Scheduling method, medium, electronic equipment and scheduling equipment

Abstract

The invention provides a scheduling method for virtual machine computing resources, a medium, an electronic device and a scheduling device.The scheduling method comprises the steps that a resource abstraction layer is established, and computing resource information is abstracted into a universal resource description model in a unified mode; establishing a resource view based on the resource description model; based on the resource view, a unified management and control layer is established, and computing resources are managed in a unified mode. According to the scheduling method for the virtual machine computing resources, the medium, the electronic equipment and the scheduling equipment, heterogeneous resource information from a virtual machine management platform and a container management platform can be fused, and information such as specifications, states and association relationships of the resources can be automatically extracted and standardized through a uniform resource abstraction layer; unified view display, centralized strategy management and control and integrated operation and maintenance operation of the whole life cycle of virtualized and containerized resources are achieved, and the centrality, safety and efficiency of computing resource management are improved.

Description

Technical Field

[0001] This application relates to the field of virtual machine resource scheduling, and in particular to a scheduling method, medium, electronic device and scheduling device for virtual machine computing resources. Background Technology

[0002] Against the backdrop of the continuous development of cloud computing technology, virtualization and containerization have become core technologies for building public, private, and hybrid cloud infrastructures. Virtualization technologies, represented by KVM and OpenStack, and containerization technologies, represented by Docker and Kubernetes (K8s), both abstract and encapsulate computing resources (such as CPU, memory, and storage) and provide standardized API interfaces, enabling unified scheduling and management of underlying hardware resources. They have been widely used in various cloud platforms.

[0003] However, in the existing technology system, virtual machines (VMs) and containers differ significantly in design philosophy and application scenarios: VMs emphasize strong isolation and runtime environment compatibility, making them suitable for traditional scenarios such as enterprise applications; while containers focus on lightweight design, rapid start-up and shutdown, and high-density deployment, making them more suitable for cloud-native and microservice architectures. Since they are typically managed independently by different management platforms (such as OpenStack and Kubernetes), management entry points are relatively dispersed, and functions such as resource monitoring, management, billing, permissions, and security need to be maintained separately. This not only leads to dispersed management entry points and high operational complexity, but also requires enterprises to maintain two resource management systems simultaneously in actual operation and maintenance. Operations personnel need to switch between multiple platforms, making it difficult to achieve globally unified resource management and policy specification. Furthermore, it makes it difficult to achieve unified monitoring, quota allocation, and scheduling optimization across resource types in hybrid cloud or multi-tenant scenarios, resulting in problems such as uneven utilization of computing resources, fragmented policy configuration, and difficulties in security auditing.

[0004] Therefore, there is an urgent need for a technical solution that can integrate virtual machine and container resource management to solve the operation and scheduling challenges caused by the fragmentation of heterogeneous computing resources.

[0005] The statements herein provide only background information in relation to this invention and do not necessarily constitute prior art. Summary of the Invention

[0006] The purpose of this invention is to provide a scheduling method, medium, electronic device, and scheduling device for virtual machine computing resources, which has the advantage of high resource management efficiency.

[0007] To achieve the above objectives, the present invention provides a method for scheduling virtual machine computing resources, comprising: S10. Establish a resource abstraction layer to abstract computing resource information into a general resource description model; S20. Based on the resource description model, establish a resource view; S30. Based on the resource view, establish a unified management and control layer to manage computing resources in a unified manner.

[0008] In some embodiments, in step S10, the computing resource information includes central processing unit resources, memory resources, storage resources, and network information from a virtual machine management platform or a container management platform.

[0009] In some embodiments, step S10 includes: S101, constructing a first adapter and a second adapter, wherein the first adapter is used to interface with the virtual machine management platform and the second adapter is used to interface with the container management platform; S102, collecting computing resource information of the virtual machine management platform through the first adapter; collecting computing resource information of the container management platform through the second adapter; S103, mapping the computing resource information of the virtual machine management platform and the computing resource information of the container management platform to the resource description model.

