Hardware resource management method and device, electronic equipment and storage medium

Abstract

The invention discloses a hardware resource management method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring hardware resource demand information of an application system, and determining at least one hardware server based on the hardware resource demand information; adding the hardware server into the shared cluster, and setting a corresponding resource label and a corresponding taint label for the hardware server; acquiring a deployment configuration file corresponding to the application system, and deploying the application system into the shared cluster based on the deployment configuration file; the deployment configuration file comprises a node selection label and stain tolerance; and when the application system is operated, if the node selection tag is matched with the resource tag and the stain tag is matched with the stain tolerance, scheduling the application system to a hardware server for operation. According to the method and the device, on the premise of not additionally increasing hardware resources, the isolation of the resources and the network among the application systems in the shared cluster is improved, and the balance problem between the isolation and the cost during hardware resource management is solved.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing, and in particular to a hardware resource management method, device, electronic device and storage medium. Background Art

[0002] Kubernetes is an open source container orchestration platform that can provide a containerized runtime environment for application systems by combining container technology. It has the characteristics of being lightweight and efficient, high resource utilization, portability and strong compatibility, and is widely used in the field of enterprise informatization in various industries.

[0003] To deploy a containerized operating environment based on Kubernetes, you must first have a certain amount of underlying hardware resources. The management of Kubernetes containerized hardware resources currently includes the following three methods in the industry:

[0004] 1. Shared cluster mode

[0005] This method usually creates a larger-scale kubernetes, applies for and adds hardware resources to the cluster according to the resource requirements of the application system, and each is provided to multiple application systems for sharing. This method has fewer clusters, simple resource management, and resource conservation, but the isolation is relatively weak. It is mostly used to support small-scale application systems with low isolation requirements;

[0006] 2. Dedicated cluster mode

[0007] This method applies for dedicated hardware resources based on the resource requirements of the application system and creates an independent Kubernetes cluster for each application system. This method has complex resource management and high costs, and is usually used to support large-scale systems with high isolation requirements.

[0008] 3. Combination of shared and dedicated clusters

[0009] This method selects shared or dedicated cluster mode according to the characteristics of the supporting application system. For large-scale or high-isolation application systems, use dedicated cluster mode for deployment, and for small-scale and low-isolation application systems, use shared cluster mode for deployment.

[0010] The above three methods all start from the cluster dimension, taking into account factors such as application system scale, isolation, and resource utilization to manage Kubernetes hardware resources. In many large-scale enterprise applications, there is a balance between isolation and cost. Summary of the invention

[0011] The present invention provides a hardware resource management method, device, electronic device and storage medium to solve the balance problem between isolation and cost in hardware resource management.

[0012] According to one aspect of the present invention, there is provided a hardware resource management method, comprising:

[0013] Acquire hardware resource requirement information of the application system, and determine at least one hardware server based on the hardware resource requirement information;

[0014] Adding the hardware server to the shared cluster and setting corresponding resource tags and taint tags for the hardware server;

[0015] Obtaining a deployment configuration file corresponding to the application system, and deploying the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance;

[0016] When the application system is running, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server.

[0017] According to another aspect of the present invention, there is provided a hardware resource management device, comprising:

[0018] A hardware server determination module, used to obtain hardware resource requirement information of the application system and determine at least one hardware server based on the hardware resource requirement information;

[0019] A label setting module, used to add the hardware server to the shared cluster and set corresponding resource labels and taint labels for the hardware server;

[0020] An application system deployment module, used to obtain a deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance;

[0021] The application system running module is used to schedule the application system to run on the hardware server if the node selection label matches the resource label and the taint label matches the taint tolerance when the application system is running.

[0022] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0023] at least one processor; and

[0024] a memory communicatively connected to the at least one processor; wherein,

[0025] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the hardware resource management method described in any embodiment of the present invention.

[0026] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the hardware resource management method described in any embodiment of the present invention when executed.

[0027] The technical solution of the embodiment of the present invention obtains the hardware resource demand information of the application system, determines at least one hardware server based on the hardware resource demand information; adds the hardware server to the shared cluster, and sets the corresponding resource label and taint label for the hardware server; obtains the deployment configuration file corresponding to the application system, and deploys the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes node selection labels and taint tolerance; when running the application system, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server. By setting the corresponding resource label and taint label on the hardware server, and setting the node selection label and taint tolerance for the application system, the resource and network isolation between application systems in the shared cluster is improved without the need to increase additional hardware resources, and the balance problem between isolation and cost in hardware resource management is solved.

