CN117519973A - Resource adjusting method, device and equipment - Google Patents
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
- G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
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- G06F9/44—Arrangements for executing specific programs
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- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/4557—Distribution of virtual machine instances; Migration and load balancing
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Abstract
The application provides a resource adjusting method, a device and equipment, and relates to the field of big data. The method comprises the following steps: acquiring historical load information of a target application in a historical period, wherein the historical load information comprises a plurality of historical moments and historical load amounts corresponding to each historical moment; determining estimated load of the target application in a target period according to the historical load information; determining a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount; acquiring historical resource use information of the target application according to the target resource adjustment period, and determining target resource allocation amount of the target application according to the historical resource use information and the maximum resource allocation amount; and carrying out resource allocation for the target application according to the target resource allocation amount. The method improves the flexibility of resource adjustment.
Description
Technical Field
The present disclosure relates to the field of big data, and in particular, to a method, an apparatus, and a device for resource adjustment.
Background
The resource adjusting means may perform resource allocation and adjustment for the application.
Currently, the resource adjusting device can adjust resources for an application according to the load of the application. For example, the load amount may be the number of service processing requests received in an application unit time unit, etc., and the resource may be the number of container groups (Pods). However, the resource adjustment device defaults to perform resource adjustment for the application according to a fixed resource adjustment period, and cannot flexibly adjust the resource adjustment period in a service peak period or a service low peak period, which results in poor flexibility of resource adjustment.
Disclosure of Invention
The application provides a resource adjusting method, a device and equipment, which are used for solving the problem of poor flexibility of resource adjustment.
In a first aspect, the present application provides a resource adjustment method, including: acquiring historical load information of a target application in a historical period, wherein the historical load information comprises a plurality of historical moments and historical load amounts corresponding to each historical moment;
determining estimated load of the target application in a target period according to the historical load information;
determining a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount;
Acquiring historical resource use information of the target application according to the target resource adjustment period, and determining target resource allocation amount of the target application according to the historical resource use information and the maximum resource allocation amount;
and carrying out resource allocation for the target application according to the target resource allocation amount.
In a possible implementation manner, determining, according to the historical load information, an estimated load amount of the target application in a target period includes:
according to the historical load information, determining a historical load curve of the target application in the historical period;
acquiring service information of the target application in the target period, wherein the service information comprises at least one of the following: order information, activity information, or index demand information;
and determining the estimated load according to the historical load curve and the service information.
In a possible implementation manner, determining the estimated load according to the historical load curve and the service information includes:
determining an initial load amount according to the historical load curve and the target period;
according to the service information, determining a load factor, wherein the load factor is used for indicating the ratio of the load capacity corresponding to the service information to the preset load capacity;
And determining the product of the initial load and the load coefficient as the estimated load.
In a possible implementation manner, determining a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount includes:
in the multiple load areas, determining a target load interval in which the estimated load is located;
acquiring a plurality of historical resource adjustment information, wherein the historical resource adjustment period comprises: history load amount, history adjustment period, history resource utilization rate and history processing efficiency;
and determining the target resource adjustment period and the maximum resource allocation amount according to the target load interval and the plurality of historical resource adjustment information.
In a possible implementation manner, determining the target resource adjustment period and the maximum resource allocation amount according to the target load interval and the plurality of historical resource adjustment information includes:
determining a plurality of pieces of resource adjustment information to be selected from the plurality of pieces of historical resource adjustment information according to the target load capacity interval, wherein the historical load capacity in the resource adjustment information to be selected is located in the target load capacity interval;
According to the historical resource utilization rate and the historical processing efficiency in the resource adjustment information to be selected, determining first resource adjustment information in the plurality of resource adjustment information to be selected, wherein the historical processing efficiency in the first resource adjustment information is greater than or equal to a first threshold value, and the historical resource utilization rate in the first resource adjustment information is greater than or equal to a second threshold value;
and determining the target resource adjustment period and the maximum resource allocation amount according to the first resource adjustment information.
In a possible implementation manner, determining the target resource adjustment period and the maximum resource allocation amount according to the first resource adjustment information includes:
if the number of the first resource adjustment information is 1, determining a resource adjustment period in the first resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the first adjustment information as the maximum resource allocation amount;
if the number of the first resource adjustment information is greater than 1, determining target resource adjustment information in a plurality of first resource adjustment information according to the historical resource utilization rate and the historical processing efficiency in each first resource adjustment information, determining a resource adjustment period in the target resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the target adjustment information as the maximum resource allocation amount.
In a possible implementation manner, determining target resource adjustment information in a plurality of first resource adjustment information according to the historical resource utilization rate and the historical processing efficiency in each first resource adjustment information includes:
for any one piece of first resource adjustment information, carrying out weighted summation processing on the historical resource utilization rate and the historical processing efficiency in the first resource adjustment information to obtain a weight value corresponding to the first resource adjustment information;
and determining the first resource adjustment information with the maximum weight value as the target resource adjustment information.
