CN117435335A - Computing power dispatching method, computing power dispatching device, computer equipment and storage medium - Google Patents
Computing power dispatching method, computing power dispatching device, computer equipment and storage medium Download PDFInfo
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- 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
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- G06F9/46—Multiprogramming arrangements
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Abstract
The application relates to a power dispatching method, a power dispatching device, computer equipment, a storage medium and a computer program product, and relates to the technical field of big data. The method comprises the following steps: under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and a preset calculated force value; if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application; and determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and a power capacity increasing mode. By adopting the method, the calculation force used by the application in real time can be monitored, whether the provided calculation force value is excessive or insufficient or not is monitored in real time, the utilization rate of the calculation force resource of the data center is improved, and the matching degree between the calculation force value required by the application and the distributed calculation force value is improved.
Description
Technical Field
The present application relates to the field of big data technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for power scheduling.
Background
With the rapid development of information technology, mass server equipment of a data center machine room has become an important foundation in the technical fields of big data, cloud computing and the like, the number of server resources is rapidly increased, and uneven distribution of computing power, waste of computing power resources and the like are caused by unordered delivery of resources.
In the related art, in a data center resource allocation mode, corresponding computing power is configured according to the performance capacity of a server required by service application; however, after the calculation force is distributed, whether the distributed calculation force meets the service requirement cannot be monitored in time, which results in poor matching between the distributed calculation force value and the service.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a computing power scheduling method, apparatus, computer device, computer readable storage medium, and computer program product capable of improving the matching between computing power values and services.
In a first aspect, the present application provides a method of power dispatch. The method comprises the following steps:
under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and a preset calculated force value;
If the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application;
and determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and the power capacity increasing mode.
In one embodiment, the generating process of the abnormal prompt information of the calculated power value includes:
if the real-time calculated force value of the target application is larger than or equal to a preset calculated force threshold value, outputting abnormal prompt information of the calculated force value through a calculated force monitoring module, wherein the real-time calculated force value is determined by detecting the target application in real time.
In one embodiment, the method further comprises:
obtaining the number of servers, the number of virtual machines and the number of containers corresponding to the target application;
and calculating the required calculation force value of the target application based on the server calculation force value, the number of servers, the virtual machine calculation force value, the number of virtual machines, the container calculation force value and the container number corresponding to the target application.
In one embodiment, the calculating the required computing power value of the target application based on the server computing power value, the number of servers, the virtual machine computing power value, the number of virtual machines, the container computing power value and the number of containers corresponding to the target application includes:
And calculating a required calculation force value of the target application based on the number of servers, the server performance peak multiplying power, the number of virtual machines, the virtual machine performance peak multiplying power, the number of containers and the container performance peak multiplying power corresponding to the target application.
In one embodiment, the preconfigured power calculation value is a power calculation value of a preset power calculation resource pool; the method further comprises the steps of:
if the calculated force value required by the target application is greater than or equal to the calculated force value of the calculated force resource pool, determining a capacity expansion mode corresponding to the preset calculated force resource pool;
and performing capacity expansion processing on the preset computing power resource pool based on a capacity expansion mode corresponding to the preset computing power resource pool.
In one embodiment, the performing the capacity expansion processing on the preset computing power resource pool based on the capacity expansion mode corresponding to the preset computing power resource pool includes:
performing capacity expansion treatment on the preset computing power resource pool based on a computing power capacity expansion mode; or,
and performing capacity expansion processing on the preset computing force resource pool based on a computing force new adding mode.
In one embodiment, the method further comprises:
inquiring the calculation force increasing rate in each preset time period in the calculation force increasing trend module;
And determining the current calculation force increasing rate based on the average value of the calculation force increasing rates in the preset time periods.
In a second aspect, the present application also provides a computing power scheduling apparatus. The device comprises:
the first calculation module is used for calculating a calculation force value difference value between a calculation force value required by the target application and a preset calculation force value under the condition that calculation force value abnormality prompt information corresponding to the target application is detected;
the first determining module is used for determining a target computing force module corresponding to the target application if the computing force value required by the target application is smaller than the computing force value of the computing force resource pool based on the computing force value difference value;
and the scheduling module is used for determining a target power scheduling strategy based on the type of the target power module and performing power scheduling based on the target power scheduling strategy and the power capacity increasing mode.
In one embodiment, the apparatus further comprises:
and the output module is used for outputting abnormal prompt information of the calculated force value through the calculated force monitoring module if the real-time calculated force value of the target application is larger than or equal to a preset calculated force threshold value, wherein the real-time calculated force value is determined by detecting the target application in real time.
