CN114500549B

CN114500549B - Method, device and medium for deploying k8s hosting clusters for users in public cloud

Info

Publication number: CN114500549B
Application number: CN202011268416.3A
Authority: CN
Inventors: 彭世柱
Original assignee: Tianyi Cloud Technology Co Ltd
Current assignee: Tianyi Cloud Technology Co Ltd
Priority date: 2020-11-13
Filing date: 2020-11-13
Publication date: 2023-08-08
Anticipated expiration: 2040-11-13
Also published as: CN114500549A

Abstract

The present disclosure relates to methods, devices, and media for deploying k8s hosted clusters for users in a public cloud. The present disclosure provides a method of deploying a k8s hosted cluster for a user in a public cloud, wherein the user has at least one host and the at least one host constitutes the k8s hosted cluster, the method comprising: creating a k8s management cluster in the public cloud; and containerizing the Master component of the k8s hosting cluster to form a Master container; deploying the Master container in the k8s management cluster, wherein the Master container comprises: creating a orchestration file for the k8s managed cluster in the k8s managed cluster; and creating, by a controller in the k8s management cluster, a corresponding number of containers in the k8s management cluster for each subcomponent of a Master container using the orchestration file to form a high availability k8s managed cluster.

Description

Method, device and medium for deploying k8s hosting clusters for users in public cloud

Technical Field

The present disclosure relates generally to the field of container orchestration tools k8s technology, and more particularly to a method, apparatus, and medium for deploying k8s hosted clusters for users in a public cloud.

Background

K8s is short for Kubernetes. Kubernetes is a container orchestration engine of Google open source, is the most widely used container orchestration tool at present, and solves the problem of large-scale deployment after application containerization. In Kubernetes, multiple containers may be created, one application instance running in each container, and then management, discovery, and access to the set of application instances is implemented through a built-in load balancing policy, where no complex manual configuration and processing by operation and maintenance personnel is required for these details.

The components of Kubernetes fall into two categories: master components and Node components. Included in the Master set are Etcd, kube-apiserver, kube-scheduler, kube-controller-manager. The Node components include Kubelet and Kube-proxy. In the Master component, etcd is a key-value database, and k8s data are stored in Etcd; kube-apiserver is an HTTP server exposing rest api to external users and Node nodes; kube-scheduler is a scheduler that will always listen to Pod in the cluster through the API of Kube-apiserver and then schedule it to a Node. Kube-controller-manager will also always monitor the API of Kube-apiserver, performing some loop tasks.

In a traditional k8s cluster deployment architecture, a high-availability k8s cluster is deployed, at least three nodes are needed, and a Master component is deployed on each Node and shares a host with the Node component.

In public cloud mode, such scenarios are typically encountered: the application scale of the user is small, and one or two hosts can meet the requirement. At this time, if a traditional k8s cluster is to be built, the user needs to purchase at least three hosts, which is high in cost. Therefore, the mode of the support pipe cluster is very suitable for small users.

There are many implementations of managed clusters: the simplest method is to select three hosts, and when a user opens a hosting cluster, the configuration and the number of the working nodes are selected. For this example, a set of highly available k8s Master components is deployed on the three hosts (multiple sets of Master can be deployed on one host). However, this approach lacks the ability to laterally expand, and at best they may only be able to deploy masters for N clusters. It is therefore not feasible to run the Master of the hosting cluster directly on the host in a physical manner.

Thus, there is a need in the art for a technique that can deploy scalable k8s hosted clusters in public clouds for users with any number of hosts.

Disclosure of Invention

The following presents a simplified summary of the disclosure in order to provide a basic understanding of some aspects of the disclosure. However, it should be understood that this summary is not an exhaustive overview of the disclosure. It is not intended to identify key or critical elements of the disclosure or to delineate the scope of the disclosure. Its purpose is to present some concepts related to the disclosure in a simplified form as a prelude to the more detailed description that is presented later.

According to one aspect of the present disclosure, there is provided a method of deploying a k8s hosting cluster for a user in a public cloud, wherein the user has at least one host and the at least one host constitutes the k8s hosting cluster, the method comprising: creating a k8s management cluster in the public cloud; and containerizing the Master components of the k8s hosting cluster to form a Master container; deploying the Master container in the k8s management cluster, wherein the Master container comprises: creating a orchestration file for the k8s managed cluster in the k8s managed cluster; and creating, by a controller in the k8s management cluster, a corresponding number of containers for each subcomponent of a Master container in the k8s management cluster using the orchestration file to form a high availability k8s managed cluster.

According to another aspect of the present disclosure, there is provided a server in a public cloud, comprising: a memory having instructions stored thereon; and a processor configured to execute instructions stored on the memory to perform a method according to the above aspects of the present disclosure.

