Information processing method, first node, first cluster, storage medium and product

Abstract

The invention discloses an information processing method which comprises the following steps: in a first node, deploying a core component required by operation of a first cluster in the form of a containerized workload hosted in the first cluster. The invention further discloses a first node, a first cluster, a computer readable storage medium and a computer program product.

Description

Technical Field

[0001] The present application relates to, but is not limited to, the field of communications, and in particular to an information processing method, a first node, a first cluster, a computer-readable storage medium, and a computer program product. Background Art

[0002] The cloud-native platform Kubernetes (K8s for short, with 8 replacing the eight characters in the middle of the name "ubernete") is an open source system for automatically deploying, scaling, and managing containerized applications. The components required for K8s to run are collectively referred to as the control plane, and the containerized workloads hosted in K8s are called the data plane. The main functions of K8s can be summarized as follows: When the control plane is working normally, K8s will automatically ensure that all containerized workloads on the data plane are deployed according to the expected specifications and work normally based on the configuration information of the data plane.

[0003] In view of the above background, the related technologies often adopt the control plane multi-copy deployment solution or the external control cluster solution to ensure the normal operation of the control plane. However, in the above solutions, if a node fails, professional operation and maintenance personnel need to intervene to handle it. Therefore, the solutions provided in the related technologies to ensure the normal operation of the control plane at least have the problem of high complexity. Summary of the invention

[0004] The present application provides an information processing method, a first node, a first cluster, a computer-readable storage medium, and a computer program product.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides an information processing method, which is applied to a first node, and the method includes:

[0007] In the first node of the first cluster, core components required for the operation of the first cluster are deployed in the form of containerized workloads hosted in the first cluster.

[0008] In a second aspect, an embodiment of the present application provides an information processing method, which is applied to a first cluster, and the method includes:

[0009] Building a first node of the first cluster, and deploying, in the first node, core components required for running the first cluster in the form of containerized workloads hosted in the first cluster;

[0010] Adding N second nodes to the first cluster; where N is a positive integer;

[0011] Reschedule the core components deployed in the first node as containerized workloads hosted in the first cluster so that the core components deployed in the first cluster as containerized workloads hosted in the first cluster are distributed to the second node.

[0012] In a third aspect, an embodiment of the present application provides a first node, wherein the first node includes:

[0013] A processing module is used to deploy core components required for the operation of the first cluster in the form of containerized workloads hosted in the first cluster.

[0014] In a fourth aspect, an embodiment of the present application provides a first node, the first node comprising:

[0015] A memory for storing executable instructions;

[0016] The processor is used to implement the above-mentioned information processing method when executing the executable instructions stored in the memory.

[0017] In a fifth aspect, an embodiment of the present application provides a first cluster, wherein the first cluster includes a first node and N second nodes, where N is a positive integer, and the first node and the N second nodes cooperate to execute the above-mentioned information processing method.

[0018] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium on which one or more computer programs are stored. The one or more programs can be executed by one or more processors to implement the steps of the above-mentioned information processing method.

[0019] In the seventh aspect, an embodiment of the present application provides a computer program product, including a computer program, which implements the steps of the above-mentioned information processing method when executed by a processor.

[0020] This application proposes a new way to deploy cluster core components, that is, to deploy cluster core components in the form of cluster-native workloads, so that when a failure occurs, new available core components can be pulled up through the high availability characteristics of cluster-native workloads, thereby automatically ensuring the normal operation of the cluster control plane components with high reliability. When there is a need to expand / shrink the cluster, it is only necessary to modify the number of replicas of the workload, which is simpler than the expansion / shrinking solutions in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Schematic diagram of the information processing method provided in the embodiment of the present application Figure 1 ;

[0022] Figure 2 Schematic diagram of the information processing method provided in the embodiment of the present application Figure 2 ;

[0023] Figure 3 A flow chart of the K8s cluster deployment solution provided for the embodiment of the present application;

[0024] Figure 4 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 1 ;

[0025] Figure 5 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 2 ;

[0026] Figure 6 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 3 ;

[0027] Figure 7 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 4 ;

[0028] Figure 8 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 5 ;

[0029] Fig. 9 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 6 ;

[0030] Fig.10 Schematic diagram of the architecture of the K8s master node provided in the embodiment of the present application Figure 7 ;

[0031] Fig.11 A schematic block diagram of a first node provided in an embodiment of the present application;

[0032] Fig.12 A schematic block diagram of a first cluster provided in an embodiment of the present application;

[0033] Fig.13 A schematic structural diagram of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Here, the "another" or "yet another" mentioned in the description of the drawings does not refer to a specific embodiment, and the various embodiments of the present application can be combined with each other without conflict.