[0028] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 is a flowchart of a hardware resource management method provided by Embodiment 1 of the present invention;

[0031] Figure 2 is a flowchart of a hardware resource management method provided by Embodiment 2 of the present invention;

[0032] Figure 3 It is a structural diagram of a hardware resource management device provided by Embodiment 3 of the present invention;

[0033] Figure 4 It is a structural schematic diagram of an electronic device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] Embodiment 1

[0037] Figure 1 This is a flowchart of a hardware resource management method provided by the first embodiment of the present invention. This embodiment is applicable to the allocation and management of resource nodes in a shared kubernetes cluster. The method can be executed by a hardware resource management device. The hardware resource management device can be implemented in the form of hardware and / or software. The hardware resource management device can be configured in electronic devices such as computers and servers. Figure 1 As shown, the method includes:

[0038] S110. Obtain hardware resource requirement information of the application system, and determine at least one hardware server based on the hardware resource requirement information.

[0039] The hardware resource requirement information refers to the specific specifications and requirements of the hardware resources required by the application system during operation and deployment. Specifically, the hardware resources include but are not limited to CPU, memory, storage, network bandwidth, etc. Correspondingly, the hardware resource requirement information includes the number of CPU cores, memory size, storage type and capacity, etc. In this embodiment, the hardware resource requirement information of the application system is obtained, and at least one hardware server is determined according to the hardware resource requirement information.

[0040] Based on the above embodiment, optionally, determining at least one hardware server based on the hardware resource requirement information includes: determining a server type based on the hardware resource requirement information; and determining at least one hardware server based on the server type and the hardware resource requirement information.

[0041] In this embodiment, the appropriate hardware server type is selected according to the hardware resource requirement information. The required number of servers is determined according to the hardware resource requirement information and the hardware server type of the application system. The hardware server type includes but is not limited to physical servers, virtual machines, or containers, etc., which are not limited here.

[0042] For example, assuming that application system A consists of 10 microservices, each service plans to deploy 3 instances, and the single instance specification is 2C4G, it can be obtained that the required memory of application system A is 120G. It should be noted that each node of the shared cluster needs to reserve 4G memory to deploy components such as security, storage, monitoring, and log collection. Therefore, if the hardware server type is a 16C32G specification virtual machine, each virtual machine can deploy 7 instances, and application system A needs to apply for a total of 5 virtual machines.

[0043] S120: Add the hardware server to a shared cluster, and set a corresponding resource label and a taint label for the hardware server.

[0044] Define dedicated Kubernetes resource labels and taints for system A.

[0045] The resource tag is used to identify the hardware server as a dedicated server for the application system. Specifically, the resource tag exists in the form of a key-value pair, such as app=example, env=production, etc. The taint tag is used to restrict the running units of the application system that are not set with taint tolerance from being scheduled to the hardware server.

[0046] In this embodiment, the hardware server is added to the shared cluster, and the corresponding resource label and taint label are set for the hardware server. It should be noted that the hardware server added to the shared cluster is used as a node in the shared cluster.

[0047] Exemplarily, the resource labels and taint labels of application system A are set as follows:

[0048] Resource tag: project=A is used to identify nodes (i.e. hardware servers) that are dedicated to application system A. When scheduling services, it is ensured that the services of application system A run on these dedicated nodes.

[0049] The taint label: project=A:NoExecute is used to prevent services of other application systems from being scheduled to the dedicated node of application system A.

[0050] S130. Obtain a deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance.

[0051] The node selection label is a label selector in the deployment configuration file that specifies which nodes the running unit should be scheduled on. In this embodiment, you need to ensure that the node selection label in the deployment configuration file matches the resource label previously set on the hardware server. For example, if the label of the hardware server is set to project=A, the node selection label in the deployment configuration file should also contain project:A to ensure that the running unit is scheduled on these dedicated nodes.

