Distributed container cluster management method and device, electronic equipment and storage medium

Abstract

The disclosure provides a distributed container cluster management method and device, electronic equipment and storage medium, and relates to the technical field of computers. The distributed container cluster management method comprises the following steps: deploying cluster components on a center cloud node and an edge cloud node respectively according to a hierarchical structure through a global cluster controller, and deploying a terminal cluster working face component on a terminal cloud node; the cluster component comprises a cluster control plane component and a cluster working face component; an association relationship between the cluster control plane components is established, and the cluster control plane components are uniformly managed based on the association relationship; when a resource request is received, a target working face component is determined from the cluster working face component and the terminal cluster working face component, so that the low-latency response of the resource request is realized through the target working face component. The technical scheme of the embodiment of the disclosure can realize the unified management of the distributed container cluster, and can also schedule resources across nodes through the target working face component, so as to realize the low-latency response of the resource request.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to a distributed container cluster management method, a distributed container cluster management device, an electronic device, and a computer-readable storage medium. Background Technology

[0002] With the continuous development of container cluster construction technology in the field of cloud computing, distributed container cluster management has also become an important factor affecting the development of the cloud computing field.

[0003] However, in the relevant distributed container cluster construction methods, the container clusters of the central cloud, edge cloud, and terminal cloud are mostly built using different cloud platform technologies, which makes it difficult to manage the container clusters between the central cloud, edge cloud, and terminal cloud. At the same time, there are also resource scheduling barriers between the central cloud, edge cloud, and terminal cloud, making it difficult to meet the resource needs of enterprises or users in real time.

[0004] Therefore, proposing a distributed container cluster management method that can meet the diverse needs of enterprise applications and the low-latency requirements of resource scheduling has important practical significance in the field of cloud computing.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this disclosure is to provide a distributed container cluster management method, a distributed container cluster management device, an electronic device, and a computer-readable storage medium, thereby overcoming, to at least a certain extent, the problems of high complexity in distributed container cluster management and high resource request response latency.

[0007] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part from practice of this disclosure.

[0008] According to a first aspect of the present disclosure, a distributed container cluster management method is provided, comprising: deploying cluster components sequentially on a central cloud node and an edge cloud node according to a hierarchical structure through a global cluster controller, and deploying a terminal cluster working plane component on a terminal cloud node; the cluster components include a cluster control plane component and a cluster working plane component; establishing an association relationship between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node based on a service discovery mechanism, and uniformly managing the cluster control plane component based on the association relationship; upon receiving a resource request, acquiring status data of the cluster working plane component and the terminal cluster working plane component using a listening mechanism, and determining a target working plane component from the cluster working plane component and the terminal cluster working plane component based on the status data, so as to achieve a low-latency response to the resource request through the target working plane component.

[0009] In some example embodiments of this disclosure, based on the foregoing scheme, the method further includes: deploying a standard container engine and an image repository sequentially on the central cloud node and the edge cloud node according to the hierarchical structure through the global cluster controller, and deploying a custom container engine on the terminal cloud node, so as to provide download services for the images of the standard container engine and the custom container engine, as well as the images of the cluster components and the images of the terminal cluster working surface components through the image repository.

[0010] In some example embodiments of this disclosure, based on the foregoing scheme, the method further includes: deploying a distributed service registry at the central cloud node to register the cluster control plane components of the edge cloud node to the distributed service registry.

[0011] In some example embodiments of this disclosure, based on the foregoing scheme, establishing the association between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node, and uniformly managing the cluster control plane component based on the association, includes: obtaining cluster control plane component information in the edge cloud node from the distributed service registry through the member cluster controller of the cluster control plane component in the central cloud node, and connecting the cluster control plane component corresponding to the cluster control plane component information to the cluster control plane component in the central cloud node; establishing the association between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node based on the cluster control plane information, the cluster control plane component corresponding to the cluster control plane information, and the cluster control plane component in the central cloud node, and uniformly managing the cluster control plane component based on the association.

[0012] In some example embodiments of this disclosure, based on the foregoing scheme, the method further includes: caching the configuration data of the cluster control plane component of the edge cloud node and sending it to the terminal cloud node; establishing an association relationship between the terminal cluster working plane component in the terminal cloud node and the cluster control plane component in the edge cloud node according to the configuration data; and configuring the sharing of the cluster control plane component in the edge cloud node and the terminal cluster control plane component in the terminal cloud node based on the association relationship.

[0013] In some example embodiments of this disclosure, based on the foregoing scheme, the step of acquiring the status data of the cluster working plane component and the terminal cluster working plane component using a listening mechanism, and determining the target working plane component from the cluster working plane component and the terminal cluster working plane based on the status data, includes: listening to the status data of the cluster working plane in the central cloud node through the scheduler corresponding to the cluster control plane component in the central cloud node, and sending a resource request to the scheduler corresponding to the cluster control plane component in the edge cloud node when the status data is detected to be busy; when the scheduler corresponding to the cluster control plane component in the edge cloud node listens to the resource request, acquiring the status data of the cluster working plane component in the edge cloud node, and determining the target working plane component responding to the resource request based on the status data of the cluster working plane component in the edge cloud node and the status data of the terminal cluster working plane component.

[0014] In some example embodiments of this disclosure, based on the foregoing scheme, determining the target workface component responding to the resource request based on the status data of the cluster workface component in the edge cloud node and the status data of the terminal cluster workface component includes: when the status data of the cluster workface component in the edge cloud node is detected to be busy, allocating the resource request to the terminal cluster workface component through the scheduler in the cluster control plane of the edge cloud node; and monitoring the status data of the terminal cluster workface component to determine the target workface component that satisfies the resource request from the cluster workface components based on the status data of the terminal cluster workface component.

