud disk with a capacity of 100GB is 98% in capacity utilization, the capacity utilization rate is high, resulting in frequent triggering of flow control. According to the current capacity, the target capacity can be determined. In some embodiments, multiple gear capacities can be preset. When the capacity of the tenant cloud disk needs to be expanded, the target capacity can be determined to be a higher gear capacity than the current capacity. For example, the gears can be preset as 100GB, 200GB, and 300GB. Assuming that the current capacity of the tenant cloud disk is 200GB, the target capacity can be determined to be 300GB. In other embodiments, the capacity increase ratio can be preset. For example, the increase ratio can be set to 100%. Assuming that the current capacity of the tenant cloud disk is 200GB, the target capacity can be determined to be 400GB.

[0096] Based on the above solution, when the cloud disk capacity needs to be expanded, the target capacity can also be calculated, and the tenants can be recommended to upgrade the cloud disk to expand the cloud disk capacity to the target capacity, thereby effectively improving the performance of the tenant's cloud disk, avoiding frequent triggering of flow control, and improving the tenant's user experience.

[0097] See also Figure 3 In some embodiments, the change strategy is determined based on the flow control parameter, including: when the flow control parameter is less than a third threshold, determining that the change strategy is to automatically increase performance during flow control, wherein the third threshold is greater than the first threshold; when the flow control parameter is greater than or equal to the third threshold, determining that the change strategy is to switch to a second cloud disk.

[0098] The third threshold is a value greater than the first threshold. If the flow control parameter is greater than or equal to the third threshold, it means that the tenant's first cloud disk triggers flow control very frequently, indicating that the tenant has long-term high-performance requirements. Therefore, it can be determined that the change strategy is to replace a new cloud disk with higher performance. If the flow control parameter is less than the third threshold, it means that although the tenant's first cloud disk needs to be upgraded, the tenant's demand for high performance is only occasional. Therefore, it can be determined that the change strategy is to automatically increase performance when flow control is used. In this way, when high-performance requirements arise, performance can be temporarily increased to improve the tenant's user experience. When high-performance requirements disappear, the first cloud disk can be used without additional expenses, thereby saving the tenant's usage costs.

[0099] Based on the above solution, when the flow control is triggered very frequently, the change strategy can be determined to replace the new cloud disk with higher performance to meet the tenant's long-term high-performance needs and improve the tenant's user experience. When the flow control is triggered between not too frequent and very frequent, the change strategy can be determined to automatically increase performance during flow control, so that when high-performance needs arise, the performance can be temporarily increased to improve the tenant's user experience. When the high-performance needs disappear, the previous cloud disk can be used to save the tenant's usage costs.

[0100] In some embodiments, the operating data of the first cloud disk also includes performance parameters, wherein determining the change strategy to switch to a second cloud disk includes: determining the target performance based on the performance parameters of the first cloud disk; and determining the change strategy to switch to a second cloud disk that meets the target performance.

[0101] The performance parameters may include a performance upper limit. The performance upper limit of the first cloud disk may be understood as the maximum performance of the first cloud disk, such as maximum IOPS, maximum throughput, and the like.

[0102] According to the performance parameters, the target performance can be determined. In some embodiments, multiple performance levels can be preset. When the tenant needs to switch to a higher performance cloud disk, the target performance can be determined to be a higher performance level than the current performance limit. In other embodiments, the performance improvement ratio can be preset.

[0103] Based on the above solution, when performance needs to be improved, the target performance can also be calculated, and tenants can be recommended to upgrade the cloud disk to a new cloud disk that meets the target performance, thereby effectively avoiding frequent triggering of flow control and improving the tenant's user experience.

[0104] In some embodiments, the method 200 also includes: obtaining the operating data of the storage pool; determining the upgrade time corresponding to the change strategy based on the operating data of the storage pool; wherein, providing a recommendation interface to the tenants of the first cloud disk includes: providing a recommendation interface to the tenants of the first cloud disk, and the recommendation interface also includes the upgrade time.