In one embodiment, the apparatus further comprises:
the first acquisition module is used for acquiring the number of servers, the number of virtual machines and the number of containers corresponding to the target application;
and the second calculation module is used for calculating the required calculation force value of the target application based on the server calculation force value, the number of servers, the virtual machine calculation force value, the number of virtual machines, the container calculation force value and the number of containers corresponding to the target application.
In one embodiment, the second computing module is specifically configured to:
and based on the number of servers, the peak power of server performance, the number of virtual machines, the peak power of virtual machine performance, the number of containers and the peak power of container performance corresponding to the target application.
In one embodiment, the preconfigured power calculation value is a power calculation value of a preset power calculation resource pool; the apparatus further comprises:
the second determining module is used for determining a capacity expansion mode corresponding to the preset computing force resource pool if the computing force value required by the target application is greater than or equal to the computing force value of the computing force resource pool;
and the capacity expansion module is used for carrying out capacity expansion processing on the preset computing power resource pool based on a capacity expansion mode corresponding to the preset computing power resource pool.
In one embodiment, the capacity expansion module is specifically configured to:
performing capacity expansion treatment on the preset computing power resource pool based on a computing power capacity expansion mode; or performing capacity expansion processing on the preset computing power resource pool based on a computing power new adding mode.
In one embodiment, the apparatus further comprises:
the query module is used for querying the calculation force increasing rate in each preset time period in the calculation force increasing trend module;
and the third determining module is used for determining the current calculation force increasing rate based on the average value of the calculation force increasing rates in the preset time periods.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and a preset calculated force value;
if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application;
And determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and the power capacity increasing mode.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and a preset calculated force value;
if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application;
and determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and the power capacity increasing mode.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:
Under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and a preset calculated force value;
if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application;
and determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and the power capacity increasing mode.
The above-described computing power scheduling method, apparatus, computer device, storage medium, and computer program product, the method comprising: under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and a preset calculated force value; if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application; and determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and the power capacity increasing mode. By adopting the method, after the calculation force required by the application is analyzed and scheduled based on the multidimensional degree of the physical server, the virtual machine, the container and the like, the calculation force used by the application in real time can be monitored, whether the provided calculation force value is excessive or insufficient can be monitored in real time, the utilization rate of the calculation force resource of the data center is improved, and the matching degree between the calculation force value required by the application and the distributed calculation force value is improved.
Drawings
FIG. 1 is a flow chart of a method of computing power scheduling in one embodiment;
FIG. 2 is a flow chart of the steps of calculating the required calculation force in one embodiment;
FIG. 3 is a flow chart illustrating the steps of performing a capacity expansion process in one embodiment;
FIG. 4 is a flow chart illustrating the steps of performing a capacity expansion process in one embodiment;
FIG. 5 is a flow chart of the calculation of the rate of increase of the calculated force in one embodiment;
FIG. 6 is a schematic diagram of the architecture of a computational force reference subsystem in one embodiment;
FIG. 7 is a schematic diagram of an application performance baseline subsystem in one embodiment;
FIG. 8 is a schematic diagram of the architecture of a computational force analysis subsystem in one embodiment;
FIG. 9 is a schematic diagram of a power dispatch subsystem in one embodiment;
FIG. 10 is a flow chart of a method of computing power scheduling in another embodiment;
FIG. 11 is a block diagram of a power calculation scheduling apparatus in one embodiment;
fig. 12 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a power scheduling method is provided, where the method is applied to a terminal to illustrate the method, it can be understood that the method may also be applied to a server, and may also be applied to a system including a terminal and a server, and implemented through interaction between the terminal and the server, where the terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and the like, and the server may be implemented by using a separate server or a server cluster formed by a plurality of servers. In this embodiment, the power calculation scheduling method includes the following steps:
step 110, calculating a difference value between the calculated force value required by the target application and the preset calculated force value under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected.
The target application can be any application program on the service system, or can be an application program requiring computing power resources in the service system, and the like; the abnormal prompt information of the calculated power value can be alarm information, and is used for representing that the target application has the shortage of the calculated power value under the current condition; the calculation force value required by the target application can be a specific value corresponding to the calculation force resource required by the target application at present; the preset computing power value can be a computing power value corresponding to a computing power resource preset in a preset computing power resource pool, or can be a computing power value corresponding to a computing power resource preset in the preset resource pool for the target application; in one example, the computing power resources may include at least one or more of physical server resources, virtual machine resources, and container resources.
Specifically, the terminal can detect whether the application computing power monitoring module outputs the computing power value abnormal prompt information, and under the condition that the application computing power monitoring module outputs the computing power value abnormal prompt information corresponding to the target application, the terminal can determine that the target application has the computing power problem under the current condition. In this way, the terminal can calculate a calculated force value difference between the required calculated force value of the target application and the pre-configured calculated force value based on the required calculated force value of the target application and the pre-configured calculated force value.