[0052] Taint tolerance is a setting in the deployment configuration file that specifies which nodes a running unit can tolerate taints on. The taint tolerance setting should match the taints on the hardware server to allow the running unit to be scheduled to the node with the corresponding taint. In this embodiment, if the hardware server sets the taint project=A:NoExecute, the running unit in the deployment configuration file needs to include the corresponding taint tolerance setting to indicate that the running unit can tolerate this taint.

[0053] In this embodiment, the node selection label and taint tolerance corresponding to the application system are set in advance in the deployment configuration file, and the set deployment configuration file is deployed to the shared cluster.

[0054] Exemplarily, the node selection label is set as follows:

[0055] template:

[0056] spec:

[0057] nodeSelector:

[0058] project:A#Set the node selection label to ensure that it is scheduled to the node with the same label.

[0059] The taint tolerance settings are as follows:

[0060] tolerations: #Set tolerance to the same taint as the node, so that it is allowed to be scheduled to the node with the same taint

[0061] -key:"project"

[0062] operator:"Equal"

[0063] value:"A"

[0064] effect:"NoExecute".

[0065] Based on the above embodiment, optionally, deploying the application system to the shared cluster based on the deployment configuration file includes: applying the deployment configuration file configuration to the shared cluster, establishing an operating unit of the application system based on the deployment configuration file, and configuring the node selection label and taint tolerance to the operating unit.

[0066] In this embodiment, the deployment configuration file is applied to the shared cluster, the running unit of the application system is established based on the deployment configuration file, and the node selection label and taint tolerance are configured on the running unit, which can ensure that the running unit is scheduled to the appropriate node as expected, thereby meeting the resource needs and operation requirements of the application system.

[0067] S140. When the application system is running, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server.

[0068] In this embodiment, when running the application system, the resource label of the node corresponding to the hardware resource server and the node selection label corresponding to the application system are matched, and the taint label of the node corresponding to the hardware resource server and the taint tolerance corresponding to the application system are matched. If the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server.

[0069] Based on the above embodiment, optionally, scheduling the application system to run on the hardware server includes: scheduling an operating unit of the application system to run on the hardware server.

[0070] Specifically, when the application system is running, if the node selection label and the resource label are the same and the taint label matches the taint tolerance, the running unit of the application system is scheduled to run on the hardware server.

[0071] Based on the above embodiment, optionally, the method further includes: obtaining a network policy configuration file corresponding to the hardware server; the network policy configuration file includes a server network policy and an application system network policy. In response to a network policy configuration command, the server network policy and the application system network policy are applied to the shared cluster based on the network policy configuration command.

[0072] Among them, the network policy configuration file is used to configure the network policy of the application system. Specifically, the network policy configuration file includes the server network policy and the application system network policy. The server network policy mainly involves the communication rules between the server and the external network, while the application system network policy mainly focuses on the mutual access rules between the application system and other systems or components.

[0073] In this embodiment, before deploying the application system to the shared cluster, it is necessary to obtain a network policy configuration file, respond to the network policy configuration command, specify the path of the network policy configuration file by running the network policy configuration command, and apply the server network policy and the application system network policy to the shared cluster. Specifically, the communication rules between the server and the external network can be configured according to the server network policy in the network policy configuration file. The server network policy configuration includes the setting of firewall rules, the configuration of network address translation (NAT), etc. The mutual access rules between the application system and other systems or components can be configured according to the application system network policy in the network policy configuration file. The application system network policy configuration includes the configuration of service discovery, load balancing, access control, etc.

[0074] The technical solution of this embodiment is to obtain the hardware resource demand information of the application system, determine at least one hardware server based on the hardware resource demand information; add the hardware server to the shared cluster, and set the corresponding resource label and taint label for the hardware server; obtain the deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes node selection labels and taint tolerance; when running the application system, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server. By setting the corresponding resource label and taint label on the hardware server, and setting the node selection label and taint tolerance for the application system, the resource and network isolation between application systems in the shared cluster is improved without the need to increase additional hardware resources, and the balance problem between isolation and cost in hardware resource management is solved.

[0075] Embodiment 2

[0076] Figure 2This is a flowchart of a hardware resource management method provided by Embodiment 2 of the present invention. In this embodiment, based on the above embodiments, optionally, the step of obtaining the hardware resource demand information of the application system includes: obtaining resource usage data of the node corresponding to the application system in the shared cluster; inputting the resource usage data into a resource demand prediction model for prediction to obtain the hardware resource demand information of the application system. The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here.