[0105] For example, the operation data of the storage pool may include the throughput limit, IOPS limit, real-time read / write latency, real-time throughput, real-time IOPS, performance warning times, etc. of the storage pool where the first cloud disk is located. Multiple cloud disks can be created in a storage pool, and the sum of the performance of these cloud disks can be regarded as the performance of the storage pool. For example, the sum of the throughput of these cloud disks at a certain moment can be regarded as the throughput of the storage pool at that moment.

[0106] If the performance of the storage pool reaches the upper limit, a "pool explosion" will occur. To avoid this, you can set a performance warning threshold, for example, the performance warning threshold is 70% of the performance parameter. In this way, when the performance of the storage pool reaches 70% of the performance parameter, a performance warning will be triggered.

[0107] Based on the operation data of the storage pool, it can be determined whether the cloud disk can execute the change policy in the storage pool. If it can be executed, it can be determined that the required upgrade time is short, for example, it can be determined that the upgrade time is a predetermined shorter time. If it cannot be executed, then the cloud disk needs to be migrated to another storage pool for upgrade. On the one hand, it is necessary to determine the storage pool that can accommodate the upgraded cloud disk, and on the other hand, it is necessary to migrate the data in the cloud disk, so the upgrade time is longer. In this case, the upgrade time can be determined based on factors such as the operation data of each storage pool and the data that needs to be migrated from the current cloud disk.

[0108] Based on the above scheme, the cloud disk service change recommendation method provided in the embodiment of the present application can determine the upgrade time according to the storage pool operation data, and provide the upgrade time to the tenant, which helps the tenant make a decision on whether to upgrade and improves the tenant's user experience.

[0109] Combine the following Figure 4 The present application describes in detail an embodiment of a recommendation interface.

[0110] Figure 4 It is a schematic diagram of a recommendation interface 400 provided in an embodiment of the present application. Figure 4 This is merely exemplary and does not constitute a limitation to the present application. For example, the change strategy may also be shown in other forms. For another example, the recommendation interface 400 includes two change strategies, or may include more or fewer change strategies.

[0111] In some embodiments, the recommendation interface also includes the operation data of the first cloud disk, for example, the capacity utilization rate and performance data of the cloud disk.

[0112] Based on the above solution, the recommendation interface also includes the operation data of the cloud disk, so that the tenants can clearly know the operation status of the cloud disk, which helps the tenants make decisions and improves the tenants' usage experience.

[0113] The recommendation interface 400 may include a risk level, which can comprehensively describe the current status of the tenant's use of the cloud disk. For example, the tenant frequently triggers flow control, the capacity utilization rate is high, and the performance utilization rate is also high, and the risk level can be "high". For another example, the tenant's capacity utilization rate is low, and the performance utilization rate is also low, and the risk level can be "good". It can be understood that there can be more levels of risk levels, for example, the risk level can be "extremely high", "high", "medium", "low", "good", etc., and this application does not limit this.

[0114] In some embodiments, the risk level can be determined based on the flow control parameters. For example, a sample is taken every minute to determine whether flow control occurs. If flow control occurs in this minute, the count of the flow control parameter is increased by 1. In this way, the highest flow control parameter per day is 1440. If the daily flow control parameter is less than 144, that is, within 10%, the risk can be determined to be "low". If the daily flow control parameter is between 144 and 720, that is, 10% to 50%, the risk can be determined to be "medium". If the daily flow control parameter is greater than 720, that is, more than 50%, the risk can be determined to be "high". It should be noted that the above embodiments are merely illustrative and do not constitute a limitation of the present application. Obviously, the risk level can also be determined in other ways.

[0115] For a cloud disk, the recommendation interface 400 may also provide multiple change strategies. For example, for a cloud disk, if the cloud disk needs to expand the cloud disk capacity, multiple change strategies for the cloud disk may be provided to the tenant, such as expanding less capacity, expanding more capacity, and expanding a lot of capacity. These change strategies may be sorted according to multiple dimensions such as upgrade cost and risk level, providing tenants with more choices. For example, for a tenant with multiple cloud disks, change strategies for these cloud disks may be provided, such as Figure 4 As shown, change strategies for 2 cloud disks can be provided at a time. This application is not limited to this, for example, more or fewer change strategies can be provided at a time. These change strategies can be sorted by multiple dimensions such as tenant satisfaction and tenant type. For example, if a tenant often uses type A applications, and the database shows that tenants with type A applications are more satisfied with change strategy B, then change strategy B can be recommended to the tenant first.