[0035] It should be understood that the "embodiments of the present application" or "the aforementioned embodiments" mentioned throughout the specification mean that specific features, structures or characteristics related to the embodiments are included in at least one embodiment of the present application. Therefore, "in the embodiments of the present application" or "in the aforementioned embodiments" appearing throughout the specification may not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. In the various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned sequence numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments.

[0036] Before explaining this application, here is an explanation of the solution for ensuring the normal operation of the control plane of K8s in the related art:

[0037] The multi-copy deployment of the control plane is a high-availability solution for the control plane recommended by the K8s project. All components of the K8s control plane are directly deployed on different hosts, which are called master nodes. In terms of design, the components of the control plane support such deployment to achieve high availability. Therefore, as long as the number of failures in these master nodes is less than half of the total number, the normal operation of the entire control plane will not be affected. However, for the multi-copy control plane solution, after a master node fails, professional operation and maintenance personnel must intervene to handle it in order to restore it to normal operation. In most scenarios, it cannot be handled automatically by the machine. Furthermore, if the failure is a hardware problem, the recovery process will also involve backup machine application, component installation, cluster adjustment, etc. Under the process constraints of enterprise IT management, it may take a very long time to complete various approvals; if the failure is not handled for a long time, after multiple failures accumulate, the status of the master node in the K8s cluster may no longer meet the condition of "the number of failures is less than half of the total number", causing the control plane components of the cluster to fail to work normally.

[0038] An external control cluster is another set of K8s (called a control cluster) deployed. The control plane of the control cluster manages the components of the control plane of the current cluster, thereby ensuring the normal operation of the components of the control plane of the current cluster. However, solutions for external control clusters are often seen in cloud computing business scenarios that serve multiple tenants. The cloud computing service provider arranges professionals to maintain the control cluster. Tenants do not need to worry about its availability, but only need to focus on their own business scenarios, deploying and scheduling data plane workloads. However, from the perspective of tenants, for privacy, convenience and cost, many are unwilling to choose this solution, which completely entrusts the cluster control plane to the operator for hosting; further, in the scenario of self-built K8s clusters, this solution cannot be used at all.

[0039] Figure 1 A flowchart of an information processing method provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the method is applied to a first node, in which all components of a control plane of a first cluster are deployed, and the method includes:

[0040] Step 101: In a first node of a first cluster, core components required for running the first cluster are deployed in the form of containerized workloads hosted in the first cluster.

[0041] In the embodiment of the present application, the first node is a node configured to deploy all components of the control plane of the first cluster, also known as a master node.

[0042] In some embodiments, the first cluster is a cluster implemented using K8s, which can also be called a K8S cluster. A K8S cluster includes several physical machines or virtual machines, and a physical machine or a virtual machine can be regarded as a node. K8S creates containers in the cluster with pod as the smallest unit. A pod can include one or more containers, and these one or more containers implement corresponding services.

[0043] In some embodiments, core components include but are not limited to running an application programming interface server (apiserver), a scheduler, a controller, and storage (etcd).

[0044] In an embodiment of the present application, the containerized workload hosted in the first cluster relies on the container network for connection and interaction, and will automatically restart when the container exits abnormally or the load fails. In this way, the containerized workload has high availability; then, the core components are deployed in the form of containerized workloads hosted in the first cluster. Through the high availability characteristics of the containerized workload, new available core components can be pulled up, thereby automatically ensuring the normal operation of the cluster control plane components.

[0045] An embodiment of the present application provides an information processing method, which includes: in a first node, deploying the core components required for the operation of the first cluster in the form of a containerized workload hosted in the first cluster. In other words, the present application proposes a new way to deploy the core components of the cluster, that is, to deploy the core components of the cluster in the form of a cluster-native workload, so that when a failure occurs, new available core components can be pulled up through the high availability characteristics of the cluster-native workload, thereby automatically ensuring the normal operation of the control plane components of the cluster with high reliability. When there is a need to expand / shrink the cluster, it is only necessary to modify the number of replicas of the workload parameter, which is simpler than the expansion / shrinkage solutions in related technologies.

[0046] It should be noted that in the solution proposed in this application, the core components may be distributed on any node. Compared with the technical solutions in the related art, there is no need to perform special configuration for the cluster master node alone.

[0047] In some embodiments, step 101, in a first node of a first cluster, deploying core components required for the operation of the first cluster in the form of containerized workloads hosted in the first cluster, can be implemented by the following steps:

[0048] Step A1: directly deploy a first component in a first node; wherein the first component includes a core component.

