CN115348264A - Multi-tenant cloud service management method, device, equipment and storage medium - Google Patents
Multi-tenant cloud service management method, device, equipment and storage medium Download PDFInfo
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- CN115348264A CN115348264A CN202210897600.7A CN202210897600A CN115348264A CN 115348264 A CN115348264 A CN 115348264A CN 202210897600 A CN202210897600 A CN 202210897600A CN 115348264 A CN115348264 A CN 115348264A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H04L67/1074—Peer-to-peer [P2P] networks for supporting data block transmission mechanisms
Abstract
The invention relates to a cloud service technology, and discloses a multi-tenant cloud service management method, which comprises the following steps: the method comprises the steps of dividing a plurality of resource pools for tenants in a private cloud scene, receiving cloud service requests of the tenants, obtaining corresponding cloud services based on the cloud service requests, distributing the cloud services to independent resource pools in the resource pools, calculating and smoothing the resource utilization rate of the cloud services in the independent resource pools to obtain standard resource utilization rate, scheduling the cloud services to temporary resource pools in the resource pools according to the standard resource utilization rate, performing resource management scheduling on the independent resource pools in the resource pools and the cloud services in a shared resource pool based on the temporary resource pools, and performing resource management scheduling on the cloud services in the shared resource pool based on the standard resource utilization rate in a preset time period. The invention also provides a multi-tenant cloud service management method and device, electronic equipment and a computer readable storage medium. The cloud service management method and the cloud service management system can improve the management efficiency of the cloud service.
Description
Technical Field
The invention relates to the technical field of cloud services, in particular to a multi-tenant cloud service management method and device, electronic equipment and a computer-readable storage medium.
Background
With the rise and popularization of cloud computing, more and more software products and services are delivered in a cloud service manner. The traditional software is directly oriented to users, the cloud service is generally oriented to tenants, the tenants can be individual users or organization units, the tenants sign with cloud service providers, and the services such as IaaS, paaS and SaaS provided by the cloud service providers are leased.
Under the existing multi-tenant private cloud scene, when tenants apply for cloud proxy services, one virtual machine is often purchased independently, and the cloud proxy services are deployed on the virtual machines, so that a large number of cloud proxy servers occupy precious virtual machine resources independently, and the cloud proxy services only utilize a small part of cpu, memory and network resources of the virtual machines, so that a large amount of waste of the virtual machine resources is caused. If the tenant deploys a plurality of cloud agent services to the same virtual machine, mutual influence among the services cannot be guaranteed, and the situation that limited virtual machine resources are mutually occupied among the services when the service request volume is high in peak possibly to cause unavailable services can occur, so that the stability among the services is influenced.
Disclosure of Invention
The invention provides a multi-tenant cloud service management method, a multi-tenant cloud service management device, multi-tenant cloud service management equipment and a storage medium, and aims to improve the management efficiency of cloud services.
In order to achieve the above object, the present invention provides a multi-tenant cloud service management method, including:
acquiring tenant information in a private cloud scene, and dividing a plurality of resource pools for tenants in the private cloud scene based on the tenant information;
receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and allocating the cloud service to an exclusive resource pool in the plurality of resource pools;
calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing treatment to obtain the standard resource utilization rate;
scheduling the cloud service to a temporary resource pool of the multiple resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the multiple resource pools based on the temporary resource pool;
and in a preset time period, carrying out resource management scheduling on the shared resource pool in the multiple resource pools and the cloud service in the shared resource pool based on the standard resource utilization rate.
Optionally, the partitioning, based on the tenant information, a plurality of resource pools for tenants in the private cloud scenario includes:
searching historical resource calling information of the tenant based on the tenant information;
and dividing a shared resource pool, an exclusive resource pool and a temporary resource pool in the virtual machine preset by the tenant based on the historical resource calling information.
Optionally, the obtaining of the corresponding cloud service based on the cloud service request and allocating the cloud service to an exclusive resource pool of the resource pools includes:
performing service marking on the cloud service corresponding to the cloud service request based on the tenant;
and distributing the cloud service to an exclusive resource pool of the tenant according to a preset network based on the service mark.
Optionally, the calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing processing to obtain a standard resource utilization rate includes:
calculating the resource utilization rate of the cloud service according to preset granularity to obtain the original resource utilization rate;
and removing burr points in the original resource utilization rate by using an exponential smoothing algorithm to obtain the standard resource utilization rate.
Optionally, the removing the bur points in the original resource usage by using an exponential smoothing algorithm to obtain a standard resource usage, including:
selecting a preset number of resource sequences from the original resource utilization rate to calculate a resource initial value;
and calculating the standard resource utilization rate under each preset granularity by utilizing a preset exponential smoothing formula based on the resource initial value.
Optionally, the preset exponential smoothing formula is as follows:
S t ＝a*y t +(1-a)S t-1
wherein S is t A is the standard resource utilization rate of time t, a is the preset weight, y t Original resource usage as time t, S t-1 Is the standard resource usage at time t-1.