[0116] See also Figure 4 In some embodiments, the recommendation interface 400 may further include a control 410. When the tenant clicks the control 410, it indicates that the tenant agrees to the change policy above the control 410, and the backend will upgrade the cloud disk according to the change policy.

[0117] See also Figure 4 For the first cloud disk and the second cloud disk, what the tenants perceive are high flow control parameters and large delays. However, the change strategies for the first cloud disk and the second cloud disk are completely different. The reason is that the flow control of the first cloud disk is caused by the excessive capacity utilization rate, and the flow control of the third cloud disk is caused by IOPS exceeding the performance parameters. However, tenants are often unclear about the reasons for the flow control and are prone to blindly upgrade. If the tenant replaces the first cloud disk with a higher-performance cloud disk, the problem may not be solved and costs will be increased. Therefore, the cloud disk service change recommendation method provided in the embodiment of the present application can help tenants select appropriate change strategies, thereby improving the tenant's user experience.

[0118] The method embodiments of the present application are described in detail above. The device embodiments of the present application are described below. The device embodiments correspond to the method embodiments, so the parts not described in detail can refer to the previous method embodiments. The device can implement any possible implementation of the above method.

[0119] Figure 5 It is a schematic block diagram of a cloud disk service change recommendation device 500 provided in an embodiment of the present application.

[0120] Figure 5 As shown, the cloud disk service change recommendation device 500 is applied to a cloud management platform 110, which is used to manage an infrastructure for providing cloud services, wherein the infrastructure includes a storage pool composed of storage spaces of multiple cloud servers, and the storage pool is virtually divided into multiple cloud disks. The cloud disk service change recommendation device 500 includes: an acquisition module 510, which is used to obtain operating data of a first cloud disk among multiple cloud disks, wherein the operating data of the first cloud disk includes flow control parameters and capacity utilization rate; a processing module 520, which is used to determine a change strategy for the first cloud disk based on the operating data of the first cloud disk; and a recommendation module 530, which is used to provide a recommendation interface to tenants of the first cloud disk, wherein the recommendation interface includes the change strategy.

[0121] In some embodiments, the processing module 520 is specifically used to: determine the change strategy according to the capacity utilization rate when the flow control parameter is greater than or equal to the first threshold.

[0122] In some embodiments, the processing module 520 is specifically used to: when the capacity utilization rate is greater than a second threshold, determine that the change strategy is to expand the cloud disk capacity; when the capacity utilization rate is less than or equal to the second threshold, determine the change strategy according to the flow control parameter.

[0123] In some embodiments, the operating data of the first cloud disk also includes the current capacity of the first cloud disk, wherein the processing module 520 is specifically used to: determine the target capacity based on the current capacity of the first cloud disk; and determine that the change strategy is to expand the cloud disk capacity to the target capacity.

[0124] In some embodiments, the processing module 520 is specifically used to, when the flow control parameter is less than a third threshold, determine that the change strategy is to automatically increase performance during flow control, wherein the third threshold is greater than the first threshold; when the flow control parameter is greater than or equal to the third threshold, the processing module 520 is specifically used to determine that the change strategy is to switch to a second cloud disk.

[0125] In some embodiments, the operating data of the first cloud disk also includes performance parameters, wherein the processing module 520 is specifically used to: determine the target performance based on the performance parameters of the first cloud disk; and determine that the change strategy is to switch to a second cloud disk that meets the target performance.

[0126] In some embodiments, the processing module 520 is specifically used to: when the flow control parameter is less than a first threshold, determine that the change strategy is not to upgrade.