And step 111, if the calculated force value required by the target application is determined to be smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application.
The computing power value of the computing power resource pool can be an available computing power value in the computing power resource pool under the current condition, for example, can be an idle computing power value or a residual computing power value, and the computing power value of the computing power resource pool can also be a computing power value configured for the computing power resource pool in advance, or can also be a computing power of available server resources including a data center, an available virtual machine resource, an available container resource and the like.
Specifically, the terminal may determine an association relationship between the calculated force value required by the target application and the calculated force value of the calculated force resource pool based on the calculated force value difference value. For example, the terminal may determine, based on the calculated difference in the calculated calculation power values, if it is determined that the calculation power value required by the target application is smaller than the calculation power value of the calculation power resource pool, the terminal may determine a calculation power resource pre-configured in the current calculation power resource pool, or that is, an available calculation power resource in the current calculation power resource pool, so as to satisfy the current calculation power requirement of the target application. Based on the above, the terminal can determine a target computing power module corresponding to the target application based on the type of the target application; the target computing module may include one or more of a physical server computing module, a virtual machine computing module, and a container computing module.
And step 112, determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and a power capacity increasing mode.
The target power computing scheduling policy may be a scheduling policy for scheduling a power computing module to meet a power computing requirement of a target application; the power-added capacity-adding mode can comprise a power-added capacity-adding mode and/or a power-added new mode.
Specifically, the terminal may determine a target power scheduling policy corresponding to the target application based on the determined type of the target power module, so that the terminal may schedule the target power module based on the determined target power scheduling policy and the power capacity increasing manner to meet the power demand of the target application.
In the power calculation scheduling method, the power calculation value difference value between the power calculation value required by the target application and the preset power calculation value can be calculated under the condition that the power calculation value abnormality prompt information corresponding to the target application is detected; if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application; and determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and a power capacity increasing mode. By adopting the method, after the calculation force required by the application is analyzed and scheduled based on the multidimensional degree of the physical server, the virtual machine, the container and the like, the calculation force used by the application in real time can be monitored, whether the provided calculation force value is excessive or insufficient can be monitored in real time, the utilization rate of the calculation force resource of the data center is improved, and the matching degree between the calculation force value required by the application and the distributed calculation force value is improved.
In one embodiment, the generating process of the abnormal prompt information of the calculated power value includes:
if the real-time calculated force value of the target application is larger than or equal to the preset calculated force threshold value, outputting abnormal prompt information of the calculated force value through the calculated force monitoring module.
The real-time calculation force value is determined by detecting the target application in real time, the real-time calculation force value of the target application can be the calculation force value which is currently used in real time by the target application, the preset calculation force threshold value can be a preset calculation force monitoring threshold value, and the preset calculation force threshold value can be preset by operation and maintenance personnel; the computing power monitoring module may be an application computing power monitoring sub-module.
Specifically, the terminal may monitor the currently used computing power values of each target application through the application computing power monitoring sub-module, and if the application computing power monitoring sub-module determines that the currently used real-time computing power value of the target application is greater than or equal to the preset computing power threshold, the application computing power monitoring sub-module may generate computing power value abnormality prompting information corresponding to the target application, and output computing power value abnormality prompting information corresponding to the target application.
In this embodiment, by detecting the applied real-time calculation force value in real time, timeliness of calculation force monitoring can be ensured, and abnormal prompt information can be timely output.
In one embodiment, as shown in fig. 2, the power scheduling method further includes:
step 202, obtaining the number of servers, the number of virtual machines and the number of containers corresponding to the target application.
The number of servers corresponding to the target application may be the number of servers used by the target application, for example, the number of servers used by the physical server; the number of virtual machines may be the number of virtual machines used by the target application and the number of containers may be the number of containers used by the target application.
Specifically, after determining the target application, the terminal may determine the number of servers, the number of virtual machines, and the number of containers corresponding to the target application based on the identification information of the same target in the preset database.
Step 204, calculating the required computing power value of the target application based on the server computing power value, the number of servers, the virtual machine computing power value, the number of virtual machines, the container computing power value and the number of containers corresponding to the target application.
The server computing force value can be a computing force value which can be provided by a physical server, and the virtual machine computing force value can be a computing force value which corresponds to a computing force resource which can be provided by a virtual machine; the container computing force value may be a computing force value corresponding to a computing force resource that a container can provide.