[0015] According to a second aspect of the present disclosure, a distributed container cluster management device is provided, comprising: a component deployment module, configured to deploy cluster components sequentially on a central cloud node and an edge cloud node according to a hierarchical structure through a global cluster controller, and to deploy a terminal cluster working plane component on a terminal cloud node; the cluster components include a cluster control plane component and a cluster working plane component; a component management module, configured to establish an association relationship between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node based on a service discovery mechanism, and to uniformly manage the cluster control plane component based on the association relationship; and a resource request response module, configured to, upon receiving a resource request, acquire status data of the cluster working plane component and the terminal cluster working plane component using a listening mechanism, and determine a target working plane component from the cluster working plane component and the terminal cluster working plane component based on the status data, so as to schedule business data matching the resource request through the target working plane component, thereby realizing cross-node scheduling of business data.

[0016] In some example embodiments of this disclosure, based on the foregoing scheme, the component deployment module further includes a container engine deployment unit. The container engine deployment unit is used to deploy a standard container engine and an image repository sequentially on the central cloud node and the edge cloud node according to the hierarchical structure through the global cluster controller, and to deploy a custom container engine on the terminal cloud node, so as to provide download services for the images of the standard container engine and the custom container engine, as well as the images of the cluster components and the images of the terminal cluster working surface components through the image repository.

[0017] In some example embodiments of this disclosure, based on the foregoing scheme, the component management module further includes a service registry deployment unit, which is used to deploy a distributed service registry on the central cloud node to register the cluster control plane components of the edge cloud node to the distributed service registry.

[0018] In some example embodiments of this disclosure, based on the foregoing scheme, the component management module includes an association relationship establishment unit. The association relationship establishment unit is used to obtain the cluster control plane component information of the edge cloud node from the distributed service registry through the member cluster controller of the cluster control plane component in the central cloud node, and connect the cluster control plane component corresponding to the cluster control plane component information to the cluster control plane component in the central cloud node; based on the cluster control plane information, and the cluster control plane component corresponding to the cluster control plane information and the cluster control plane component in the central cloud node, establish an association relationship between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node, and uniformly manage the cluster control plane component based on the association relationship.

[0019] In some example embodiments of this disclosure, based on the foregoing scheme, the distributed container cluster management device further includes a component sharing module. The component sharing module is used to cache the configuration data of the cluster control plane component of the edge cloud node and send it to the terminal cloud node; establish an association relationship between the terminal cluster working plane component in the terminal cloud node and the cluster control plane component in the edge cloud node according to the configuration data; and configure the sharing of the cluster control plane component in the edge cloud node and the terminal cluster control plane component in the terminal cloud node based on the association relationship.

[0020] In some example embodiments of this disclosure, based on the foregoing scheme, the resource request response module includes a resource request scheduling unit. The resource request scheduling unit is used to monitor the status data of the cluster working plane in the central cloud node through the scheduler corresponding to the cluster control plane component in the central cloud node, and when the status data is detected to be busy, send a resource request to the scheduler corresponding to the cluster control plane component in the edge cloud node; when the scheduler corresponding to the cluster control plane component in the edge cloud node detects the resource request, it obtains the status data of the cluster working plane component of the edge cloud node, and determines the target working plane component to respond to the resource request based on the status data of the cluster working plane component of the edge cloud node and the status data of the terminal cluster working plane component.

[0021] In some example embodiments of this disclosure, based on the foregoing scheme, the resource request response module further includes a target workface component determination unit. The target workface component determination unit is used to allocate the resource request to the terminal cluster workface component through the scheduler in the cluster control plane of the edge cloud node when the status data of the cluster workface component of the edge cloud node is detected to be busy; and to listen to the status data of the terminal cluster workface component to determine the target workface component that satisfies the resource request from the cluster workface components based on the status data of the terminal cluster workface component.

[0022] According to a third aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the distributed container cluster management method described in any one of the preceding embodiments.

[0023] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the distributed container cluster management method according to any one of the preceding claims.

[0024] The technical solutions provided in this disclosure may have the following beneficial effects:

[0025] The distributed container cluster management method in the example embodiments of this disclosure deploys cluster components sequentially on the central cloud node and edge cloud node according to a hierarchical structure through a global cluster controller, and deploys terminal cluster working plane components on the terminal cloud node. The cluster components include cluster control plane components and cluster working plane components. Based on a service discovery mechanism, an association relationship is established between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node, and the cluster control plane components in the central cloud node and edge cloud node are managed uniformly based on this association relationship. When a resource request is received, a listening mechanism is used to obtain the status data of the cluster working plane components in the central cloud node and edge cloud node, as well as the terminal cluster working plane components. Based on the status data, a target working plane component is determined from the cluster working plane components in the central cloud node and edge cloud node, as well as the terminal cluster working plane components, to achieve a low-latency response to the resource request through the target working plane component. On the one hand, by establishing the association between the cluster control planes in the distributed container cluster and managing all cluster control planes in a unified manner based on this association, the management complexity of the cluster control planes in different cloud nodes is reduced, thereby improving the management efficiency of the distributed container cluster. On the other hand, by adopting a listening mechanism, the target working plane component can be determined from the central cloud node, edge cloud node, and terminal cloud node, so as to schedule the resources corresponding to the resource request through the target working plane component, realize cross-node scheduling of resources, and thus achieve low-latency response to resource requests.

