CN111400023A - Resource pool redundancy rate adjusting method, device, medium and equipment - Google Patents
Resource pool redundancy rate adjusting method, device, medium and equipment Download PDFInfo
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Abstract
The present invention relates to the field of core network technologies, and in particular, to a method, an apparatus, a medium, and a device for adjusting a redundancy rate of a resource pool. According to the scheme provided by the embodiment of the invention, the redundancy rate of the resource pool can be monitored in real time, the capacity expansion of the resource pool can be triggered once the redundancy rate of the resource pool is too low, and the capacity contraction of the resource pool can be triggered once the redundancy rate of the resource pool is too high, so that the redundancy rate of the resource pool can be timely adjusted. After the network element capacity expansion and the fault recovery self-healing are completed, the influence on the network element capacity expansion and the fault recovery self-healing performance due to the reduction of the redundancy rate of the resource pool is avoided. And the problem of resource waste caused by the increase of the redundancy rate of the resource pool after the network element is subjected to capacity reduction and failure can be avoided.
Description
Technical Field
The present invention relates to the field of core network technologies, and in particular, to a method, an apparatus, a medium, and a device for adjusting a redundancy rate of a resource pool.
Background
In a Network Function Virtualization (NFV) scenario, a bearer manner of a network element in a resource pool may be divided into the following 3 scenarios:
scene 1, a network element is borne on a virtual machine in a container mode, and the virtual machine is borne on a server;
scene 2, the network element is loaded on the server in the form of a container;
scene 3, the network element is loaded on the server in the form of a virtual machine.
In order to meet the requirement of network element scaling capacity, a part of idle standby resources (i.e., redundant resources) are required in the resource pool, and the proportion of the idle standby resources in the total resources of the resource pool is called the resource pool redundancy rate. For example, for scenario 1, a part of virtual machines and servers in the resource pool need to idle for standby, and for scenarios 2 and 3, a part of servers in the resource pool need to idle for standby.
After the network element has capacity expansion, failure or failure recovery self-healing, the redundancy rate of the resource pool changes, and the existing mechanism cannot adjust the redundancy rate of the resource pool in time, which may affect the performance of the network element such as capacity expansion, failure recovery self-healing, or may cause energy waste.
For example, when the network element is initially deployed in scenario 1, a server and a virtual machine in a resource pool reserve certain redundant resources (e.g., 30%) to cope with the network element capacity expansion and fault recovery self-healing processes. After the network element capacity expansion and the fault recovery self-healing are completed, the redundancy rate of the resource pool is reduced, and the capacity expansion and the fault recovery self-healing performance of the network element can be influenced due to the low redundancy rate of the resource pool. After the network element is scaled and fails, the redundancy rate of the resource pool is increased, and a certain resource waste exists due to the high redundancy rate of the resource pool.
When the network elements in the scenarios 2 and 3 are initially deployed, the server in the resource pool reserves a certain redundant resource (for example, 30%) to cope with the network element capacity expansion and fault recovery self-healing processes. After the network element capacity expansion and the fault recovery self-healing are completed, the redundancy rate of the resource pool is reduced, and the capacity expansion and the fault recovery self-healing performance of the network element can be influenced due to the low redundancy rate of the resource pool. After the network element is scaled and fails, the redundancy rate of the resource pool is increased, and a certain resource waste exists due to the high redundancy rate of the resource pool.
Disclosure of Invention
The embodiment of the invention provides a method, a device, a medium and equipment for adjusting the redundancy rate of a resource pool, which are used for solving the problem that the redundancy rate of the resource pool cannot be adjusted in time.
The invention provides a resource pool redundancy rate adjusting method, which comprises the following steps:
monitoring the redundancy rate of the resource pool in real time;
and when the monitoring result shows that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, carrying out capacity expansion on the resource pool, and when the monitoring result shows that the redundancy rate of the resource pool is higher than the preset redundancy rate set value of the resource pool, carrying out capacity reduction on the resource pool.