Optionally, the scheduling the cloud service to a temporary resource pool of the multiple resource pools according to the standard resource usage rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the multiple resource pools based on the temporary resource pool includes:
performing accumulation processing on the standard resource utilization rate, obtaining a resource usage score;
taking the cloud service with the resource use score larger than or equal to a preset score threshold value as a cloud service with high resource use rate;
taking the cloud service with the resource usage score smaller than the score threshold value as a cloud service with low resource usage rate;
judging whether the cloud service judged to be low in resource utilization rate in the exclusive resource pool meets a preset first time range or not;
if the first time range is met, scheduling to a temporary resource pool, and if the first time range is not met, reserving in the exclusive resource pool;
continuously judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets a preset second time range or not;
if the preset second time range is met, scheduling the cloud service to a shared resource pool, and if the preset second time range is not met, scheduling the cloud service to the exclusive resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets the preset second time range;
judging whether the cloud service judged as the high resource utilization rate in the shared resource pool meets a preset third time range or not;
if the preset third time range is met, scheduling the resource to the temporary resource pool, and if the preset third time range is not met, remaining the resource in the shared resource pool;
continuously judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets a preset fourth time range or not;
and if the preset fourth time range is met, scheduling to an exclusive resource pool, and if the preset fourth time range is not met, scheduling to the shared resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service determined as the high resource utilization rate in the temporary resource pool meets the preset fourth time range.
In order to solve the above problem, the present invention further provides a device of a multi-tenant cloud service management method, where the device includes:
the resource pool dividing module is used for acquiring tenant information in a private cloud scene and dividing a plurality of resource pools for the tenants in the private cloud scene based on the tenant information;
the cloud service allocation module is used for receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and allocating the cloud service to an exclusive resource pool in the plurality of resource pools;
the resource smoothing processing module is used for calculating the resource utilization rate of the cloud service in the exclusive resource pool and performing smoothing processing to obtain the standard resource utilization rate;
and the cloud service scheduling module is used for scheduling the cloud service to a temporary resource pool in the plurality of resource pools according to the standard resource utilization rate, performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool in the plurality of resource pools on the basis of the temporary resource pool, and performing resource management scheduling on the cloud service in the shared resource pool and the shared resource pool in the plurality of resource pools on the basis of the standard resource utilization rate in a preset time period.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one instruction; and
and the processor executes the instructions stored in the memory to realize the multi-tenant cloud service management method.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, where at least one instruction is stored, and the at least one instruction is executed by a processor in an electronic device to implement the multi-tenant cloud service management method.
According to the method, a plurality of resource pools are divided for tenants in a private cloud scene, the cloud service corresponding to the cloud service request is firstly allocated to the exclusive resource pool, the resource utilization rate of the cloud service in the exclusive resource pool is calculated and smoothed to obtain the standard resource utilization rate, the cloud service is scheduled to the temporary resource pools in the resource pools according to the standard resource utilization rate, the cloud service in the exclusive resource pools and the cloud service in the shared resource pools are subjected to resource management scheduling based on the temporary resource pools, the cloud service can be dynamically adjusted by dividing different resource pools to perform resource scheduling, and the utilization rate of the virtual machine resources is improved. Meanwhile, resource management is carried out through the resource pools, so that the cloud service with high resource utilization rate can be found and dispatched in time at the service peak, the stability of the service is ensured, and the management efficiency of the cloud service is improved. Therefore, the multi-tenant cloud service management method, the multi-tenant cloud service management device, the electronic equipment and the computer readable storage medium can improve the management efficiency of the cloud service.
Drawings
Fig. 1 is a schematic flowchart of a multi-tenant cloud service management method according to an embodiment of the present invention;
fig. 2 is a functional block diagram of a multi-tenant cloud service management apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device implementing the multi-tenant cloud service management method according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a multi-tenant cloud service management method. The executing subject of the multi-tenant cloud service management method includes, but is not limited to, at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the multi-tenant cloud service management method may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Fig. 1 is a schematic flow diagram of a multi-tenant cloud service management method according to an embodiment of the present invention. In this embodiment, the multi-tenant cloud service management method includes:
s1, acquiring tenant information in a private cloud scene, and dividing a plurality of resource pools for tenants in the private cloud scene based on the tenant information.
In the embodiment of the invention, in a multi-tenant private cloud service scene, tenants refer to various departments (such as enterprise departments or government departments) occupying IT resources, and the occupation is different from the prior permanent occupation of the resources and refers to the sharing of the resources in the private cloud in a specific time period or place. For example, a video conference system of a certain company is deployed in a private cloud data center of a company headquarters, and a branch company a rents the set of video conference systems at 16-00. Because the time and the resource amount of resource application of different tenants are different, in order to ensure that the service application between different tenants is not influenced, the resource pool is constructed for each tenant.
In detail, the partitioning, for tenants in the private cloud scenario, a plurality of resource pools based on the tenant information includes:
searching historical resource calling information of the tenant based on the tenant information;
and dividing a shared resource pool, an exclusive resource pool and a temporary resource pool in the virtual machine preset by the tenant based on the historical resource calling information.
In the embodiment of the invention, the tenant information comprises information such as tenant name, authority and the like in the private cloud. The historical resource calling information comprises information of resource calling time, size and the like of each tenant, and three cloud proxy resource pools such as a shared resource pool, an exclusive resource pool and a temporary resource pool are divided for each tenant based on the size records of the resource calling. For example, three cloud proxy resource pools are partitioned for tenant 1: a shared resource pool 1, an exclusive resource pool 1 and a temporary resource pool 1.