[0049] It should be noted that the first component includes a core component and a non-core component; wherein the non-core component is run on the first node to maintain the running container and provide a running environment.

[0050] Step A2: deploy the second component on the data plane of the first cluster in a stateless application deployment or a stateful application deployment or in a manner that ensures that all nodes run the same container; wherein the second component includes a core component.

[0051] In some embodiments, in the data plane, M first data plane workloads are deployed in a stateful application deployment (StatefulSet); M is a positive integer; the M first data plane workloads are interconnected through a headless service;

[0052] Here, M may be preset or determined based on the actual operating environment, and this application does not make any specific limitation on this. For example, M may be set to 3.

[0053] In an embodiment of the present application, deploying M first data plane workloads in a StatefulSet manner can be understood as using a StatefulSet workload controller to manage the M first data plane workloads.

[0054] In some embodiments, the first data plane workload is an etcd component deployed in the cluster data plane.

[0055] On the data plane, the second data plane workload, the third data plane workload and the fourth data plane workload are deployed in a stateless application deployment (Deployment) manner.

[0056] In an embodiment of the present application, deploying the second data plane workload, the third data plane workload and the fourth data plane workload in a Deployment manner can be understood as using a Deployment workload controller to manage the second data plane workload, the third data plane workload and the fourth data plane workload.

[0057] In some embodiments, the second data plane workload is the apiserver component deployed on the cluster data plane, or kube-apiserver load; the third data plane workload is the controller component deployed on the cluster data plane, or kube-controller-manager load; the fourth data plane workload is the scheduler component deployed on the cluster data plane, or kube-scheduler load.

[0058] In the data plane, deploy the fifth data plane workload in a way that ensures all nodes run the same container (DaemonSet).

[0059] In the embodiment of the present application, deploying the fifth data plane workload in a DaemonSet manner can be understood as using a DaemonSet workload controller to manage the fifth data plane workload.

[0060] In some embodiments, the fifth data plane workload is a kube-proxy workload / component deployed on the cluster data plane.

[0061] In the data plane, the sixth data plane workload is deployed in a stateless application deployment (Deployment) manner; wherein the second component includes M first data plane workloads, a second data plane workload, a third data plane workload, a fourth data plane workload, a fifth data plane workload and a sixth data plane workload.

[0062] In the embodiment of the present application, deploying the sixth data plane workload in a Deployment manner can be understood as using a Deployment workload controller to manage the sixth data plane workload.

[0063] In some embodiments, the sixth data plane workload is a coredns load / component deployed in the cluster data plane.

[0064] Step A3: Establish a connection between the first component and the second component.

[0065] In an embodiment of the present application, a first control plane workload and M first data plane workloads, a first control plane workload and a second control plane workload, a second control plane workload and a third control plane workload, a second control plane workload and a fourth control plane workload, a second control plane workload and a fifth workload, a second control plane workload and a fifth data plane workload, and a second control plane workload and a sixth data plane workload are connected through a network; wherein the first component includes the first control plane workload, the second control plane workload, the third control plane workload, the fourth control plane workload and the fifth workload.

[0066] Here, the network connection may be based on a cloud communication channel, or may be other wired or wireless communication channels for network communication.

[0067] Here, the network may be a network that complies with the 3GPP standard requirements, referred to as a 3GPP network. Usually, a 3GPP network is operated by an operator, including but not limited to the fifth generation mobile communication technology (5G) network (5G network), the fourth generation mobile communication technology (4G) network (4G network), the third generation mobile communication technology (3G) network (3G network), and the second generation mobile communication technology (2G) network (2G network).

[0068] In an embodiment of the present application, a virtual network protocol address (Cluster IP) that is only accessible within the first cluster and provided by a service function is used to connect the second data plane workload and the fifth workload, M first data plane workloads and second data plane workloads, the second data plane workload and the third data plane workload, the second data plane workload and the fourth data plane workload, the second data plane workload and the fifth data plane workload, and the second data plane workload and the sixth data plane workload.

[0069] Step A4: Migrate the traffic of the core component in the first component to the core component in the second component.

[0070] Step A5: Uninstall the core component in the first component.

[0071] In the embodiment of the present application, the first control plane workload, the second control plane workload, the third control plane workload and the fourth control plane workload are shut down and removed.

[0072] Figure 2 A flowchart of an information processing method provided in an embodiment of the present application is shown as follows: Figure 2 As shown, the method is applied to the first cluster, and the method includes:

[0073] Step 201: Build a first node of a first cluster, and deploy core components required for running the first cluster in the first node in the form of containerized workloads hosted in the first cluster.