[0127] In some embodiments, the acquisition module 510 is also used to obtain the operating data of the storage pool; the processing module 520 is also used to determine the upgrade time corresponding to the change strategy based on the operating data of the storage pool; wherein, the recommendation module 530 is also used to provide a recommendation interface to the tenants of the first cloud disk, and the recommendation interface also includes the upgrade time.

[0128] Specifically, the specific implementation of various operations of the recommended method for changing the cloud disk service performed by the device 500 can refer to the description of the relevant content in the above method embodiment, which will not be repeated here.

[0129] Among them, the acquisition module 510, the processing module 520 and the recommendation module 530 can all be implemented by software, or can be implemented by hardware. Exemplarily, the following takes the acquisition module 510 as an example to introduce the implementation of the acquisition module 510. Similarly, the implementation of the processing module 520 and the recommendation module 530 can refer to the implementation of the acquisition module 510.

[0130] As an example of a software functional unit, the acquisition module 510 may include code running on a computing instance. Among them, the computing instance may include at least one of a physical host (computing device), a virtual machine, and a container. Further, the above-mentioned computing instance may be one or more. For example, the acquisition module 510 may include code running on multiple hosts / virtual machines / containers. It should be noted that the multiple hosts / virtual machines / containers used to run the code may be distributed in the same region (region) or in different regions. Furthermore, the multiple hosts / virtual machines / containers used to run the code may be distributed in the same availability zone (AZ) or in different AZs, each AZ including a data center or multiple data centers with similar geographical locations. Among them, usually a region may include multiple AZs.

[0131] Similarly, multiple hosts / virtual machines / containers used to run the code can be distributed in the same virtual private cloud (VPC) or in multiple VPCs. Usually, a VPC is set up in a region. For cross-region communication between two VPCs in the same region and between VPCs in different regions, a communication gateway needs to be set up in each VPC to achieve interconnection between VPCs through the communication gateway.

[0132] As an example of a hardware functional unit, the acquisition module 510 may include at least one computing device, such as a server, etc. Alternatively, the acquisition module 510 may also be a device implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD). The PLD may be a complex programmable logical device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0133] The multiple computing devices included in the acquisition module 510 can be distributed in the same region or in different regions. The multiple computing devices included in the acquisition module 510 can be distributed in the same AZ or in different AZs. Similarly, the multiple computing devices included in the Java acquisition module 510 can be distributed in the same VPC or in multiple VPCs. The multiple computing devices can be any combination of computing devices such as servers, ASICs, PLDs, CPLDs, FPGAs, and GALs.

[0134] It should be noted that, in other embodiments, the acquisition module 510 can be used to execute any step in the recommended method for changing the cloud disk service, the processing module 520 can be used to execute any step in the recommended method for changing the cloud disk service, and the steps that the acquisition module 510, the processing module 520 and the recommendation module 530 are responsible for implementing can be specified as needed. The full functions of the cloud disk service change recommendation device 500 are realized by respectively implementing different steps in the recommended method for changing the cloud disk service through the acquisition module 510, the processing module 520 and the recommendation module 530.

[0135] The present application also provides a computing device 600. Figure 6As shown, computing device 600 includes: bus 602, processor 604, memory 606 and communication interface 608. Processor 604, memory 606 and communication interface 608 communicate through bus 602. Computing device 600 can be a server or a terminal device. It should be understood that the present application does not limit the number of processors and memories in computing device 600.

[0136] The bus 602 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 The bus 602 may include a path for transmitting information between various components of the computing device 600 (eg, the memory 606, the processor 604, and the communication interface 608).

[0137] The processor 604 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0138] The memory 606 may include a volatile memory, such as a random access memory (RAM). The memory 606 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0139] The memory 606 stores executable program codes, and the processor 604 executes the executable program codes to respectively implement the functions of the aforementioned acquisition module 510, processing module 520, and recommendation module 530, thereby implementing the recommendation method for changing the cloud disk service. That is, the memory 606 stores instructions for executing the recommendation method for changing the cloud disk service.

[0140] The communication interface 608 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computing device 600 and other devices or communication networks.