The present invention also provides a virtual infrastructure manager, VIM, comprising:
the monitoring module is used for monitoring the redundancy rate of the resource pool in real time;
and the adjusting module is used for expanding the capacity of the resource pool when the redundancy rate of the resource pool monitored by the monitoring module is lower than a preset value of the redundancy rate of the resource pool, and reducing the capacity of the resource pool when the redundancy rate of the resource pool monitored by the monitoring module is higher than a preset specified value of the redundancy rate of the resource pool.
The present invention also provides a non-volatile computer storage medium having stored thereon an executable program for execution by a processor to perform the steps of implementing the method as described above.
The invention also provides a resource pool redundancy rate adjusting device, which comprises a memory, a processor, a transceiver and a bus interface; the processor is used for reading the program in the memory and executing: monitoring a resource pool redundancy rate in real time by the transceiver; and when the monitoring result shows that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, carrying out capacity expansion on the resource pool, and when the monitoring result shows that the redundancy rate of the resource pool is higher than the preset redundancy rate set value of the resource pool, carrying out capacity reduction on the resource pool.
According to the scheme provided by the embodiment of the invention, the redundancy rate of the resource pool can be monitored in real time, the capacity expansion of the resource pool can be triggered once the redundancy rate of the resource pool is too low, and the capacity contraction of the resource pool can be triggered once the redundancy rate of the resource pool is too high, so that the redundancy rate of the resource pool can be timely adjusted. The method avoids the influence on performance and reliability caused by the reduction of the redundancy rate of the resource pool after the network element acts, such as capacity expansion and fault recovery self-healing. And the problem of resource waste caused by the increase of the redundancy rate of the resource pool after the network element acts, such as capacity reduction and failure can be avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for adjusting a redundancy rate of a resource pool according to an embodiment of the present invention;
fig. 2 is a schematic view of a scenario 1 of a bearer manner of a network element in a resource pool according to an embodiment of the present invention;
fig. 3 is a schematic view of a scenario 2/3 of a bearer manner of a network element in a resource pool according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a VIM according to a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of a resource pool redundancy rate adjustment device according to a third embodiment of the present invention.
Detailed Description
The inventor researches and discovers that the existing mechanism has no automatic adjustment function of the redundancy rate of the resource pool, is lack of flexibility, cannot follow the actions of the network element, such as expansion and contraction capacity, fault occurrence, fault recovery and self-healing and other automatic adjustments, and can influence the capacity expansion and fault recovery and self-healing performance of the network element or cause resource waste and the like.
Therefore, the embodiment of the invention provides an automatic adjustment scheme for the redundancy rate of a resource pool. In the scheme, the resource pool redundancy rate is used as a monitoring index (the index can be set), when the resource pool redundancy rate changes, if the resource pool redundancy rate is smaller than a set threshold value, the capacity expansion of the resource pool is triggered, and if the resource pool redundancy rate is larger than a specified threshold value, the capacity reduction of the resource pool is triggered.
The scheme provided by the embodiment of the invention can trigger the capacity expansion by the physical layer under the condition of not influencing the network architecture. By enhancing the capability of a Virtual Infrastructure Manager (VIM), a resource pool redundancy rate monitoring mechanism and an automatic capacity expansion and reduction function of a resource pool can be added aiming at different scenes of a bearing mode of a network element in the resource pool. Therefore, the method can be matched with network element actions such as automatic expansion and contraction capacity, fault occurrence and fault recovery self-healing, the performance and the reliability are ensured, and energy conservation and emission reduction are realized.
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that, the "plurality" or "a plurality" mentioned herein means two or more. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
The terms "first," "second," and the like in the description and in the claims, and in the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
An embodiment of the present invention provides a method for adjusting a redundancy rate of a resource pool, where a flow of steps of the method may be as shown in fig. 1, and the method includes:
step 101, monitoring the redundancy rate of the resource pool in real time.