[0026] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0028] Figure 1 The illustration shows a schematic diagram of a distributed container cluster management method flow according to some embodiments of the present disclosure;

[0029] Figure 2 The diagram illustrates a distributed container cluster architecture according to some embodiments of the present disclosure;

[0030] Figure 3The diagram illustrates a flow chart of a cluster control plane component management method according to some embodiments of the present disclosure;

[0031] Figure 4 The illustration shows a schematic diagram of a component sharing method flow according to some embodiments of the present disclosure;

[0032] Figure 5 The illustration shows a schematic diagram of a resource request and response method flow according to some embodiments of the present disclosure;

[0033] Figure 6 The illustration schematically shows a flow diagram of a method for determining target working components according to some embodiments of the present disclosure;

[0034] Figure 7 A schematic diagram of a distributed container cluster management apparatus according to some embodiments of the present disclosure is shown.

[0035] Figure 8 The schematic diagram illustrates the structural schematic of a computer system of an electronic device according to some embodiments of the present disclosure;

[0036] Figure 9 A schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure is shown.

[0037] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0038] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art.

[0039] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0040] Furthermore, the accompanying drawings are for illustrative purposes only and are not necessarily drawn to scale. The block diagrams shown in the drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0041] In this example embodiment, a distributed container cluster management method is first provided, which can be applied to server clusters. Figure 1 The illustration schematically depicts a distributed container cluster management method flow according to some embodiments of the present disclosure. (Reference) Figure 1 As shown, this distributed container cluster management method may include the following steps:

[0042] In step S110, cluster components are deployed sequentially on the central cloud node and edge cloud node according to the hierarchical structure through the global cluster controller, and terminal cluster working plane components are deployed on the terminal cloud node; the cluster components include cluster control plane components and cluster working plane components.

[0043] In step S120, based on the service discovery mechanism, the association between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node is established, and the cluster control plane component is managed uniformly based on the association.

[0044] In step S130, upon receiving a resource request, a listening mechanism is used to obtain the status data of the cluster working plane component and the terminal cluster working plane component, and a target working plane component is determined from the cluster working plane component and the terminal cluster working plane component based on the status data, so as to achieve a low-latency response to the resource request through the target working plane component.

[0045] According to the distributed container cluster management method in this example embodiment, on the one hand, by establishing the association relationship of the cluster control plane in the distributed container cluster and managing the cluster control plane in a unified manner based on the association relationship, the management complexity of the cluster control plane in different cloud nodes is reduced, thereby improving the management efficiency of the distributed container cluster; on the other hand, by adopting a listening mechanism, the target working plane component can be determined from the central cloud node, edge cloud node, and terminal cloud node, so as to schedule the resources corresponding to the resource request through the target working plane component, realize cross-node scheduling of resources, and thus achieve low-latency response to resource requests.

[0046] The distributed container cluster management method in this example embodiment will be further explained below.

[0047] In step S110, cluster components are deployed sequentially on the central cloud node and edge cloud node according to the hierarchical structure through the global cluster controller, and terminal cluster working plane components are deployed on the terminal cloud node; the cluster components include cluster control plane components and cluster working plane components.

[0048] In one example embodiment of this disclosure, the hierarchical structure can refer to the distributed deployment structure of a distributed container cluster. For example, the hierarchical structure can be a distributed deployment structure in a distributed container cluster with the global node as the root node, the central cloud node as the child node of the global node, the edge cloud node as the child node of the central cloud node, and the terminal cloud node as the child node of the edge cloud node. Of course, the hierarchical structure can also be other distributed deployment structures of the distributed container cluster, and this example embodiment does not make any special limitations on this.

[0049] A hierarchical structure can be used to deploy full-featured container cluster control plane components, container cluster working plane components, and standard container engines in the central cloud node through the global cluster controller in the global node, and lightweight container cluster control plane components, lightweight container cluster working plane components, and standard container engines in the edge cloud node. Furthermore, a custom container engine and terminal cluster working plane components can be deployed in the terminal cloud node, such as a fat terminal, and a lightweight container engine and terminal cluster working plane components can be deployed in a thin terminal. This hierarchical structure supports large-scale container resource scheduling.

[0050] In step S120, based on the service discovery mechanism, the association between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node is established, and the cluster control plane component is managed uniformly based on the association.

[0051] In one example embodiment of this disclosure, the service discovery mechanism can refer to a mechanism that exposes sub-cluster information to the upper-level cluster based on a distributed service registry. For example, the service discovery mechanism can be a mechanism that uses a distributed service registry to make the container cluster control plane of the edge cloud node a sub-control plane member of the container cluster control plane of the central cloud node. The service discovery mechanism can also be a mechanism that uses a distributed service registry to make the container cluster working plane of the terminal cloud node a self-control plane member of the container cluster control plane of the edge cloud node. Of course, the service discovery mechanism can also be a mechanism that uses a distributed service registry to expose other sub-cluster information to other upper-level clusters. This example embodiment does not make any special limitations on this.

[0052] By establishing associations between cluster control plane components in the central cloud node and those in the edge cloud nodes, all cluster control plane components in both nodes can be managed uniformly based on these associations. For example, a distributed service registry can be deployed in the central cloud node, allowing the cluster control plane components in the edge cloud nodes to register with this registry. This enables the central cloud node to retrieve information about all cluster control plane components in the edge cloud nodes from the registry, and to designate the cluster control plane components corresponding to those in the edge cloud nodes as sub-control plane components of the central cloud node's cluster control plane components. This achieves unified management of all cluster control planes across both nodes, improving the convenience of managing cross-node cluster control plane components and consequently increasing the management efficiency of the distributed container cluster.