In the embodiment of the invention, the utilization rate of virtual machine resources of the tenants can be improved by dividing different cloud agent resource pools for each tenant and dynamically adjusting the cloud agent service through the resource pools of different levels.
S2, receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and distributing the cloud service to an exclusive resource pool in the plurality of resource pools.
In the embodiment of the present invention, the cloud service request refers to a specific resource request of a tenant based on a certain service, for example, for a video conference service, a department a requests a service using request from two to four points in monday, wednesday and afternoon.
Specifically, the acquiring the corresponding cloud service based on the cloud service request and allocating the cloud service to an exclusive resource pool in the multiple resource pools includes:
performing service marking on the cloud service corresponding to the cloud service request based on the tenant;
and distributing the cloud service to the exclusive resource pool of the tenant according to a preset network based on the service mark.
In an optional embodiment of the present invention, in a multi-tenant private cloud service scenario, server virtualization virtualizes a traditional physical server into a plurality of virtual servers (i.e., virtual machines), each virtual server runs an independent operating system, and each tenant owns one virtual server or a group of virtual servers in a virtual server resource pool. In the invention, because the resource pool is divided based on the virtual server, and the cloud service of the same kind may have a plurality of tenant requests, in order to avoid the mutual influence of the services of different tenants, the multi-tenant network must be able to meet the isolation requirement between the virtual machines, so each tenant has an independent transmission network, for example, a certain cloud service is marked as cloud service 1, and the network of tenant A includes: the tenant 1, the network port 1 and the virtual server sub-interface 1 transmit the cloud service 1 through a network corresponding to the tenant A.
And S3, calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing treatment to obtain the standard resource utilization rate.
In the embodiment of the present invention, the resource utilization refers to a traffic utilization, a memory utilization, a cpu utilization, and the like of the cloud service. Meanwhile, because the resource utilization rate is time sequence data, a burr point may occur, and therefore, the burr needs to be removed through smoothing processing, and the accuracy of time sequence data analysis is improved.
In detail, the calculating the resource utilization rate of the cloud service in the exclusive resource pool and performing smoothing processing to obtain a standard resource utilization rate includes:
calculating the resource utilization rate of the cloud service according to preset granularity to obtain the original resource utilization rate;
and removing burr points in the original resource utilization rate by using an exponential smoothing algorithm to obtain the standard resource utilization rate.
In an optional embodiment of the present invention, the calculating the resource usage rate of the cloud service according to the preset granularity may be performed to calculate a resource usage rate score of the cloud service according to a granularity of 5 minutes and one day.
Further, the removing the bur points in the original resource utilization rate by using an exponential smoothing algorithm to obtain a standard resource utilization rate includes:
selecting a preset number of resource sequences from the original resource utilization rate to calculate a resource initial value;
and calculating the standard resource utilization rate under each preset granularity by utilizing a preset exponential smoothing formula based on the resource initial value.
In an optional embodiment of the present invention, the preset exponential smoothing formula is as follows:
S t ＝a*y t +(1-a)S t-1
wherein S is t A is the standard resource utilization rate of time t, a is a predetermined weight, y t Original resource usage at time t, S t-1 Is the standard resource usage at time t-1.
For example, taking the cpu resource usage rate with granularity of every five minutes as an example, the average value of the cpu resource usage rates of the first three five minutes is selected as the initial value S of the cpu resource 0 Then S is 1 ＝a*y 1 +(1-a)S 0 ，y 1 Cpu resource usage for the first five minutes, S 2 ＝a*y 2 +(1-a)S 1 ，y 2 The second cpu resource utilization rate of five minutes, and so on to obtain the standard resource utilization rates after all smoothing processes.
In the embodiment of the invention, more smooth and accurate time sequence data can be obtained by counting the resource utilization rates of different granularities and removing burrs through an exponential smoothing algorithm.
And S4, scheduling the cloud service to a temporary resource pool in the plurality of resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool in the plurality of resource pools based on the temporary resource pool.
In the embodiment of the invention, the cloud agent service is scheduled according to the standard resource utilization rate and is scheduled to different resource pools, so that the stability of the service can be ensured.
Specifically, the scheduling the cloud service to a temporary resource pool of the resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the resource pools based on the temporary resource pool includes:
accumulating the standard resource utilization rate to obtain a resource utilization score;
taking the cloud service with the resource utilization score larger than or equal to a preset score threshold value as a cloud service with high resource utilization rate;
taking the cloud service with the resource usage score smaller than the score threshold value as a cloud service with low resource usage rate;
judging whether the cloud service judged to be low in resource utilization rate in the exclusive resource pool meets a preset first time range or not;
if the first time range is not met, the temporary resource pool is scheduled, and if the first time range is not met, the temporary resource pool is reserved in the exclusive resource pool;
continuously judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets a preset second time range or not;
if the preset second time range is met, scheduling to a shared resource pool, if the preset second time range is not met, scheduling to the exclusive resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets the preset second time range;
judging whether the cloud service judged as the high resource utilization rate in the shared resource pool meets a preset third time range or not;
if the preset third time range is met, scheduling the resource to the temporary resource pool, and if the preset third time range is not met, remaining the resource in the shared resource pool;
continuously judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets a preset fourth time range or not;
and if the preset fourth time range is met, scheduling the cloud service to an exclusive resource pool, and if the preset fourth time range is not met, scheduling the cloud service to the shared resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets the preset fourth time range.