In this step, the redundancy rate of the resource pool can be monitored in real time, so that the expansion and contraction capacity of the resource pool can be performed in time according to the change of the redundancy rate of the resource pool.
The real-time monitoring of the redundancy rate of the resource pool can be realized by monitoring any redundancy rate monitoring index of the resource pool. For example, but not limited to, this may be accomplished by monitoring any of a Central Processing Unit (CPU) redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate. As another example, the monitoring may be performed by monitoring three of a Central Processing Unit (CPU) redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate.
And 102, carrying out expansion and contraction.
In this step, when it is monitored that the redundancy rate of the resource pool is lower than a preset value of the redundancy rate of the resource pool, the resource pool is expanded, and when it is monitored that the redundancy rate of the resource pool is higher than a preset specified value of the redundancy rate of the resource pool, the resource pool is contracted.
For example, when the preset resource pool redundancy rate is 30%, the capacity of the resource pool may be expanded when the resource pool redundancy rate is monitored to be lower than 20% (i.e., the set value is 10%). For another example, when the preset resource pool redundancy rate is 30%, it may be monitored that the resource pool redundancy rate is higher than 20% (that is, the designated value is 10%, in this embodiment, the designated value and the set value may be the same or different), the resource pool is reduced.
It should be noted that the preset resource pool redundancy rate may have different values according to different time periods. Specifically, the preset resource pool redundancy rate may not be greater than a first set value in a first designated period, and/or the preset resource pool redundancy rate may not be less than a second set value in a second designated period.
For example, considering that night traffic is relatively not heavy, a smaller resource pool redundancy rate may be set for the night time period, and the first setting value may be determined, but not limited to, according to historical data analysis corresponding to the night time period. As another example, considering that the holiday (which may be understood to include weekends) is relatively busy in traffic, a greater resource pool redundancy rate may be set for the holiday period, where the second set value may be determined, but not limited to, from historical data analysis corresponding to the holiday period.
When the redundancy rate of the resource pool monitored in real time is low, the capacity of the resource pool is expanded in time, so that the effect of improving the performance and the reliability of the resource pool can be achieved, and when the redundancy rate of the resource pool monitored in real time is high, the capacity of the resource pool is reduced in time, so that the effect of reducing resource waste can be achieved.
It should be noted that, in a possible implementation manner, when the resource pool is expanded, the expansion size may be, but is not limited to, the number of resources required to achieve the preset resource pool redundancy rate; when the resource pool is scaled, the scaling size may be, but is not limited to, the number of resources required to achieve the preset resource pool redundancy rate. That is, in this embodiment, the expansion/contraction capacity can be automatically determined according to the resource pool redundancy rate monitored in real time and the preset resource pool redundancy rate.
It should be noted that, if in step 101, any one of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate of the central processing unit corresponding to the resource pool is monitored in real time, in this step, when it is monitored that the CPU redundancy rate, the network bandwidth redundancy rate, or the memory redundancy rate is lower than a preset resource pool redundancy rate set value, capacity expansion may be performed on the resource pool; and when the CPU redundancy rate, the network bandwidth redundancy rate or the memory redundancy rate is monitored to be higher than a preset specified value of the resource pool redundancy rate, capacity reduction can be carried out on the resource pool.
If the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate of the central processing unit corresponding to the resource pool are monitored in real time in step 101, in this step, when it is monitored that any one of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate is lower than a preset resource pool redundancy rate set value, capacity expansion of the resource pool may be performed; and when the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate are monitored to be higher than preset resource pool redundancy rate set values, capacity reduction can be carried out on the resource pool.
If the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate of the central processing unit corresponding to the resource pool are monitored in real time in step 101, in this step, the capacity of the resource pool may be expanded when the average of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate is monitored to be lower than a preset resource pool redundancy rate set value; and when the average value of the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate is higher than a preset resource pool redundancy rate set value, carrying out capacity reduction on the resource pool.