In a possible implementation manner, determining the target resource allocation amount of the target application according to the historical resource usage information and the maximum resource allocation amount includes:
updating a first model according to the historical resource use information to obtain an updating result of the first model, wherein the first model is obtained by learning the historical resource allocation information of the target application;
if the updating result is successful and the state of the first model is normal, the historical resource use information is processed through the first model to obtain a first resource allocation amount;
If the updating result is that the updating is failed or the state of the first model is an abnormal state, the historical resource information is processed through a second model to obtain a first resource allocation amount, and the second model is obtained by learning the historical resource allocation information of a plurality of applications;
and determining the minimum value of the first resource allocation amount and the maximum resource allocation amount as the target resource allocation amount.
In a second aspect, the present application provides a resource adjustment device, including: the device comprises an acquisition module, a determination module and an allocation module, wherein,
the acquisition module is used for acquiring historical load information of the target application in a historical period, wherein the historical load information comprises a plurality of historical moments and historical load amounts corresponding to each historical moment;
the determining module is used for determining estimated load of the target application in a target period according to the historical load information;
the determining module is further configured to determine a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount;
the acquisition module is further used for acquiring historical resource use information of the target application according to the resource adjustment period;
The determining module is further configured to determine a target resource allocation amount of the target application according to the historical resource usage information and the maximum resource allocation amount;
the allocation module is used for allocating resources for the target application according to the target resource allocation amount.
In a possible implementation, the determining module is specifically configured to,
according to the historical load information, determining a historical load curve of the target application in the historical period;
acquiring service information of the target application in the target period, wherein the service information comprises at least one of the following: order information, activity information, or index demand information;
and determining the estimated load according to the historical load curve and the service information.
In a possible implementation, the determining module is specifically configured to,
determining an initial load amount according to the historical load curve and the target period;
according to the service information, determining a load factor, wherein the load factor is used for indicating the ratio of the load capacity corresponding to the service information to the preset load capacity;
and determining the product of the initial load and the load coefficient as the estimated load.
In a possible implementation, the determining module is specifically configured to,
in the multiple load areas, determining a target load interval in which the estimated load is located;
acquiring a plurality of historical resource adjustment information, wherein the historical resource adjustment period comprises: history load amount, history adjustment period, history resource utilization rate and history processing efficiency;
and determining the target resource adjustment period and the maximum resource allocation amount according to the target load interval and the plurality of historical resource adjustment information.
In a possible implementation, the determining module is specifically configured to,
determining a plurality of pieces of resource adjustment information to be selected from the plurality of pieces of historical resource adjustment information according to the target load capacity interval, wherein the historical load capacity in the resource adjustment information to be selected is located in the target load capacity interval;
according to the historical resource utilization rate and the historical processing efficiency in the resource adjustment information to be selected, determining first resource adjustment information in the plurality of resource adjustment information to be selected, wherein the historical processing efficiency in the first resource adjustment information is greater than or equal to a first threshold value, and the historical resource utilization rate in the first resource adjustment information is greater than or equal to a second threshold value;
And determining the target resource adjustment period and the maximum resource allocation amount according to the first resource adjustment information.
In a possible implementation, the determining module is specifically configured to,
if the number of the first resource adjustment information is 1, determining a resource adjustment period in the first resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the first adjustment information as the maximum resource allocation amount;
if the number of the first resource adjustment information is greater than 1, determining target resource adjustment information in a plurality of first resource adjustment information according to the historical resource utilization rate and the historical processing efficiency in each first resource adjustment information, determining a resource adjustment period in the target resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the target adjustment information as the maximum resource allocation amount.
In a possible implementation, the determining module is specifically configured to,
for any one piece of first resource adjustment information, carrying out weighted summation processing on the historical resource utilization rate and the historical processing efficiency in the first resource adjustment information to obtain a weight value corresponding to the first resource adjustment information;
And determining the first resource adjustment information with the maximum weight value as the target resource adjustment information.
In a possible implementation, the determining module is specifically configured to,
updating a first model according to the historical resource use information to obtain an updating result of the first model, wherein the first model is obtained by learning the historical resource allocation information of the target application;
if the updating result is successful and the state of the first model is normal, the historical resource use information is processed through the first model to obtain a first resource allocation amount;
if the updating result is that the updating is failed or the state of the first model is an abnormal state, the historical resource information is processed through a second model to obtain a first resource allocation amount, and the second model is obtained by learning the historical resource allocation information of a plurality of applications;
and determining the minimum value of the first resource allocation amount and the maximum resource allocation amount as the target resource allocation amount.
In a third aspect, the present application provides a resource adjustment device, including: a processor, and a memory communicatively coupled to the processor;
The memory stores computer-executable instructions;
the processor executes computer-executable instructions stored in the memory to implement the method of any one of the first aspects.
In a fourth aspect, the present application provides a computer-readable storage medium having stored therein computer-executable instructions for performing the method of any of the first aspects when executed by a processor.
In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by a computer, implements the method according to any of the first aspects.