[0074] Step 202: Add N second nodes to the first cluster.

[0075] Wherein, N is a positive integer.

[0076] In an embodiment of the present application, a first rule is created in the second node; wherein the first rule is used to indicate that a request for accessing a virtual network protocol address corresponding to the second data plane workload that is only accessible within the first cluster is forwarded to a port of the first node that is already in the first cluster; in the first node, based on the first rule, the second data plane workload is accessed using a virtual network protocol address that is only accessible within the first cluster that is provided based on a service function; after the fifth workload is started, the fifth data plane workload is automatically deployed in the data plane corresponding to the second data plane workload, and the update process is taken over by the fifth data plane workload.

[0077] Step 203: reschedule the core components deployed in the first node in the form of containerized workloads hosted in the first cluster so that the core components deployed in the form of containerized workloads hosted in the first cluster are distributed to the second node.

[0078] In an embodiment of the present application, the affinity configuration of the core components deployed in the first node is modified so that the core components are distributed to the second node.

[0079] It should be noted that, for the description of the same steps and the same contents in this embodiment as those in other embodiments, reference can be made to the description in other embodiments and will not be repeated here.

[0080] Below, taking the first cluster as a K8s cluster as an example, an exemplary application of an embodiment of the present application in an actual application scenario will be described.

[0081] This application proposes a method for integrating the control plane and the data plane, converting the control plane components of K8s into the workload of the data plane, and automatically ensuring the normal operation of the control plane components of this cluster through the high availability characteristics of the data plane when a failure occurs; further, the hybrid deployment solution of the control plane and the data plane provides a practical idea for fully automated processing of fault recovery.

[0082] Figure 3 This is a flow chart of a K8s cluster deployment solution provided by this application, such as Figure 3 As shown:

[0083] Step 301: Regularly deploy the K8s master node.

[0084] In some embodiments, reference Figure 4 First, build a single master node of the cluster, and deploy the core components of the control plane (etcd, kube-apiserver, kube-controller-manager, kube-scheduler) and kubelet components directly on the host; deploy the kube-proxy workload in DaemonSet mode and the coredns workload in Deployment mode in the K8s data plane, that is, add communication links between the core components of the control plane, kubelet components, kube-proxy workload, and coredns workload in the master node.

[0085] Step 302: Use StatefulSet to deploy three storage components on the data plane as slave nodes of the storage components on the master node.

[0086] In some embodiments, reference Figure 5In the data plane, deploy three etcd workloads, such as etcd-0, etcd-1, and etcd-2, by using StatefulSet. Connect the three etcd workloads in the data plane with the etcd component of the control plane of the master node to form a cluster. That is, add a communication link between the etcd component of the control plane and the three etcd workloads in the data plane in the master node.

[0087] At this point, relying on the coredns workload in the data plane, the three etcd workloads can be interconnected through headless services, and the three etcd workloads and the etcd components of the control plane are interconnected through the host network; and because the deployment of workloads in StatefulSet is sequential and synchronous, that is, a single workload will not start the deployment and initialization process until the deployment and initialization processes of all workloads with smaller sequence numbers are completed; that is, at any time, there will not be more than one etcd node that is still being initialized and not working properly; for an etcd cluster consisting of one control plane etcd node and three data plane etcd nodes, at most one node is being initialized at any time, and the etcd cluster can always work normally.

[0088] Among them, the core components of the control plane, kubelet components, kube-proxy workloads, and coredns workloads are interconnected through the host network.

[0089] Step 303: Use the Deployment method to deploy the application programming interface server / controller / scheduler components on the data plane, exposing the new application programming interface server (apiserver) address.

[0090] In some embodiments, reference Figure 6 In the data plane, the kube-apiserver workload, kube-controller-manager workload, and kube-scheduler workload are deployed in sequence through the Deployment method; among them, relying on the kube-proxy workload in the data plane, the kube-apiserver workload can use the Cluster IP provided by the Service function to connect to the three nodes of the etcd cluster in the data plane; the kube-controller-manager workload and kube-scheduler workload of the data plane can use the Cluster IP provided by the Service function to connect to the kube-apiserver workload in the data plane.

[0091] It should be noted that the three nodes of the etcd cluster in the data plane, the kube-apiserver workload in the data plane, the kube-controller-manager workload in the data plane, and the kube-scheduler workload in the data plane are interconnected through the container network.