Of course, the triggering conditions for the expansion/contraction capacity may be different according to different monitored resource pool redundancy rate monitoring indexes, and this embodiment is not described again.
It should be noted that the scheme provided in this embodiment is applicable to all of the 3 scenarios of the bearer mode of the network element in the resource pool mentioned in the background art.
With respect to scenario 1, a schematic diagram thereof may be as shown in fig. 2, where the network element is carried in the form of a container (denoted by c in fig. 2) on a virtual machine (denoted by VM in fig. 2), and it may be assumed that two virtual machines are carried on the same server (denoted by server1 in fig. 2). In scenario 1, when the network elements are not deployed together with a virtual machine, each network element is composed of a plurality of unshared virtual machines into a dedicated resource pool. At this time, the resource pool corresponding to the monitored resource pool redundancy rate may be understood as a resource pool corresponding to a single network element. When the network element co-virtual machine is deployed, the resource pool corresponding to the monitored resource pool redundancy rate can be understood as an overall resource pool corresponding to a plurality of network elements.
In scenario 1, upon initial deployment of a network element, the required resources may be declared to the orchestration container tool (K8S) for instantiation. Furthermore, a resource pool redundancy rate can be preset, and the resource pool redundancy rate of the resource pool can be monitored in real time.
When the network element acts, such as automatic capacity expansion, the number of containers is increased, the resource allocation rate in the resource pool is increased, and the redundancy rate of the resource pool is reduced. When the redundancy rate of the resource pool is lower than the preset redundancy rate setting value of the resource pool, the capacity of the resource pool needs to be expanded.
For scenario 1, expanding the resource pool may include:
opening a first number of servers in the resource pool that have been closed, creating a second number of virtual machines on the servers, and adding the virtual machines to a container infrastructure.
Specifically, the K8S interface may be invoked to join the virtual machine into the K8S infrastructure. And when the expansion size is the quantity of the resources required for reaching the preset redundancy rate of the resource pool, the first quantity and the second quantity can be determined according to the quantity of the required resources.
When the network element acts, such as automatic capacity reduction, the number of containers is reduced, the resource allocation rate in the resource pool is reduced, and the redundancy rate of the resource pool is increased. When the redundancy rate of the resource pool is higher than the preset specified value of the redundancy rate of the resource pool, the capacity of the resource pool needs to be expanded.
For scenario 1, the capacity reduction of the resource pool may include:
removing a third number of virtual machines in the resource pool that no longer bear containers from the container infrastructure, deleting the virtual machines, and shutting down a fourth number of servers bearing the virtual machines.
Specifically, the K8S interface may be invoked to remove the virtual machine from the K8S infrastructure. And when the size of the capacity reduction is the number of resources required for achieving the preset redundancy rate of the resource pool, the third number and the fourth number can be determined according to the number of the required resources.
For scenario 2/3, a schematic diagram thereof may be as shown in fig. 3, where network elements are hosted on a server (represented in fig. 3 by server 1) in the form of containers/virtual machines (represented in fig. 3 by C and by VM), and it may be assumed that two containers/virtual machines are hosted on the same server. In the scenario 2/3, when the network element is directly loaded on the server in the form of a virtual machine or the network element is loaded on the server in the form of a container (network element co-virtual machine), the container may be directly deployed on a physical server, and containers or virtual machines of different network elements may be deployed on the same server/virtual machine, where a resource pool corresponding to the monitored resource pool redundancy rate may be understood as an entire resource pool corresponding to a plurality of network elements.
In the scenario 2/3, when the network elements are initially deployed, the required resources may be declared to K8S/VIM, and each network element may be instantiated and deployed. Furthermore, a resource pool redundancy rate can be preset, and the resource pool redundancy rate of the resource pool can be monitored in real time.