[0010] In some embodiments, the virtual machine management platform includes OpenStack or KubeVirt, and the container management platform includes Kubernetes.

[0011] In some embodiments, step S20 further includes displaying the resource view.

[0012] In some embodiments, in step S30, the unified management of computing resources includes tenant management, system security auditing, and global access control.

[0013] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the scheduling method for virtual machine computing resources as described above.

[0014] This application also provides an electronic device, including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the scheduling method for virtual machine computing resources as described above.

[0015] This application also provides a scheduling device for virtual machine computing resources, used in the scheduling method for virtual machine computing resources as described above, the scheduling device comprising: The resource access module includes multiple adapters, which connect to the virtual machine management platform and the container management platform respectively, and are used to collect computing resource information; The resource abstraction module, electrically connected to the resource access module, is used to uniformly model the computing resource information of the virtual machine management platform and the container management platform into a general resource description model; A unified display module, electrically connected to the resource abstraction module, is used to display the operating status and configuration information of computing resources; The resource management module is electrically connected to the resource abstraction module and is used to perform tenant management, quota allocation, security auditing and unified access control across resource types.

[0016] In some embodiments, the scheduling device further includes an extended access module electrically connected to the resource abstraction module, the extended access module including a standardized driver interface for accessing a third-party platform.

[0017] In summary, compared with the prior art, the scheduling method, medium, electronic device, and scheduling device for virtual machine computing resources provided by the present invention have the following beneficial effects: The scheduling method, medium, electronic device, and scheduling device for virtual machine computing resources disclosed in this application can integrate heterogeneous resource information from virtual machine management platforms and container management platforms. By automatically extracting and standardizing information such as resource specifications, status, and relationships through a unified resource abstraction layer, it can achieve a unified view of the entire lifecycle of virtualized and containerized resources, centralized policy control, and integrated operation and maintenance, thereby improving the centralization, security, and efficiency of computing resource management. Attached Figure Description

[0018] Figure 1 This is a flowchart of the scheduling method for virtual machine computing resources used in this application.

[0019] Figure 2 This is a diagram illustrating the resource view.

[0020] Figure 3 A schematic diagram of a unified management and control platform.

[0021] Figure 4 A schematic diagram of the platform architecture for unified management and control.

[0022] Figure 5 A schematic diagram for unified modeling of resources.

[0023] Figure 6 This is a diagram illustrating multi-cloud access and unified management. Detailed Implementation

[0024] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a more detailed account of the scheduling method, medium, electronic device, and scheduling device for virtual machine computing resources proposed in this invention. The advantages and features of this invention will become clearer from the following description. It should be noted that the accompanying drawings are in a very simplified form and use non-precise proportions, used only to facilitate and clearly illustrate the embodiments of this invention. Please refer to the accompanying drawings to make the objectives, features, and advantages of this invention more apparent and understandable. It should be understood that the structures, proportions, sizes, etc., depicted in the accompanying drawings are only for illustrative purposes to aid those skilled in the art and are not intended to limit the implementation conditions of this invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in proportions, or adjustments to the size, without affecting the effects and objectives achieved by this invention, should still fall within the scope of the technical content disclosed in this invention.

[0025] like Figure 1 As shown, this invention provides a scheduling method for virtual machine computing resources. Without altering the existing underlying scheduling algorithms for virtual machines and containers, it achieves unified access, centralized display, and management strategies for the computing resources of virtual machines and containers. This solves the problems of fragmented virtual machine and container resources and complex resource scheduling and management. The scheduling method includes: S10. Establish a resource abstraction layer to unify and abstract computing resource information into a common resource description model. Computing resources include CPU resources, memory resources, storage resources, and network information from virtual machine management platforms or container management platforms. The virtual machine management platform, including the virtual CPU (virtual CPU), vMem (virtual memory), and vDisk (virtual disk) of virtual machines, and the container management platform, including the CPU (central processing unit), memory, and storage of containers, are uniformly abstracted into a common resource description model, shielding the underlying differences in computing resources between virtual machines and containers. The vCPU of virtual machines and the CPU of containers are uniformly connected.