[0141] The embodiment of the present application also provides a computing device cluster. The computing device cluster includes at least one computing device. The computing device can be a server, such as a central server, an edge server, or a local server in a local data center. In some embodiments, the computing device can also be a terminal device such as a desktop computer, a laptop computer, or a smart phone.

[0142] like Figure 7 As shown, the computing device cluster includes at least one computing device 600. The memory 606 in one or more computing devices 600 in the computing device cluster may store the same instructions for executing the recommended method for changing the cloud disk service.

[0143] In some embodiments, the memory 606 of one or more computing devices 600 in the computing device cluster may also store partial instructions for executing the recommended method for changing the cloud disk service. In other words, the combination of one or more computing devices 600 may jointly execute instructions for executing the recommended method for detecting changes in the cloud disk service.

[0144] It should be noted that the memory 606 in different computing devices 600 in the computing device cluster may store different instructions, which are respectively used to execute part of the functions of the cloud disk service change recommendation device 500. That is, the instructions stored in the memory 606 in different computing devices 600 may implement the functions of one or more modules among the acquisition module 510, the processing module 520 and the recommendation module 520.

[0145] In some embodiments, one or more computing devices in the computing device cluster may be connected via a network, which may be a wide area network or a local area network.

[0146] Figure 8 A possible implementation is shown. Figure 8 As shown, two computing devices 600A and 600B are connected via a network. Specifically, the network is connected via a communication interface in each computing device. In this type of possible implementation, the memory 606 in the computing device 600A stores instructions for executing the functions of the acquisition module 510 and the recommendation module 530. At the same time, the memory 606 in the computing device 600B stores instructions for the functions of the processing module 520.

[0147] Figure 8The connection method between the computing device clusters shown may be based on the consideration that the recommended method for changing the cloud disk service provided in this application requires a large amount of operating data to be acquired and a change strategy to be determined, so it is considered that the functions implemented by the processing module 520 are handed over to the computing device 600B for execution.

[0148] It should be understood that Figure 8 The functions of the computing device 600A shown in FIG. 6A may also be completed by multiple computing devices 600. Similarly, the functions of the computing device 600B may also be completed by multiple computing devices 600.

[0149] In some embodiments, the memory 606 of one or more computing devices 600 in the computing device cluster may also store partial instructions for executing the recommended method for changing the cloud disk service. In other words, the combination of one or more computing devices 600 can jointly execute the instructions for executing the recommended method for changing the cloud disk service.

[0150] The embodiment of the present application also provides a computer program product including instructions. The computer program product may be a software or program product including instructions that can be run on a computing device or stored in any available medium. When the computer program product is run on at least one computing device, the at least one computing device executes the above-mentioned method for recommending changes to the cloud disk service.

[0151] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by the computing device or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the computing device to execute the recommended method for changing the above-mentioned cloud disk service.

[0152] Fig. 9 It is a schematic block diagram of a cloud disk service change recommendation system 900 provided in an embodiment of the present application.

[0153] See also Fig. 9 The client 130 can implement cloud storage through a block storage service system 940 (eg, a cinder component). For example, the block storage service system 940 can run in the cloud management platform 110.

[0154] After the block storage service system 940 receives an instruction (such as a read instruction or a write instruction) sent by the client 130, it can call the virtual block storage system 950 to execute the instruction. The virtual block storage system 950 can disguise the underlying object storage as block storage. The virtual block storage system 950 can also be called a virtual block service (VBS) system, and the VBS system can access the VBS cluster. The virtual block storage system 950 can be responsible for the management of volumes and metadata, which belongs to the business IO process. For example, a VBS process can be deployed on each cloud server to form a VBS cluster, so that the client 130 can access the information stored on each cloud server through the VBS cluster.

[0155] Object storage device (OSD) 960 can be used to perform specific IO operations. Generally speaking, one OSD process can be deployed on a physical disk. Since there are multiple physical disks on a cloud server, multiple OSD processes can be deployed on a cloud server. Object storage device 960 can take over the underlying storage medium and simulate it into object storage, receive IO requests from virtual block storage system 950, and perform specific IO actions on the underlying physical disk according to the IO request.