When the network element acts, such as automatic capacity expansion, the number of containers/virtual machines is increased, the resource allocation rate in the resource pool is increased, and the redundancy rate of the resource pool is reduced. When the redundancy rate of the resource pool is lower than the preset redundancy rate setting value of the resource pool, the capacity of the resource pool needs to be expanded.
For scenario 2/3, expanding the resource pool may include:
and opening a fifth number of closed servers in the resource pool.
Specifically, when the capacity expansion size is the number of resources required to achieve the preset resource pool redundancy rate, the fifth number may be determined according to the number of resources required.
When the network element acts, such as automatic capacity reduction, the number of containers/virtual machines is reduced, the resource allocation rate in the resource pool is reduced, and the redundancy rate of the resource pool is increased. When the redundancy rate of the resource pool is higher than the preset specified value of the redundancy rate of the resource pool, the capacity of the resource pool needs to be expanded.
For scenario 2/3, the capacity reduction of the resource pool may include:
shutting down a sixth number of servers in the resource pool that are no longer hosting containers or virtual machines.
Specifically, when the expansion size is the number of resources required to achieve the preset resource pool redundancy rate, the sixth number may be determined according to the number of resources required.
In the solution provided in the first embodiment of the present invention, network element actions, such as automatic capacity expansion and capacity expansion, may be matched to perform automatic capacity expansion and capacity expansion of the resource pool as needed, so as to implement real-time adjustment of the redundancy rate of the resource pool, implement optimized use of resources, avoid resource idling, and provide sufficient redundant resources.
The scheme provided by the embodiment of the invention can be applied to 3 scenes of the bearing mode of the network element in the resource pool. And the preset resource pool redundancy rate can be dynamically adjusted, and an intelligent adjustment mechanism of the preset resource pool redundancy rate is added, so that the method is suitable for severe changes of network elements in special time periods such as holidays and the like. And the expansion and contraction capacity amplitude of the resource pool can be reasonably determined according to network element actions, such as expansion and contraction capacity conditions. The monitoring index of the resource pool redundancy rate may include, but is not limited to, a CPU redundancy rate, a network bandwidth redundancy rate, a memory redundancy rate, and the like.
Based on the same inventive concept as the first embodiment, the following apparatuses are provided.
Example two
An embodiment of the present invention provides a VIM, where a structure of the VIM may be as shown in fig. 4, and the VIM includes:
the monitoring module 11 is used for monitoring the redundancy rate of the resource pool in real time;
the adjusting module 12 is configured to expand the resource pool when the redundancy rate of the resource pool monitored by the monitoring module is lower than a preset value of the redundancy rate of the resource pool, and reduce the capacity of the resource pool when the redundancy rate of the resource pool monitored by the monitoring module is higher than a preset value of the redundancy rate of the resource pool.
When the adjustment module 12 expands the resource pool, the expansion size is the quantity of the resources needed to reach the preset resource pool redundancy rate; and when the resource pool is subjected to capacity reduction, the capacity reduction size is the quantity of the resources required for reaching the preset resource pool redundancy rate.
It should be noted that, during the first designated period, the preset resource pool redundancy rate may not be greater than the first set value, and/or, during the second designated period, the preset resource pool redundancy rate may not be less than the second set value.
The network element is borne on a virtual machine in a container mode, and when the virtual machine is borne on a server:
the adjustment module 12 expands the capacity of the resource pool, including:
opening a first number of closed servers in the resource pool, creating a second number of virtual machines on the servers, and adding the virtual machines into a container infrastructure;
the adjusting module 12 reduces the capacity of the resource pool, including:
removing a third number of virtual machines in the resource pool that no longer bear containers from the container infrastructure, deleting the virtual machines, and shutting down a fourth number of servers bearing the virtual machines.
When the network element is borne on the server in the form of a container, or the network element is borne on the server in the form of a virtual machine:
the adjustment module 12 expands the capacity of the resource pool, including:
starting a fifth number of closed servers in the resource pool;
the adjusting module 12 reduces the capacity of the resource pool, including:
shutting down a sixth number of servers in the resource pool that are no longer hosting containers or virtual machines.