[0026] In one embodiment, step S10 includes: S101, constructing a first adapter and a second adapter. The first adapter is used to interface with a virtual machine management platform, and the second adapter is used to interface with a container management platform. In this embodiment, the virtual machine management platform includes OpenStack or KubeVirt, and the container management platform includes Kubernetes. The first adapter collects computing resource information from the virtual machine management platform, and the second adapter collects computing resource information from the container management platform. The computing resource information includes CPU, memory, storage, network, etc.

[0027] S102. Collect computing resource information of the virtual machine management platform through the first adapter; collect computing resource information of the container management platform through the second adapter.

[0028] S103. Map the computing resource information of the virtual machine management platform and the computing resource information of the container management platform to the resource description model.

[0029] S20. Based on the resource description model, establish a unified resource view. Furthermore, this embodiment also includes displaying the resource view. For example... Figure 2 As shown, virtual machines and containers are displayed in a unified manner to administrators, which facilitates the unified management and scheduling of computing resources in the future.

[0030] S30. Based on the resource view, establish a unified management and control layer to uniformly manage computing resources. In this step, a unified management layer is established to achieve unified policies and management, supporting unified management of computing resources including tenant management, system security auditing, and global access control. It provides unified policy distribution across resource pools, allowing administrators to define policies only once in the unified management layer, and these policies will automatically take effect on all managed resources, avoiding fragmented configurations across multiple platforms and reducing the administrator's management complexity. Furthermore, as... Figure 3 As shown, in this step, administrators can also monitor the running status of virtual machines and containers in a unified management and control platform based on a unified management layer, and allocate resource quotas in a unified manner.

[0031] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the scheduling method for virtual machine computing resources as described above.

[0032] This application also provides an electronic device, including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the scheduling method for virtual machine computing resources as described above.

[0033] This application also provides a scheduling device for virtual machine computing resources, used in the scheduling method for virtual machine computing resources as described above. The scheduling device includes a resource access module, a resource abstraction module, a unified display module, and a resource management module.

[0034] The resource access module includes multiple adapters, which connect to the virtual machine management platform and the container management platform respectively, for collecting computing resource information. The resource abstraction module is electrically connected to the resource access module and is used to uniformly model the computing resource information from the virtual machine management platform and the container management platform into a general resource description model. The unified display module is electrically connected to the resource abstraction module and is used to display the running status and configuration information of computing resources. The resource management module is electrically connected to the resource abstraction module and is used to perform cross-resource type tenant management, quota allocation, security auditing, and unified access control. Administrators can uniformly monitor the running status of each virtual machine and container and uniformly allocate resource quotas in the resource management module. In addition, the scheduling device also includes a driver layer to facilitate the access of various types of adapters to the scheduling device, enabling use by other third-party cloud platforms or virtualization platforms for rapid integration. For example, the scheduling device in this embodiment supports seamless access to kubevirt, third-party cloud such as Huawei Cloud, etc., to achieve unified resource management and scheduling across multiple clouds.

[0035] In this embodiment, the scheduling device further includes an extended access module electrically connected to the resource abstraction module. The extended access module includes a standardized driver interface for accessing a third-party platform.

[0036] The overall architecture diagram of the unified management platform in this application is shown below. Figure 4 As shown, the unified management platform adopts a three-tier architecture, including a UI / API layer, a policy and control layer, and a resource management layer. The UI / API layer provides a user interface and API interfaces for users and external systems to access, supporting the RESTful interface protocol. The policy and control layer implements tenant management, cooperation / cost management, unified monitoring, and policy distribution. It is responsible for the unified management of various resource types (containers, virtual machines, and cloud resources). The resource management layer supports various heterogeneous resources: KubeVirt virtual machines, third-party cloud resources (Alibaba Cloud, AWS, Huawei Cloud, etc.), providing unified modeling, scheduling, and lifecycle management.