In the resource adjusting method, the resource adjusting device and the equipment provided by the application, the resource adjusting device can acquire the historical load information of the target application in the historical period; the estimated load of the target application in the target period can be determined according to the historical load information; the target resource adjustment period and the maximum resource allocation amount of the target application can be determined according to the estimated load; the historical resource use information of the target application can be obtained according to the target resource adjustment period, and the target resource allocation amount of the target application is determined according to the historical resource use information and the maximum resource allocation amount; and the resource allocation can be performed for the target application according to the target resource allocation amount. By the method, the resource adjusting device can flexibly adjust the resource adjusting period according to the historical load information of the application, so that the resource adjustment is carried out for the application according to the adjusted resource adjusting period, and the flexibility of the resource adjustment is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of a resource adjustment method according to an embodiment of the present application;
FIG. 3 is a flowchart illustrating another resource adjustment method according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a resource adjusting device according to an embodiment of the present application;
fig. 5 is a schematic hardware structure of a resource adjusting device according to an embodiment of the present application.
Specific embodiments thereof have been shown by way of example in the drawings and will herein be described in more detail. These drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or fully authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards, and provide corresponding operation entries for the user to select authorization or rejection.
It should be noted that, the resource adjustment method, the device and the equipment provided in the embodiments of the present application may be used in the big data field, and may also be used in any field other than the big data field, and the resource adjustment method, the device and the equipment provided in the embodiments of the present application are not limited.
For ease of understanding, the technical terms related to the embodiments of the present application will be explained first.
Application template (deviyment): acts on the creation and execution of a set of container groups (Pods) that adjust the number of Pods by controlling the number of copies in the application template through a copy controller (ReplicaSet).
Automatic scaling (AutoScale) component: the method is used in cloud computing and is used for dynamically adjusting the number of the copies in the application template. In general, the number of the Pods is automatically adjusted according to the average resource usage (such as CPU usage, or memory usage) of the Pods under the application template, and the number of the Pods may be scaled at a specific time point according to the timing requirement of the user.
Zero sample learning: the method refers to a deep learning model which does not need to be pre-trained by using data in advance, and can automatically identify objects according to the provided feature description.
For ease of understanding, an application scenario related to the present application is described below with reference to fig. 1.
Fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the present application. Referring to fig. 1, a resource adjustment device and a plurality of applications may be deployed in a cluster. For example, the plurality of applications may be application 1, application 2, … …, and application n, n being an integer greater than or equal to 1.
For any one application, the resource adjusting device can adjust the resources for the application according to the load capacity of the application. For example, the load may be the number of service processing requests received in a unit time of an application, the CPU usage of the application, or the memory usage of the application, and the resource may be the number of the Pods.
Currently, the resource adjustment device may perform resource adjustment for each application according to a fixed resource adjustment period. The resource adjustment period cannot be flexibly adjusted according to the actual service requirements of the application in the service peak period or the service low peak period, so that the flexibility of resource adjustment is poor.
In view of this, the embodiments of the present application provide a resource adjustment method to solve the technical problem of poor flexibility of resource adjustment. In the resource adjustment method provided by the embodiment of the application, the resource adjustment device can adjust the resource adjustment period in time according to the historical load information of the application, so that the resource adjustment is performed for the application according to the adjusted resource adjustment period, and the flexibility of the resource adjustment is improved.
The following describes the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 2 is a flow chart of a resource adjustment method according to an embodiment of the present application. The execution subject of the method can be a resource adjusting system or a resource adjusting device arranged in the resource adjusting system. The resource adjusting device can be realized by software or a combination of software and hardware. Referring to fig. 2, the method may include:
S201, historical load information of the target application in a historical period is acquired.
The target application may be any one of a plurality of applications deployed in a cluster.
The history load information includes a plurality of history times, and a history load amount corresponding to each history time.
For any one history time, the history load corresponding to the history time may be the number of service processing requests received by the target application at the history time.
In this embodiment, obtaining the historical load information of the target application in the historical period may include at least two cases:
case 1, the resource adjusting device may acquire the history load information of the target application in the history period from the other device. The other devices may store historical load information of the target application over the historical period, or the other devices may collect historical load information of the target application over the historical period. The other devices may be any devices that can store or acquire the historical load information of the target application in the historical period, and the embodiment of the present application does not limit the structure of the other devices.
In this case, the resource adjusting device does not need to collect the historical load information itself, so that the cost of the resource adjusting device is small.
And 2, an information acquisition component can be arranged in the resource adjusting device and can be used for acquiring historical load information of the target application in a historical period. The source modulation device may obtain the historical load information of the target application from the local for the historical period.
Under the condition, the resource adjusting device can collect historical load information, so that the information collection efficiency is higher.
In this embodiment, the database of the resource adjustment device may store application template data of each application. The resource adjusting device can be independently allocated with a thread task, and the thread task is used for actively detecting whether an application template of the target application is running or not and determining a cluster deployed by the application template of the target application. After the thread task detects that the application template of the target application runs, the method provided by the embodiment of the application can be executed to adjust the resources of the target application.
S202, determining estimated load of the target application in the target period according to the historical load information.
The target period may be a period after the current time. The duration corresponding to the target period, the starting time of the target period, and the ending time of the target period may be set according to actual needs, which is not limited in the embodiment of the present application.