[0092] Step 304: Modify the kube-proxy / coredns / kubelet component configuration to point to the new application programming interface server (apiserver) service deployed using Deployment.

[0093] It should be noted that the control plane traffic is migrated to the newly created workload.

[0094] In some embodiments, reference Figure 7 , in the data plane, modify the deployed kube-proxy workload and coredns workload, and use the Cluster IP provided by the Service function to connect to the kube-apiserver workload in the data plane. When the kube-proxy workload is restarted, it will not affect the ipvs rules already configured on this node. After the kube-proxy workload is started, it will reuse the existing rules and connect to the kube-apiserver workload in the data plane; when the coredns workload is restarted, because the rolling update mechanism of the Deployment will ensure that at least one workload can always work normally, the restart process will not cause abnormal connectivity between other workloads.

[0095] In some embodiments, reference Figure 8 , on the current master node, modify the kubelet configuration file, configure and use the Cluster IP provided by the Service function to connect to the kube-apiserver workload in the data plane. When you restart the kubelet to make the new configuration take effect, it will not affect the containers running on the master node, in other words, it will not affect the kube-proxy workload in the data plane. Therefore, after the kubelet is restarted, the Cluster IP provided by the Service function can be used correctly to connect to the kube-apiserver workload in the data plane.

[0096] Step 305: Remove K8s core components such as the control plane controller that are normally deployed on the master node.

[0097] In some embodiments, reference Fig. 9On the current master node, the functions provided by the control plane components (etcd, kube-apiserver, kube-controller-manager, kube-scheduler) deployed directly in the host have all been replaced by the corresponding workloads of the data plane. You can shut down and remove the etcd, kube-apiserver, kube-controller-manager and kube-scheduler components deployed directly on the master node host.

[0098] In some embodiments, reference Fig.10 , in the data plane, modify the configuration of the etcd workload, remove the etcd originally deployed on the master node host from the etcd cluster, change the cluster size to 3 nodes, and according to the update rules of StatefulSet, the 3 etcd workloads of the data plane will be restarted in sequence, and no more than 1 node will be unavailable, which will make the entire Kubernetes cluster unavailable. At this point, the control plane components of the Kubernetes cluster are all deployed on a single master node and all run in the cluster as data plane workloads.

[0099] It should be noted that this application designs a component migration and deployment method based on native Kubernetes. The relevant components are migrated from the native solution to the new solution, and lossless migration can be guaranteed during the migration process.

[0100] Step 306: Add new cluster nodes to meet cluster size requirements.

[0101] Next, a single master node cannot meet the requirements of high availability, and more hosts need to be added to the Kubernetes cluster. On any host that is planned to be added to the cluster, first create a temporary rule in ipvs: Requests to access the Cluster IP corresponding to the kube-apiserver workload are forwarded to the NodePort of the host that is already in the cluster. The kubelet on the host can use this temporary rule to access the kube-apiserver workload using the Cluster IP provided by the Service. After the kubelet is started, the kube-proxy workload will be automatically deployed on the data plane corresponding to this host, and the kube-proxy workload will take over the update process of ipvs, including automatically overwriting the temporary rules mentioned above. At this point, the new host has been added to the Kubernetes cluster. Repeat this step to add multiple hosts to the cluster until the cluster size requirements are met.

[0102] Furthermore, for this cluster, the K8s core components are rescheduled to meet the high availability requirements of the components.

[0103] In the data plane, modify the affinity configuration of the deployed etcd workload so that it is distributed to different host nodes according to the high availability requirements. During the modification process, according to the update rules of StatefulSet, the three etcd workloads of the data plane will be restarted in sequence, and no more than one node will be unavailable, which will make the entire Kubernetes cluster unavailable.

[0104] In the data plane, modify the affinity configuration of the deployed kube-apiserver, kube-controller-manager, and kube-scheduler workloads to distribute them to different host nodes according to high availability requirements. During the modification process, according to the rolling update rules of Deployment, it will be guaranteed that at least one workload is available at any time, which will not affect the availability of the entire Kubernetes cluster. At this point, the construction of a high-availability Kubernetes cluster is complete.

[0105] In this way, the core components of the Kubernetes cluster we deployed (etcd, kube-apiserver, kube-controller-manager, and kube-schedule) are deployed as Kubernetes native workloads (Deployment, StatefulSet). If an instance fails, the Kubernetes workload controller will automatically create a new instance, which has higher reliability than the native Kubernetes control plane node. Moreover, if the number of instances of these core components needs to be expanded later, you only need to modify the number of replicas of the corresponding workload. The expansion process is transparent and imperceptible to users and operation and maintenance personnel.