[0053] Preferably, while establishing the association between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node, and uniformly managing all cluster control plane components in the central cloud node and edge cloud node based on this association, a central cloud workplane management node can be deployed in the central cloud node for centralized management of all cluster workplane components in the central cloud node, and an edge cloud workplane management node can be deployed in the edge cloud node for centralized management of all cluster workplane components in the edge cloud node. The terminal cluster workplane components in the terminal cloud node are also included in the edge cloud workplane management node. This achieves centralized management of all cluster workplane components in the central cloud node and edge cloud node, as well as the terminal cluster workplane components in the terminal cloud node, reducing the management complexity of the distributed container cluster and thus improving the convenience and effectiveness of distributed container cluster management.

[0054] In step S130, upon receiving a resource request, a listening mechanism is used to obtain the status data of the cluster working plane component and the terminal cluster working plane component, and a target working plane component is determined from the cluster working plane component and the terminal cluster working plane component based on the status data, so as to achieve a low-latency response to the resource request through the target working plane component.

[0055] In one example embodiment of this disclosure, the listening mechanism can refer to a mechanism in which the scheduler in the cluster control plane listens to whether the upper-level cluster sends a resource request. For example, the listening mechanism can be a mechanism in which the scheduler in the cluster control plane component of the edge cloud node listens to whether the central cloud node sends a resource request. The listening mechanism can also be a mechanism in which the resource request is sent to the terminal cluster working plane in the terminal cloud node when the scheduler in the cluster control plane component of the edge cloud node cannot allocate the resource request to the cluster working plane component in the edge cloud node. Of course, the listening mechanism can also be a mechanism in which the scheduler in the cluster control plane listens to whether other upper-level clusters send resource requests. This example embodiment does not make any special limitation on this.

[0056] Status data can refer to status indicator data used to measure whether cluster working plane components or terminal cluster working plane components can meet resource requests. For example, status data can be indicator data used to measure whether cluster working plane components in central cloud nodes or edge cloud nodes are in a busy state. Status data can also be indicator data used to measure whether terminal cluster working plane components in terminal cloud nodes are in a busy state. Of course, status data can also be other status indicator data used to measure whether cluster working plane components or terminal cluster working plane components can meet resource requests. This example does not make any special limitations on this.

[0057] The status data of the cluster workface components and the terminal cluster workface components can be obtained through a listening mechanism. Based on the status data, the target workface component that can satisfy the resource request can be determined from the cluster workface components and the terminal cluster workface components, so as to achieve a low-latency response to the resource request through the target workface component. For example, resource requests can be sent from the scheduler of the cluster control plane component in the central cloud node to the cluster workplane component in the central cloud node. When all cluster workplane components in the central cloud node are busy, the resource request is scheduled to the scheduler of the cluster control plane component in the edge cloud node. When the scheduler of the cluster control plane component in the edge cloud node hears the resource request sent by the scheduler of the cluster control plane component in the central cloud node, it sends the resource request to its local cluster workplane component (the cluster workplane component in the edge cloud node). If it is detected that all cluster workplane components in the edge cloud node are busy, the resource request is then sent to the terminal cluster workplane component in the terminal cloud node. The target workplane component in the terminal cluster workplane component can determine the target workplane component that can satisfy the resource request, and the resource is scheduled through the target workplane component. This achieves a low-latency response to the resource request, improves the satisfaction of the user's or enterprise's resource needs, and thus improves the user or enterprise's user experience.

[0058] In one example embodiment of this disclosure, a standard container engine and an image repository can be deployed sequentially on the central cloud node and the edge cloud node according to a hierarchical structure through a global cluster controller, and a custom container engine can be deployed on the terminal cloud node, so as to provide download services for standard container engine images and custom container engine images, as well as cluster component images and terminal cluster workface component images through the image repository.

[0059] Specifically, an image repository can be deployed on both the central cloud node and the edge cloud node. The image repository on the central cloud node can synchronize component container image files from the global image repository on the global node, and then deploy the component container cluster on the central cloud node according to these component container image files through the global cluster controller. Similarly, the image repository on the edge cloud node can synchronize component container image files from the image repository on the central cloud node, and then deploy component containers on the edge node based on these edge cloud component container image files.

[0060] By deploying image repositories on both central and edge cloud nodes, central cloud nodes can obtain component container image files from the global image repository, while edge cloud nodes can obtain component container image files from the image repository within the central cloud node. When building a distributed container cluster, component containers can be deployed on the central cloud node based on the image files in its image repository, and simultaneously, they can be deployed on the edge cloud nodes based on the image files in their image repositories. This achieves localized downloading of component containers, reduces installation latency, and improves the efficiency of building the distributed container cluster.

[0061] Figure 2 The schematic diagram illustrates a distributed container cluster architecture according to some embodiments of the present disclosure. The distributed container cluster architecture 200 mainly includes a global node 210, a central cloud node 220, an edge cloud node 230, and a terminal cloud node 240.

[0062] The global node 210 includes a global cluster controller 211 and a global image repository 212. The global cluster controller 211 is primarily used to deploy cluster control plane components and cluster working plane components, as well as a standard container engine, on the central cloud node 220 and edge cloud nodes 230, and to deploy terminal cluster working plane components and a custom container engine on the terminal cloud node 240. The global image repository 212 is primarily used to provide component container image files to the central cloud node, edge cloud node, and terminal cloud node, providing a localized download service for component container images to these nodes. The central cloud node 220 includes cluster control plane components and cluster working plane components, as well as an image repository and a distributed service discovery mechanism. The edge cloud node 230 includes cluster control plane components and cluster working plane components, as well as an image repository and a distributed service discovery mechanism.