The estimated load may be a load of the target application within the target period determined according to the historical load information of the target application.
In this embodiment, the resource adjusting device may determine the historical load curve according to the historical load information. The historical load curve may include a correspondence between indicating historical time and load amount.
In this embodiment, the resource adjustment device may determine an estimated load curve according to the historical load curve, and may determine an estimated load amount in the target period according to the estimated load curve and the target period. The period corresponding to the estimated load curve includes a target period. For example, the resource adjustment device may determine the estimated load curve through a load curve model, which may be a pre-trained model for determining the estimated load curve from the historical load curve.
And S203, determining a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount.
The target resource adjustment period may be a period for adjusting the resource allocation amount of the target application within the target period. For example, the target resource adjustment period may be 10s, 15s, or the like.
The maximum resource allocation amount may be an upper limit of the amount of resources allocated for the target application within the target period. For example, the maximum resource allocation amount may be the maximum number of pois allocated for the target application within the target period.
In this embodiment, the target resource adjustment period and the maximum resource allocation amount may be adjusted according to the estimated load amount. If the estimated load indicates that the target period is a service peak period, the resource adjusting device can reduce the target resource adjusting period, increase the maximum resource allocation amount, timely increase the resource allocation amount, and flexibly cope with the burst traffic. If the estimated load indicates that the target period is a traffic low-peak period, the resource adjusting device can increase the target resource adjusting period, reduce the maximum resource allocation amount, and timely release unused resources of the target application, so that resource waste is avoided.
It should be noted that, the specific implementation manner of adjusting the target resource adjustment period and the maximum resource allocation amount according to the estimated load amount may refer to the embodiment of fig. 3, which is not described herein again.
S204, according to the target resource adjustment period, acquiring historical resource use information of the target application, and determining target resource allocation amount of the target application according to the historical resource use information and the maximum resource allocation amount.
In this embodiment, an information acquisition component may be set in the resource adjustment device, and the resource adjustment device may automatically acquire, through the information acquisition component, historical resource adaptation information of the target application, so that information acquisition efficiency is higher.
The historical resource use information is according to a target resource adjustment period, a plurality of historical load amounts in the collected resource adjustment period and a historical resource allocation amount corresponding to each historical load amount. For example, the historical resource allocation amount may be the number of allocated hits for the target application.
The target resource allocation amount may be the amount of resources allocated to the target application in the target period determined by the resource adjustment device.
In this embodiment, the resource adjusting device may update the first model according to the historical resource usage information to obtain an update result of the first model, where the first model is obtained by learning the historical resource allocation information of the target application; if the updating result is successful in updating and the state of the first model is normal, the historical resource use information is processed through the first model to obtain a first resource allocation amount; if the updating result is that the updating is failed or the state of the first model is abnormal, the historical resource information is processed through a second model to obtain a first resource allocation amount, and the second model is obtained by learning the historical resource allocation information of a plurality of applications; and determining the minimum value of the first resource allocation amount and the maximum resource allocation amount as a target resource allocation amount.
The historical resource allocation information may include a plurality of historical load amounts, and a historical resource allocation amount corresponding to each of the historical load amounts.
The first model may be a model that is trained in advance according to historical resource allocation information of the target application. The first model may be used to predict an amount of resource allocation for the target application.
The second model may be a model that is pre-trained based on historical resource allocation information for a plurality of applications. The second model may be used to predict the amount of resource allocation for a plurality of applications.
Specifically, the resource adjusting means may update the first model by the historical resource usage information of the target application. If the updating is successful and the state of the first model is normal, the resource adjusting device can process the historical resource use information through the first model to obtain a first resource allocation amount. If the updating fails or the state of the first model is abnormal, the resource adjusting device can process the historical resource information through the second model to obtain a first resource allocation amount. The resource adjustment device may further determine a minimum value of the first resource allocation amount and the maximum resource allocation amount as the target resource allocation amount.
In this embodiment, historical resource usage information may be periodically collected according to a target resource adjustment period, and the first model may be updated by using the historical resource usage information, so that the target resource allocation amount may be determined by using the first model. The second model can be automatically trained through historical resource use information, so that the freshness and effectiveness (freshness preservation effect) of the data are guaranteed.
In this embodiment, according to the target resource adjustment period, the first model is periodically updated and the second model is trained, so that the prediction accuracy of the first model and the second model can be improved, and the use duration of the first model and the second model can be prolonged.
In this embodiment, the second model may be used to determine the first resource allocation amounts of the plurality of applications, so that the second model has a strong versatility.
S205, performing resource allocation for the target application according to the target resource allocation amount.
In this embodiment, the resource adjusting device may determine the difference between the target resource allocation amount and the resource allocation amount allocated by the target application at the previous time of the target period. If the difference value is greater than zero, the resource adjusting device can increase the resource allocation amount of the target application in the target period, and the increased resource amount is equal to the difference value; if the difference value is smaller than zero, the resource adjusting device can reduce the resource allocation amount of the target application in the target period, and the reduced resource amount is equal to the difference value; if the difference is equal to zero, the resource adjusting device can control the resource allocation amount of the target application not to change.