The monitoring module 11 is specifically configured to monitor any one of a CPU redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate of a central processing unit corresponding to the resource pool in real time;
the adjusting module 12 is specifically configured to expand the resource pool when the CPU redundancy rate, the network bandwidth redundancy rate, or the memory redundancy rate monitored by the monitoring module is lower than a preset resource pool redundancy rate set value; and when the CPU redundancy rate, the network bandwidth redundancy rate or the memory redundancy rate monitored by the monitoring module is higher than a preset specified value of the resource pool redundancy rate, performing capacity reduction on the resource pool.
The monitoring module 11 is specifically configured to monitor a CPU redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate of a central processing unit corresponding to the resource pool in real time;
the adjusting module 12 is specifically configured to expand the resource pool when any one of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate monitored by the monitoring module is lower than a preset resource pool redundancy rate set value; and when the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate monitored by the monitoring module are all higher than preset resource pool redundancy rate set values, capacity reduction is carried out on the resource pool.
The monitoring module 11 is specifically configured to monitor a CPU redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate of a central processing unit corresponding to the resource pool in real time;
the adjusting module 12 is specifically configured to expand the resource pool when the average value of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate monitored by the monitoring module is lower than a preset resource pool redundancy rate set value; and when the average value of the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate monitored by the monitoring module is higher than a preset resource pool redundancy rate set value, performing capacity reduction on the resource pool.
Based on the same inventive concept, embodiments of the present invention provide the following apparatus and medium.
EXAMPLE III
A third embodiment of the present invention provides a device for adjusting a redundancy rate of a resource pool, where the device may have a structure as shown in fig. 5, and includes a memory 21, a processor 22, and a computer program stored in the memory, and when the processor 22 executes the computer program, the steps of the method in the first embodiment of the present invention are implemented.
Optionally, the processor 22 may specifically include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), one or more integrated circuits for controlling program execution, a hardware circuit developed by using a Field Programmable Gate Array (FPGA), or a baseband processor.
Optionally, the processor 22 may include at least one processing core.
Alternatively, the memory 21 may include a Read Only Memory (ROM), a Random Access Memory (RAM), and a disk memory. The memory 21 is used for storing data required by the at least one processor 22 during operation. The number of the memory 21 may be one or more.
A fourth embodiment of the present invention provides a non-volatile computer storage medium, where the computer storage medium stores an executable program, and when the executable program is executed by a processor, the method provided in the first embodiment of the present invention is implemented.
In particular implementations, computer storage media may include: various storage media capable of storing program codes, such as a Universal Serial Bus flash drive (USB), a mobile hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
In the embodiments of the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the described unit or division of units is only one division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical or other form.
The functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be an independent physical module.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the technical solutions of the embodiments of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device, such as a personal computer, a server, or a network device, or a processor (processor) to execute all or part of the steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media that can store program codes, such as a universal serial bus flash drive (usb flash drive), a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (18)
1. A resource pool redundancy rate adjustment method is characterized by comprising the following steps:
monitoring the redundancy rate of the resource pool in real time;
and when the monitoring result shows that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, carrying out capacity expansion on the resource pool, and when the monitoring result shows that the redundancy rate of the resource pool is higher than the preset redundancy rate set value of the resource pool, carrying out capacity reduction on the resource pool.
2. The method of claim 1, wherein when the resource pool is expanded, the expansion size is the amount of resources needed to achieve the preset resource pool redundancy rate;
and when the resource pool is subjected to capacity reduction, the capacity reduction size is the quantity of the resources required for reaching the preset resource pool redundancy rate.
3. The method of claim 1, wherein the predetermined resource pool redundancy rate is not greater than a first set point for a first specified period of time and/or the predetermined resource pool redundancy rate is not less than a second set point for a second specified period of time.