[0106] The embodiment of the present application provides a first node, which can be applied to Figure 1 In an information processing method provided in a corresponding embodiment, referring to Fig.11 As shown, the first node 1100 includes:

[0107] The processing module 1101 is used to deploy the core components required for the operation of the first cluster in the form of containerized workloads hosted in the first cluster.

[0108] In other embodiments of the present application, the processing module 1101 is used to directly deploy a first component in a first node; wherein the first component includes a core component;

[0109] The processing module 1101 is used to deploy the second component on the data plane of the first cluster in a stateless application deployment or a stateful application deployment or in a manner of ensuring that all nodes run the same container; the second component includes a core component;

[0110] Processing module 1101, used to establish a connection between the first component and the second component;

[0111] The processing module 1101 is used to migrate the traffic of the core component in the first component to the core component in the second component;

[0112] The processing module 1101 is used to uninstall the core component in the first component.

[0113] In other embodiments of the present application, the processing module 1101 is used to deploy M first data plane workloads in a stateful application deployment manner on the data plane; M is a positive integer; the M first data plane workloads are interconnected through a headless service;

[0114] The processing module 1101 is used to deploy the second data plane workload, the third data plane workload and the fourth data plane workload in a stateless application deployment manner on the data plane;

[0115] Processing module 1101, configured to deploy a fifth data plane workload in a data plane in a manner to ensure that all nodes run the same container;

[0116] Processing module 1101 is used to deploy the sixth data plane workload in the data plane in a stateless application deployment manner; wherein the second component includes M first data plane workloads, second data plane workloads, third data plane workloads, fourth data plane workloads, fifth data plane workloads and sixth data plane workloads.

[0117] In other embodiments of the present application, the processing module 1101 is used to connect the first control plane workload and M first data plane workloads, the first control plane workload and the second control plane workload, the second control plane workload and the third control plane workload, the second control plane workload and the fourth control plane workload, the second control plane workload and the fifth workload, the second control plane workload and the fifth data plane workload, and the second control plane workload and the sixth data plane workload through a network; wherein the first component includes the first control plane workload, the second control plane workload, the third control plane workload, the fourth control plane workload, and the fifth workload;

[0118] Processing module 1101 is used to connect the second data plane workload and the fifth workload, M first data plane workloads and second data plane workloads, the second data plane workload and the third data plane workload, the second data plane workload and the fourth data plane workload, the second data plane workload and the fifth data plane workload, and the second data plane workload and the sixth data plane workload through a virtual network protocol address provided by the service function and accessible only within the first cluster.

[0119] In other embodiments of the present application, the core components include a first control plane workload, a second control plane workload, a third control plane workload, and a fourth control plane workload; a processing module 1101 is used to shut down and remove the first control plane workload, the second control plane workload, the third control plane workload, and the fourth control plane workload.

[0120] The description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0121] It should be noted that in the embodiment of the present application, if the above-mentioned information processing method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions for a terminal device to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0122] The embodiment of the present application provides a first cluster, which can be applied to Figure 2 In an information processing method provided in a corresponding embodiment, referring to Fig.12 As shown, the first cluster 1200 includes: a first node 1201 and N second nodes 1202;

[0123] The first node 1201 and the N second nodes 1202 cooperate to perform the following information processing method:

[0124] Building a first node of the first cluster, and deploying, in the first node, core components required for running the first cluster in the form of containerized workloads hosted in the first cluster;

[0125] Add N second nodes to the first cluster; N is a positive integer;

[0126] Reschedule the core components deployed in the first node as containerized workloads hosted in the first cluster so that the core components deployed in the first cluster as containerized workloads hosted in the first cluster are distributed to the second node.

[0127] In other embodiments of the present application, the first node 1201 and the N second nodes 1202 cooperate to perform the following information processing method:

[0128] In the second node, a first rule is created; wherein the first rule is used to indicate that a request for accessing a virtual network protocol address corresponding to a second data plane workload that is only accessible within the first cluster is forwarded to a port of the first node that is already in the first cluster;

[0129] In the first node, based on the first rule, accessing the second data plane workload using a virtual network protocol address provided based on the service function and accessible only within the first cluster;

[0130] After the fifth workload is started, the fifth data plane workload is automatically deployed on the data plane corresponding to the second data plane workload, and the update process is taken over by the fifth data plane workload.

[0131] In other embodiments of the present application, the first node 1201 and the N second nodes 1202 cooperate to perform the following information processing method:

[0132] The affinity configuration of the core component deployed in the first node is modified so that the core component is distributed to the second node.