Illustratively, assuming that the number of allocated points of the target application is 3 and the number of points corresponding to the target resource allocation amount is 5 at the previous time of the target period. The resource adjustment device can increase 2 pods on the basis of the previous moment to complete the resource adjustment of the target application.
According to the resource adjusting method provided by the embodiment, the resource adjusting device can acquire the historical load information of the target application in the historical period; the estimated load of the target application in the target period can be determined according to the historical load information; the target resource adjustment period and the maximum resource allocation amount of the target application can be determined according to the estimated load; the historical resource use information of the target application can be obtained according to the target resource adjustment period, and the target resource allocation amount of the target application is determined according to the historical resource use information and the maximum resource allocation amount; and the resource allocation can be performed for the target application according to the target resource allocation amount. By the method, the resource adjusting device can flexibly adjust the resource adjusting period according to the historical load information of the application, so that the resource adjustment is carried out for the application according to the adjusted resource adjusting period, and the flexibility of the resource adjustment is improved.
On the basis of the above embodiment, a method for adjusting the target resource adjustment period and the maximum resource allocation amount according to the estimated load amount will be described below with reference to fig. 3.
Fig. 3 is a flow chart of another resource adjustment method according to an embodiment of the present application. The execution subject of the method can be a resource adjusting system or a resource adjusting device arranged in the resource adjusting system. The resource adjusting device can be realized by software or a combination of software and hardware. Referring to fig. 3, the method may include:
S301, acquiring historical load information of a target application in a historical period.
It should be noted that, the specific implementation of S301 may refer to S201, which is not described herein.
S302, according to the historical load information, determining a historical load curve of the target application in a historical period.
The historical load curve may be used to indicate a historical load corresponding to a plurality of historical moments.
S303, acquiring service information of the target application in the target period.
The service information includes at least one of: order information, activity information, or index demand information;
the order information may be a predetermined number of business requests that the target application needs to process within the target period.
The activity information may be a predetermined amount of activity traffic that the target application needs to complete within the target period.
The index demand information may be the minimum number of service requests that the target application needs to complete within the target period.
In this embodiment, the resource adjustment device may store service information of the target application. That is, the resource adjusting device may acquire the traffic information within the target period from the local.
S304, determining estimated load according to the historical load curve and the service information.
In this embodiment, when determining the estimated load according to the historical load curve and the service information, the resource adjusting device may determine the initial load according to the historical load curve and the target period; according to the service information, determining a load factor, wherein the load factor is used for indicating the ratio of the load capacity corresponding to the service information to the preset load capacity; and determining the product of the initial load and the load coefficient as the estimated load.
The initial load may be an estimated load determined by the resource adjustment device through a historical load curve. The specific manner in which the resource adjusting device determines the estimated load through the historical load curve may refer to S202, which is not described herein.
The preset load capacity can be the load capacity set according to actual demands. The magnitude of the preset load is not limited in this embodiment.
For example, assuming an initial load of 2 and a load factor of 1.5, the estimated load may be 3.
It should be noted that, if the estimated load determined according to the initial load and the load coefficient is a decimal, it may be determined that the estimated load is an integer obtained by rounding up the decimal. For example, assuming that the estimated load amount determined according to the initial load amount and the load factor is 3.2, the estimated load amount may be determined to be 4.
S305, determining a target load interval in which the estimated load exists in the plurality of load areas.
In this embodiment, the load capacity of the target application may be divided into a plurality of load capacity regions according to the order from small to large.
The target load zone may be a load zone including a predicted load.
S306, acquiring a plurality of pieces of historical resource adjustment information.
In this embodiment, the resource adjustment device may acquire a plurality of historical resource adjustment information through the information acquisition component.
The historical resource adjustment period includes: history load amount, history adjustment period, history resource utilization rate, and history processing efficiency.
It should be understood that, for any one of the history resource adjustment information, the history load amount, the history adjustment period, the history resource utilization ratio, and the history processing efficiency included in the history resource adjustment information have a correspondence relationship. That is, the history adjustment period may be an adjustment period corresponding to a history load amount, the history resource utilization rate may be a resource utilization rate corresponding to the history load amount, and the history processing efficiency may be a processing efficiency corresponding to the history load amount.
S307, determining a plurality of pieces of resource adjustment information to be selected from a plurality of pieces of historical resource adjustment information according to the target load capacity interval.
The historical load capacity in the resource adjustment information to be selected is located in a target load capacity interval.
Specifically, the resource adjusting device may screen at least one historical resource adjustment information in which the historical load is located in the target load interval from the plurality of historical resource adjustment information; and the historical resource adjustment information obtained by screening can be determined as the resource adjustment information to be selected.
Illustratively, the target load interval is assumed to be 10 to 12. Then the historical resource adjustment information including the historical load amount between 10 and 12 can be determined, and the historical resource adjustment information obtained by screening can be determined as the candidate resource adjustment information.
S308, determining first resource adjustment information in a plurality of pieces of resource adjustment information to be selected according to the historical resource utilization rate and the historical processing efficiency in the resource adjustment information to be selected.