[0156] The cloud disk service change recommendation system 900 includes a storage unit 910 , a judgment unit 920 and an execution unit 930 .

[0157] The object storage device 960 may be used to collect the operation data of the cloud disk and report it to the virtual block storage system 950. The virtual block storage system 950 may transmit the operation data to the cloud disk service change recommendation system 900. The storage unit 910 may be used to store the operation data.

[0158] The judgment unit 920 can serve as the aforementioned cloud disk service change recommendation device 500 to execute the aforementioned cloud disk service change recommendation method. In this way, the judgment unit 920 can determine whether an upgrade is required and provide a recommendation interface to the tenant. In some embodiments, the judgment unit 920 can also analyze whether the performance and capacity of the storage pool where the cloud disk is located supports the change strategy and calculate the time required for the upgrade. In this embodiment, the recommendation interface also includes the time required for the upgrade.

[0159] The execution unit 930 may send a corresponding execution command to the virtual block storage system 950 according to the tenant's instruction. For example, if the tenant agrees to upgrade according to the change policy, the execution unit 930 may send the execution command of the change policy to the virtual block storage system 950. After the upgrade is completed, a notification message of successful upgrade is pushed to the tenant, and the performance parameters or capacity limit of the tenant's cloud disk are updated to implement the cloud disk service change.

[0160] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0161] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0162] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0163] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0165] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0166] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for recommending a change in cloud disk service, characterized in that: The method is applied to a cloud management platform, the cloud management platform is used to manage an infrastructure for providing cloud services, the infrastructure includes a storage pool composed of storage spaces of multiple cloud servers, the storage pool is virtually divided into multiple cloud disks, the method includes: Acquire operation data of a first cloud disk among the multiple cloud disks, wherein the operation data of the first cloud disk includes flow control parameters and capacity usage rate; Determining a change strategy for the first cloud disk according to the operation data of the first cloud disk; A recommendation interface is provided to the tenant of the first cloud disk, where the recommendation interface includes the change strategy.

2. The method according to claim 1, characterized in that: The change strategy includes one or more of not upgrading, expanding the cloud disk capacity, switching to a second cloud disk, or automatically increasing performance during flow control, wherein the performance of the second cloud disk is greater than the performance of the first cloud disk.

3. The method according to claim 1 or 2, characterized in that: The determining, according to the operation data of the first cloud disk, a change strategy of the first cloud disk includes: When the flow control parameter is greater than or equal to a first threshold, the change strategy is determined according to the capacity usage rate.

4. The method according to claim 3, characterized in that The determining the change strategy according to the capacity utilization rate includes: When the capacity usage rate is greater than a second threshold, determining that the change strategy is to expand the cloud disk capacity; When the capacity usage rate is less than or equal to a second threshold, the change strategy is determined according to the flow control parameter.

5. The method according to claim 4, characterized in that The operation data of the first cloud disk also includes the current capacity of the first cloud disk, wherein determining that the change strategy is to expand the cloud disk capacity includes: Determining a target capacity according to the current capacity of the first cloud disk; Determine that the change strategy is to expand the cloud disk capacity to the target capacity.

6. The method according to claim 4 or 5, characterized in that: The determining the change strategy according to the flow control parameter includes: When the flow control parameter is less than a third threshold, determining that the change strategy is to automatically increase performance when flow control, wherein the third threshold is greater than the first threshold; When the flow control parameter is greater than or equal to the third threshold, the change strategy is determined to be switching to a second cloud disk.

7. The method according to claim 6, characterized in that The operation data of the first cloud disk also includes performance parameters, wherein determining the change strategy to switch to the second cloud disk includes: Determining target performance according to the performance parameters of the first cloud disk; The change strategy is determined to be to switch to a second cloud disk that meets the target performance.

8. The method according to any one of claims 1 to 7, characterized in that The determining, according to the operation data of the first cloud disk, a change strategy of the first cloud disk includes: When the flow control parameter is less than the first threshold, the change strategy is determined to be not to upgrade.