[0063] The cluster control plane components include the APIServer (resource configuration control service for application access) bus, scheduler, controller, member cluster controllers, and database. The scheduler, controller, member cluster controllers, and database interface with the APIServer bus, which in turn interacts with the cluster workplane. The member cluster controller is responsible for managing the lifecycle of lower-level sub-clusters connecting to the upper-level cluster, including cluster deployment, upgrades, and scaling. The scheduler allocates resource requests to its own cluster workplane nodes or lower-level cluster schedulers. Simultaneously, lower-level schedulers listen for resource requests allocated to them by the upper-level scheduler, prioritizing resources at the same level. The cluster workplane components primarily maintain the container environment for running applications, including agents and container engines. Agents interact with the APIServer bus in the control plane, and the container engine provides the application Pod (data structure) container environment.

[0064] Image repositories are primarily responsible for the distributed storage of cluster component images in a central cloud or edge cloud, providing a localized download service for each component image in the distributed container cluster. Specifically, the central image repository synchronizes local component images from the global image repository, while edge image repositories synchronize local images from the central image repository.

[0065] Distributed service discovery is mainly used to register information of lower-level sub-clusters with the distributed service registry. The member cluster controllers of the upper-level cluster obtain information of lower-level clusters from the distributed service registry and connect the lower-level clusters to the control plane of the upper-level cluster.

[0066] In one example embodiment of this disclosure, a distributed service registry can be deployed on the central cloud node to register cluster control plane components in the edge cloud nodes to the distributed service registry on the central cloud node.

[0067] In this context, the distributed service registry can refer to a service center that provides cluster information registration. For example, a distributed service registry can be a service center that provides registration of lower-level sub-cluster information to the upper-level cluster. Of course, a distributed service registry can also be a center that provides registration services for other cluster information. This example does not impose any special limitations on this.

[0068] By deploying a distributed service registry at the central cloud node, cluster control plane component information from edge cloud nodes can be registered with the distributed service registry at the central cloud node. This allows the central cloud node to obtain the cluster control plane components from the edge cloud nodes from the distributed service registry. Based on the service discovery mechanism, an association relationship can be established between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud nodes. Based on this association relationship, unified management of all cluster control plane components in the central cloud node and edge cloud nodes can be achieved, reducing the management complexity of cross-node container clusters in distributed container clusters and thus improving the management efficiency of distributed container clusters.

[0069] Figure 3 The illustration schematically depicts a cluster control plane component management method flow according to some embodiments of the present disclosure. (Reference) Figure 3 As shown, the cluster control plane component management method may include the following steps:

[0070] In step S310, the cluster control plane component information in the edge cloud node is obtained from the distributed service registry through the member cluster controller of the cluster control plane component in the central cloud node, and the cluster control plane component corresponding to the cluster control plane component information is connected to the cluster control plane component in the central cloud node.

[0071] In step S320, based on the cluster control plane information, the cluster control plane components corresponding to the cluster control plane information, and the cluster control plane components in the central cloud node, an association relationship is established between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node, and the cluster control plane components are managed uniformly based on the association relationship.

[0072] The cluster control plane component information can refer to the attribute information of the cluster control plane component in the edge cloud node. For example, the cluster control plane component information can be the protocol parameter information of the cluster control plane component in the edge cloud node, the data transmission rule information of the cluster control plane component in the edge cloud node, or the identification information of the cluster control plane component in the edge cloud node. Of course, the cluster control plane component information can also be other attribute information of the cluster control plane component in the edge cloud node. This example does not impose any special limitations on this.

[0073] By establishing a distributed service registry at the central cloud node and registering all cluster control plane component information from the edge cloud nodes to this registry, the cluster control plane components in the edge cloud nodes become sub-members of the cluster control plane components in the central cloud node. Member cluster controllers in the cluster control plane components of the central cloud node can obtain the cluster control plane component information from the distributed service registry. Based on the cluster control plane component information in the edge cloud nodes, the corresponding cluster control plane components, and the cluster control plane components in the central cloud node, an association relationship is established between all cluster control plane components in the central cloud node and the edge cloud nodes. This association relationship enables unified management of all cluster control plane components in the central cloud node and the edge cloud nodes, reducing the management complexity and cost of cross-node cluster control plane components and thus improving the efficiency of managing distributed container clusters.

[0074] Figure 4 The illustration schematically depicts a component sharing method flow according to some embodiments of the present disclosure. Reference Figure 4 As shown, the component sharing method may include the following steps:

[0075] In step S410, the configuration data of the cluster control plane component in the edge cloud node is cached and sent to the terminal cloud node;

[0076] In step S420, the terminal cluster working plane component in the terminal cloud node establishes an association with the cluster control plane component in the edge cloud node according to the configuration data.

[0077] In step S430, the sharing of the cluster control plane component in the edge cloud node and the terminal cluster control plane component in the terminal cloud node is configured based on the association relationship.