In an optional embodiment of the present invention, the standard resource usage score of the cloud service may be accumulated and counted every day in the morning, the cloud service with the resource usage score greater than or equal to the preset score threshold is used as the service with high resource usage, and the cloud service with the resource usage score smaller than the preset score threshold is used as the service with low resource usage.
For example, in the morning, cloud services judged to be high in resource utilization rate for the first 1 day (which can be modified according to actual conditions) are scheduled from the shared resource pool to the temporary resource pool, and cloud services judged to be low in resource utilization rate for the next 7 days (which can be modified according to actual conditions) are scheduled from the exclusive resource pool to the temporary resource pool.
In the embodiment of the present invention, for example, the temporary resource pool performs cloud service resource scheduling according to the following steps:
a. for an exclusive resource pool: in the morning every day, the cloud service judged to be low in resource utilization rate for 7 continuous days (namely, the first time range can be modified according to actual conditions) is dispatched from the exclusive resource pool to the temporary resource pool, on the basis, the cloud service judged to be low in resource utilization rate for 5 continuous days (namely, the second time range can be modified according to actual conditions) is dispatched from the temporary resource pool to the shared resource pool, otherwise (the cloud service is not judged to be low in resource utilization rate for 5 continuous days), if the cloud service is judged to be high in resource utilization rate for more than half of days, the cloud service is dispatched back to the exclusive resource pool, and if the cloud service is judged to be low in resource utilization rate for more than half of days, the cloud service is still placed in the temporary resource pool. And if the resource is still placed in the temporary resource pool, continuing the judgment of the step a.
b. For a shared resource pool: in the morning every day, the cloud service which is judged to be high in resource utilization rate for 1 continuous day (the third time range can be modified according to actual conditions) is dispatched from the shared resource pool to the temporary resource pool, on the basis, the cloud service which is judged to be high in resource utilization rate for 3 continuous days (namely, the fourth time range can be modified according to actual conditions) is dispatched from the temporary resource pool to the exclusive resource pool, otherwise (the cloud service is not high in resource utilization rate for 3 continuous days), and if the cloud service is judged to be high in resource utilization rate for more than half of days, the cloud service is still placed in the temporary resource pool. And if the number of days exceeds half, the shared resource pool is dispatched back, and if the number of days exceeds half, the shared resource pool is judged to be high, the shared resource pool is still placed in the temporary resource pool. And if the temporary resource pool is still placed, continuing the judgment b.
And S5, performing resource management scheduling on the shared resource pools in the multiple resource pools and the cloud services in the shared resource pools based on the standard resource utilization rate in a preset time period.
In an optional embodiment of the present invention, the preset time period may be a peak time period set for different services. For example, during the peak period of the a business, according to the resource utilization score of 5 minutes, the cloud service with the resource utilization score exceeding a given threshold value is scheduled from the shared resource pool to the temporary resource pool, and after the peak period is finished, if the resource utilization rate is reduced below the threshold value, the cloud service is scheduled back to the shared resource pool. And if the cloud service does not fall below the threshold value, the cloud service is still placed in the temporary resource pool, and for the cloud service in the temporary resource pool, the step of performing resource management scheduling on the cloud service in the independent resource pool and the shared resource pool in the plurality of resource pools based on the temporary resource pool in the S4 is returned.
In the embodiment of the invention, the cloud service in the temporary resource pool is scheduled according to the resource usage score threshold value or when the preset time range (such as the time range of the peak period) is met, so that the cloud service with high resource usage rate can be found and scheduled in time in the service peak period, resource conflict is reduced, the influence on other cloud services on the same virtual machine resource and the stability of service are ensured, and meanwhile, the cloud service with low resource usage rate can be scheduled back to the shared resource pool in time to share and allocate the virtual machine resource after the peak period is finished, so that a large amount of virtual machine resources are saved.
According to the method, a plurality of resource pools are divided for tenants in a private cloud scene, the cloud service corresponding to the cloud service request is firstly allocated to the exclusive resource pool, the resource utilization rate of the cloud service in the exclusive resource pool is calculated and smoothed to obtain the standard resource utilization rate, the cloud service is scheduled to the temporary resource pools in the resource pools according to the standard resource utilization rate, the cloud service in the exclusive resource pools and the cloud service in the shared resource pools are subjected to resource management scheduling based on the temporary resource pools, the cloud service can be dynamically adjusted by dividing different resource pools to perform resource scheduling, and the utilization rate of the virtual machine resources is improved. Meanwhile, resource management is performed through the resource pools, so that the cloud service with high resource utilization rate can be found and dispatched in time in the service peak period, the stability of the service is ensured, and the management efficiency of the cloud service is improved. Therefore, the multi-tenant cloud service management method provided by the invention can improve the management efficiency of the cloud service.
Fig. 2 is a functional block diagram of a multi-tenant cloud service management apparatus according to an embodiment of the present invention.