According to yet another aspect of the present disclosure, there is provided a computer-readable storage medium comprising computer-executable instructions which, when executed by one or more processors, cause the one or more processors to perform a method according to the above aspects of the present disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.

The disclosure may be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings, in which:

FIG. 1 illustrates a flowchart of a process for deploying a k8s hosted cluster for a user in a public cloud, according to one embodiment of the present disclosure;

FIG. 2 illustrates a schematic diagram of a deployment architecture of a hosted cluster, according to one embodiment of the present disclosure;

FIG. 3 illustrates a schematic diagram of a orchestration file and deployment tool for hosting a cluster Master, according to one embodiment of the present disclosure;

fig. 4 illustrates an exemplary configuration of a network side server that may implement a k8s hosting cluster for user deployment in a public cloud according to one embodiment of the present disclosure.

Detailed Description

The following detailed description is made with reference to the accompanying drawings and is provided to assist in a comprehensive understanding of various example embodiments of the disclosure. The following description includes various details to aid in understanding, but these are to be considered merely examples and are not intended to limit the disclosure, which is defined by the appended claims and their equivalents. The words and phrases used in the following description are only intended to provide a clear and consistent understanding of the present disclosure. In addition, descriptions of well-known structures, functions and configurations may be omitted for clarity and conciseness. Those of ordinary skill in the art will recognize that various changes and modifications of the examples described herein can be made without departing from the spirit and scope of the present disclosure.

The inventors have recognized that it is not feasible in the prior art to run a Master of a managed cluster directly on top of a host. The inventors therefore propose to run the Master of the managed cluster in a k8s management cluster, such that the Master container of the managed cluster is equivalent to a normal container run in the management cluster.

FIG. 1 illustrates a flowchart of a process 100 for deploying a k8s hosted cluster for a user in a public cloud according to one embodiment of the present disclosure. The user may have at least one host and request to open a k8s hosting cluster. The user may select the configuration and number of hosts at turn-on. At least one host of users constitutes the k8s hosting cluster.

At step 101, the process starts. At this step, a k8s management cluster is created in the public cloud.

At step 102, the Master component of the k8s hosting cluster is containerized to form a Master container.

At step 103, the Master container is deployed in the k8s management cluster. The deployment may be achieved by: creating a layout file for the k8s support cluster in the k8s management cluster; and creating, by a controller in the k8s management cluster, a corresponding number of containers in the k8s management cluster for each subcomponent of a Master container using the orchestration file to form a high availability k8s managed cluster.

Notably, the native k8s can be parsed when this is done. When the user has one or 2 hosts, the orchestration file specifies etcd, kube-apiserver, kube-controller-manager, kube-scheduler sub-components of the Master container to create 3 containers, 2 containers, respectively.

The present process 100 may further include: the controller in the k8s management cluster sequentially initiates each of the 3 containers of the etcd subassembly according to the orchestration file.

The present process 100 may further include: the controller monitors the arranging file; and in response to monitoring the orchestration file, the controller deploys the Master container in the k8s management cluster.

The present process 100 may further include: the orchestration file is modified to accommodate the change in the number of hosts of the user.

As described above, a user in a public cloud may have only one or two hosts. In this case, the use of existing technology is not able to provide the user with a high availability of k8s hosting clusters. The present process solves this problem. When a user has only one or two hosts, 3 containers are created in the k8s management cluster for the etcd subcomponent of the Master component of the k8s managed cluster created by the user to meet the requirements of a high availability cluster.

Fig. 2 illustrates a schematic diagram of a deployment architecture of a hosted cluster, according to one embodiment of the present disclosure.

As shown in fig. 2, k8s management clusters are created in the public cloud to run Master component containers for the respective managed clusters. For example, two tote clusters 6443 and 6444, belonging to two users respectively, are shown in fig. 2. The Master components of the two managed clusters are containerized as Master containers running in the k8s management cluster. Although there are only two nodes per user, 3 containers are created in the Master container for the etcd subcomponent to meet the requirements of a highly available hosted cluster. Notably, other sub-components kube-apiserver, kube-controller-manager, kube-scheduler of the Master component may create only 2 containers for them. These are accomplished by editing the file and using a controller to monitor the editing file. This is described further below.

Fig. 2 illustrates a deployment architecture of a managed cluster. Except Etcd, fig. 2 is a stateless service, and is deployed by a common deviyment workload. Etcd is a stateful service where an open-source Etcd-operator containerization scheme may be used. Whereas Etcd's data may be stored using distributed or local storage. Under this deployment architecture, any container instance of the Master hangs up, allowing recovery in seconds. In addition, when the size of the managed cluster becomes larger, namely the Master container becomes more, the problem can be solved perfectly by only performing lateral expansion on the nodes of the managed cluster.