[0078] Since the connection between the terminal cluster working plane component in the terminal cloud node and the cluster control plane in the edge cloud node is unstable, a proxy component that interacts with the terminal cluster working plane component can report the status data of the terminal cluster working plane to the cluster control plane component in the edge cloud node, and cache the configuration data of the cluster control plane component in the edge cloud node and send it to the terminal cloud node. This ensures a stable connection between the terminal cluster working plane component in the terminal cloud node and the cluster control plane component in the edge cloud node through the status data of the cluster working plane component in the terminal cloud node and the configuration data of the cluster control plane component in the edge cloud node.

[0079] By caching the configuration data of the cluster control plane component in the edge cloud node and sending it to the terminal cloud node, and reporting the status data of the terminal cluster workface in the terminal cloud node to the edge cloud node, a stable connection between the cluster control plane component in the edge cloud node and the cluster workface in the terminal cloud node can be ensured. This allows for the configuration of shared access between the cluster control plane components in the edge cloud node and the terminal cluster control plane component in the terminal cloud node. In other words, the terminal cluster workface component in the terminal cloud node can establish a connection with the cluster control plane component in the edge cloud node, sharing the edge cloud node's cluster control plane component with the terminal cloud node's terminal cluster control plane component. Simultaneously, the terminal cluster workface in the terminal cloud node can be used as a partial cluster workface component in the edge cloud node. Furthermore, the scheduler of the cluster control plane component in the edge cloud node can deploy application services for the terminal cluster workface component in the terminal cloud node, improving the interactivity between the terminal cloud node and the edge cloud node. This enables cross-node scheduling of resource requests in the distributed container cluster, improving the efficiency of the distributed container cluster in responding to resource requests, and meeting user or enterprise resource requests in real time, thus enhancing the user or enterprise experience.

[0080] Figure 5 A schematic diagram illustrating a resource request-response method flow according to some embodiments of the present disclosure is provided. References Figure 5 As shown, the resource request-response method may include the following steps:

[0081] In step S510, the scheduler corresponding to the cluster control plane component in the central cloud node monitors the status data of the cluster working plane in the central cloud node, and when the status data is detected to be busy, a resource request is sent to the scheduler corresponding to the cluster control plane component in the edge cloud node.

[0082] In step S520, when the scheduler corresponding to the cluster control plane component in the edge cloud node listens to the resource request, it obtains the status data of the cluster working plane component of the edge cloud node, and determines the target working plane component to respond to the resource request based on the status data of the cluster working plane component in the edge cloud node and the status data of the terminal cluster working plane component.

[0083] In this process, resource requests can be allocated to the local cluster working plane node through the scheduler of the cluster control plane component in each cloud node from top to bottom in the hierarchical structure. If all cluster working plane components in the local cluster working plane node are busy, the resource request can be scheduled to the scheduler of the cluster control plane component in the lower-level cloud node through the scheduler in the local cluster control plane component, and the scheduler of the cluster control plane component in the lower-level cloud node will further allocate the resource request.

[0084] Resource requests can be prioritized for allocation to cluster workplane nodes within the central cloud node via the scheduler corresponding to the cluster control plane component. The scheduler can also monitor the status data of these workplane components. If an idle workplane component exists within the central cloud node, the resource request can be assigned to that component, which will then schedule the resource data to respond to the request. Conversely, if all cluster workplane components in the central cloud node are busy, the resource request can be allocated to the cluster control plane component in the edge cloud node, where the scheduler will allocate the resource request to the corresponding edge cloud node. The system monitors the status data of cluster workface components in edge cloud nodes. If an idle cluster workface component exists in an edge cloud node, it will schedule resource data to respond to the resource request. If all cluster workface components in an edge cloud node are busy, the resource request can be scheduled to the terminal cluster workface component in the terminal cloud node. The system will then determine the target workface component that can satisfy the resource request, thus enabling cross-node scheduling of resource requests in the distributed container cluster. This achieves low-latency response to resource requests and improves the user or enterprise experience.

[0085] Figure 6 A schematic diagram illustrating a method flow for determining target working components according to some embodiments of the present disclosure is provided. References Figure 6 As shown, the method for determining the target working component may include the following steps:

[0086] In step S610, when the status data of the cluster working plane component of the edge cloud node is detected to be busy, the resource request is allocated to the terminal cluster working plane component through the scheduler of the cluster control plane in the edge cloud node.

[0087] In step S620, the status data of the terminal cluster working surface component is monitored to determine the target working surface component that satisfies the resource request from the cluster working surface component based on the status data of the terminal cluster working surface component.

[0088] The target working component can refer to a working component in a distributed container cluster that satisfies the resource request. For example, the target working component can be a cluster control plane component in the central cloud node of the distributed container cluster that satisfies the resource request, a cluster control plane component in the edge cloud node of the distributed container cluster that satisfies the resource request, or a terminal cluster control plane component in the terminal cloud node of the distributed container cluster that satisfies the resource request. Of course, the target working component can also be other working components in the distributed container cluster that satisfy the resource request. This example does not impose any special limitations on this.

[0089] By establishing a connection between the cluster control plane component in the edge cloud node and the terminal cluster working plane component in the terminal cloud node, the scheduler corresponding to the cluster control plane component in the edge cloud node allocates resource requests to the cluster working plane component in the edge cloud node. When all the cluster working plane components in the edge cloud node are busy, the resource request can be scheduled to the terminal cluster working plane component in the terminal cloud node. The scheduler also listens to the status data of the terminal cluster working plane component and determines the target working plane component that can satisfy the resource request based on the status data. The resource data is then scheduled through the target working plane component to achieve a low-latency response to the resource request.