The multi-tenant cloud service management apparatus 100 of the present invention may be installed in an electronic device. According to the implemented functions, the multi-tenant cloud service management apparatus 100 may include a resource pool partitioning module 101, a cloud service allocation module 102, a resource smoothing module 103, and a cloud service scheduling module 104. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the resource pool dividing module 101 is configured to acquire tenant information in a private cloud scene, and divide a plurality of resource pools for tenants in the private cloud scene based on the tenant information;
the cloud service allocation module 102 is configured to receive a cloud service request of a tenant, obtain a corresponding cloud service based on the cloud service request, and allocate the cloud service to an exclusive resource pool of the multiple resource pools;
the resource smoothing processing module 103 is configured to calculate a resource utilization rate of the cloud service in the exclusive resource pool, and perform smoothing processing to obtain a standard resource utilization rate;
the cloud service scheduling module 104 is configured to schedule the cloud service to a temporary resource pool of the multiple resource pools according to the standard resource usage rate, perform resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the multiple resource pools based on the temporary resource pool, and perform resource management scheduling on the cloud service in the shared resource pool and the shared resource pool of the multiple resource pools based on the standard resource usage rate in a preset time period.
In detail, the specific implementation of each module of the multi-tenant cloud service management apparatus 100 is as follows:
the method comprises the steps of firstly, acquiring tenant information in a private cloud scene, and dividing a plurality of resource pools for tenants in the private cloud scene based on the tenant information.
In the embodiment of the invention, in a multi-tenant private cloud service scene, tenants refer to various departments (such as enterprise departments or government departments) occupying IT resources, and the occupation is different from the prior permanent occupation of the resources and refers to the sharing of the resources in the private cloud in a specific time period or place. For example, a video conference system of a company is deployed in a private cloud data center of a company headquarters, and a branch company a rents the set of video conference systems at 16-00. Because the time and the resource amount of resource application of different tenants are different, in order to ensure that the service application between different tenants is not influenced, the resource pool is constructed for each tenant.
In detail, the partitioning, for tenants in the private cloud scenario, a plurality of resource pools based on the tenant information includes:
searching historical resource calling information of the tenant based on the tenant information;
and dividing a shared resource pool, an exclusive resource pool and a temporary resource pool in the virtual machine preset by the tenant based on the historical resource calling information.
In the embodiment of the invention, the tenant information comprises information such as tenant name, authority and the like in the private cloud. The historical resource calling information comprises information of resource calling time, size and the like of each tenant, and three cloud proxy resource pools such as a shared resource pool, an exclusive resource pool and a temporary resource pool are divided for each tenant based on the size records of the resource calling. For example, three cloud proxy resource pools are partitioned for tenant 1: a shared resource pool 1, an exclusive resource pool 1 and a temporary resource pool 1.
In the embodiment of the invention, the utilization rate of virtual machine resources of the tenants can be improved by dividing different cloud agent resource pools for each tenant and dynamically adjusting the cloud agent service through the resource pools of different levels.
And step two, receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and distributing the cloud service to an exclusive resource pool in the plurality of resource pools.
In the embodiment of the present invention, the cloud service request refers to a specific resource request of a tenant based on a certain service, for example, for a video conference service, a department a requests a service using request from two to four points in monday, wednesday and afternoon.
Specifically, the obtaining of the corresponding cloud service based on the cloud service request and the allocating of the cloud service to an exclusive resource pool of the multiple resource pools includes:
performing service marking on the cloud service corresponding to the cloud service request based on the tenant;
and distributing the cloud service to the exclusive resource pool of the tenant according to a preset network based on the service mark.
In an optional embodiment of the present invention, in a multi-tenant private cloud service scenario, server virtualization virtualizes a traditional physical server into a plurality of virtual servers (i.e., virtual machines), each virtual server runs an independent operating system, and each tenant owns one virtual server or a group of virtual servers in a virtual server resource pool. In the invention, because the resource pool is divided based on the virtual server, and the cloud service of the same kind may have a plurality of tenant requests, in order to avoid the mutual influence of the services of different tenants, the multi-tenant network must be able to meet the isolation requirement between the virtual machines, therefore, each tenant has an independent transmission network, for example, a certain cloud service is marked as cloud service 1, and the network of tenant A includes: the tenant 1, the network port 1 and the virtual server sub-interface 1 transmit the cloud service 1 through a network corresponding to the tenant A.
And step three, calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing treatment to obtain the standard resource utilization rate.
In the embodiment of the present invention, the resource utilization refers to a traffic utilization, a memory utilization, a cpu utilization, and the like of the cloud service. Meanwhile, because the resource utilization rate is time sequence data, a burr point may occur, and therefore, the burr needs to be removed through smoothing processing, and the accuracy of time sequence data analysis is improved.
In detail, the calculating the resource utilization rate of the cloud service in the exclusive resource pool and performing smoothing processing to obtain a standard resource utilization rate includes:
calculating the resource utilization rate of the cloud service according to preset granularity to obtain the original resource utilization rate;
and removing burr points in the original resource utilization rate by using an exponential smoothing algorithm to obtain the standard resource utilization rate.
In an optional embodiment of the present invention, the calculating the resource usage rate of the cloud service according to the preset granularity may be performed to calculate a resource usage rate score of the cloud service according to a granularity of 5 minutes and one day.
Further, the removing the bur points in the original resource utilization rate by using an exponential smoothing algorithm to obtain a standard resource utilization rate includes:
selecting a preset number of resource sequences from the original resource utilization rate to calculate a resource initial value;
and calculating the standard resource utilization rate under each preset granularity by utilizing a preset exponential smoothing formula based on the resource initial value.