Specifically, the terminal may determine, based on the number of configured servers and the server computing power value, a computing power value corresponding to a computing power resource of the server type; the terminal can also configure the number of virtual machines and the calculation force value of the virtual machines, and determine the calculation force value corresponding to the calculation force resource of the virtual machine type; the terminal may also determine a computing power value corresponding to the computing power resource of the container type based on the configured number of containers and the container computing power value. Based on the above, the terminal may obtain the computing power value required by the target application based on the sum of the computing power value corresponding to the computing power resource of the server type, the computing power value corresponding to the computing power resource of the virtual machine type, and the computing power value corresponding to the computing power resource of the container type.
In this embodiment, by calculating different types of computing power resources corresponding to the target application, an accurate computing power value corresponding to the target application may be obtained.
In one embodiment, the specific implementation of the step of calculating the required computing power value of the target application based on the server computing power value, the number of servers, the virtual machine computing power value, the number of virtual machines, the container computing power value and the number of containers corresponding to the target application includes:
and calculating a required calculation force value of the target application based on the number of servers, the peak power of the server performance, the number of virtual machines, the peak power of the virtual machine performance, the number of containers and the peak power of the container performance corresponding to the target application.
The peak power of the server performance can be index values such as peak utilization rate of a CPU (Central processing Unit), peak utilization rate of a memory, peak utilization rate of a disk and the like of the server; the performance peak multiplying power of the virtual machine can be index values such as CPU peak core number, memory peak use rate, file system peak use rate and the like, and the container performance peak multiplying power can be index values such as CPU peak use amount, memory peak use amount and the like.
Specifically, the terminal may calculate, based on the calculated force values corresponding to each physical server and the performance peak multiplying power corresponding to each physical server, a calculated force value corresponding to a calculated force resource of a server type; the terminal can also calculate and obtain the calculated force value corresponding to the calculated force resource of the server type based on the calculated force value corresponding to each virtual machine and the performance peak multiplying power corresponding to each virtual machine respectively; the terminal can also calculate and obtain the calculated force value corresponding to the calculated force resource of the server type based on the calculated force value corresponding to each container and the performance peak multiplying power corresponding to each container. Based on the above, the terminal may obtain the computing power value required by the target application based on the sum of the computing power value corresponding to the computing power resource of the server type, the computing power value corresponding to the computing power resource of the virtual machine type, and the computing power value corresponding to the computing power resource of the container type.
In this embodiment, by calculating different types of computing power resources corresponding to the target application based on the performance peak power of the computing power resources of different computing power types, an accurate computing power value corresponding to the target application can be obtained.
In one embodiment, the preconfigured power calculation value is a power calculation value of a preset power resource pool. Specifically, the computing power value of the preset computing power resource pool may be a computing power resource corresponding to each computing power type configured for the computing power resource value in advance.
Accordingly, as shown in fig. 3, the computing power scheduling method further includes:
step 302, if the calculated force value required by the target application is greater than or equal to the calculated force value of the calculated force resource pool, determining a capacity expansion mode corresponding to the preset calculated force resource pool.
Specifically, the terminal may determine a comparison result between the calculated force value required by the target application and the calculated force value of the calculated force resource pool based on the calculated force value difference, for example, if the terminal determines that the calculated force value required by the target application is greater than or equal to the calculated force value of the calculated force resource pool based on the comparison result, the terminal may determine that the current calculated force resource pool needs to be subjected to capacity expansion processing, so that the terminal may determine a capacity expansion manner corresponding to the calculated force resource pool.
And step 304, performing capacity expansion processing on the preset computing power resource pool based on a capacity expansion mode corresponding to the preset computing power resource pool.
The capacity expansion mode corresponding to the preset computing power resource pool can comprise a computing power capacity expansion mode and a computing power new addition mode.
Specifically, after determining the capacity expansion mode corresponding to the preset computing power resource pool, the terminal performs capacity expansion processing on the preset computing power resource pool based on the capacity expansion mode corresponding to the preset computing power resource pool, and obtains the preset computing power resource pool after the capacity expansion processing.
In the embodiment, the reliability of the computing power resource pool can be improved by timely expanding the computing power resource pool, and the timely supply of the computing power resource is ensured.
In one embodiment, as shown in fig. 4, a specific implementation manner of the step of performing expansion processing on the preset computing power resource pool based on the expansion manner corresponding to the preset computing power resource pool includes:
step 402, performing capacity expansion processing on the preset computing power resource pool based on the computing power capacity expansion mode.
And 404, performing capacity expansion processing on the preset computing power resource pool based on the computing power new addition mode.