The kubead tool is only suitable for deploying the Master of the cluster to the host, and when the Master is required to be containerized and run in the k8s cluster according to the invention, the deployment of the Master needs to find another method. For this purpose, the invention designs a programming file for representing the managed cluster Master based on the CRD (Custom Resource Definition ) mechanism of k8s, then develops a corresponding controller, listens to the programming file, and then deploys the managed cluster Master in the managed cluster by the controller.

FIG. 3 illustrates a schematic diagram of a orchestration file and deployment tool for hosting a cluster Master, according to one embodiment of the present disclosure. As shown in fig. 3, two of the joined files CR have been formed in the k8s management cluster. The controller Operator constantly listens for the presence or change of CR (Custom Resource). In response to listening for the presence or change of CR, the Operator creates individual containers for the Master component.

The working mechanism of the orchestration file and the Operator is described in detail below. The master component of K8s is etcd, kube-apiserver, kube-controller-manager, kube-schedule; at least three containers of the etcd form an etcd cluster to ensure high availability, and the other containers need two to ensure high availability. This orchestration file, native k8s, is unresolved, but the Operator can identify this orchestration file and will create a corresponding number of containers for each component in the cluster based on it. Where the three containers of the etcd assembly, which do not work independently, need to form one etcd cluster. The operator controls the start-up sequence of each etcd container, and when the first one comes up, the etcd cluster has only one instance; the operator continues to start the second container and adds the second container to the cluster of the first etcd container, thus forming an etcd cluster of two instances; this is done until all etcd containers are added to make up a three container etcd cluster.

If the user increases or decreases the hosts used due to his own needs, adjustments can be made by modifying the orchestration file. The controller Operator listens for changes to the orchestration file and can create or delete the corresponding sub-component container. Thus, the present invention enables a highly available scalable k8s hosting cluster for users.

For example, one exemplary embodiment of the present invention may be implemented by the following steps: (some more detailed description of the following operations will be best given)

1. The hosting cluster is suitable for public cloud scenes. And the user selects to open a k8s hosting cluster on the public cloud, and selects the configuration and the number of the working nodes.

2. After the public cloud front end receives the request, the public cloud front end firstly sends a request to the k8s management cluster, and a CR (Custom Resource) object is created in the k8s management cluster.

3. After the operators in the management cluster monitor that CR objects are generated, the layout file which can be understood by the original k8s is created. The kube-controller-manager component in the management cluster creates a Master container such as kube-apiserver, kube-controller-manager, kube-schedule, etc. of the managed cluster from these orchestration files. The operators also need to create a specified number of etcd containers in order until they form an etcd cluster.

4. When the Master containers of the managed clusters are all running, the front end of the public cloud will continue to send a request IaaS layer to request to obtain working node hosts, then install k8 s' Worker components on these hosts, and configure the addresses of the masters for the workers as the addresses of the containers just created in the managed clusters. Thus, the Master container and the workbench node host running in the management cluster form a complete hosting cluster and are delivered to users. In addition, the Master components running above are all container images using open sources. Except that the Operator container is required to come from the main research and development in accordance with the logic described above.

The present invention has at least one of the following advantages and effects over the prior art. Firstly, compared with the traditional k8s cluster deployment mode, the method can reduce the resource cost of small users and can ensure the high availability of the managed clusters. Secondly, compared with a mode of centralized deployment of a Master on three hosts, the method has the advantages of particularly better lateral expansibility and high availability.

Fig. 4 illustrates an exemplary configuration of a network side server 1200 that may implement deploying k8s hosted clusters for users in a public cloud according to one embodiment of the disclosure.

Computing device 1200 is an example of a hardware device that can employ the above aspects of the disclosure. Computing device 1200 may be any machine configured to perform processing and/or calculations. Computing device 1200 may be, but is not limited to, a workstation, a server, a desktop computer, a laptop computer, a tablet computer, a Personal Data Assistant (PDA), a smart phone, an on-board computer, or a combination thereof.

As shown in fig. 4, computing device 1200 may include one or more elements that may be connected to or in communication with bus 1202 via one or more interfaces. The bus 2102 can include, but is not limited to, an industry standard architecture (Industry Standard Architecture, ISA) bus, a micro channel architecture (Micro Channel Architecture, MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus, among others. Computing device 1200 may include, for example, one or more processors 1204, one or more input devices 1206, and one or more output devices 1208. The one or more processors 1204 may be any kind of processor and may include, but are not limited to, one or more general purpose processors or special purpose processors (such as special purpose processing chips). The processor 1202 may be configured to implement, for example, a process of deploying k8s managed clusters for users in a public cloud. The input device 1206 may be any type of input device capable of inputting information to a computing device, and may include, but is not limited to, a mouse, keyboard, touch screen, microphone, and/or remote controller. Output device 1208 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers.