In an optional embodiment of the present invention, the preset exponential smoothing formula is as follows:
S t ＝a*y t +(1-a)S t-1
wherein S is t A is the standard resource utilization rate of time t, a is the preset weight, y t Raw resource usage for time t，S t-1 Is the standard resource usage at time t-1.
For example, taking the cpu resource usage rate with granularity of every five minutes as an example, the average value of the cpu resource usage rates of the first three five minutes is selected as the initial value S of the cpu resource 0 Then S is 1 ＝a*y 1 +(1-a)S 0 ，y 1 Cpu resource usage for the first five minutes, S 2 ＝a*y 2 +(1-a)S 1 ，y 2 The second cpu resource utilization rate of five minutes, and so on to obtain the standard resource utilization rates after all smoothing processes.
In the embodiment of the invention, more smooth and accurate time sequence data can be obtained by counting the resource utilization rates of different granularities and removing burrs through an exponential smoothing algorithm.
And fourthly, scheduling the cloud service to a temporary resource pool in the plurality of resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool in the plurality of resource pools based on the temporary resource pool.
In the embodiment of the invention, the cloud agent service is scheduled according to the standard resource utilization rate and is scheduled to different resource pools, so that the stability of the service can be ensured.
Specifically, the scheduling the cloud service to a temporary resource pool of the resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the resource pools based on the temporary resource pool includes:
accumulating the standard resource utilization rate to obtain a resource utilization score;
taking the cloud service with the resource use score larger than or equal to a preset score threshold value as a cloud service with high resource use rate;
taking the cloud service with the resource usage score smaller than the score threshold value as a cloud service with low resource usage rate;
judging whether the cloud service judged to be low in resource utilization rate in the exclusive resource pool meets a preset first time range or not;
if the first time range is met, scheduling to a temporary resource pool, and if the first time range is not met, reserving in the exclusive resource pool;
continuously judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets a preset second time range or not;
if the preset second time range is met, scheduling to a shared resource pool, if the preset second time range is not met, scheduling to the exclusive resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets the preset second time range;
judging whether the cloud service judged as the high resource utilization rate in the shared resource pool meets a preset third time range or not;
if the preset third time range is met, scheduling the resource to the temporary resource pool, and if the preset third time range is not met, remaining the resource in the shared resource pool;
continuously judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets a preset fourth time range or not;
and if the preset fourth time range is met, scheduling the cloud service to an exclusive resource pool, and if the preset fourth time range is not met, scheduling the cloud service to the shared resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets the preset fourth time range.
In an optional embodiment of the present invention, the standard resource usage score of the cloud service may be accumulated and counted every day in the morning, the cloud service with the resource usage score greater than or equal to the preset score threshold is used as the service with high resource usage, and the cloud service with the resource usage score smaller than the preset score threshold is used as the service with low resource usage.
For example, in the morning, cloud services judged to be high in resource utilization rate for the first 1 day (which can be modified according to actual conditions) are scheduled from the shared resource pool to the temporary resource pool, and cloud services judged to be low in resource utilization rate for the next 7 days (which can be modified according to actual conditions) are scheduled from the exclusive resource pool to the temporary resource pool.
In the embodiment of the present invention, for example, the temporary resource pool performs cloud service resource scheduling according to the following steps:
a. for an exclusive resource pool: in the morning every day, the cloud service judged to be low in resource utilization rate for 7 continuous days (namely, the first time range can be modified according to actual conditions) is dispatched from the exclusive resource pool to the temporary resource pool, on the basis, the cloud service judged to be low in resource utilization rate for 5 continuous days (namely, the second time range can be modified according to actual conditions) is dispatched from the temporary resource pool to the shared resource pool, otherwise (the cloud service is not judged to be low in resource utilization rate for 5 continuous days), if the cloud service is judged to be high in resource utilization rate for more than half of days, the cloud service is dispatched back to the exclusive resource pool, and if the cloud service is judged to be low in resource utilization rate for more than half of days, the cloud service is still placed in the temporary resource pool. And if the temporary resource pool is still placed, continuing the judgment of the step a.
b. For a shared resource pool: and dispatching the cloud service judged to be high in resource utilization rate for 1 continuous day (the third time range can be modified according to actual conditions) from the shared resource pool to the temporary resource pool every morning, and on the basis, dispatching the cloud service judged to be high in resource utilization rate for 3 continuous days (namely the fourth time range can be modified according to actual conditions) from the temporary resource pool to the exclusive resource pool, otherwise (the high in utilization rate for 3 continuous days), and if the cloud service is judged to be high in resource utilization rate for more than half of days, still placing the cloud service in the temporary resource pool. And if the number of days exceeds half, the shared resource pool is dispatched back, and if the number of days exceeds half, the shared resource pool is judged to be high, the shared resource pool is still placed in the temporary resource pool. And if the temporary resource pool is still placed, continuing the judgment b.
And fifthly, in a preset time period, carrying out resource management scheduling on the shared resource pool in the multiple resource pools and the cloud service in the shared resource pool based on the standard resource utilization rate.