Specifically, the terminal may determine a capacity expansion mode corresponding to the preset computing power resource pool, and perform capacity expansion processing on the preset computing power resource pool based on the capacity expansion mode to obtain a preset computing power resource pool after the capacity expansion processing. Specifically, the process of performing capacity expansion processing on the preset computing resource pool by the terminal based on the computing capacity expansion mode may be that the terminal performs capacity expansion processing on computing resources that can be provided by each computing module of the preset computing resource pool, for example, adjusting a first computing capacity value that can be provided by the physical server to a second computing capacity value, where the first computing capacity value is smaller than the second computing capacity value. The process of performing capacity expansion processing on the preset computing resource pool by the terminal based on the computing power new adding mode may be that the terminal adds computing power resources corresponding to each computing power type which is newly added to the preset computing power resource pool, for example, a physical server, a virtual machine and a container which can be newly added to the preset computing power resource pool in a target number, and the preset computing power resource pool processed by the computing power new adding mode is obtained.
In an example, the capacity expansion manner of the terminal for performing capacity expansion processing on the preset computing power resource pool may further include increasing the number of physical servers, increasing the configuration of the physical servers, increasing the virtualization multiplying power of the virtual machine, and so on.
In one example, the capacity expansion process of the original computing power resource of the business application in the business application may be: smooth migration can be performed in the original computing power resource and the expanded computing power module through a computing power smooth migration module, and migration modes include but are not limited to physical migration, virtualization migration, mirror image migration and the like. If the capacity expansion mode corresponding to the service application is a new calculation force demand, the terminal can select an adaptive calculation force module in a calculation force resource pool according to a scene calculation force matching result to perform calculation force scheduling, namely, a target calculation force module is determined in the calculation force resource pool, and calculation force resources corresponding to the target calculation force module are deployed to the target application based on the target calculation force module.
Alternatively, the present embodiment does not limit the execution sequence of step 402 and step 404, and the terminal may execute only step 402 or execute only step 404.
In this embodiment, timeliness of capacity expansion of the preset computing power resource pool is ensured by enriching capacity expansion modes of the preset computing power resource pool.
In one embodiment, as shown in fig. 5, the power scheduling method further includes:
step 502, query the computational power growth rate in each preset time period in the computational power growth trend module.
The calculation force increasing trend module can store the calculation force increasing rate in a preset time period.
Specifically, the terminal may adjust the power growth trend module to obtain power growth rates corresponding to each preset time period.
Step 504, determining a current computational power growth rate based on the average of the computational power growth rates in each preset time period.
Specifically, the terminal may perform average processing on the calculated force increase rates corresponding to the preset time periods respectively, and use the obtained average as the calculated force increase rate corresponding to the target application currently.
In one example, the rate of increase in the power of the current version period may be measured with reference to the historical contemporaneous rate of increase in the power trend module.
In this embodiment, the accurate calculation force increase rate can be obtained by the calculation force increase rate in each preset time period.
The following describes in detail, in connection with a specific embodiment, a specific implementation procedure of the foregoing computing power scheduling method:
the computing power scheduling method provided by the embodiment can be based on the digitization technology of the business data center computing power scheduling, and is used for the intensive management of computing power resource allocation and supply of a data center server, so that unordered growth and resource waste caused by rapid growth of large-scale data center resources are avoided, and the operation cost can be saved.
The computing power scheduling method provided by the embodiment can overcome the limitation of service application performance capacity assessment, and the methods of service application performance baseline, computing power analysis, computing power monitoring scheduling and the like are adopted through server performance benchmark test, so that the purposes of computing power analysis and computing power scheduling of a data center server according to service application requirements from multiple dimensions such as a physical server, a virtual machine, a container and the like are achieved, and the sufficient computing power resources of the service application are ensured.
The power calculation scheduling method provided by the embodiment can provide services such as power calculation resource calculation, power analysis, power calculation scheduling and the like for a server required by a service application scene for a user. The platform supports multi-user concurrent access through server deployment, local installation is not needed, and flexibility is high. The data center computing force dispatching platform provided by the embodiment mainly comprises a computing force reference subsystem 101, an application performance baseline subsystem 102, a computing force analysis subsystem 103 and a computing force dispatching subsystem 104.
The terminal can construct a calculation force reference subsystem through a data center calculation force scheduling platform, obtain calculation force values of a server component calculation force, a server whole calculation force, a standard service scene calculation force and the like, and construct a calculation force reference comprehensive index system. And dividing the application environment requirements into three types of physical servers, virtual machines and containers by using an application performance baseline subsystem, and monitoring the utilization rate of system resources according to different dimensions. And carrying out statistical analysis by combining the data of the calculation force reference subsystem and the data of the application performance baseline subsystem to obtain the data required by the calculation force analysis subsystem, carrying out actual use calculation force calculation according to service application in the calculation force analysis subsystem, and starting the calculation force scheduling subsystem according to calculation result to realize calculation force resource scheduling among three different environments according to service application scenes.