The historical processing efficiency in the first resource adjustment information is greater than or equal to a first threshold value, and the historical resource utilization rate in the first resource adjustment information is greater than or equal to a second threshold value;
it should be noted that, the magnitudes of the first threshold and the second threshold may be set according to actual needs, which is not limited in this embodiment.
Specifically, among the plurality of pieces of resource adjustment information to be selected, resource adjustment information including a history processing efficiency greater than or equal to a first threshold and including a history resource utilization rate greater than or equal to a second threshold may be determined as the first resource adjustment information.
S309, determining a target resource adjustment period and a maximum resource allocation amount according to the first resource adjustment information.
In this embodiment, if the number of the first resource adjustment information is 1, determining the resource adjustment period in the first resource adjustment information as the target resource adjustment period, and determining the resource allocation amount corresponding to the first adjustment information as the maximum resource allocation amount; if the number of the first resource adjustment information is greater than 1, determining target resource adjustment information in the plurality of first resource adjustment information according to the historical resource utilization rate and the historical processing efficiency in each first resource adjustment information, determining a resource adjustment period in the target resource adjustment information as a target resource adjustment period, and determining a resource allocation amount corresponding to the target adjustment information as a maximum resource allocation amount.
In this embodiment, if the number of the first resource adjustment information is greater than 1, for any one of the first resource adjustment information, the resource adjustment device may perform weighted summation processing on the historical resource utilization rate and the historical processing efficiency in the first resource adjustment information, to obtain a weight value corresponding to the first resource adjustment information; and determining the first resource adjustment information with the maximum weight value as target resource adjustment information.
Specifically, if the number of the first resource adjustment information is 1, the resource adjustment period in the first resource adjustment information may be determined as the target resource adjustment period, and the resource allocation amount corresponding to the first adjustment information may be determined as the maximum resource allocation amount. If the number of the first resource adjustment information is greater than 1, a weight value corresponding to each first resource adjustment information can be determined, a resource adjustment period in the first resource adjustment information with the largest weight value is determined as a target resource adjustment period, and a resource allocation amount corresponding to the first adjustment information with the largest weight value is determined as a maximum resource allocation amount.
S310, acquiring historical resource use information of the target application according to the target resource adjustment period, and determining target resource allocation amount of the target application according to the historical resource use information and the maximum resource allocation amount.
And S311, performing resource allocation for the target application according to the target resource allocation amount.
It should be noted that, the specific implementation manner of S310-S311 may refer to S204-S205, which are not described herein.
According to the resource adjusting method provided by the embodiment, the resource adjusting device can acquire the historical load information of the target application in the historical period; determining a historical load curve of the target application in a historical period according to the historical load information; the service information of the target application in the target period can be acquired; the estimated load capacity can be determined according to the historical load curve and the service information; the target load interval where the estimated load is located can be determined in a plurality of load areas; multiple pieces of historical resource adjustment information can be obtained, and multiple pieces of resource adjustment information to be selected are determined in the multiple pieces of historical resource adjustment information according to the target load capacity interval; the first resource adjustment information can be determined from a plurality of pieces of resource adjustment information to be selected according to the historical resource utilization rate and the historical processing efficiency in the resource adjustment information to be selected; and the target resource adjustment period and the maximum resource allocation amount can be determined according to the first resource adjustment information; the historical resource use information of the target application can be obtained according to the target resource adjustment period, and the target resource allocation amount of the target application is determined according to the historical resource use information and the maximum resource allocation amount; and the resource allocation can be performed for the target application according to the target resource allocation amount. By the method, the resource adjusting device can flexibly adjust the resource adjusting period according to the historical load information of the application, so that the resource adjustment is carried out for the application according to the adjusted resource adjusting period, and the flexibility of the resource adjustment is improved.
Fig. 4 is a schematic structural diagram of a resource adjusting device according to an embodiment of the present application. Referring to fig. 4, the resource adjusting apparatus 10 includes: an acquisition module 11, a determination module 12 and an allocation module 13, wherein,
the acquiring module 11 is configured to acquire historical load information of a target application in a historical period, where the historical load information includes a plurality of historical moments and a historical load amount corresponding to each historical moment;
the determining module 12 is configured to determine, according to the historical load information, an estimated load amount of the target application in a target period;
the determining module 12 is further configured to determine a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount;
the obtaining module 11 is further configured to obtain historical resource usage information of the target application according to the resource adjustment period;
the determining module 12 is further configured to determine a target resource allocation amount of the target application according to the historical resource usage information and the maximum resource allocation amount;
the allocation module 13 is configured to allocate resources for the target application according to the target resource allocation amount.
The resource adjusting device provided in this embodiment may be used to execute the method shown in any of the above method embodiments, and its implementation principle and technical effects are similar, and will not be described herein.
In one possible implementation, the determining module 12 is specifically configured to,
according to the historical load information, determining a historical load curve of the target application in the historical period;
acquiring service information of the target application in the target period, wherein the service information comprises at least one of the following: order information, activity information, or index demand information;
and determining the estimated load according to the historical load curve and the service information.