[0133] The description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0134] It should be noted that in the embodiments of the present application, if the above-mentioned information processing method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions for a terminal device to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a magnetic disk or an optical disk. In this way, the embodiments of the present application are not limited to any specific combination of hardware and software.

[0135] Fig.13 1 is a schematic structural diagram of a communication device 1300 provided in an embodiment of the present application. The communication device may be a first node, a second node, or a first cluster. Fig.13 The communication device 1300 shown includes a processor 1310, and the processor 1310 can call and run a computer program from a memory to implement the method in the embodiment of the present application.

[0136] Alternatively, if Fig.13 As shown, the communication device 1300 may further include a memory 1320. The processor 1310 may call and run a computer program from the memory 1320 to implement the method in the embodiment of the present application.

[0137] The memory 1320 may be a separate device independent of the processor 1310 , or may be integrated into the processor 1310 .

[0138] Alternatively, if Fig.13 As shown, the communication device 1300 may further include a transceiver 1330, and the processor 1310 may control the transceiver 1330 to communicate with other devices, specifically, may send information or data to other devices, or receive information or data sent by other devices.

[0139] The transceiver 1330 may include a transmitter and a receiver. The transceiver 1330 may further include an antenna, and the number of antennas may be one or more.

[0140] Optionally, the communication device 1300 may specifically be the first node / first cluster / second node of an embodiment of the present application, and the communication device 1300 may implement the corresponding processes implemented by the first node / first cluster / second node in each method of the embodiment of the present application, which will not be described again for the sake of brevity.

[0141] In some embodiments, the embodiments of the present application further provide a computer program product, including a computer program, which can be executed by the processor 1310 of the communication device 1300 to complete any of the aforementioned method steps.

[0142] It should be understood that the processor of the embodiment of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by the hardware integrated logic circuit or software instructions in the processor. The above processor can be a general processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to perform, or the hardware and software modules in the decoding processor are combined and performed. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, and other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0143] As an embodiment, the processor may include one or more general-purpose central processing units (CPUs). Each of these processors may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer execution instructions).

[0144] It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a ROM, a programmable read-only memory (Programmable ROM, PROM), an erasable programmable read-only memory (Erasable PROM, EPROM), an electrically erasable programmable read-only memory (Electrically EPROM, EEPROM) or a flash memory. The volatile memory can be a random access memory (Random Access Memory, RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus random access memory (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0145] An embodiment of the present application also provides a computer-readable storage medium for storing a computer program.

[0146] Optionally, the computer-readable storage medium can be applied to the first node / first cluster in the embodiments of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the model training device in the various methods of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0147] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0148] The computer program product includes one or more computer instructions. When loading and executing the computer program instructions on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instruction can be stored in a computer-readable storage medium, or transmitted from a computer-readable storage medium to another computer-readable storage medium. For example, the computer instruction can be transmitted from a website site, a computer, a server, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server, or data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server, a data center, etc. that includes one or more available media integration. Available media can be magnetic media, (e.g., floppy disk, hard disk, tape), optical media (e.g., DVD), or semiconductor media (e.g., solid-state hard disk (SSD)), etc.

[0149] The information processing method, the first node, the first cluster, the computer-readable storage medium and the computer program product provided in the embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the ideas of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present application.

[0150] It should be understood that the "one embodiment" or "an embodiment" or "an embodiment of the present application" or "the aforementioned embodiment" or "some implementations" or "some embodiments" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" or "an embodiment of the present application" or "the aforementioned embodiment" or "some implementations" or "some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0151] Unless otherwise specified, the first node / first cluster performs any step in the embodiment of the present application, and the processor of the first node / first cluster may perform the step. Unless otherwise specified, the embodiment of the present application does not limit the order in which the first node / first cluster performs the following steps. In addition, the methods used to process data in different embodiments may be the same method or different methods.

[0152] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0153] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0154] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0155] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain a new method embodiment. The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain a new product embodiment. The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain a new method embodiment or device embodiment.

[0156] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, magnetic disks or optical disks.

[0157] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly reflected in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0158] As used in the embodiments of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0159] It should be noted that in each embodiment involved in the present application, all steps may be executed or part of the steps may be executed as long as a complete technical solution can be formed.

[0160] The above are only implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An information processing method, characterized in that: Applied to the first node, the method comprises: In the first node of the first cluster, core components required for the operation of the first cluster are deployed in the form of containerized workloads hosted in the first cluster.