As shown in fig. 6, the structural schematic diagram of the power calculation reference subsystem 101 may be a structural schematic diagram including a power calculation of a server component, a power calculation of the server, a power calculation of a standard service scenario, and corresponding power calculation values thereof, where the power calculation of the server component is divided into a CPU, a memory, a hard disk, a network card, and a power calculation effect. The calculation method of the calculation force value comprises, but is not limited to, using performance testing tools such as SPEC2017, stream, FIO and the like to test the calculation force value and the calculation efficiency of the obtained CPU, memory, hard disk and network card. The server total computing force comprises a typical configuration model computing force and an incremental configuration model computing force, wherein the server typical configuration model computing force is a server total computing force value of fixed configuration, and the fixed configuration can make a standard and be classified according to models. The incremental model is empirically configured after combining with service application scenes, and can be divided into a general calculation type, a high-performance calculation type, a storage type and the like, and the whole computer calculation force value is obtained by using a test tool according to different types. The standard service scene calculation force value comprises specific scenes such as traditional service application, big data, distributed storage, cloud computing and the like, wherein each type of scene is a set of calculation forces of a plurality of server complete machines, virtual machines and containers.
As shown in fig. 7, the configuration diagram of the application performance baseline subsystem 102 may be shown, where the application performance baseline subsystem 102 may include a physical server, a virtual machine, and container data used by each service application, and the terminal may obtain the data stored in the application performance baseline subsystem 102 by installing a customized script in an operating system, and obtaining the data from an IPMI server out-of-band management system. The obtained data are respectively the CPU peak value utilization rate, the memory peak value utilization rate and the disk peak value utilization rate corresponding to the physical server corresponding to the single application, the CPU peak value utilization rate, the memory peak value utilization rate and the disk peak value utilization rate corresponding to the virtual machine, and the CPU peak value utilization rate, the memory peak value utilization rate and the disk peak value utilization rate corresponding to the container. The time range of the peak data acquisition is the time from the last version of business application to the current system.
As shown in fig. 8, a schematic structural diagram of the computing power analysis subsystem 103 may be provided, where the computing power analysis subsystem 103 may include four sub-modules including an application computing power monitor, a computing power structure distribution, a computing power degradation analysis and a computing power growth trend, and the computing power structure distribution module mainly includes computing power values of various environments classified by service applications after being calculated by two sub-system data of the computing power reference subsystem 101 and the application performance baseline subsystem 102.
In one example, the target application may be application a, whose configuration calculation force value may be calculated by the following formula:
wherein n is the number of physical servers corresponding to the application, m is the number of virtual machines corresponding to the application, and p is the number of containers corresponding to the application.
The usage calculation force value of the target application a can be calculated by the following formula:
wherein n is the number of physical servers corresponding to the application, m is the number of virtual machines corresponding to the application, and p is the number of containers corresponding to the application. Optionally, the server performance peak multiplying power may be indexes such as server CPU peak usage, memory peak usage, and disk peak usage, the virtual machine performance peak multiplying power may be indexes such as CPU peak core number, memory peak usage, and file system peak usage, and the container performance peak multiplying power may be indexes such as CPU peak usage and memory peak usage.
The application calculation power monitoring sub-module can set an overall calculation power monitoring threshold value according to a service application manager, can set a monitoring threshold value according to an environment type, and outputs alarm information and simultaneously starts the calculation power scheduling sub-system 104 after the service application calculation power reaches or exceeds the calculation power monitoring threshold value set by the manager. The calculation force degradation analysis sub-module and the calculation force increase trend sub-module use calculation force according to the service application statistics history, and output a report according to the statistics result. The computing force degradation sub-module is an application and environment in which the computing force value in the application is low or grows negatively for a long time, and the computing force growth trend sub-module is an application and environment in which the computing force value in the application is high or grows positively for a long time. The two types of data are incorporated into an applied computing power monitoring system, and for the degradation computing power, integration and cleaning are required to be carried out regularly; for increasing the computing power, the computing power resource pool needs to be expanded in advance according to the increasing speed of the computing power.