In an optional embodiment of the present invention, the preset time period may be a peak time period set for different services. For example, during the peak period of the a business, according to the resource utilization score of 5 minutes, the cloud service with the resource utilization score exceeding a given threshold value is scheduled from the shared resource pool to the temporary resource pool, and after the peak period is finished, if the resource utilization rate is reduced below the threshold value, the cloud service is scheduled back to the shared resource pool. If the cloud service does not fall below the threshold value, the cloud service is still placed in the temporary resource pool, and for the cloud service in the temporary resource pool, the step of performing resource management scheduling on the cloud service in the independent resource pool and the shared resource pool in the plurality of resource pools based on the temporary resource pool in the step four is returned.
In the embodiment of the invention, the cloud service in the temporary resource pool is scheduled according to the resource usage score threshold value or when the preset time range (such as the time range of the peak period) is met, so that the cloud service with high resource usage rate can be found and scheduled in time in the service peak period, resource conflict is reduced, the influence on other cloud services on the same virtual machine resource and the stability of service are ensured, and meanwhile, the cloud service with low resource usage rate can be scheduled back to the shared resource pool in time to share and allocate the virtual machine resource after the peak period is finished, so that a large amount of virtual machine resources are saved.
According to the method, a plurality of resource pools are divided for tenants in a private cloud scene, the cloud service corresponding to the cloud service request is firstly allocated to the exclusive resource pool, the resource utilization rate of the cloud service in the exclusive resource pool is calculated and smoothed to obtain the standard resource utilization rate, the cloud service is scheduled to the temporary resource pools in the resource pools according to the standard resource utilization rate, the cloud service in the exclusive resource pools and the cloud service in the shared resource pools are subjected to resource management scheduling based on the temporary resource pools, the cloud service can be dynamically adjusted by dividing different resource pools to perform resource scheduling, and the utilization rate of the virtual machine resources is improved. Meanwhile, resource management is carried out through the resource pools, so that the cloud service with high resource utilization rate can be found and dispatched in time at the service peak, the stability of the service is ensured, and the management efficiency of the cloud service is improved. Therefore, the multi-tenant cloud service management device provided by the invention can improve the management efficiency of the cloud service.
As shown in fig. 3, which is a schematic structural diagram of an electronic device for implementing the multi-tenant cloud service management method according to an embodiment of the present invention, and includes a processor 111, a communication interface 112, a memory 113, and a communication bus 114, where the processor 111, the communication interface 112, and the memory 113 complete mutual communication through the communication bus 114,
a memory 113 for storing a computer program, such as a multi-tenant cloud service management method program;
in an embodiment of the present application, when the processor 111 is configured to execute the program stored in the memory 113, the method for managing a multi-tenant cloud service provided in any one of the foregoing method embodiments is implemented, and includes:
acquiring tenant information in a private cloud scene, and dividing a plurality of resource pools for tenants in the private cloud scene based on the tenant information;
receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and distributing the cloud service to an exclusive resource pool in the plurality of resource pools;
calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing treatment to obtain a standard resource utilization rate;
scheduling the cloud service to a temporary resource pool of the multiple resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the multiple resource pools based on the temporary resource pool;
and in a preset time period, carrying out resource management scheduling on the shared resource pools in the multiple resource pools and the cloud services in the shared resource pools based on the standard resource utilization rate.
The communication bus 114 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 114 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface 112 is used for communication between the above-described electronic apparatus and other apparatuses.
The memory 113 may include a Random Access Memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. Alternatively, the memory 113 may be at least one storage device located remotely from the processor 111.
The processor 111 may be a general-purpose processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the integrated circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components.
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring tenant information in a private cloud scene, and dividing a plurality of resource pools for tenants in the private cloud scene based on the tenant information;
receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and allocating the cloud service to an exclusive resource pool in the plurality of resource pools;
calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing treatment to obtain the standard resource utilization rate;
scheduling the cloud service to a temporary resource pool of the multiple resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the multiple resource pools based on the temporary resource pool;
and in a preset time period, carrying out resource management scheduling on the shared resource pools in the multiple resource pools and the cloud services in the shared resource pools based on the standard resource utilization rate.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A multi-tenant cloud service management method, the method comprising:
acquiring tenant information in a private cloud scene, and dividing a plurality of resource pools for tenants in the private cloud scene based on the tenant information;
receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and allocating the cloud service to an exclusive resource pool in the plurality of resource pools;
calculating the resource utilization rate of the cloud service in the exclusive resource pool, and performing smoothing treatment to obtain the standard resource utilization rate;
scheduling the cloud service to a temporary resource pool of the multiple resource pools according to the standard resource utilization rate, and performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool of the multiple resource pools based on the temporary resource pool;
and in a preset time period, carrying out resource management scheduling on the shared resource pools in the multiple resource pools and the cloud services in the shared resource pools based on the standard resource utilization rate.
2. The multi-tenant cloud service management method of claim 1, wherein the partitioning resource pools for tenants in the private cloud scenario based on the tenant information comprises:
searching historical resource calling information of the tenant based on the tenant information;
and dividing a shared resource pool, an exclusive resource pool and a temporary resource pool in the virtual machine preset by the tenant based on the historical resource calling information.
3. The multi-tenant cloud service management method of claim 1, wherein the obtaining a corresponding cloud service based on the cloud service request and allocating the cloud service to an exclusive resource pool of the plurality of resource pools comprises:
performing service marking on the cloud service corresponding to the cloud service request based on the tenant;
and distributing the cloud service to an exclusive resource pool of the tenant according to a preset network based on the service mark.