[0037] The unified management platform uses the KubeVirt CRD (Custom Resource Definition) interface. As a data model within the unified resource abstraction layer, it represents a virtual machine in a standardized format within the platform, enabling unified scheduling and monitoring of virtual machines and containers. An example code implementation is shown below: { @Data public class VirtualMachine { private String name; private String namespace; private String status; private int cpu; private int memoryMB; } Unified resource modeling, such as Figure 5 As shown, the core implementation code example for unified resource modeling is as follows: / / Query virtual machine status public List <virtualmachine>listVirtualMachines(String namespace) { return kubeVirtClient.virtualMachines().inNamespace(namespace).list() .getItems() .stream() .map(vm -> { VirtualMachine v = new VirtualMachine(); v.setName(vm.getMetadata().getName()); v.setNamespace(vm.getMetadata().getNamespace()); v.setStatus(vm.getStatus().getPrintStatus()); v.setCpu(vm.getSpec().getTemplate().getSpec().getDomain().getCpu().getCores()); v.setMemoryMB(Integer.parseInt(vm.getSpec().getTemplate().getSpec().getDomain().getMemory().getQuantity().getAmount())); return v; }).collect(Collectors.toList()); }} The platform encapsulates APIs from different cloud vendors through a unified interface, enabling unified management of multi-cloud resources. Code examples are as follows: { @Data public class ServerResource { private String envId; Kubevirt / H3C / Openstack private String region; private String securityType; private String flavorId; private Integer vcpus; private Integer memoryMb; private List <networkcreate>networks; private List <blockdevicemapping>blockDevice; } / / Example: Calling the Alibaba Cloud ECS API to query instances public List <cloudresource>listAliyunInstances(String region) { return aliyunClient.describeInstances(region).stream() .map(ins -> { CloudResource cr = new CloudResource(); cr.setCloudProvider("Aliyun"); cr.setRegion(region); cr.setResourceType("ECS"); cr.setResourceId(ins.getInstanceId()); cr.setStatus(ins.getStatus()); return cr; }).collect(Collectors.toList()); } } like Figure 6 As shown, users submit resource scheduling or policy requests through the unified management platform's UI / API. The policy and control layer verifies user permissions and tenant information, and issues quota / cost / security policies. The resource management layer executes specific operations based on resource type (container, virtual machine, multi-cloud): containers schedule Pods via the Kubernetes API, virtual machines schedule VMs via KubeVirt, and cloud resources are created, monitored, and deleted via APIs from various cloud vendors. The platform uniformly collects resource status and ultimately feeds it back to the monitoring module for visualized monitoring.

[0038] The scheduling device in this embodiment achieves unified management of cross-cloud resources through a unified abstract cloud resource model and a cloud adapter model. The unified abstract cloud resource model defines standardized fields such as resource type, status, and metrics, allowing resources from different cloud vendors to be mapped to the same model. For example, resource attributes from different cloud vendors include: resource ID, cloud vendor, type, region, status, specifications, and tags.

[0039] For different cloud vendors, each cloud platform implements its own adapter, encapsulating and translating the cloud API within the adapter. Upper-layer business logic calls a unified interface, eliminating the need to concern itself with underlying differences. Adding a new cloud platform only requires implementing the adapter, without modifying the upper-layer business logic, significantly reducing development complexity and cognitive burden. Business logic developers can focus on realizing business value without getting bogged down in the technical details of multi-cloud integration. When adding a new cloud platform, only one adapter needs to be developed for the new platform; there's no need to modify upper-layer business code, monitoring modules, policy engines, or user interfaces. An example of the unified interface code is as follows: { public interface CloudAdapter { List <cloudresource>listResources(String region); void createResource(CloudResource resource); void deleteResource(String resourceId); void startResource(String resourceId); Resource detail(String resourceId); } } For unified access control, Java annotations are used to apply a uniform access model to all resource types (Container, VM, CloudResource). Operation types (Read, Write, Delete), resource scope, and tenant relationships are defined uniformly. This way, upper-layer services only need to call a unified interface to verify permissions, without needing to worry about differences in underlying resource types or cloud platforms. A code example for unified access control is as follows: { @Target({ElementType.METHOD}) @Retention(RetentionPolicy.RUNTIME) @Documented @Inherited Public @interface HasPermission{ String[] value() default {}; } } @Aspect Public class PermissionAspect{ @Before() Public void before(JoinPoint joinPoint){ / / Authentication Processing iamPermissionService.hasPermission(premissionCode, username); } } Through unified access control, cloud resource permissions are mapped to a unified access model via adapters, enabling consistent control across platforms.