The computing device 1200 may also include or be connected to a non-transitory storage device 1214, which non-transitory storage device 1214 may be any storage device that is non-transitory and that may enable data storage, and may include, but is not limited to, disk drives, optical storage devices, solid-state storage, floppy diskettes, flexible diskettes, hard disks, magnetic tape, or any other magnetic medium, compact disk, or any other optical medium, cache memory, and/or any other memory chip or module, and/or any other medium from which a computer may read data, instructions, and/or code. Computing device 1200 may also include Random Access Memory (RAM) 1210 and Read Only Memory (ROM) 1212. The ROM 1212 may store programs, utilities or processes to be executed in a non-volatile manner. The RAM 1210 may provide volatile data storage and stores instructions related to the operation of the computing device 1200. The computing device 1200 may also include a network/bus interface 1216 coupled to the data link 1218. The network/bus interface 1216 can be any kind of device or system capable of enabling communication with external equipment and/or networks, and can include, but is not limited to, modems, network cards, infrared communication devices, wireless communication devices, and/or chip sets (such as bluetooth @) ^TM Devices, 802.11 devices, wiFi devices, wiMax devices, cellular communication facilities, etc.).

The present disclosure may be implemented as any combination of apparatuses, systems, integrated circuits, and computer programs on a non-transitory computer readable medium. One or more processors may be implemented as an Integrated Circuit (IC), application Specific Integrated Circuit (ASIC), or large scale integrated circuit (LSI), system LSI, super LSI, or super LSI assembly that performs some or all of the functions described in this disclosure.

The present disclosure includes the use of software, applications, computer programs, or algorithms. The software, application, computer program or algorithm may be stored on a non-transitory computer readable medium to cause a computer, such as one or more processors, to perform the steps described above and depicted in the drawings. For example, one or more memories may store software or algorithms in executable instructions and one or more processors may associate a set of instructions to execute the software or algorithms to provide various functions in accordance with the embodiments described in this disclosure.

Software and computer programs (which may also be referred to as programs, software applications, components, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural, object-oriented, functional, logical, or assembly or machine language. The term "computer-readable medium" refers to any computer program product, apparatus or device, such as magnetic disks, optical disks, solid state memory devices, memory, and Programmable Logic Devices (PLDs), for providing machine instructions or data to a programmable data processor, including a computer-readable medium that receives machine instructions as a computer-readable signal.

By way of example, computer-readable media can comprise Dynamic Random Access Memory (DRAM), random Access Memory (RAM), read Only Memory (ROM), electrically erasable read only memory (EEPROM), compact disk read only memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired computer-readable program code in the form of instructions or data structures and that can be accessed by a general purpose or special purpose computer or general purpose or special purpose processor. Disk or disc, as used herein, includes Compact Disc (CD), laser disc, optical disc, digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above are also included within the scope of computer-readable media.

Similarly, although operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multi-tasking and parallel processing may be advantageous.

Claims

1. A method of deploying a k8s hosted cluster for a user in a public cloud, wherein the user has at least one host and the at least one host comprises the k8s hosted cluster, the method comprising:

creating a k8s management cluster in the public cloud; and

containerizing the Master components of the k8s hosting cluster to form a Master container;

deploying the Master container in the k8s management cluster, wherein the Master container comprises:

creating a orchestration file for the k8s managed cluster in the k8s managed cluster; and

creating, by a controller in the k8s management cluster, a corresponding number of containers for each sub-component of a Master container in the k8s management cluster using the monitored orchestration file to form a high availability k8s managed cluster, wherein when the user has one or 2 hosts, the orchestration file specifies creating 3 containers for etcd sub-components of a Master container, the controller sequentially starting each of the 3 containers according to the orchestration file.

2. The method of claim 1, wherein when the user has one or 2 hosts, the orchestration file specifies kube-apiserver, kube-controller-manager, kube-scheduler sub-components of a Master container create 2 containers, respectively.

3. The method of claim 1, further comprising:

the orchestration file is modified to accommodate the change in the number of hosts of the user.

4. A server in a public cloud, comprising:

a memory having instructions stored thereon; and

a processor configured to execute instructions stored on the memory to perform the method according to any one of claims 1 to 3.

5. A computer-readable storage medium comprising computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the method of any of claims 1-3.