2. The method according to claim 1, characterized in that The step of deploying, in the first node of the first cluster, core components required for the operation of the first cluster in the form of containerized workloads hosted in the first cluster, includes: Directly deploying a first component in the first node; wherein the first component includes the core component; Deploy a second component on the data plane of the first cluster in a stateless application deployment or a stateful application deployment or in a manner that ensures that all nodes run the same container; wherein the second component includes the core component; establishing a connection between the first component and the second component; Migrating the traffic of the core component in the first component to the core component in the second component; Uninstall the core components in the first component.

3. The method according to claim 2, characterized in that The method of deploying the second component on the data plane of the first cluster by using stateless application deployment or stateful application deployment or ensuring that all nodes run the same container includes: On the data plane, M first data plane workloads are deployed in a stateful application deployment manner; M is a positive integer; the M first data plane workloads are interconnected through a headless service; On the data plane, deploying a second data plane workload, a third data plane workload, and a fourth data plane workload in a stateless application deployment manner; deploying a fifth data plane workload on the data plane in a manner that ensures all nodes run the same container; In the data plane, the sixth data plane workload is deployed in a stateless application deployment manner; wherein the second component includes the M first data plane workloads, the second data plane workload, the third data plane workload, the fourth data plane workload, the fifth data plane workload and the sixth data plane workload.

4. The method according to claim 3, characterized in that The establishing a connection between the first component and the second component includes: Connecting a first control plane workload and M first data plane workloads, the first control plane workload and the second control plane workload, the second control plane workload and the third control plane workload, the second control plane workload and the fourth control plane workload, the second control plane workload and the fifth workload, the second control plane workload and the fifth data plane workload, and the second control plane workload and the sixth data plane workload through a network; wherein the first component includes the first control plane workload, the second control plane workload, the third control plane workload, the fourth control plane workload, and the fifth workload; The second data plane workload and the fifth workload, the M first data plane workloads and the second data plane workloads, the second data plane workload and the third data plane workload, the second data plane workload and the fourth data plane workload, the second data plane workload and the fifth data plane workload, and the second data plane workload and the sixth data plane workload are connected through a virtual network protocol address provided by the service function and accessible only within the first cluster.

5. The method according to claim 4, characterized in that The core components include a first control plane workload, a second control plane workload, a third control plane workload, and a fourth control plane workload, and the core components of the direct deployment of the offloading include: The first control plane workload, the second control plane workload, the third control plane workload, and the fourth control plane workload are shut down and removed.

6. An information processing method, characterized in that: Applied to the first cluster, the method comprises: Building a first node of the first cluster, and deploying, in the first node, core components required for running the first cluster in the form of containerized workloads hosted in the first cluster; Adding N second nodes to the first cluster; N is a positive integer; Reschedule the core components deployed in the first node as containerized workloads hosted in the first cluster so that the core components deployed in the first cluster as containerized workloads hosted in the first cluster are distributed to the second node.

7. The method according to claim 6, characterized in that The adding N second nodes to the first cluster includes: In the second node, a first rule is created; wherein the first rule is used to indicate that a request for accessing a second data plane workload corresponding to a virtual network protocol address that is only accessible within the first cluster is forwarded to a port of the first node that is already in the first cluster; In the first node, based on the first rule, accessing a second data plane workload using a virtual network protocol address provided based on a service function and accessible only within the first cluster; After the fifth workload is started, the fifth data plane workload is automatically deployed on the data plane corresponding to the second data plane workload, and the update process is taken over by the fifth data plane workload.

8. The method according to claim 6, characterized in that The rescheduling of the core components deployed in the first node in the form of containerized workloads hosted in the first cluster so that the core components deployed in the form of containerized workloads hosted in the first cluster are distributed to the second node includes: Modify the affinity configuration of the core component deployed in the first node so that the core component is distributed to the second node.

9. A first node, characterized in that: The first node comprises: A processing module is used to deploy core components required for the operation of the first cluster in the form of containerized workloads hosted in the first cluster.

10. A first node, characterized in that: The first node comprises: A memory for storing executable instructions; A processor, configured to implement the information processing method according to any one of claims 1 to 5 when executing the executable instructions stored in the memory.

11. A first cluster, characterized in that: The first cluster includes a first node and N second nodes, where N is a positive integer, and the first node and the N second nodes cooperate to perform the information processing method as described in any one of claims 6 to 8.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the information processing method described in any one of claims 1 to 6, or to implement the information processing method described in any one of claims 6 to 8.

13. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the computer program implements the information processing method according to any one of claims 1 to 6, or implements the information processing method according to any one of claims 6 to 8.

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