[0040] This application presents a scheduling method and device for virtual machine computing resources, integrating both virtual machine and container technology frameworks. This achieves a unified abstraction of virtual machine and container resources, avoiding the complexity of multi-platform management. Centralized resource management on a single platform improves operational efficiency. Furthermore, the technical solution integrates resources from different models, supporting unified resource computation, auditing, and access control, enhancing security. It also offers better scalability for future platforms of various types and is compatible with a wider range of computing resources.

[0041] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0042] In the description of this invention, it should be understood that the terms "center," "height," "thickness," "upper," "lower," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are used only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0043] In the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "joining," and "fixation" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0044] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0045] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.< / cloudresource> < / cloudresource> < / blockdevicemapping> < / networkcreate> < / virtualmachine>

Claims

1. A method for scheduling virtual machine computing resources, characterized in that, The scheduling method includes: S10, establishing a resource abstraction layer to uniformly abstract computing resource information into a general resource description model; S20, establishing a resource view based on the resource description model; S30, establishing a unified management and control layer based on the resource view to uniformly manage computing resources.

2. The scheduling method for virtual machine computing resources as described in claim 1, characterized in that, In step S10, the computing resource information includes central processing unit resources, memory resources, storage resources, and network information from the virtual machine management platform or container management platform.

3. The scheduling method for virtual machine computing resources as described in claim 2, characterized in that, Step S10 includes: S101, constructing a first adapter and a second adapter, wherein the first adapter is used to interface with the virtual machine management platform and the second adapter is used to interface with the container management platform; S102, collecting computing resource information of the virtual machine management platform through the first adapter; collecting computing resource information of the container management platform through the second adapter; S103, mapping the computing resource information of the virtual machine management platform and the computing resource information of the container management platform to the resource description model.

4. The scheduling method for virtual machine computing resources as described in claim 2, characterized in that, The virtual machine management platform includes OpenStack or KubeVirt, and the container management platform includes Kubernetes.

5. The scheduling method for virtual machine computing resources as described in claim 1, characterized in that, Step S20 also includes displaying the resource view.

6. The scheduling method for virtual machine computing resources as described in claim 1, characterized in that, In step S30, the unified management of computing resources includes tenant management, system security auditing, and global access control.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the scheduling method for virtual machine computing resources as described in any one of claims 1-6.

8. An electronic device, characterized in that, It includes a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the scheduling method for virtual machine computing resources as described in any one of claims 1-6.

9. A scheduling device for virtual machine computing resources, characterized in that, The scheduling device for scheduling virtual machine computing resources as described in any one of claims 1-6 comprises: a resource access module, including multiple adapters respectively connected to a virtual machine management platform and a container management platform, for collecting computing resource information; a resource abstraction module, electrically connected to the resource access module, for uniformly modeling the computing resource information of the virtual machine management platform and the container management platform into a general resource description model; a unified display module, electrically connected to the resource abstraction module, for displaying the running status and configuration information of the computing resources; and a resource management module, electrically connected to the resource abstraction module, for performing cross-resource type tenant management, quota allocation, security auditing, and unified access control.

10. The scheduling device for virtual machine computing resources as described in claim 9, characterized in that, The scheduling device also includes an extended access module electrically connected to the resource abstraction module. The extended access module includes a standardized driver interface for accessing third-party platforms.

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