[0077] like Figure 2 As shown, the method includes:

[0078] S210. Obtain resource usage data of the node corresponding to the application system in the shared cluster; input the resource usage data into a resource demand prediction model for prediction to obtain hardware resource demand information of the application system, and determine at least one hardware server based on the hardware resource demand information.

[0079] Among them, resource usage data refers to the resource usage data of the corresponding node of the application system in the shared cluster when the application system is not expanded. Specifically, the resource usage data includes the CPU, memory and other resource usage of each node. In this embodiment, the resource usage data of the corresponding node of the application system in the shared cluster is obtained through the kubectl command line tool or the integrated Prometheus monitoring system; the resource usage data is input into the resource demand prediction model for prediction to obtain the hardware resource demand information of the application system, and at least one hardware server is determined based on the hardware resource demand information. Among them, the resource demand prediction model includes but is not limited to machine learning models, deep learning models, statistical models, etc., and the machine learning algorithms used by the machine learning model include but are not limited to linear regression, decision trees, random forests, etc.

[0080] S220, adding the hardware server to a shared cluster, and setting a corresponding resource tag and a taint tag for the hardware server;

[0081] S230, obtaining a deployment configuration file corresponding to the application system, and deploying the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance;

[0082] S250. When the application system is running, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server.

[0083] The technical solution of this embodiment is to obtain resource usage data of the corresponding node of the application system in the shared cluster; input the resource usage data into the resource demand prediction model for prediction, obtain the hardware resource demand information of the application system, and determine at least one hardware server based on the hardware resource demand information; add the hardware server to the shared cluster, and set the corresponding resource label and taint label for the hardware server; obtain the deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes node selection label and taint tolerance; when running the application system, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server. The hardware resource demand information of the application system is predicted by the resource usage data of the application system, and the hardware resource demand information of the application system is monitored, so as to expand the capacity of the application system in time to meet the needs of the application system.

[0084] Embodiment 3

[0085] Figure 3 Schematic diagram of the structure of a hardware resource management device provided by Embodiment 3 of the present invention. Figure 3 As shown, the device comprises:

[0086] A hardware server determination module 310 is used to obtain hardware resource requirement information of the application system and determine at least one hardware server based on the hardware resource requirement information;

[0087] The label setting module 320 is used to add the hardware server to the shared cluster and set corresponding resource labels and taint labels for the hardware server;

[0088] The application system deployment module 330 is used to obtain a deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance;

[0089] The application system running module 340 is used to schedule the application system to run on the hardware server if the node selection label matches the resource label and the taint label matches the taint tolerance when running the application system.

[0090] The technical solution of this embodiment is to obtain the hardware resource demand information of the application system, determine at least one hardware server based on the hardware resource demand information; add the hardware server to the shared cluster, and set the corresponding resource label and taint label for the hardware server; obtain the deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes node selection labels and taint tolerance; when running the application system, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server. By setting the corresponding resource label and taint label on the hardware server, and setting the node selection label and taint tolerance for the application system, the resource and network isolation between application systems in the shared cluster is improved without the need to increase additional hardware resources, and the balance problem between isolation and cost in hardware resource management is solved.

[0091] Based on the above embodiment, optionally, the hardware server determination module includes a hardware resource requirement information determination module, which is used to:

[0092] Obtain resource usage data of the node corresponding to the application system in the shared cluster;

[0093] The resource usage data is input into a resource demand prediction model for prediction to obtain hardware resource demand information of the application system.

[0094] Based on the above embodiment, optionally, the hardware server determination module 310 is used to:

[0095] Evaluate the memory of the application system based on the hardware resource requirement information to obtain a memory evaluation result;

[0096] At least one hardware server is determined based on the memory evaluation result.

[0097] Based on the above embodiment, optionally, the application system deployment module 330 is used to:

[0098] The deployment configuration file is applied to the shared cluster, an operating unit of the application system is established based on the deployment configuration file, and the node selection label and taint tolerance are configured on the operating unit.

[0099] Based on the above embodiment, optionally, the application system running module 340 is used to schedule the running unit of the application system to run on the hardware server.