4. The method for managing the multi-tenant cloud service according to claim 1, wherein the computing the resource utilization rate of the cloud service in the exclusive resource pool and performing smoothing processing to obtain a standard resource utilization rate includes:
calculating the resource utilization rate of the cloud service according to preset granularity to obtain the original resource utilization rate;
and removing burr points in the original resource utilization rate by using an exponential smoothing algorithm to obtain the standard resource utilization rate.
5. The method for multi-tenant cloud service management as claimed in claim 4, wherein the removing a bur point in the original resource usage by using an exponential smoothing algorithm to obtain a standard resource usage comprises:
selecting a preset number of resource sequences from the original resource utilization rate to calculate a resource initial value;
and calculating the standard resource utilization rate under each preset granularity by utilizing a preset exponential smoothing formula based on the resource initial value.
6. The multi-tenant cloud service management method of claim 5, wherein the preset exponential smoothing formula is as follows:
S t ＝a*y t +(1-a)S t-1
wherein S is t A is the standard resource utilization rate of time t, a is the preset weight, y t Original resource usage as time t, S t-1 Is the standard resource usage at time t-1.
7. The method for multi-tenant cloud service management of claim 1, wherein the scheduling the cloud service to a temporary resource pool of the plurality of resource pools according to the standard resource usage rate, and performing resource management scheduling for cloud services in an exclusive resource pool and a shared resource pool of the plurality of resource pools based on the temporary resource pool comprises:
accumulating the standard resource utilization rate to obtain a resource utilization score;
taking the cloud service with the resource utilization score larger than or equal to a preset score threshold value as a cloud service with high resource utilization rate;
taking the cloud service with the resource utilization score smaller than the score threshold value as a cloud service with low resource utilization rate;
judging whether the cloud service judged to be low in resource utilization rate in the exclusive resource pool meets a preset first time range or not;
if the first time range is not met, the temporary resource pool is scheduled, and if the first time range is not met, the temporary resource pool is reserved in the exclusive resource pool;
continuously judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets a preset second time range or not;
if the preset second time range is met, scheduling the cloud service to a shared resource pool, and if the preset second time range is not met, scheduling the cloud service to the exclusive resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the low resource utilization rate in the temporary resource pool meets the preset second time range;
judging whether the cloud service judged as the high resource utilization rate in the shared resource pool meets a preset third time range or not;
if the preset third time range is met, scheduling the resource to the temporary resource pool, and if the preset third time range is not met, remaining the resource in the shared resource pool;
continuously judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets a preset fourth time range or not;
and if the preset fourth time range is met, scheduling the cloud service to an exclusive resource pool, and if the preset fourth time range is not met, scheduling the cloud service to the shared resource pool or the temporary resource pool, and returning to the step of judging whether the cloud service judged as the high resource utilization rate in the temporary resource pool meets the preset fourth time range.
8. An apparatus for multi-tenant cloud service management, the apparatus comprising:
the resource pool dividing module is used for acquiring tenant information in a private cloud scene and dividing a plurality of resource pools for the tenants in the private cloud scene based on the tenant information;
the cloud service allocation module is used for receiving a cloud service request of a tenant, acquiring a corresponding cloud service based on the cloud service request, and allocating the cloud service to an exclusive resource pool in the plurality of resource pools;
the resource smoothing processing module is used for calculating the resource utilization rate of the cloud service in the exclusive resource pool and performing smoothing processing to obtain the standard resource utilization rate;
and the cloud service scheduling module is used for scheduling the cloud service to a temporary resource pool in the plurality of resource pools according to the standard resource utilization rate, performing resource management scheduling on the cloud service in an exclusive resource pool and a shared resource pool in the plurality of resource pools based on the temporary resource pool, and performing resource management scheduling on the cloud service in the shared resource pool and the shared resource pool in the plurality of resource pools based on the standard resource utilization rate in a preset time period.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the multi-tenant cloud service management method of any of claims 1-7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the multi-tenant cloud service management method of any one of claims 1 through 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116610457A (en) * | 2023-07-20 | 2023-08-18 | 北京万界数据科技有限责任公司 | Resource scheduling method for AI cloud computing server group |
| CN116781729A (en) * | 2023-08-21 | 2023-09-19 | 中移(苏州)软件技术有限公司 | Resource information synchronization method, device, equipment and medium |
| CN117076142A (en) * | 2023-10-17 | 2023-11-17 | 阿里云计算有限公司 | Multi-tenant resource pool configuration method and multi-tenant service system |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116610457A (en) * | 2023-07-20 | 2023-08-18 | 北京万界数据科技有限责任公司 | Resource scheduling method for AI cloud computing server group |
| CN116610457B (en) * | 2023-07-20 | 2023-09-12 | 北京万界数据科技有限责任公司 | Resource scheduling method for AI cloud computing server group |
| CN116781729A (en) * | 2023-08-21 | 2023-09-19 | 中移(苏州)软件技术有限公司 | Resource information synchronization method, device, equipment and medium |
| CN117076142A (en) * | 2023-10-17 | 2023-11-17 | 阿里云计算有限公司 | Multi-tenant resource pool configuration method and multi-tenant service system |
| CN117076142B (en) * | 2023-10-17 | 2024-01-30 | 阿里云计算有限公司 | Multi-tenant resource pool configuration method and multi-tenant service system |
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