4. The method according to any one of claims 1 to 3, wherein the network element is loaded in the form of a container in the virtual machine, and when the virtual machine is loaded on the server, capacity expansion is performed on the resource pool, including:
opening a first number of closed servers in the resource pool, creating a second number of virtual machines on the servers, and adding the virtual machines into a container infrastructure;
the network element is loaded on a virtual machine in a container mode, and when the virtual machine is loaded on a server, the capacity reduction is carried out on a resource pool, and the capacity reduction method comprises the following steps:
removing a third number of virtual machines in the resource pool that no longer bear containers from the container infrastructure, deleting the virtual machines, and shutting down a fourth number of servers bearing the virtual machines.
5. The method according to any one of claims 1 to 3, wherein the expanding the capacity of the resource pool when the network element is carried on the server in a container form or when the network element is carried on the server in a virtual machine form includes:
starting a fifth number of closed servers in the resource pool;
when the network element is loaded on the server in the form of a container, or the network element is loaded on the server in the form of a virtual machine, the method for capacity reduction of the resource pool comprises the following steps:
shutting down a sixth number of servers in the resource pool that are no longer hosting containers or virtual machines.
6. The method of any one of claims 1 to 3, wherein monitoring the resource pool redundancy rate in real time comprises:
monitoring any item of CPU redundancy rate, network bandwidth redundancy rate and memory redundancy rate corresponding to the resource pool in real time;
when monitoring that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, expanding the capacity of the resource pool, including:
when the CPU redundancy rate, the network bandwidth redundancy rate or the memory redundancy rate is monitored to be lower than a preset resource pool redundancy rate set value, expanding the capacity of the resource pool;
when monitoring that the redundancy rate of the resource pool is higher than the preset specified value of the redundancy rate of the resource pool, carrying out capacity reduction on the resource pool, comprising the following steps:
and when the CPU redundancy rate, the network bandwidth redundancy rate or the memory redundancy rate is monitored to be higher than a preset specified value of the resource pool redundancy rate, carrying out capacity reduction on the resource pool.
7. The method of any one of claims 1 to 3, wherein monitoring the resource pool redundancy rate in real time comprises:
monitoring the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate of a central processing unit corresponding to the resource pool in real time;
when monitoring that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, expanding the capacity of the resource pool, including:
when any one of the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate is monitored to be lower than a preset resource pool redundancy rate set value, carrying out capacity expansion on a resource pool;
when monitoring that the redundancy rate of the resource pool is higher than the preset specified value of the redundancy rate of the resource pool, carrying out capacity reduction on the resource pool, comprising the following steps:
and when the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate are monitored to be higher than preset resource pool redundancy rate set values, carrying out capacity reduction on the resource pool.
8. The method of any one of claims 1 to 3, wherein monitoring the resource pool redundancy rate in real time comprises:
monitoring the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate of a central processing unit corresponding to the resource pool in real time;
when monitoring that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, expanding the capacity of the resource pool, including:
when the average value of the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate is lower than a preset resource pool redundancy rate set value, expanding the capacity of the resource pool;
when monitoring that the redundancy rate of the resource pool is higher than the preset specified value of the redundancy rate of the resource pool, carrying out capacity reduction on the resource pool, comprising the following steps:
and when the average value of the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate is higher than a preset resource pool redundancy rate set value, carrying out capacity reduction on the resource pool.
9. A virtual infrastructure manager, VIM, comprising:
the monitoring module is used for monitoring the redundancy rate of the resource pool in real time;
and the adjusting module is used for expanding the capacity of the resource pool when the redundancy rate of the resource pool monitored by the monitoring module is lower than a preset value of the redundancy rate of the resource pool, and reducing the capacity of the resource pool when the redundancy rate of the resource pool monitored by the monitoring module is higher than a preset specified value of the redundancy rate of the resource pool.