As shown in fig. 9, a schematic structural diagram of the computing power scheduling subsystem 104 may be provided, where the computing power scheduling subsystem 104 may include a computing power resource pool module, a scene computing power matching module, a computing power smooth migration module, and a computing power capacity increasing module. The computing force resource pool module comprises available pooled resources classified according to environment, and taking a physical server as an example, the computing force resource pool available computing force comprises the computing force of available server resources of a data center. The computing power resource pool can be segmented according to computing power values stored in the computing power reference subsystem 101 by the physical servers, the virtual machines and the containers, and the segmented computing power module can comprise a plurality of physical servers, the virtual machines and the containers. When the service application computing power monitoring finds that a certain application computing power resource alarms or the service application needs to capacity-increase the computing power, the application computing power difference value stored by the current application required computing power and the application performance baseline subsystem is measured in the scene computing power matching module. The calculation process can refer to report data of a calculation force increasing trend module in the calculation force analysis subsystem. Taking the application A as an example, the calculation power increase rate of the current version period can be calculated by referring to the historical synchronous increase rate in the calculation power increase trend module. When the calculated force difference value is larger than the calculated force of the calculated force resource pool, the calculated force resource pool is required to be expanded, and the expansion mode comprises, but is not limited to, increasing the number of physical servers, increasing the configuration of the physical servers, improving the virtual machine virtualization multiplying power and the like. When the calculated force difference value is smaller than the calculated force of the calculated force resource pool, the calculated force difference value can be distributed according to the calculated force value of the calculated force module. Particularly, if the business application needs to expand capacity on the original computing power resource, the computing power is smoothly migrated in the original computing power resource and the expanded computing power module by using the computing power smooth migration module function, and the migration modes include but are not limited to physical migration, virtualization migration, mirror migration and the like. And if the service application is the newly increased computing power demand, selecting an adaptive computing power module from a computing power resource pool according to the scene computing power matching result.
As shown in fig. 10, a schematic diagram of a business-based data center mental arithmetic force scheduling flow may be shown, and a specific implementation process may be: after detecting the service application computing power monitoring alarm, the terminal can perform scene computing power matching processing and judge whether the computing power resource pool resources are sufficient. Under the condition that the resources of the computing power resource pool are sufficient, the computing power module can be selected in the computing power resource pool, the computing power capacity increasing mode can be judged, the computing power capacity increasing processing can be carried out, or the computing power is newly increased, and the computing power scheduling is carried out based on the determined computing power capacity increasing mode. Under the condition that the computing power resource pool is insufficient, the computing power resource pool capacity expansion processing can be performed, the computing power capacity expansion mode can be judged, the computing power capacity expansion processing or the computing power new expansion processing can be performed, and the computing power scheduling is performed based on the determined computing power capacity expansion mode.
According to the calculation power scheduling method provided by the embodiment, the calculation power evaluation of the use of the server is closer to the actual performance capacity of the service application, the application performance capacity evaluation can be rapidly measured and calculated according to the historical data and the standardized calculation power configuration model, the server resource supply can be provided according to the calculation power angle, the server type does not need to be distinguished, and therefore the server resource configuration work can be more efficiently completed. And after the server computing power delivery service is applied, whether the server computing power is excessive or in shortage can be timely monitored. In addition, the business application does not need to pay attention to whether to use a physical server, a virtual machine or a container, but rather relies on the evaluation force value to accurately evaluate the performance capacity required by the application. The deployment time of the service application environment is greatly shortened, and the utilization rate of the computational resources of the data center is improved.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a computing power scheduling device for realizing the above-mentioned computing power scheduling method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the one or more computing power scheduling devices provided below may be referred to the limitation of the computing power scheduling method hereinabove, and will not be described herein.
In one embodiment, as shown in fig. 11, a computing power scheduling apparatus 1100 is provided, comprising a first computing module 1102, a first determining module 1104, and a scheduling module 1106, wherein:
the first calculating module 1102 is configured to calculate a difference value between a calculated force value required by the target application and a preset calculated force value when detecting abnormal prompt information of the calculated force value corresponding to the target application;
a first determining module 1104, configured to determine a target computing power module corresponding to the target application if it is determined, based on the computing power value difference, that the computing power value required by the target application is less than the computing power value of the computing power resource pool;
the scheduling module 1106 is configured to determine a target power scheduling policy based on the type of the target power module, and perform power scheduling based on the target power scheduling policy and a power capacity increasing manner.
In one embodiment, the apparatus further comprises:
and the output module is used for outputting the abnormal prompt information of the calculated force value through the calculated force monitoring module if the real-time calculated force value of the target application is larger than or equal to the preset calculated force threshold value, wherein the real-time calculated force value is determined by detecting the target application in real time.
In one embodiment, the apparatus further comprises:
The first acquisition module is used for acquiring the number of servers, the number of virtual machines and the number of containers corresponding to the target application;
the second calculation module is used for calculating the required calculation force value of the target application based on the server calculation force value, the number of servers, the virtual machine calculation force value, the number of virtual machines, the container calculation force value and the container number corresponding to the target application.
In one embodiment, the second computing module is specifically configured to:
the method comprises the steps of based on the number of servers, the peak power of server performance, the number of virtual machines, the peak power of virtual machine performance, the number of containers and the peak power of container performance corresponding to target applications.