[0090] It should be noted that although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0091] Furthermore, this example embodiment also provides a distributed container cluster management device. (Refer to...) Figure 7As shown, the distributed container cluster management device 700 includes: a component deployment module 710, a component management module 720, and a resource request response module 730. Specifically: the component deployment module 710 is used to deploy cluster components sequentially on the central cloud node and edge cloud node according to a hierarchical structure through a global cluster controller, and to deploy terminal cluster workplane components on the terminal cloud node; the cluster components include cluster control plane components and cluster workplane components; the component management module 720 is used to establish the association relationship between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node based on a service discovery mechanism, and to uniformly manage the cluster control plane components based on the association relationship; the resource request response module 730 is used to, upon receiving a resource request, use a listening mechanism to obtain the status data of the cluster workplane components and the terminal cluster workplane components, and determine the target workplane component from the cluster workplane components and the terminal cluster workplane components based on the status data, so as to schedule business data matching the resource request through the target workplane component, thereby realizing cross-node scheduling of business data.

[0092] In some example embodiments of this disclosure, based on the foregoing scheme, the component deployment module 710 further includes a container engine deployment unit. The container engine deployment unit is used to deploy a standard container engine and an image repository sequentially on the central cloud node and the edge cloud node according to the hierarchical structure through the global cluster controller, and to deploy a custom container engine on the terminal cloud node, so as to provide download services for the images of the standard container engine and the custom container engine, as well as the images of the cluster components and the images of the terminal cluster working surface components through the image repository.

[0093] In some example embodiments of this disclosure, based on the foregoing scheme, the component management module 720 further includes a service registry deployment unit, which is used to deploy a distributed service registry on the central cloud node to register the cluster control plane components of the edge cloud node to the distributed service registry.

[0094] In some example embodiments of this disclosure, based on the foregoing scheme, the component management module 720 includes an association relationship establishment unit. The association relationship establishment unit is used to obtain the cluster control plane component information of the edge cloud node from the distributed service registry through the member cluster controller of the cluster control plane component in the central cloud node, and connect the cluster control plane component corresponding to the cluster control plane component information to the cluster control plane component in the central cloud node; based on the cluster control plane information, and the cluster control plane component corresponding to the cluster control plane information and the cluster control plane component in the central cloud node, establish an association relationship between the cluster control plane component in the central cloud node and the cluster control plane component in the edge cloud node, and uniformly manage the cluster control plane component based on the association relationship.

[0095] In some example embodiments of this disclosure, based on the foregoing scheme, the distributed container cluster management device 700 further includes a component sharing module. The component sharing module is used to cache the configuration data of the cluster control plane component of the edge cloud node and send it to the terminal cloud node; establish an association relationship between the terminal cluster working plane component in the terminal cloud node and the cluster control plane component in the edge cloud node according to the configuration data; and configure the sharing of the cluster control plane component in the edge cloud node and the terminal cluster control plane component in the terminal cloud node based on the association relationship.

[0096] In some example embodiments of this disclosure, based on the foregoing scheme, the resource request response module 730 includes a resource request scheduling unit. The resource request scheduling unit is used to monitor the status data of the cluster working plane in the central cloud node through the scheduler corresponding to the cluster control plane component in the central cloud node, and when the status data is detected to be busy, send a resource request to the scheduler corresponding to the cluster control plane component in the edge cloud node; when the scheduler in the edge cloud node hears the resource request, it obtains the status data of the cluster working plane component in the edge cloud node, and determines the target working plane component to respond to the resource request based on the status data of the cluster working plane component in the edge cloud node and the status data of the terminal cluster working plane component.

[0097] In some example embodiments of this disclosure, based on the foregoing scheme, the resource request response module 730 further includes a target workface component determination unit. The target workface component determination unit is used to allocate the resource request to the terminal cluster workface component through the scheduler of the cluster control plane in the edge cloud node when the status data of the cluster workface component in the edge cloud node is detected to be busy; and to listen to the status data of the terminal cluster workface component to determine the target workface component that satisfies the resource request from the cluster workface component based on the status data of the terminal cluster workface component.

[0098] The specific details of each module of the distributed container cluster management device mentioned above have been described in detail in the corresponding distributed container cluster management methods, so they will not be repeated here.

[0099] It should be noted that although several modules or units of the distributed container cluster management device have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0100] Furthermore, in an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described distributed container cluster management method is also provided.

[0101] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be embodied in the following forms: a completely hardware embodiment, a completely software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0102] The following reference Figure 8 To describe an electronic device 800 according to such an embodiment of the present disclosure. Figure 8 The electronic device 800 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0103] like Figure 8 As shown, the electronic device 800 is presented in the form of a general-purpose computing device. The components of the electronic device 800 may include, but are not limited to: at least one processing unit 810, at least one storage unit 820, a bus 830 connecting different system components (including storage unit 820 and processing unit 810), and a display unit 840.

[0104] The storage unit stores program code that can be executed by the processing unit 810, causing the processing unit 810 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 810 can perform actions such as... Figure 1 In step S110, the global cluster controller deploys cluster components sequentially on the central cloud node and edge cloud node according to the hierarchical structure, and deploys terminal cluster working plane components on the terminal cloud node; the cluster components include cluster control plane components and cluster working plane components; in step S120, based on the service discovery mechanism, the association relationship between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node is established, and the cluster control plane components are uniformly managed based on the association relationship; in step S130, when a resource request is received, a listening mechanism is used to obtain the status data of the cluster working plane components and the terminal cluster working plane components, and the target working plane component is determined from the cluster working plane components and the terminal cluster working plane components according to the status data, so as to achieve a low-latency response to the resource request through the target working plane component.