[0100] Based on the above embodiment, optionally, the device further includes a network policy configuration module, which is used to:

[0101] Obtain a network policy configuration file corresponding to the hardware server; the network policy configuration file includes a server network policy and an application system network policy.

[0102] In response to a network policy configuration command, the server network policy and the application system network policy are applied to the shared cluster based on the network policy configuration command.

[0103] The hardware resource management device provided in the embodiment of the present invention can execute the hardware resource management method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0104] Embodiment 4

[0105] Figure 4 1 is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0106] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0107] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0108] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a hardware resource management method.

[0109] In some embodiments, the hardware resource management method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the hardware resource management method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the hardware resource management method in any other appropriate manner (e.g., by means of firmware).

[0110] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0111] The computer program for implementing the hardware resource management method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or the block diagram are implemented. The computer program can be executed completely on the machine, partially on the machine, partially on the machine as an independent software package and partially on a remote machine, or completely on a remote machine or server.

[0112] Embodiment 5

[0113] Embodiment 5 of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a processor to execute a hardware resource management method, the method comprising:

[0114] Acquire hardware resource requirement information of the application system, and determine at least one hardware server based on the hardware resource requirement information;

[0115] Adding the hardware server to the shared cluster and setting corresponding resource tags and taint tags for the hardware server;

[0116] Obtaining a deployment configuration file corresponding to the application system, and deploying the application system to the shared cluster based on the deployment configuration file; the load configuration file includes a node selection label and taint tolerance;

[0117] When the application system is running, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server.

[0118] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0119] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0120] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0121] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0122] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0123] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for hardware resource management, characterized in that: include: Acquire hardware resource requirement information of the application system, and determine at least one hardware server based on the hardware resource requirement information; Adding the hardware server to the shared cluster and setting corresponding resource tags and taint tags for the hardware server; Obtaining a deployment configuration file corresponding to the application system, and deploying the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance; When the application system is running, if the node selection label matches the resource label and the taint label matches the taint tolerance, the application system is scheduled to run on the hardware server.

2. The method according to claim 1, characterized in that The obtaining of the hardware resource requirement information of the application system includes: Obtain resource usage data of the node corresponding to the application system in the shared cluster; The resource usage data is input into a resource demand prediction model for prediction to obtain hardware resource demand information of the application system.

3. The method according to claim 1, characterized in that: The determining at least one hardware server based on the hardware resource requirement information comprises: Evaluate the memory of the application system based on the hardware resource requirement information to obtain a memory evaluation result; At least one hardware server is determined based on the memory evaluation result.

4. The method according to claim 1, characterized in that: The deploying the application system to the shared cluster based on the deployment configuration file includes: The deployment configuration file is applied to the shared cluster, an operating unit of the application system is established based on the deployment configuration file, and the node selection label and taint tolerance are configured on the operating unit.

5. The method according to claim 4, characterized in that The step of scheduling the application system to run on the hardware server includes: The operating unit of the application system is dispatched to the hardware server for execution.

6. The method according to claim 1, characterized in that The method further comprises: Obtain a network policy configuration file corresponding to the hardware server; the network policy configuration file includes a server network policy and an application system network policy. In response to a network policy configuration command, the server network policy and the application system network policy are applied to the shared cluster based on the network policy configuration command.

7. A hardware resource management device, characterized in that: include: A hardware server determination module, used to obtain hardware resource requirement information of the application system and determine at least one hardware server based on the hardware resource requirement information; A label setting module, used to add the hardware server to the shared cluster and set corresponding resource labels and taint labels for the hardware server; An application system deployment module, used to obtain a deployment configuration file corresponding to the application system, and deploy the application system to the shared cluster based on the deployment configuration file; the deployment configuration file includes a node selection label and taint tolerance; The application system running module is used to schedule the application system to run on the hardware server if the node selection label matches the resource label and the taint label matches the taint tolerance when the application system is running.

8. The device according to claim 7, characterized in that The hardware server determination module includes a hardware resource requirement information determination module, which is used to: Obtain resource usage data of the node corresponding to the application system in the shared cluster; The resource usage data is input into a resource demand prediction model for prediction to obtain hardware resource demand information of the application system.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the hardware resource management method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the hardware resource management method according to any one of claims 1 to 6 when executed.

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