In one possible implementation, the determining module 12 is specifically configured to,
determining an initial load amount according to the historical load curve and the target period;
according to the service information, determining a load factor, wherein the load factor is used for indicating the ratio of the load capacity corresponding to the service information to the preset load capacity;
and determining the product of the initial load and the load coefficient as the estimated load.
In one possible implementation, the determining module 12 is specifically configured to,
In the multiple load areas, determining a target load interval in which the estimated load is located;
acquiring a plurality of historical resource adjustment information, wherein the historical resource adjustment period comprises: history load amount, history adjustment period, history resource utilization rate and history processing efficiency;
and determining the target resource adjustment period and the maximum resource allocation amount according to the target load interval and the plurality of historical resource adjustment information.
In one possible implementation, the determining module 12 is specifically configured to,
determining a plurality of pieces of resource adjustment information to be selected from the plurality of pieces of historical resource adjustment information according to the target load capacity interval, wherein the historical load capacity in the resource adjustment information to be selected is located in the target load capacity interval;
according to the historical resource utilization rate and the historical processing efficiency in the resource adjustment information to be selected, determining first resource adjustment information in the plurality of resource adjustment information to be selected, wherein the historical processing efficiency in the first resource adjustment information is greater than or equal to a first threshold value, and the historical resource utilization rate in the first resource adjustment information is greater than or equal to a second threshold value;
and determining the target resource adjustment period and the maximum resource allocation amount according to the first resource adjustment information.
In one possible implementation, the determining module 12 is specifically configured to,
if the number of the first resource adjustment information is 1, determining a resource adjustment period in the first resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the first adjustment information as the maximum resource allocation amount;
if the number of the first resource adjustment information is greater than 1, determining target resource adjustment information in a plurality of first resource adjustment information according to the historical resource utilization rate and the historical processing efficiency in each first resource adjustment information, determining a resource adjustment period in the target resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the target adjustment information as the maximum resource allocation amount.
In one possible implementation, the determining module 12 is specifically configured to,
for any one piece of first resource adjustment information, carrying out weighted summation processing on the historical resource utilization rate and the historical processing efficiency in the first resource adjustment information to obtain a weight value corresponding to the first resource adjustment information;
and determining the first resource adjustment information with the maximum weight value as the target resource adjustment information.
In one possible implementation, the determining module 12 is specifically configured to,
updating a first model according to the historical resource use information to obtain an updating result of the first model, wherein the first model is obtained by learning the historical resource allocation information of the target application;
if the updating result is successful and the state of the first model is normal, the historical resource use information is processed through the first model to obtain a first resource allocation amount;
if the updating result is that the updating is failed or the state of the first model is an abnormal state, the historical resource information is processed through a second model to obtain a first resource allocation amount, and the second model is obtained by learning the historical resource allocation information of a plurality of applications;
and determining the minimum value of the first resource allocation amount and the maximum resource allocation amount as the target resource allocation amount.
The resource adjusting device provided in this embodiment may be used to execute the method shown in any of the above method embodiments, and its implementation principle and technical effects are similar, and will not be described herein.
Fig. 5 is a schematic hardware structure of a resource adjusting device according to an embodiment of the present application. Referring to fig. 5, the resource adjusting apparatus 20 may include: a processor 21 and a memory 22, wherein the processor 21 and the memory 22 may communicate; illustratively, the processor 21 and the memory 22 are in communication via a communication bus 23, said memory 22 for storing computer-executable instructions, said processor 21 for invoking the computer-executable instructions in the memory for performing the method as shown in any of the method embodiments described above.
Optionally, the resource adjustment device 20 may also include a communication interface, which may include a transmitter and/or a receiver.
Alternatively, the processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present application may be embodied directly in a hardware processor or in a combination of hardware and software modules within a processor.
The present application provides a computer-readable storage medium having stored thereon computer-executable instructions; the computer-executable instructions are for implementing the method as described in any of the method embodiments above.
Embodiments of the present application provide a computer program product comprising a computer program which, when executed, causes a computer to perform the method shown in any of the method embodiments described above.
All or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a readable memory. The program, when executed, performs steps including the method embodiments described above; and the aforementioned memory (storage medium) includes: read-only memory (ROM), RAM, flash memory, hard disk, solid state disk, magnetic tape, floppy disk, optical disk, and any combination thereof.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, embedded processor, or other programmable terminal device to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable terminal device, 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 terminal device 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 terminal device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer implemented process such that the instructions which execute on the computer or other programmable device provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made to the embodiments of the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to encompass such modifications and variations.
In the present application, the term "include" and variations thereof may refer to non-limiting inclusion; the term "or" and variations thereof may refer to "and/or". The terms "first," "second," and the like in this application are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. In the present application, "plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the disclosed invention. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains.
Claims (11)
1. A method of resource adjustment, comprising:
acquiring historical load information of a target application in a historical period, wherein the historical load information comprises a plurality of historical moments and historical load amounts corresponding to each historical moment;
Determining estimated load of the target application in a target period according to the historical load information;
determining a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount;
acquiring historical resource use information of the target application according to the target resource adjustment period, and determining target resource allocation amount of the target application according to the historical resource use information and the maximum resource allocation amount;
and carrying out resource allocation for the target application according to the target resource allocation amount.