In one embodiment, the pre-configured computing power value is a computing power value of a preset computing power resource pool; the apparatus further comprises:
the second determining module is used for determining a capacity expansion mode corresponding to the preset computing force resource pool if the computing force value required by the target application is greater than or equal to the computing force value of the computing force resource pool;
and the capacity expansion module is used for carrying out capacity expansion treatment on the preset computing power resource pool based on a capacity expansion mode corresponding to the preset computing power resource pool.
In one embodiment, the capacity expansion module is specifically configured to:
performing capacity expansion treatment on a preset computing power resource pool based on a computing power capacity expansion mode; or performing capacity expansion processing on the preset computing resource pool based on the computing new adding mode.
In one embodiment, the apparatus further comprises:
the query module is used for querying the calculation force increasing rate in each preset time period in the calculation force increasing trend module;
and the third determining module is used for determining the current calculation force increasing rate based on the average value of the calculation force increasing rates in each preset time period.
The various modules in the computing power scheduler 1100 described above may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 12. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store data related to the application. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of power scheduling.
It will be appreciated by those skilled in the art that the structure shown in fig. 12 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, user information (including but not limited to user equipment information, user personal information, etc.) and 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 sufficiently authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples represent only a few embodiments of the present application, which are described in more detail and are not thereby to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A method of power calculation scheduling, the method comprising:
under the condition that the abnormal prompt information of the calculated force value corresponding to the target application is detected, calculating a calculated force value difference value between the calculated force value required by the target application and the calculated force value of the calculated force resource pool;
if the calculated force value required by the target application is smaller than the calculated force value of the calculated force resource pool based on the calculated force value difference value, determining a target calculated force module corresponding to the target application;
And determining a target power dispatching strategy based on the type of the target power module, and carrying out power dispatching based on the target power dispatching strategy and the power capacity increasing mode.
2. The method according to claim 1, wherein the generating of the calculation value abnormality prompt information includes:
if the real-time calculated force value of the target application is larger than or equal to a preset calculated force threshold value, outputting abnormal prompt information of the calculated force value through a calculated force monitoring module, wherein the real-time calculated force value is determined by detecting the target application in real time.
3. The method according to claim 1, wherein the method further comprises:
obtaining the number of servers, the number of virtual machines and the number of containers corresponding to the target application;
and calculating the required calculation force value of the target application based on the server calculation force value, the number of servers, the virtual machine calculation force value, the number of virtual machines, the container calculation force value and the container number corresponding to the target application.
4. The method of claim 3, wherein calculating the required computing power value for the target application based on the server computing power value, the number of servers, the virtual machine computing power value, the number of virtual machines, the container computing power value, and the number of containers for the target application comprises:
And calculating a required calculation force value of the target application based on the number of servers, the server performance peak multiplying power, the number of virtual machines, the virtual machine performance peak multiplying power, the number of containers and the container performance peak multiplying power corresponding to the target application.
5. The method of claim 1, wherein the computational power value of the computational power resource pool is a pre-configured computational power value of a pre-set computational power resource pool; the method further comprises the steps of:
if the calculated force value required by the target application is greater than or equal to the calculated force value of the calculated force resource pool, determining a capacity expansion mode corresponding to the preset calculated force resource pool;
and performing capacity expansion processing on the preset computing power resource pool based on a capacity expansion mode corresponding to the preset computing power resource pool.
6. The method according to claim 5, wherein the expanding the preset computing power resource pool based on the expansion mode corresponding to the preset computing power resource pool comprises:
performing capacity expansion treatment on the preset computing power resource pool based on a computing power capacity expansion mode; or,
and performing capacity expansion processing on the preset computing force resource pool based on a computing force new adding mode.
7. The method according to any one of claims 1 to 6, further comprising:
Inquiring the calculation force increasing rate in each preset time period in the calculation force increasing trend module;
and determining the current calculation force increasing rate based on the average value of the calculation force increasing rates in the preset time periods.
8. A computing power scheduling apparatus, the apparatus comprising:
the first calculation module is used for calculating a calculation force value difference value between a calculation force value required by the target application and a preset calculation force value under the condition that calculation force value abnormality prompt information corresponding to the target application is detected;
the first determining module is used for determining a target computing power module corresponding to the target application if the computing power value required by the target application is smaller than the computing power value of the computing power resource pool based on the computing power value difference value;
and the scheduling module is used for determining a target power scheduling strategy based on the type of the target power module and performing power scheduling based on the target power scheduling strategy and the power capacity increasing mode.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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| CN117950879B (en) * | 2024-03-26 | 2024-06-07 | 深圳威尔视觉科技有限公司 | Self-adaptive cloud server distribution method and device and computer equipment |
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