9. The method according to any one of claims 1 to 8, characterized in that The recommendation interface also includes the operating data of the first cloud disk.

10. The method according to any one of claims 1 to 9, characterized in that Also includes: Acquiring operation data of the storage pool; Determining an upgrade time corresponding to the change strategy according to the operation data of the storage pool; wherein providing a recommendation interface to the tenant of the first cloud disk includes: A recommendation interface is provided to the tenant of the first cloud disk, wherein the recommendation interface also includes the upgrade time.

11. A device for recommending changes to cloud disk services, characterized in that: The device is applied to a cloud management platform, and the cloud management platform is used to manage an infrastructure for providing cloud services, wherein the infrastructure includes a storage pool composed of storage spaces of multiple cloud servers, and the storage pool is virtually divided into multiple cloud disks. The device includes: An acquisition module, configured to acquire operation data of a first cloud disk among the plurality of cloud disks, wherein the operation data of the first cloud disk includes flow control parameters and capacity utilization rate; A processing module, configured to determine a change strategy of the first cloud disk according to the operation data of the first cloud disk; A recommendation module is used to provide a recommendation interface to the tenants of the first cloud disk, and the recommendation interface includes the change strategy.

12. The device according to claim 11, characterized in that The change strategy includes one or more of not upgrading, expanding the cloud disk capacity, switching to a second cloud disk, or automatically increasing performance during flow control, wherein the performance of the second cloud disk is greater than the performance of the first cloud disk.

13. The device according to claim 11 or 12, characterized in that The processing module is specifically used for: When the flow control parameter is greater than or equal to a first threshold, the change strategy is determined according to the capacity usage rate.

14. The device according to claim 13, characterized in that The processing module is specifically used for: When the capacity usage rate is greater than a second threshold, determining that the change strategy is to expand the cloud disk capacity; When the capacity usage rate is less than or equal to a second threshold, the change strategy is determined according to the flow control parameter.

15. The device according to claim 14, characterized in that The operation data of the first cloud disk also includes the current capacity of the first cloud disk, wherein the processing module is specifically used to: Determining a target capacity according to the current capacity of the first cloud disk; Determine that the change strategy is to expand the cloud disk capacity to the target capacity.

16. The device according to claim 14 or 15, characterized in that The processing module is specifically used for: When the flow control parameter is less than a third threshold, determining that the change strategy is to automatically increase performance when flow control, wherein the third threshold is greater than the first threshold; When the flow control parameter is greater than or equal to the third threshold, the change strategy is determined to be switching to a second cloud disk.

17. The device according to claim 16, characterized in that The operation data of the first cloud disk also includes performance parameters, wherein the processing module is specifically used to: Determining target performance according to the performance parameters of the first cloud disk; The change strategy is determined to be to switch to a second cloud disk that meets the target performance.

18. The device according to any one of claims 11 to 17, characterized in that The processing module is specifically used for: When the flow control parameter is less than the first threshold, the change strategy is determined to be not to upgrade.

19. The device according to any one of claims 11 to 18, characterized in that The recommendation interface also includes the operating data of the first cloud disk.

20. The device according to any one of claims 11 to 19, characterized in that The acquisition module is also used to acquire the operation data of the storage pool; The processing module is also used to determine the upgrade time corresponding to the change strategy according to the operation data of the storage pool; wherein, The recommendation module is further used to provide a recommendation interface to the tenant of the first cloud disk, and the recommendation interface also includes the upgrade time.

21. A computing device cluster, characterized in that: comprising at least one computing device, each computing device comprising a processor and a memory; The processor of the at least one computing device is configured to execute instructions stored in the memory of the at least one computing device, so that the computing device cluster executes the method according to any one of claims 1 to 10.

22. A computer program product comprising instructions, characterized in that When the instructions are executed by a computing device cluster, the computing device cluster is caused to perform the method according to any one of claims 1 to 10.

23. A computer-readable storage medium, characterized in that: The method comprises computer program instructions. When the computer program instructions are executed by a computing device cluster, the computing device cluster performs the method according to any one of claims 1 to 10.

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