2. The method of claim 1, wherein determining an estimated load of the target application within a target period based on the historical load information comprises:
according to the historical load information, determining a historical load curve of the target application in the historical period;
acquiring service information of the target application in the target period, wherein the service information comprises at least one of the following: order information, activity information, or index demand information;
and determining the estimated load according to the historical load curve and the service information.
3. The method of claim 2, wherein determining the estimated load based on the historical load curve and the traffic information comprises:
determining an initial load amount according to the historical load curve and the target period;
according to the service information, determining a load factor, wherein the load factor is used for indicating the ratio of the load capacity corresponding to the service information to the preset load capacity;
and determining the product of the initial load and the load coefficient as the estimated load.
4. A method according to any of claims 1-3, wherein determining a target resource adjustment period for the target application and a maximum resource allocation amount based on the estimated load amount comprises:
in the multiple load areas, determining a target load interval in which the estimated load is located;
acquiring a plurality of historical resource adjustment information, wherein the historical resource adjustment period comprises: history load amount, history adjustment period, history resource utilization rate and history processing efficiency;
and determining the target resource adjustment period and the maximum resource allocation amount according to the target load interval and the plurality of historical resource adjustment information.
5. The method of claim 4, wherein determining the target resource adjustment period and the maximum resource allocation amount based on the target load interval and the plurality of historical resource adjustment information comprises:
determining a plurality of pieces of resource adjustment information to be selected from the plurality of pieces of historical resource adjustment information according to the target load capacity interval, wherein the historical load capacity in the resource adjustment information to be selected is located in the target load capacity interval;
according to the historical resource utilization rate and the historical processing efficiency in the resource adjustment information to be selected, determining first resource adjustment information in the plurality of resource adjustment information to be selected, wherein the historical processing efficiency in the first resource adjustment information is greater than or equal to a first threshold value, and the historical resource utilization rate in the first resource adjustment information is greater than or equal to a second threshold value;
and determining the target resource adjustment period and the maximum resource allocation amount according to the first resource adjustment information.
6. The method of claim 5, wherein determining the target resource adjustment period and the maximum resource allocation amount based on the first resource adjustment information comprises:
if the number of the first resource adjustment information is 1, determining a resource adjustment period in the first resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the first adjustment information as the maximum resource allocation amount;
If the number of the first resource adjustment information is greater than 1, determining target resource adjustment information in a plurality of first resource adjustment information according to the historical resource utilization rate and the historical processing efficiency in each first resource adjustment information, determining a resource adjustment period in the target resource adjustment information as the target resource adjustment period, and determining a resource allocation amount corresponding to the target adjustment information as the maximum resource allocation amount.
7. The method of claim 6, wherein determining target resource adjustment information from among the plurality of first resource adjustment information based on the historical resource utilization and the historical processing efficiency in each of the first resource adjustment information, comprises:
for any one piece of first resource adjustment information, carrying out weighted summation processing on the historical resource utilization rate and the historical processing efficiency in the first resource adjustment information to obtain a weight value corresponding to the first resource adjustment information;
and determining the first resource adjustment information with the maximum weight value as the target resource adjustment information.
8. The method of any of claims 1-7, wherein determining a target resource allocation amount for the target application based on the historical resource usage information and the maximum resource allocation amount comprises:
Updating a first model according to the historical resource use information to obtain an updating result of the first model, wherein the first model is obtained by learning the historical resource allocation information of the target application;
if the updating result is successful and the state of the first model is normal, the historical resource use information is processed through the first model to obtain a first resource allocation amount;
if the updating result is that the updating is failed or the state of the first model is an abnormal state, the historical resource information is processed through a second model to obtain a first resource allocation amount, and the second model is obtained by learning the historical resource allocation information of a plurality of applications;
and determining the minimum value of the first resource allocation amount and the maximum resource allocation amount as the target resource allocation amount.
9. A resource adjustment device, the device comprising: the device comprises an acquisition module, a determination module and an allocation module, wherein,
the acquisition module is used for acquiring historical load information of the target application in a historical period, wherein the historical load information comprises a plurality of historical moments and historical load amounts corresponding to each historical moment;
The determining module is used for determining estimated load of the target application in a target period according to the historical load information;
the determining module is further configured to determine a target resource adjustment period and a maximum resource allocation amount of the target application according to the estimated load amount;
the acquisition module is further used for acquiring historical resource use information of the target application according to the resource adjustment period;
the determining module is further configured to determine a target resource allocation amount of the target application according to the historical resource usage information and the maximum resource allocation amount;
the allocation module is used for allocating resources for the target application according to the target resource allocation amount.
10. A resource adjustment device, comprising: a processor, and a memory communicatively coupled to the processor;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1 to 8.
11. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1 to 8.
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CN117726925B (en) * | 2024-02-07 | 2024-06-04 | 广州思涵信息科技有限公司 | Face recognition resource scheduling method, device and equipment |
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