10. The VIM of claim 9, wherein the adjustment module, when expanding the capacity of the resource pool, expands the capacity to the amount of resources needed to achieve the predetermined resource pool redundancy rate; and when the resource pool is subjected to capacity reduction, the capacity reduction size is the quantity of the resources required for reaching the preset resource pool redundancy rate.
11. The VIM of claim 9, wherein the predetermined resource pool redundancy rate is not greater than a first set point for a first designated time period, and/or wherein the predetermined resource pool redundancy rate is not less than a second set point for a second designated time period.
12. The VIM of any of claims 9 to 11, wherein the network element is hosted by a virtual machine in the form of a container, and when the virtual machine is hosted by a server, the adjusting module expands the resource pool, including:
opening a first number of closed servers in the resource pool, creating a second number of virtual machines on the servers, and adding the virtual machines into a container infrastructure;
when the network element is loaded on the virtual machine in the form of a container and the virtual machine is loaded on the server, the adjusting module reduces the capacity of the resource pool, including:
removing a third number of virtual machines in the resource pool that no longer bear containers from the container infrastructure, deleting the virtual machines, and shutting down a fourth number of servers bearing the virtual machines.
13. The VIM of any of claims 9 to 11, wherein the adjusting module, when the network element is loaded on the server in the form of a container, or when the network element is loaded on the server in the form of a virtual machine, performs capacity expansion on the resource pool, and includes:
starting a fifth number of closed servers in the resource pool;
when the network element is loaded on the server in the form of a container, or the network element is loaded on the server in the form of a virtual machine, the adjusting module reduces the capacity of the resource pool, and the method includes:
shutting down a sixth number of servers in the resource pool that are no longer hosting containers or virtual machines.
14. The VIM of any of claims 9 to 11, wherein the monitoring module is specifically configured to monitor any of a CPU redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate of the resource pool in real time;
the adjusting module is specifically configured to expand the resource pool when the CPU redundancy rate, the network bandwidth redundancy rate, or the memory redundancy rate monitored by the monitoring module is lower than a preset resource pool redundancy rate set value; and when the CPU redundancy rate, the network bandwidth redundancy rate or the memory redundancy rate monitored by the monitoring module is higher than a preset specified value of the resource pool redundancy rate, performing capacity reduction on the resource pool.
15. The VIM of any of claims 9 to 11, wherein the monitoring module is specifically configured to monitor a CPU redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate of the resource pool in real time;
the adjusting module is specifically configured to expand the resource pool when any one of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate monitored by the monitoring module is lower than a preset resource pool redundancy rate set value; and when the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate monitored by the monitoring module are all higher than preset resource pool redundancy rate set values, capacity reduction is carried out on the resource pool.
16. The VIM of any of claims 9 to 11, wherein the monitoring module is specifically configured to monitor a CPU redundancy rate, a network bandwidth redundancy rate, and a memory redundancy rate of the resource pool in real time;
the adjusting module is specifically configured to expand the resource pool when an average value of the CPU redundancy rate, the network bandwidth redundancy rate, and the memory redundancy rate monitored by the monitoring module is lower than a preset resource pool redundancy rate set value; and when the average value of the CPU redundancy rate, the network bandwidth redundancy rate and the memory redundancy rate monitored by the monitoring module is higher than a preset resource pool redundancy rate set value, performing capacity reduction on the resource pool.
17. A non-transitory computer storage medium storing an executable program for execution by a processor to perform the steps of the method of any one of claims 1 to 8.
18. A resource pool redundancy rate adjusting device is characterized by comprising a memory, a processor, a transceiver and a bus interface; the processor is used for reading the program in the memory and executing: monitoring a resource pool redundancy rate in real time by the transceiver; and when the monitoring result shows that the redundancy rate of the resource pool is lower than the preset redundancy rate set value of the resource pool, carrying out capacity expansion on the resource pool, and when the monitoring result shows that the redundancy rate of the resource pool is higher than the preset redundancy rate set value of the resource pool, carrying out capacity reduction on the resource pool.
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