[0105] Storage unit 820 may include readable media in the form of volatile storage units, such as random access memory (RAM) 821 and / or cache memory 822, and may further include read-only memory (ROM) 823.

[0106] The storage unit 820 may also include a program / utility 824 having a set (at least one) of program modules 825, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0107] Bus 830 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0108] Electronic device 800 can also communicate with one or more external devices 870 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 800, and / or with any device that enables electronic device 800 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 850. Furthermore, electronic device 800 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0109] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0110] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of this disclosure may also be implemented as a program product including program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0111] refer to Figure 9 As shown, a program product 900 for implementing the above-described distributed container cluster management method according to embodiments of the present disclosure is described. This product may be a portable compact disk read-only memory (CD-ROM) and includes program code, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0112] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0113] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0114] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0115] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0116] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0117] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0118] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0119] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A distributed container cluster management method, characterized in that, include: Cluster components are deployed sequentially on the central cloud node and edge cloud node according to a hierarchical structure through a global cluster controller, and terminal cluster working plane components are deployed on the terminal cloud node; the cluster components include cluster control plane components and cluster working plane components. Based on the service discovery mechanism, the association between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node is established, and the cluster control plane components are managed uniformly based on the association. Upon receiving a resource request, a listening mechanism is used to obtain the status data of the cluster working plane component and the terminal cluster working plane component, and a target working plane component is determined from the cluster working plane component and the terminal cluster working plane component based on the status data, so as to achieve a low-latency response to the resource request through the target working plane component.

2. The distributed container cluster management method according to claim 1, characterized in that, The method further includes: The global cluster controller deploys standard container engines and image repositories sequentially on the central cloud node and the edge cloud node according to the hierarchical structure, and deploys custom container engines on the terminal cloud node, so as to provide download services for images of the standard container engine, the custom container engine, the cluster components, and the terminal cluster workface components through the image repository.

3. The distributed container cluster management method according to claim 1, characterized in that, The method further includes: A distributed service registry is deployed on the central cloud node to register the cluster control plane components of the edge cloud nodes to the distributed service registry.

4. The distributed container cluster management method according to claim 1, characterized in that, The process of establishing the association between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud nodes, and managing the cluster control plane components uniformly based on the association, includes: The member cluster controller of the cluster control plane component in the central cloud node obtains the cluster control plane component information in the edge cloud node from the distributed service registry, and connects the cluster control plane component corresponding to the cluster control plane component information to the cluster control plane component in the central cloud node. Based on the cluster control plane information and the cluster control plane components corresponding to the cluster control plane information, as well as the cluster control plane components of the central cloud node, an association relationship is established between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node, and the cluster control plane components are managed uniformly based on the association relationship.

5. The distributed container cluster management method according to claim 1, characterized in that, The method further includes: The configuration of the cluster control plane component in the edge cloud node is cached and sent to the terminal cloud node; The terminal cluster working plane component in the terminal cloud node establishes an association with the cluster control plane component in the edge cloud node according to the configuration data. Based on the aforementioned association, the cluster control plane component in the edge cloud node and the terminal cluster control plane component in the terminal cloud node are configured to share the same configuration.

6. The distributed container cluster management method according to claim 1, characterized in that, The step of acquiring status data of the cluster working plane component and the terminal cluster working plane component using a listening mechanism, and determining the target working plane component from the cluster working plane component and the terminal cluster working plane based on the status data, includes: The scheduler corresponding to the cluster control plane component in the central cloud node monitors the status data of the cluster working plane in the central cloud node, and sends a resource request to the scheduler corresponding to the cluster control plane component in the edge cloud node when the status data is detected to be busy. When the scheduler corresponding to the cluster control plane component in the edge cloud node detects the resource request, it obtains the status data of the cluster working plane component of the edge cloud node, and determines the target working plane component to respond to the resource request based on the status data of the cluster working plane component of the edge cloud node and the status data of the terminal cluster working plane component.

7. The distributed container cluster management method according to claim 6, characterized in that, The determination of the target working plane component responding to the resource request based on the status data of the cluster working plane component of the edge cloud node and the status data of the terminal cluster working plane component includes: When the status data of the cluster working plane component in the edge cloud node is detected to be busy, the resource request is allocated to the terminal cluster working plane component by the scheduler in the cluster control plane of the edge cloud node. Monitor the status data of the terminal cluster workface components to determine the target workface component that satisfies the resource request from the terminal cluster workface components based on the status data of the terminal cluster workface components.

8. A distributed container cluster management device, characterized in that, include: The component deployment module is used to deploy cluster components sequentially on the central cloud node and edge cloud node according to the hierarchical structure through the global cluster controller, and to deploy terminal cluster working plane components on the terminal cloud node; the cluster components include cluster control plane components and cluster working plane components. The component management module is used to establish the association between the cluster control plane components in the central cloud node and the cluster control plane components in the edge cloud node based on the service discovery mechanism, and to manage the cluster control plane components in a unified manner based on the association. The resource request response module is used to obtain the status data of the cluster working plane component and the terminal cluster working plane component by means of a listening mechanism when a resource request is received, and to determine the target working plane component from the cluster working plane component and the terminal cluster working plane based on the status data, so as to schedule the business data matching the resource request through the target working plane component, thereby realizing cross-node scheduling of business data.

9. An electronic device, comprising: processor; as well as A memory storing computer-readable instructions that, when executed by the processor, implement the distributed container cluster management method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, the computer program implementing the distributed container cluster management method as described in any one of claims 1 to 7 when executed by a processor.

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